Miracle-dz/UniFAR-FTUs huggingface dataset:
MPEG content summarization based on compressed domain feature analysis

This paper addresses automatic summarization of MPEG audiovisual content on compressed domain. By analyzing semantically important low-level and mid-level audiovisual features, our method universally summarizes the MPEG-1/-2 contents in the form of digest or highlight. The former is a shortened version of an original, while the latter is an aggregation of important or interesting events. In our proposal, first, the incoming MPEG stream is segmented into shots and the above features are derived from each shot. Then the features are adaptively evaluated in an integrated manner, and finally the qualified shots are aggregated into a summary. Since all the processes are performed completely on compressed domain, summarization is achieved at very low computational cost. The experimental results show that news highlights and sports highlights in TV baseball games can be successfully extracted according to simple shot transition models. As for digest extraction, subjective evaluation proves that meaningful shots are extracted from content without a priori knowledge, even if it contains multiple genres of programs. Our method also has the advantage of generating an MPEG-7 based description such as summary and audiovisual segments in the course of summarization.
ILAC: an automated layout tool for analog CMOS circuits

A description is given of ILAC (Interactive Layout of Analog CMOS Circuits), a CAD (computer-aided design) tool that automatically generates geometrical layout for analog CMOS leaf cells from netlist information and user-specified constraints on cell bounds and input/output locations. ILAC is the companion tool of IDAC, a design tool that sizes analog CMOS circuits from a library of proven schematics given a set of functional specifications and technological parameters. Unlike existing analog silicon compilers that use some predefined placement for a specific type of circuit, ILAC determines an optimal layout for any circuit and any set of input parameters. <<ETX>>
Scheme of Model Updating and Implement for Structural Dynamics Analysis

Model updating techniques are used to modify structural model for more accurate predictions of dynamics behavior. A simple survey on the model updating methods and correlation criteria is presented. Based on the inverse eigensensitivity method (IESM) and modal assurance criterion (MAC), a scheme of model updating for structures is presented and realized by user defined subroutine combined with APDL in commercial software ANSYS®. A four-DOF spring-mass system is assumed and updated, from which the predicted frequencies and MAC values are satisfied compared to the actual dynamics characteristics. This gives evidence that the presented model updating scheme is feasible and efficient. Furthermore, a cylindrical shell structure containing global and local modal information is established to research the updating ability of the scheme on some focused local modal information. The results due to the updated model of cylindrical shell structure show that not only the global modal data but also the local modal data have a good agreement with that of the actual structure.
A Meta-analysis of the Effectiveness of Computer-Assisted Instruction in Science Education

Abstract This meta-analysis investigated how effective computer-assisted instruction (CAI) is on student achievement in secondary and college science education when compared to traditional instruction. An overall effect size of 0.273 was calculated from 42 studies yielding 108 effect sizes, suggesting that a typical student moved from the 50th percentile to the 62nd percentile in science when CAI was used. The results of the study also indicated that some study characteristics such as student-to-computer ratio, CAI mode, and duration of treatment were significantly related to the effectiveness of CAI.
A Decision Aid Approach for Optimisation Problems Involving Several Economic Functions

Many concrete real life problems ranging from economic and business to industrial and engineering may be cast into a multi-objective optimisation framework. The redundancy of existing methods for solving this kind of problems susceptible to inconsistencies, coupled with the necessity for checking inherent assumptions before using a given method, make it hard for a nonspecialist to choose a method that fits well the situation at hand. Moreover, using blindly a method as proponents of the hammer principle (when you only have a hammer, you want everything in your hand to be a nail) is an awkward approach at best and a caricatural one at worst. This brings challenges to the design of a tool able to help a Decision Maker faced with these kinds of problems. The help should be at two levels. First the tool should be able to choose an appropriate multi-objective programming technique and second it should single out a satisfying solution using the chosen technique. The choice of a method should be made according to the structure of the problem and to the Decision Maker’s judgment value. This paper is an attempt to satisfy that need. We present a Decision Aid Approach that embeds a sample of good multi-objective programming techniques. The system is able to assist the Decision Maker in the above mentioned two tasks.
Depth-based representations: Which coding format for 3D video broadcast applications?

3D Video (3DV) delivery standardization is currently ongoing in MPEG. Now time is to choose 3DV data representation format. What is at stake is the final quality for end-users, i.e. synthesized views' visual quality. We focus on two major rival depth-based formats, namely Multiview Video plus Depth (MVD) and Layered Depth Video (LDV). MVD can be considered as the basic depth-based 3DV format, generated by disparity estimation from multiview sequences. LDV is more sophisticated, with the compaction of multiview data into color- and depth-occlusions layers. We compare final views quality using MVD2 and LDV (both containing two color channels plus two depth components) coded with MVC at various compression ratios. Depending on the format, the appropriate synthesis process is performed to generate final stereoscopic pairs. Comparisons are provided in terms of SSIM and PSNR with respect to original views and to synthesized references (obtained without compression). Eventually, LDV outperforms significantly MVD when using state-of-the-art reference synthesis algorithms. Occlusions management before encoding is advantageous in comparison with handling redundant signals at decoder side. Besides, we observe that depth quantization does not induce much loss on the final view quality until a significant degradation level. Improvements in disparity estimation and view synthesis algorithms are therefore still expected during the remaining standardization steps.
Investing Wisely: Citation Rankings as a Measure of Quality in Library and Information Science Journals

The library and information science field is currently confronted with difficult decisions about how best to allocate acquisition expenditures among increasingly expensive journals. This article measures the return-on-investment of serial expenditures through the use of citation analysis, which is a widely used approach to ascertaining journal quality. The frequency of citations to 116 library science journals in the bibliographies of 11 premier library journals over the period 2002–2005 is tabulated, and a price-per-citation figure (based on subscription prices) is also computed.
Spatial and Grayscale Metadata for Similarity Searches of Image Databases

This paper presents a content-based image retrieval process wherein the user identifies a feature of interest using a region quadtree decomposition of the image, spatial statistics and histograms of the grayscale values of the feature definition are calculated, and the result is compared to a database of these same calculations that have been performed on similar images. The sum of squared differences between the indices calculated for the quads that form the feature of interest and corresponding quads in the database yields a ranked list of matching image tiles. In an analysis of Landsat 7 imagery of North Georgia and an IKONOS panchromatic image of Kalamazoo, Michigan, we found that the retrieval success rate depends on the spatial and spectral characteristics of the feature of interest and the configuration of quads used to define the feature.
Validatie van de Nederlandstalige versie van de Mindful Attention Awareness Scale (MAAS)

Aandachttraining en aandachtgerichte cognitieve therapie zijn in korte tijd zeer populair geworden als behandelmethode voor diverse klachten. Centraal in deze vormen van training en therapie staat het ontwikkelen van ‘mindfulness’. Maar om verbeteringen in welbevinden tijdens de training daadwerkelijk hieraan te kunnen toeschrijven, is het nodig om mindfulness voor en na de training te kunnen vaststellen. De huidige studie onderzocht of, middels een korte schriftelijke vragenlijst, mindfulness op een betrouwbare en valide manier kan worden gemeten. De Mindfulness Attention Awareness Scale ( MAAS ) werd ontwikkeld door Brown en Ryan (2003), door ons vertaald en bij drie verschillende onderzoeksgroepen uit de Nederlandse bevolking afgenomen. De resultaten bevestigden eerder Amerikaans onderzoek en lieten zien dat de vragenlijst een dimensie meet, welke een betrouwbare indicatie geeft van de mate van mind fulness. Gezien de eenvoudige formulering van de vragen en de relatief korte afnameduur achten wij de lijst geschikt voor het gebruik in training en therapiesettings.
Commemorate National Multiple Sclerosis Day(28th of May): Seek Funding for Research

Multiple sclerosis (MS) is a chronic and often progressive inflammatory disease that attacks the myelin sheath of the central nervous system (CNS) presenting a special kind of sclerotic lesions [1]. The northern hemisphere has a high prevalence of MS. In this disease, a cell-mediated immune response accounts for discrete plaques of demyelization at sites throughout the CNS. The pathophysiology is complex and still under investigation. Some consider MS a pathological entity [2] while some consider it a clinical entity [3]. The unknown underlying condition causes damage in two phases. First some MRI-abnormal areas with hidden damage appear in the brain and spine, followed later by leaks in the blood–brain barrier where immune cells infiltrate causing demyelination [4].
Scalable Phrase-Based, Joint Probability Model for Statistical Machine Translation

The Phrase-Based, Joint Probability Model provides a strong probabilistic framework within which to learn both word and phrase translations simultaneously. However, the model’s usefulness is limited by its computational complexity. This project proposes novel hybrid models which use the highly optimized standard phrase-based models to restrict and guide the search space of the Joint Probability Model. We show that this reduces the complexity of the model and allows it to scale up to training corpora that are four times larger, while at the same time improving the quality of the final translations. We also present several other methods for reducing the training time and improving the quality of the hybrid models.
Nonlinear internal model control and model predictive control using neural networks

The ramifications of incorporating neural networks into two model-based control architectures, namely internal model control (IMC) and model predictive control (MPC), are considered. The development of a neural network analog to the conventional IMC design is described, the controller behavior is discussed, and control architectures necessary to improve controller performance are presented. The performance of the neural network controller under less restrictive assumptions is examined, and a neural network analog to the conventional MPC design is developed and tested. An IMC-type neural network controller in which the process model replaced by a neural network gives very good performance, even when only partial state data are available, also gives excellent performance. These results indicate that neural networks can learn accurate models and give good nonlinear control when model equations are not known. Suggestions for improving performance are presented. <<ETX>>
Jitter characteristics of timing recovery scheme using a prefilter

Analysis of timing jitter is presented for a baseband polar system, BPSK and QPSK with AWGN. A cosine roll-off bandlimiting scheme is assumed. The timing recovery circuit is composed of a prefilter, a square-law device, and a timing tank. Normalized jitter spectral densities and rms jitter are defined and calculated in order to examine jitter characteristics in various systems in common. The normalized jitter spectral density for the S × S component becomes negligibly small for every roll-off factor. Therefore, the rms jitter is determined only with the S × N and N × N components. The S × N component is predominant for large Eb/N0 and the total rms jitter is almost inversely proportional to the square root of Eb/N0. Numerical calculation in QPSK for a tank Q of 100 shows that a jitter reduction effect of a prefilter exists when Eb/N0 is greater than 10 dB and that the rms jitter decreases with increasing Eb/N0 and increasing roll-off factor. © 2004 Wiley Periodicals, Inc. Electron Comm Jpn Pt 1, 87(9): 28–35, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecja.10206
Cs2(SO4)0.57(SeO4)0.43·Te(OH)6, an adduct between dicaesium sulfate selenate and telluric acid

The title compound, dicaesium sulfate selenate–telluric acid adduct, Cs2(SO4)0.57(SeO4)0.43·Te(OH)6, is a solid solution in the series Cs2(SO4)·Te(OH)6/Cs2(SeO4)·Te(OH)6. It crystallizes in the same structure as the end member Cs2(SeO4)·Te(OH)6 in space group P21/c, whereas the corresponding sulfate adopts another structure type and crystallizes in space group R3. The structure contains planes of statistically distributed SO4/SeO4 tetra­hedra alternating with planes of Te(OH)6 octa­hedra, and with Cs+ cations situated between the planes. Both Te atoms lie on centres of symmetry.
Building Interoperable Learning Objects Using Reduced Learning Object Metadata

The new e-learning generation depends on Semantic Web technology to produce learning objects. As the production of these components is very costly, they should be produced and registered once, and reused and adapted in the same context or in other contexts as often as possible. To produce those components, developers should use learning standards to describe these objects in order to support interoperability. IEEE Learning Object Metadata (LOM) is the most dominant standard for describing learning objects, in which 76 different elements are used to describe the different aspects of e-learning. Nonetheless, it will still be time consuming to build these learning objects. This paper introduces a model for building Global Interoperable Learning Objects (GILO) for the e-learning community. This is achieved by using a reduced set of the LOM elements, and giving a unique global ID to the learning object. This will enable software agents to query these learning object repositories, to automatically deliver the required material to the e-learning consumer.
Applications of MHT to dim moving targets

This paper discusses the application of a particular implementation of Multiple Hypothesis Tracking (MHT) to the problem of detection and tracking of dim targets in a heavy clutter or false alarm background. The MHT method and the performance improvement associated with MHT for these applications is well documented [1—6], but the actual implementation has been limited due to the computational load and complexity associated with "traditional" implementations. We present an approach (Structured Branching) that offers significant computational savings as compared with alternative approaches, and can maintain hundreds of "possible" tracks that are initiated in a dense clutter or false alarm background without overwhelming computational or memory requirements. Further, this method can be applied to much more limited implementations according to the computational resources available—there is minimal "overhead" associated with Structured Branching (SB) since hypotheses are not propagated explicitly. The SB algorithm is described, highlighting the ways in which computational savings are achieved, and simulation results are presented. Then, approximate techniques are developed for predicting the performance of MHT (any implementation, not just SB), and results comparing predicted performance with simulation results are presented.
GPU-Based Image Pyramid Transform Algorithm

With the development of semiconductor technology, the GPU's floating point computing capacity improves rapidly. How to GPU rendering from the traditional video game applied to the general computing has become a highlight in the research field of high performance computing.Pyramid transform is commonly used image processing algorithms. The experiment proves that NVIDIA GPU-based pyramid transform of image and rebuilding the image, as opposed to CPU platform acceleration achieved good results.
Retracted: Semantic Information Integration with Linked Data Mashups Approaches

The introduction of semantic web and Linked Data helps facilitate sharing of data on the Internet more easily. Subsequently, the resource description framework (RDF) is the standard in publishing structured data resources on the Internet and is used in interconnecting with other data resources. To remedy the data integration issues of the traditional web mashups, the semantic web technology uses the Linked Data based on RDF data model as the unified data model for combining, aggregating, and transforming data from heterogeneous data resources to build Linked Data mashups. There have been tremendous amounts of efforts of semantic web community to enable Linked Data mashups but there is still lack of a systematic survey on concepts, technologies, applications, and challenges. Therefore, in this paper, we investigate in detail semantic mashups research and application approaches in the information integration. This paper also presents a Linked Data mashup application as an illustration of the proposed approaches.
Texture classification using transform vector quantization

Abstract This paper presents a method for the classification and coding of textures based upon the use of trans-form vector quantization. Techniques for texture classification and vector quantization similarly process small, nonoverlapping blocks of image data which are extracted independently from the image. Localspatial frequency features have been identified as being appropriate for texture classification, indicatingthat a transform vector quantization scheme should be capable of characterizing and classifying texturedregions. A data set consisting of 7 natural textures is used to demonstrate the utility of this approach.The experimental results show acceptable classification rates and suggest avenuws for future researchwhich will yield significant improvements in future work. 1 Introduction Various approaches have been adopted for the solution of the texture classification problem, includingthe use of structural pattern recognition, second order statistical analysis and local spatial frequency
Laser Signature Prediction Using The VALUE Computer Program

A variety of enhancements are being made to the 1976-vintage LASERX computer code. These include: - Surface characterization with BDRF tabular data - Specular reflection from transparent surfaces - Generation of glint direction maps - Generation of relative range imagery - Interface to the LOWTRAN atmospheric transmission code - Interface to the LEOPS laser sensor code - User friendly menu prompting for easy setup Versions of VALUE have been written for both VAX/VMS and PC/DOS computer environments. Outputs have also been revised to be user friendly and include tables, plots, and images for (1) intensity, (2) cross section,(3) reflectance, (4) relative range, (5) region type, and (6) silhouette.
Error-resilient image compression based on JPEG

JPEG-compressed images, when transmitted over a noisy channel, are highly susceptible to errors. The effects of bit errors on images compressed by any method, including JPEG, are significantly augmented since the majority of statistical redundancies are removed in the compression process. Furthermore, errors affecting the run-lengths and Huffman codewords within JPEG have a much more profound influence on reconstructed images than those affecting only coefficient values. This paper presents a detailed investigation of uncompressed and JPEG-compressed (baseline and progressive) image transmission in noisy channels. Several modifications within JPEG are proposed to improve reconstructed image quality. Among the techniques investigated, a hybrid technique, combining the concepts of the baseline and progressive JPEG modes, appears to give the best performance. Here, the DC coefficients (with absolute and/or fixed bit encoding), AC codewords, and some positional information are separately coded and protected using forward error correction. The actual AC coefficient values are sent separately. This partitioning of codewords and values enable isolating, for special protection, portions of the representation that are highly sensitive to errors and that may cause lengthy error propagation. It enables sending `view-quality' images in the presence of a channel bit error rate as high as 0.01.
Adding New Vocabulary While Playing Casual Games: Young People in Brunei as a Case Study

Playing casual games has become a popular activity for young people. One main reason is casual games can be played everywhere using smart phones or tablets. The easy accessibility has made casual game the most playable video game during leisure time. Although playing casual games is a leisure activity, without knowing, young people have developed a new group of vocabulary. Drawing upon data from observations and think-aloud techniques, this paper presents the findings of how young people develop new vocabulary while playing casual games.
Three-dimensional performance of an LMS adaptive array with inverted-F elements

The performance of an adaptive array with two inverted-F elements is analyzed by using the method of moments. A random signal model for mobile communication in a typical urban area is used. Three-dimensional analysis is applied to give a clear expression of the array output signal-to-interference plus noise ratio (SINR) performance. Also, a factor called SINR pattern angle ratio (PAR) is introduced with which a quantitative evaluation of the SINR patterns becomes possible. By using the PAR, the array performance for different array parameters such as inverted-F antenna (IFA) element orientations, interelement spacings and incident signal directions are computed. As a result, the IFA element is found preferable to a quarterwave monopole array in the assumed signal environment. >
Perceptual tools for quality-aware video networks

Monitoring and controlling the quality of the viewing experience of videos transmitted over increasingly congested networks (especially wireless networks) is a pressing problem owing to rapid advances in video-centric mobile communication and display devices that are straining the capacity of the network infrastructure. New developments in automatic perceptual video quality models offer tools that have the potential to be used to perceptually optimize wireless video, leading to more efficient video data delivery and better received quality. In this talk I will review key perceptual principles that are, or could be used to create effective video quality prediction models, and leading quality prediction models that utilize these principles. The goal is to be able to monitor and perceptually optimize video networks by making them “quality-aware. ”