Miracle-dz/UniFAR-FTUs huggingface dataset:
A robust servo based headtracker with auto-zooming in cluttered environment

In this paper, we establish a nearly real-time surveillance tracking system, which is able to detect any person who intrudes to a prohibited area and lock his head image at the scene center. The entire underlying algorithm consists of a motion detector, a modified ellipse head tracking algorithm, auto-zooming ability, and a VPDA filter which is modified by probabilistic data association filter (PDA filter). The system operates about 35 ms and actively controls the camera platform pan and tilt motion to track a person in real environment. Finally, a number of experiments are conducted to validate the effective functionality of the head tracking system.
The changing face of technology in distributed systems

Discusses some distribution support aspects, which are the structuring principles and the technologies that will change, or that are already changing, the face of distributed systems, and investigates how to take advantage of them. In particular, I examine internetworking and interprocess communication, the basis for the formation of large-scale distributed systems. I also discuss how multipoint communication, logical addressing, membership management, and topology protocols can be used to implement efficient and robust infrastructures. <<ETX>>
ELLIPS: providing web-based language learning for Higher Education in the Netherlands

This paper presents the overall considerations and pedagogical approach which were at the basis of the development of an innovative web-based CALL application, Ellips (Electronic Language Learning Interactive Practising System). It describes the program’s most salient features, illustrating in particular the technical challenges involved in the realization of this multilingual, server-hosted, database-supported language-learning application. Ellips, the product of a cooperative project between four Dutch universities, offers effective web-based support for language learning in Higher Education (HE) institutions. Ellips focuses particularly on grammar training, listening and pronunciation skills; although it can be accessed on its own, it has been created with integration with virtual learning environments (VLEs) like Blackboard and WebCT in mind. As a matter of fact, Ellips offers functionality lacking in these systems, which have not been specifically developed for language learning and offer more assessment than practising opportunities. Moreover, in Ellips all learning materials are coded with language-specific metadata (mainly based on descriptors derived from the Common European Framework), so that developers can easily find and reuse materials and so-called ‘semi-adaptivity’ is allowed (students automatically receive more exercises on the topics which they have not yet mastered). Other important features of Ellips are full Unicode support, extensive feedback (for every item in an exercise and for the whole exercise), a student-tracking system, the use of (streaming) audio and video, and the possibility to record student input and store it in a portfolio.
Topic Trend in Aceh Online Newspaper Based on Significant Term

Abstract. Online newspaper is very common these days and provides information faster than hardcopy newspaper. Online newspaper can be accessed very easily and mostly free. Lots of articles are published every day in online newspaper so we can get lots of information from it. Text and web mining is a way to gain information from online newspaper. This research is trying to find topic trend in Aceh online newspaper based on significant term. This research uses articles from “Serambi Indonesia”, one of newspaper that has online version, as the online newspaper data source. This research has mined 28.071 articles in one year from Serambi Indonesia online newspaper. The research approach has two steps: (i) Data preprocessing; (ii) Significant term extraction and term history generation. The first step uses agent to download the articles automatically and extracts the content of those articles. The second step uses an existing external memory approach to extract significant terms while computing term history simultaneously. Significant term is a series of words that are significant enough to represent one event, action or concept. Term history of one significant term is the term frequency over consecutive time periods. This research has found out 1.402. 634 significant terms and stored them in database. The terms can be searched and viewed as graphics divided by months as period division. So by knowing the significant term, this research provides topic trend in Aceh online newspaper in monthly time. Keywords: online newspaper, significant term, topic trend, text and web mining
An Intergrid-Boundary Definition Method for Overset Unstructured Grid Approach

The use of the overset concept for the unstructured grid method is relatively unexplored. However, the overset approach can extend the applicability of the unstructured grid method for real engineering problems without much need for code development. The multiple moving-body problem is one of those applications. Improvement in local resolution for Euler/Navier-Stokes computations on unstructured grids is another use of the overset concept. An efficient and robust algorithm to localize the intergrid boundaries for the overset unstructured grid method is proposed. Simplicity and automation in the intergrid-boundary definition are realized using the wall distance as a basic parameter. The neighbor-to-neighbor jump search algorithm is efficiently utilized in the method. The robustness and efficiency of the search is improved by the use of subsidiary grids that are generated as a byproduct of the Delaunay triangulation method. The basic procedure of the present method is described for a multielement airfoil problem. The effects of the overset method on the solution accuracy and the convergence are tested by ONERA M6-wing
EM-code optimization algorithm using tree pattern matching

The ACK intermediate code optimizer generates a good code through performing a peephole optimization over the EM intermediate code. The peephole optimization is very cost efficient and should use a string pattern matching algorithm to find the optimization pattern corresponding to the EM intermediate code when it is in the optimization. The authors have designed and implemented a tree pattern matching algorithm for more efficient optimization by improving the string pattern matching method of the ACK intermediate code optimizer. For this, an appropriate EM tree is constructed to the tree pattern matching of the EM code with a sequential structure from the front end of the ACK. Also, the pattern described in the optimization pattern table and the replacement should be reconstructed as a tree structure. The tree pattern matching optimizer conducting an optimization in real-time, applies a tree pattern matching algorithm in order to find an optimization pattern more efficiently while it circulates in the top-down method. Thus the tree pattern matching method requires a searching time to find an optimization pattern that is less than the string pattern matching method of ACK.
A COMPARISON OF SUBSCORE REPORTING METHODS FOR A STATE ASSESSMENT OF ENGLISH LANGUAGE PROFICIENCY

Educational tests that assess multiple content domains related to varying degrees often have subsections based on these content domains; scores assigned to these subsections are commonly known as subscores. Testing programs face increasing customer demands for the reporting of subscores in addition to the total test scores in today's accountability-oriented educational environment. While reporting subscores can provide much-needed information for teachers, administrators, and students about proficiency in the test domains, one of the major drawbacks of subscore reporting includes their lower reliability as compared to the test as a whole. This dissertation explored several methods of assigning subscores to the four domains of an English language proficiency test (listening, reading, writing, and speaking), including classical test theory (CTT)-based number correct, unidimensional item response theory (UIRT), augmented item response theory (A-IRT), and multidimensional item response theory (MIRT), and compared the reliability and precision of these different methods across language domains and grade bands. CTT and UIRT methods were found to have similar reliability and precision that was lower than that of augmented IRT and MIRT methods. The reliability of augmented IRT and MIRT was found to be comparable for most domains and grade bands. The policy implications and limitations of this study, as well as directions for further research, were discussed.
Semi-Supervised Multi-Label Classification Through Topological Active Learning

Multi-label classification is becoming increasingly widespread as a data mining technique. Its objective is to categorize models in several non-exclusive groups, and is applied in such areas as news categorization, image labeling and music classification, among others. Our contribution is to use the paradigm of active learning with the topological power of the Act-SOM for semi-supervised multi-label classification, taking into account the multi-label information, and selecting unlabeled data which can lead to the largest reduction of the expected model loss. This paper deals with various multi-label datasets by presenting in active learning, a set of results ranging from: 1) Transductive classifier TSVM with relevance sampling methods for multi-labeled data in various application domains; 2) Proposed semi-supervised classifier Act-SOM in multi-label active learning, adopting a strategy relative to the evaluation by the uncertainty of the labels. Act-SOM based on active learning selects the most uncertain data while clearly improving the test rate with less than 30% of labeled instances added, which is our main contribution. We present the results from the statistical tests using critical diagrams. Thus, potential of the proposed multi-label classification method is demonstrate, due mainly to the competitive properties with global consistency of the semi-supervised Act-SOM through topological active learning.
To Improve Content Based Face Retrieval By Creating Semantic Code Words

The importance and the complete amount of human face photos make manipulations e.g., search and mining of large-scale human face images a really vital research problem and allow many real world applications. We aim to make use of automatically detected human attributes that contain semantic prompts of the face photos to improve content based face retrieval by constructing semantic code words for efficient large-scale face retrieval. By leveraging human attributes in a scalable and systematic framework we propose two orthogonal methods named attribute-enhanced sparse coding and attribute embedded inverted indexing to perk up the face retrieval in the offline and online stages. We examine the efficiency of different attributes and vital factors necessary for face retrieval. The purpose in this paper is to deal with one of the imperative and challenging problems large-scale content-based face image retrieval. Given a uncertainty face image content-based face image retrieval seeks to find similar face images from a large image database. It is and facilitates equipment for many applications including automatic face annotation crime investigation etc.
An Introduction to Dublin Core

This tutorial will provide a basic introduction to the Dublin Core (DC) metadata set, starting with a brief overview of how and why DC began and how it has developed to the present day. Simple DC and Qualified DC will be explained, with practical examples of real-life usage to illustrate the application of DC in different working environments. The tutorial will have a 'hands on' approach, giving participants an opportunity to explore the elements through group work and to use both Simple and Qualified DC to describe objects.
Applying mathematics to digital image processing using a spreadsheet

Students are familiar with digital images, most likely because of their mobile phone camera, and many are also familiar with the post-processing possibilities either using in-camera tools or through tools such as Photoshop. Many students have a good working knowledge of spreadsheets particularly Microsoft Excel as they are widely used as a support tool in their course. This paper describes a tool developed to allow students to make use of their spreadsheet skills in applying the mathematical techniques necessary to implement a variety of image modifications. It is an Excel add-in which decomposes the image to its red, green and blue parts, putting each into a separate worksheet. It can also recompile a JPG image from the data in these worksheets.
A Holistic Study on Electronic and Visual Signal Integration for Efficient Surveillance

Surveillance systems are widely deployed with military, public security, urban management, and transportation applications. They are mainly used for monitoring people’s locations, behavior, and activities. In addition, they can collect information from other objects such as vehicles. Currently, visual (V ) signals play a major role in surveillance because they provide copious details about objects of interest. With an increasing number of surveillance cameras deployed, the volume of surveillance videos grows rapidly, which poses challenges for efficient surveillance. Besides visual signals, electronic (E ) signals are very common in surveillance systems as wireless devices are pervasive. Electronic signals show great potential upon integration with visual signals for efficient surveillance. In this dissertation, we study efficient surveillance on both visual and electronic data. First, we explore how to process large surveillance video datasets efficiently with “big data” processing tools. This dissertation focuses on two types of objects of interest: vehicles and humans. We propose TaG, an augmented MapReduce framework for time-bounded analytics jobs on large traffic videos. By studying the characteristics of traffic videos, we propose a novel sampling algorithm based on motion information encoded in videos, which we embody in the MapReduce framework. Besides traffic analytics, we also study rapid retrieval in surveillance videos where humans are the objects of interest. We propose SurvSurf, a human retrieval system using large
Calibration of components in an optical measurement system for obtaining 3D data of complex parts

In this paper, we study calibration of all components in optical measurement system, which is a fundamental issue in optical measurement. For physical components we use Zhang’s method to calibrate the binocular cameras. And we utilize Zhang’s method in fringe projection profilometry to calibrate the projector, in which detailed calibration steps are given. For virtual components, three vital coordinate systems need to calibrate in our measurement system. We use cloud registration and epipolar rectification algorithm to locate their position and orientation. The results show that accuracy of physical components’ calibration parameters is enough and calibration algorithm for virtual components is feasible.
DEVELOPMENTAL SCIENCE REVIEW Biased to learn language

Abstract Some recent publications that explore the foundations of early language development are reviewed in this article. The reviewadopts the pivotal idea that infants’ advancements are helped by the existence of different types of biases. The infant’s disco veryof the phonological properties of the language of the environment, as well as their learning of words, is assisted by differenttypes of processing biases, ranging from perceptual to social factors. Introduction When thinking about research topics in language develop-ment over the last ten years, I believe that the ﬁndingwith the largest impact is the discovery that 8-month-oldinfants are able to segment words from a continuousstream of syllables, after just 2 minutes of exposure.Saffran, Aslin and Newport’s (1996) publication pro-voked a tsunami of studies in the sea of early languagedevelopment. Discovering the scope and limits of thecapacity to extract regularities from the input was put atthe top of the agenda of many different laboratories. Alook at the papers recently published in
Two Step Verification for Withdraw the Amount from ATM

Two step verification of ATM card is required to prevent the illegal access of an account. This paper describes the two step verification of account by matching the distance of the top, left, right, bottom of the human skull image. The skull of the human is captured by the pseudo 3D image capture at the ATM terminal. The feature points are calculated and encrypted and sent to the server via a secure channel. The encryption is based on bio keys. If the value matches with the encoded value in the database, it allows for withdraw of amount. If not it declines to withdraw.
Techniques to build and reuse assets

Several techniques have been proposed to achieve the goal of maximising the reuse of basic software artifacts, of architectural designs and even of the software designers’ experience in solving problems in specific contexts. All of these techniques offer partial (sometimes overlapping) views and solutions to the problem of software development: individually, they support only one or some parts and phases of the software life cycle. We review the contributions of each, and their place in the software life cycle. 7.1. Rationale The aim of the chapter is to present the most relevant techniques to build and reuse software. For this reason, the structure of the chapter reflects the relationships between the techniques. Section 7.2 describes object oriented techniques (OOT) with specific reference to OO analysis (OOA), OO design (OOD), and OO programming (OOP). The following three sections (7.3 to 7.5) describe techniques which have emerged from the OO world, namely design patterns, OO frameworks, and component based development. These three sections contain dependencies on each other and on OOT. In particular, design patterns are an attempt to overcome the limitation of the pure code reuse of the class library approach by emphasising the importance of design reuse. OO frameworks are an attempt to combine code reuse (class library) with design reuse (design patterns). Component based development is an attempt to reduce the complexity of OO framework use and reuse: a component is a black box building block with a well defined interface and an internal complexity that can range from a simple class to a complete framework. Section 7.6 describes software agents, which can be considered a promising reuse technique. Section 7.7 describes software architectures, which represent an independent research area. For most of the techniques (where appropriate), a list of enabling methodologies and technologies is presented. They include UML for OOA and OOD, CORBA and DCOM for OO frameworks, and Java Beans and ActiveX for component based development.
The 220 MHz ITS spectral allocation: potential, pitfalls, and applications

In 1992 five narrowband frequency pairs in the 220-222 MHz band were allocated for intelligent transportation system (ITS) applications. These allocations are capable of supporting low-rate digital communications (4-30 kb/s). This article examines potential applications within the ITS program which can effectively use the low data rate that these allocations can provide. An overview of the narrowband wireless data communication challenges and the communication theoretic techniques likely to be employed on high-performance modems is provided. An experimental system was built, and preliminary field test results are presented which demonstrate that spectral efficiencies in excess of 3 b/s/Hz are achievable in practical modems.
A new binary source coder and its application in bi-level image compression

We present a new binary source coder. The new coder is a combination of many truncated-run-length coders governed by an adaptive probability estimation process. The estimation process can be implemented effectively as a finite-state machine. We apply the new coder to lossless bi-level image compression and compare the results with state-of-the-art methods. The results indicate that the new coder is comparable to current ones. The proposed coder is very simple for hardware and software implementation.
The Specification Language TimeML

In this paper we provide a description of TimeML, a rich specification language for event and temporal expressions in natural language text, developed in the context of the AQUAINT program on Question Answering Systems. Unlike most previous work on event annotation, TimeML captures three distinct phenomena in temporal markup: (1) it systematically anchors event predicates to a broad range of temporally denotating expressions; (2) it orders event expressions in text relative to one another, both intrasententially and in discourse; and (3) it allows for a delayed (underspecified) interpretation of partially determined temporal expressions. We demonstrate the expressiveness of TimeML for a broad range of syntactic and semantic contexts, including aspectual predication, modal subordination, and an initial treatment of lexical and constructional causation in text.
Effects of Pedagogical Agents on Students’ Mathematics Performance

This experimental study investigated the effects of the use of two versions of a pedagogical agent named personal instructing agent (PIA) on the mathematics performance of students. The first version exhibits synthetic facial expressions while the second version does not exhibit facial expression (i.e., neutral facial expression). Two groups of students with the same levels of prior knowledge in mathematics utilized two different versions of PIA. The first group—the facial group—utilized a PIA that provides textual and facial expressions feedback (happy, sad, surprise, and neutral facial expressions). The second group—the nonfacial group—used the same software except that PIA only exhibited neutral facial expression. The study showed that the mathematics scores of the students in the facial group significantly improved as compared with those who are in the nonfacial group. The posttest scores of the facial group were found significantly higher than those of the nonfacial group. The study showed that PIA that exhibited synthetic facial expressions improved students’ mathematics learning. It is concluded that synthetic facial expressions and textual feedback of pedagogical agent can be utilized to help students learn to solve mathematics problems. Limitations and recommendations are also presented.
Main problems of programming novices and the right course of action

Programming is required in all business systems and that makes programming courses vitally important. Regardless of this fact, programming courses experience rather high failure rates. There is a need to find the reasons for this kind of state and to determine the methods that can be used in order to improve mentioned situation. This paper gives an overview of conducted research regarding described state and provides a conclusion about the difficulty of programming courses and problems that can be detected. The paper also analyses existing efforts in improving education process and gives conclusion about possible courses of action.
A Meta-Conceptual Modeling Approach for Change Modeling in Applied Ontology

Formal ontologies are explicitly representation of domain knowledge. Ontology change management should ensure maintaining its consistency, so that its users can continue to cooperate and understand each other. This paper presents a meta-conceptual modeling approach for change modeling in the domain of applied ontology. This modeling approach makes use a mathematical structure to model ontologies and its changes in order to make possible the qualification of changes regarding its consistency. Actually, the paper focuses on the meta-conceptual modeling approach inspired by Guarino's formal ontology building process.