Miracle-dz/UniFAR-FTUs huggingface dataset:
Tasking the tweeters: obtaining actionable information from human sensors

Social media sources such as Twitter have proven to be a valuable medium for obtaining real-time information on breaking events, as well as a tool for campaigning. When tweeters can be characterised in terms of location (e.g., because they geotag their updates, or mention known places) or topic (e.g., because they refer to thematic terms in an ontology or lexicon) their posts can provide actionable information. Such information can be obtained in a passive mode, by collecting data from Twitter's APIs, but even greater value can be gained from an active mode of operation, by engaging with particular tweeters and asking for clarifications or amplifications. Doing so requires knowledge of individual tweeters as "sensing assets". In this paper we show how the use of social media as a kind of sensor can be accommodated within an existing framework for sensor-task matching, by extending existing ontologies of sensors and mission tasks, and accounting for variable information quality. An integrated approach allows tweeters to be "accessed" and "tasked" in the same way as physical sensors (unmanned aerial and ground systems) and, indeed, combined with these more traditional kinds of source. We illustrate the approach using a number of case studies, including field trials (obtaining eyewitness reports from the scene of organised protests) and synthetic experiments (crowdsourced situational awareness).
A Continuously Tunable LC-VCO PLL with Bandwidth Linearization Techniques for PCI Express Gen2 Applications

This paper describes bandwidth linearization techniques in phase-locked loop (PLL) design for common-clock serial link applications. Utilizing a continuously tunable single-input dual-path LC VCO and a constant-gain phase detector, a proposed architecture is well suited to implementing PLLs that must be compliant with standards that specify minimum and maximum allowable bandwidths such as PCI Express Gen2 or FB-DIMM applications. A prototype 4.75 to 6.1-㎓ PLL is implemented in 90-nm CMOS. Measurement results show that the PLL bandwidth and random jitter (RJ) variations are well regulated and that the use of a differentially controlled dualpath VCO is important for deterministic jitter (DJ) performance.
Autonomous self-configuration of artificial neural networks for data classification or system control

Artificial neural networks (ANNs) are powerful methods for the classification of multi-dimensional data as well as for the control of dynamic systems. In general terms, ANNs consist of neurons that are, e.g., arranged in layers and interconnected by real-valued or binary neural couplings or weights. ANNs try mimicking the processing taking place in biological brains. The classification and generalization capabilities of ANNs are given by the interconnection architecture and the coupling strengths. To perform a certain classification or control task with a particular ANN architecture (i.e., number of neurons, number of layers, etc.), the inter-neuron couplings and their accordant coupling strengths must be determined (1) either by a priori design (i.e., manually) or (2) using training algorithms such as error back-propagation. The more complex the classification or control task, the less obvious it is how to determine an a priori design of an ANN, and, as a consequence, the architecture choice becomes somewhat arbitrary. Furthermore, rather than being able to determine for a given architecture directly the corresponding coupling strengths necessary to perform the classification or control task, these have to be obtained/learned through training of the ANN on test data. We report on the use of a Stochastic Optimization Framework (SOF; Fink, SPIE 2008) for the autonomous self-configuration of Artificial Neural Networks (i.e., the determination of number of hidden layers, number of neurons per hidden layer, interconnections between neurons, and respective coupling strengths) for performing classification or control tasks. This may provide an approach towards cognizant and self-adapting computing architectures and systems.
Measuring Quality in Chat Reference Consortia: A Comparative Analysis of Responses to Users’ Queries

Academic libraries have experienced growing demand for 24/7 access to resources and services. Despite the challenges and costs of chat reference service and consortia, many libraries are finding the demand for these services worth the cost. One key challenge is providing and measuring quality of service, particularly in a consortia setting. This study explores the quality of service provided in one academic library participating in a 24/7 chat reference consortium, by assessing transcripts of chat sessions using in-house reference quality standards. Findings point to both similarities and differences between chat interactions of local librarians versus consortia staff.
Introduction to Bond Graph Simulation Program (BGSP)

This paper introduces a Bond Graph Simulation Program (BGSP) developed for evaluation of hydraulic systems as well as general ones. Bond graphs represent various components and systems in an unified manner. By virtue of a symbolic manipulation method to obtain state-space system equations, not only non linear characteristic functions but also user-defined outputs can be easily dealt with. Further, any reference values of state variables can be used in the definition of component functions. New features developed recently for BGSP and future problems to be solved are also presented briefly.
Research on Dance Teaching Advantage Analysis Based on Computer Intelligent Simulation

Computer simulation technology is one of the main components of the construction of modern educational environment which provides rich and comprehensive operating model train for students and trains students in all aspects of technology and develops students' Potential ability and achieves the purpose of teaching science entertaining ultimately. This paper first analyzes the connotation of the computer intelligent simulation teaching. Based on this, it combines with three-dimensional recovery principle of dance moves under computer intelligent simulation technology. It also analyzes the dance teaching principle and teaching strength based on computer intelligent simulation. This paper puts forward relevant recommendations and enhances the systematicness and practical applicability of dance teaching in the field of education and teaching which opens up new path for dance education.
Goms on the Flight Deck: A Case Study of the Boeing 777 MCP

Despite the extensive literature available on GOMS methods for predicting task performance, there are relatively few hands-on examples of GOMS being used in an applied setting. This proof-of-concept paper will describe the use of CPM-GOMS and NGOMSL, in combination with an existing RAFIV, to evaluate the Boeing 777 autoflight system.
Markup Manual for the Tübingen Partially Parsed Corpus of Written German (TüPP-D/Z)

This document describes the document markup of TuPP-D/Z, the Tubingen Partially Parsed Corpus of Written German. It describes the encoding of segmentation (into paragraphs, sentences, and words), of part-of-speech tags, and of morphological information. It also briefly shows how the levels of clauses, chunks, and topological fields are encoded, and complements Muller (2004), which describes the encoded phenomena in more detail.
Selfrefreshing analogue memory cell for variable synaptic weights

An analogue memory cell based on a local selfrefreshing technique is presented. The circuit is suitable for long-term storage of synaptic weights in analogue VLSI implementations of neural networks. The cell refreshes the voltage on a capacitor in a multilevel fashion by automatic comparison and confirmation with a range of discrete levels locally reproduced from an external reference signal.
Russian Morphology: Ressources and Java Software Application

This paper deals with development and application of Russian morphology software and resources. The approach is particularly dependent on advanced morphological analysis. The paper presents the structure, formats and content of Russian dictionaries and corpora. Relevant aspects of the UML data models, XML format and related technologies are surveyed. We introducee the system based on Java and Oracle 9i DBMS.
Improved Web Text Classification Method for Classifying Quality Safety Accidents

Web text classification, as one of the fundamental techniques of web mining, plays an important role in the web mining system. An improved term weighting method is proposed in this paper. Besides term frequency, the location of the term is also considered when calculating the weight of a term. Web pages were divided into 4 text blocks and each text block has its location weight. Experimental result shows that the precision of improved term weighting method is higher than traditional term weighting method.
Biofeedback and Virtual Environments

This paper explains potential benefits of indirect biofeedback used within interactive virtual environments, and reflects on an earlier study that allowed for the dynamic modification of a virtual environment's graphic shaders, music and artificial intelligence, based on the biofeedback of the player. The aim was to determine which augmented effects aided or discouraged engagement in the game. Conversely, biofeedback can help calm down rather than stress participants, and attune them to different ways of interacting within a virtual environment. Other advantages of indirect biofeedback might include increased personalization, thematic object creation, atmospheric augmentation, filtering of information, and tracking of participants' understanding and engagement. Such features may help designers create more intuitive virtual environments with more thematically appropriate interaction while reducing cognitive loading on the participants. Another benefit would be more engaged clients with a better understanding of the richness and complexity of a digital environment.
Research on methodology of document classification based on generalized learning

Document classification is one of important steps in document mining. In this paper, we present a new kind of document classification method based on generalized learning model (GLM for short). GLM is an extensible machine learning model with great flexibility. It may fuses symbolic learning, fuzzy learning, statistical learning, and neural learning together. If necessary, new learning model can be incorporated. To describe and represent documents more reasonably, we develop a approach to extract membership vector as features of documents. In view of the characteristics of document classification, two kinds of document classification methods are employed under GLM frame. One is based on fuzzy set theory, the other is based on support vector machine (SVM). These two kinds of methods can supplement each other to achieve better performance.
Sharing skills: using augmented reality for human-robot collaboration

Both stationary 'industrial' and autonomous mobile robots nowadays pervade many workplaces, but human-friendly interaction with them is still very much an experimental subject. One of the reasons for this is that computer and robotic systems are very bad at performing certain tasks well and robust. A prime example is classification of sensor readings: Which part of a 3D depth image is the cup, which the saucer, which the table? These are tasks that humans excel at. To alleviate this problem, we propose a team approah, wherein the robot records sensor data and uses an Augmented-Reality (AR) system to present the data to the user directly in the 3D environment. The user can then perform classification decisions directly on the data by pointing, gestures and speech commands. After the classification has been performed by the user, the robot takes the classified data and matches it to its environment model. As a demonstration of this approach, we present an initial system for creating objects on-the-fly in the environment model. A rotating laser scanner is used to capture a 3D snapshot of the environment. This snapshot is presented to the user as an overlay over his view of the scene. The user classifies unknown objects by pointing at them. The system segments the snapshot according to the user's indications and presents the results of segmentation back to the user, who can then inspect, correct and enhance them interactively. After a satisfying result has been reached, the laser-scanner can take more snapshots from other angles and use the previous segmentation hints to construct a 3D model of the object.
NOTAS SOBRE A INFLUÊNCIA DA ORIGEM DO CAPITAL SOBRE OS PADRÕES REGIONAIS DE COMÉRCIO EXTERIOR BRASILEIRO

O artigo tem como objetivo verificar se o padrao regional de comercio das empresas estrangeiras no Brasil se diferencia das empresas domesticas e, entre as proprias estrangeiras, se a regiao de origem do capital da empresa constitui fator importante na determinacao desse padrao, tanto em termos de origem e destino quanto em termos do conteudo tecnologico da pauta de comercio. A metodologia utilizada foi a analise de painel, para um conjunto representativo de empresas, utilizando dados de comercio exterior desagregados por regiao para os anos de 1989, 1997 e 2000. Abstract The aim of this paper is to verify if the regional trade pattern of the foreign companies is different from domestic companies and if there are differences between the foreigners according the region of origin of the capital. The methodology applied was the panel analysis, for a representative set of companies, using trade information disaggregated by region for the years of 1989, 1997 and 2000.
Email Spam Filtering: A Systematic Review

Spam is information crafted to be delivered to a large number of recipients, in spite of their wishes. A spam filter is an automated tool to recognize spam so as to prevent its delivery. The purposes of spam and spam filters are diametrically opposed: spam is effective if it evades filters, while a filter is effective if it recognizes spam. The circular nature of these definitions, along with their appeal to the intent of sender and recipient make them difficult to formalize. A typical email user has a working definition no more formal than "I know it when I see it. " Yet, current spam filters are remarkably effective, more effective than might be expected given the level of uncertainty and debate over a formal definition of spam, more effective than might be expected given the state-of-the-art information retrieval and machine learning methods for seemingly similar problems. But are they effective enough? Which are better? How might they be improved? Will their effectiveness be compromised by more cleverly crafted spam? We survey current and proposed spam filtering techniques with particular emphasis on how well they work. Our primary focus is spam filtering in email; Similarities and differences with spam filtering in other communication and storage media — such as instant messaging and the Web — are addressed peripherally. In doing so we examine the definition of spam, the user's information requirements and the role of the spam filter as one component of a large and complex information universe. Well-known methods are detailed sufficiently to make the exposition self-contained, however, the focus is on considerations unique to spam. Comparisons, wherever possible, use common evaluation measures, and control for differences in experimental setup. Such comparisons are not easy, as benchmarks, measures, and methods for evaluating spam filters are still evolving. We survey these efforts, their results and their limitations. In spite of recent advances in evaluation methodology, many uncertainties (including widely held but unsubstantiated beliefs) remain as to the effectiveness of spam filtering techniques and as to the validity of spam filter evaluation methods. We outline several uncertainties and propose experimental methods to address them.
The Blog Polarity Classification Technique using Opinion Mining

Previous polarity classification using sentiment analysis utilizes a sentence rule by product reviews based rating points. It is difficult to be applied to blogs which have not rating of product reviews and is possible to fabricate product reviews by comment part-timers and managers who use web site so it is not easy to understand a product and store reviews which are reliability. Considering to these problems, if we analyze blogs which have personal and frank opinions and classify polarity, it is possible to understand rightly opinions for the product, store. This paper suggests that we extract high frequency vocabularies in blogs by several domains and choose topic words. Then we apply a technique of sentiment analysis and classify polarity about contents of blogs. To evaluate performances of sentiment analysis, we utilize the measurement index that use Precision, Recall, F-Score in an information retrieval field. In a result of evaluation, using suggested sentiment analysis is the better performances to classify polarity than previous techniques of using the sentence rule based product reviews.
Situation Awareness and Dynamic Performance Training Systems: Some Reflections on the Literature

The majority of the literature on situation awareness is focused on its perceptual definition and modeling. In contrast, this presentation focuses on the importance of training simulation systems in increasing the potential for good situation awareness. Situation awareness is defined as an evaluative product based on expert performance criteria. A conventional information processing model is used to represent situation awareness as a generalized concept and modified for specific applications. Three salient factors affecting quality situation awareness are discussed: 1) high fidelity procedural training, 2) expert knowledge and experience, and 3) the strong indeterminates of attitude and emotional state. Additional issues are discussed, including: a developmental verses a gestalt framework for the perceptual process; information processing capacities; automaticity skills; traditional verses transactional training; the novice/expert relationship; expert and novice decision making; training device fidelity and ethnographic concerns; the dimension of unpredictability; inherent psychological abilities; and workload.
Application of Text Mining Based on Neural Network Computing

Today, numbers of documents that firms must process and with the extensive amounts of information available on the Internet, an automated intelligent method is needed to sort through all available documents or sites. It would be beneficial to start with grouping similar documents or sites together based on similarities. Classifying documents and sorting them into categories could be beneficial since in most cases, no one user would be interested in all the different categories of documents at the same time. Classifying a large number of documents would also make it easier to locate a specific document. In this paper, neural network computing based text mining (TM) and its application will be discussed.
Digital watermarks as a security feature for identity documents

The personal computer and digital photography boom of the last decade has fueled growth of a variety of high quality imaging peripherals. Personal computer scanners and color printers are now widely available as prices have fallen rapidly and quality continues to improve. The cost of a high-quality color scanner has stabilized under 150 dollars US. High-quality ink-jet printers are available for under 200 dollars US. Powerful, easy to use image processing software is typically with both printers and scanners at no additional charge. This combination of powerful technology at a low price point has increased the counterfeiting and forgery threat for valuable identity documents. As traditional, optically based techniques have become less effective against digital reproduction, new methods must be developed to mitigate the threat. Digital watermarks can be used to create self-authenticating identify documents to directly address these new threats. Digital watermarks are: imperceptible, so they do not impact the visual quality of the document; robust through the print and scan operation; and require not physical real estate on the document. This aper examines how digital watermarks can be used in identity documents. It explores the key system requirements and technical challenges in enhancing physical document authentication systems with digital watermarks.
Classifier combination and score level fusion: concepts and practical aspects

This review article is about the classifier combination and score level fusion, which have received considerable attention in the research field over the past decade. The classifier combination covers research concerning the algorithms and methodologies that describe classifier combinations from a pattern recognition perspective. For the score fusion technique, this article addresses the fusion problem in those situations where the feature representations of the data are not available. These two concepts are discussed from the point of view of their mathematical formulations. Some practical aspects and applications are also treated.
Reduced Keyboard Designs Using Disambiguation

There are a number of important applications where the accuracy of typed copy is less important than other criteria, such as the speed of entry, ease of learning, reduced keyboard size, provision for innovative keyboard designs and work methods, etc. Some of these applications include communication devices for the motor handicapped and rough drafting. The applications in question still provide single finger typing as opposed to multifinger entries for chord keyboards. One approach to keyboard design for such applications involves using a multicharacter key set. Because there is more than one character on a key, the number of keys can be reduced to a point limited only by the required accuracy of the text produced which is itself limited by the ability of “disambiguation” algorithms to decode the ambiguous text strings. Reducing the number of keys increases text entry rates and reduces learning time. Experiments with keysets of 10, 12, 14, and 16 keys have produced keystroke rates of 3.3 to 1.7 characters per second and a 6% keying error while the disambiguation programs can produce an accuracy of 85 to 95%. Learning time in the experiments was about 9 to 12 minutes. The experiments demonstrate the feasibility of increasing text entry rates and freeing the keyboard from architectural constraints.
Model-based PID control of constrained robot in a dynamic environment with uncertainty

This paper investigates a model-based method for robot manipulator control by describing the kinematics and dynamics of constrained robot when contacting a dynamic environment. Parameters which concern kinematic constraints of robot end effector, dynamic interactions and uncertainty of environment are represented from the environment side. By using Lagrangian formula, the whole dynamic expressions of the robot-environment system can be derived by the variables representing the joint angles. This modeling method is suitable for hybrid control laws to fulfil the manipulation task. The simulation results obtained from PID regulators are presented. Those results suggest that in practice, fixed PID parameters may not perform well because of the strong nonlinearity of the system and this will lead to further modified PID method such as a fuzzy logic self-tuning PID controller to achieve the time-varying tracking control of the robot manipulator.