Miracle-dz/UniFAR-FTUs huggingface dataset:
A systolic array computer

A high-performance systolic array computer has been designed by CMU and is currently under construction. The first copy of the machine, to be built by CMU together with its industrial partners before the end of 1985, will incorporate a programmable systolic array of ten linearly connected cells. Each cell in the systolic array is capable of performing 10 million floating-point operations per second (10 MFLOPS), giving the total machine a peak performance of 100 MFLOPS, or higher if additional cells are used. This particular systolic array computer is named Warp, suggesting that it can perform computations at a very high speed. The 10-cell systolic array, with one cell implemented on one board, can process 1024-point complex FFTs at a rate of one FFT every 600 µs. Under program control, the same array can perform many other primitive computations in signal, image, and vision processing, including two-dimensional convolution, dynamic programming, and real or complex matrix multiplication, at a rate of 100 million floating-point operations per second. Users may view the systolic array as an array of conventional "array processors," which can efficiently implement not only systolic algorithms where communication between adjacent cells is intensive, but also non-systolic algorithms where each cell operates on its own data independently from the rest. This paper describes the hardware organization of the Warp machine.
Microblogging: A Semantic Web and Distributed Approach

While microblogging has quickly gained a lot of interest in the Web 2.0 community, it still has not been leveraged to the Semantic Web unlike blogs and wikis. This paper describes the features, methods and architecture of a distributed Semantic Web microblogging system, as well as the implementation of an initial prototype of this concept that provides ways to leverage microblogging with the Linked Data Web guidelines.
Knowledge acquisition by outsourced service providers from aging workforce of oil and gas industry

Purpose – The purpose of this paper is to provide an understanding of the major critical success factors involved in knowledge acquisition from an aging oil and gas workforce by outsourced service providers and find the outcome. In addition, the authors are also interested in finding out the outcome for the client and the service provider by following these critical success factors.Design/methodology/approach – The authors shortlisted two outsourced firms for studying, primarily because they deliver lots of service support work to oil and gas firms. For the exploratory nature of this case study, a structured, open‐ended interview was conducted. Through face‐to‐face interviews with 12 senior managers, primary data were collected. Upon content analysis of data collected, the framework was evaluated.Findings – The results of this study indicate that both client and service providers can benefit by following major critical success factors for knowledge acquisition. From the open‐ended interview with the two c.
A Simple Approach for Scientific Document Categorization

— Classification is the alignment of data or items in predefined labeled groups based on resemblances. Exponential progression amount of scientific documents leads to uncontrollable physical classification. Feature extraction is the crucial condition of automatic document classification. TF-IDF (term frequency-inverse document frequency) is frequently used to represent the text feature weight. This paper proposes a new yet simple feature weighting scheme by modifying TF-IDF formula. The experimental results show that the modified method improves the accuracy and other parameters.
Methods for Estimation and Inference in Modern Econometrics

51 one does not have a deck of cards available. Second, the connections with mathematics involve several subfields, and not only combinatorics . de Bruijn sequences and graphs, the Mandelbrot set, Penrose tiling, Bayesian analysis for reversible Markov chains (Page 42), and the I Ching. The last chapters are, however, less directly related to maths (even though Chapter 10 about great mathematical magicians includes connections with topology). Interestingly (for us academics), the book mentions a (Banff ) BIRS 2004 workshop relating to magics via de Bruijn sequences and Gray codes, with the traditional picture in front of the (old) BIRS building. (Another item of information: IBM stands for International Brotherhood of Magicians! )
A model-based Q-learning scheme for wireless channel allocation with prioritized handoff

We propose a new channel allocation scheme for improving the quality of service in cellular mobile networks. The proposed algorithm prioritizes handoff call requests over new call requests. The goal is to reduce the handoff failures while still making efficient use of the network resources. A performance measure is formed as a weighted linear function of new call and handoff call blocking probabilities. This problem is formulated as a semi-Markov decision process with an average cost criterion. A simulation-based learning algorithm is then developed to approximate the optimal control policy online using the generated samples from direct interactions with the network. It is based on an approximate model that is estimated simultaneously while learning a control policy. The estimated model is used to direct the search for an optimum policy. Extensive simulations are provided to assess the effectiveness of the algorithm under a variety of traffic conditions. Comparisons with some well-known allocation policies are also presented. Simulation results show that for the traffic conditions considered in this paper, the proposed scheme has a comparable performance to the optimal guard channel approach.
The Impact of Communication Modality on Perceived Credibility of Panel Members

The impact of communication modality on credibility is not yet fully understood. Therefore, the purpose of this study was to examine the influence of modality on the perception of news panel members. A political debate between four political analysts was presented in three different modalities, as television broadcast (TV condition), as radio broadcast (radio condition), or as magazine article (print condition). Participants evaluated panel members in terms of credibility. Findings indicate that in the TV condition, panel members were perceived as most credible, followed by the radio condition and the print condition. Statistical analyses show that the differences are significant between all three conditions. In addition, the authors found that the modality effect depends on the sources' personal characteristics. The authors discuss the theoretical and practical implications of these findings.
How to Assess Visual Communication of Uncertainty? A Systematic Review of Geospatial Uncertainty Visualisation User Studies

Abstract For decades, uncertainty visualisation has attracted attention in disciplines such as cartography and geographic visualisation, scientific visualisation and information visualisation. Most of this research deals with the development of new approaches to depict uncertainty visually; only a small part is concerned with empirical evaluation of such techniques. This systematic review aims to summarize past user studies and describe their characteristics and findings, focusing on the field of geographic visualisation and cartography and thus on displays containing geospatial uncertainty. From a discussion of the main findings, we derive lessons learned and recommendations for future evaluation in the field of uncertainty visualisation. We highlight the importance of user tasks for successful solutions and recommend moving towards task-centered typologies to support systematic evaluation in the field of uncertainty visualisation.
PIKM 2010: ACM workshop for ph.d. students in information and knowledge management

The PIKM workshop focuses on papers consisting mainly of the Ph.D. dissertation proposals of doctoral students. A wide range of topics on any area in databases, information retrieval and knowledge management are presented at this workshop. The areas of interest are similar to those at the CIKM main conference in the three respective tracks. Interdisciplinary work across these tracks is encouraged.
A Maximum Likelihood Ratio Information Retrieval Model

Abstract : In this paper we present a novel probabilistic information retrieval model that scores documents based on the relative change in the document likelihoods, expressed as the ratio of the conditional probability of the document given the query and the prior probability of the document before the query is specified. The document likelihoods are computed using statistical language modeling techniques and the model parameters are estimated automatically and dynamically for each query to optimize well-specified (maximum likelihood) objective functions. We derive the basic retrieval model, describe the details of the model, and present some extensions to the model including a method to perform automatic feedback. Development experiments are performed using the TREC-6 ad hoc text retrieval task and performance is measured using the TREC-7 ad hoc task. Official evaluation results on the 1999 TREC-8 ad hoc task are also reported. The performance results demonstrate that the model is competitive with current state-of-the-art retrieval approaches.
Exploiting Bandwidth to Reduce Average Memory Access Time in Scalable Multiprocessors.

Abstract : The overhead of remote memory accesses is a major impediment to achieving good application performance on scalable shared-memory multiprocessors. This dissertation explores ways in which to exploit network and memory bandwidth in order to reduce the average cost of memory accesses. We consider scenarios (1) where the remote access cost is dominated by contention, and (2) where the hardware provides abundant band- width and the remote access time is dominated by the unsaturated request/access/reply sequence of operations. We introduce and evaluate two techniques for increasing the effective bandwidth available to processors, software interleaving and eager combining. We also evaluate strategies for hiding the high cost of remote accesses, including several forms of prefetching and update-based coherence protocols. We use both analytic models and detailed simulations of multiprocessor systems to quantify the effectiveness of these techniques, and to provide insight into the potential and limitations of exploiting bandwidth to reduce average memory access cost.
Social, constructivist and informal learning processes: together on the Edge for designing digital game-based learning environments

The theoretical conceptions of game-based learning are different from those of traditional instruction. Indeed, the classical approaches of needs and task analysis seem to be not appropriate for designing digital serious games as computer-supported collaborative learning environments. This paper aimed at arguing that social, constructivist and informal learning processes provided accurate frameworks for analyzing needs, activities, and outcomes for designing digital serious games. After focusing on the epistemic assumptions of such theoretical frameworks, this paper described the digital serious game Cibopolis as case study, able to grasp different learning processes, involving players as learners in collaborative participation and knowledge building on nutrition and healthy lifestyle. Especially, the context, the training goal, the adopted learning solutions and the main features of the designed Cibopolis game were specified. Then, the results of the pilot test involving young learners (N=65; Range of Age=14-32 years old) was briefly reported. Specifically, it was pointed out how learners perceived the Cibopolis game in term of usability and engagement. To conclude, some relevant theoretical issues concerning digital game-based learning environments and practical implications that could support IT professionals – such as, instructional designers, developers, web designers, and so on – were highlighted.
Architecture for high‐speed evolutionary computation

Genetic algorithms (GA) are widely known as a general‐purpose optimization method, which can provide suboptimum solutions for various optimization problems by means of modeling genetic evolutionary processes of creatures. Several essential difficulties exist in GA, however, with regard to large amount of computation time and proper adjustment of many GA parameters. In order to overcome the difficulties of GA, this paper describes the architecture for a high‐speed evolutionary computation, which is optimized hierarchic pipelines to take generation models into consideration and can be flexible genetic operations corresponding to a given problem. Simulation results evaluating the proposed architecture are shown to achieve a speed 193 times faster on average compared to software processing. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 147(2): 39–52, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.10308
Tendency curves for visual clustering assessment

We improve the visual assessment of tendency (VAT) technique, which, developed by J.C. Bezdek, R.J. Hathaway and J.M. Huband, uses a visual approach to find the number of clusters in data. Instead of using square gray level images of dissimilarity matrices as in VAT, we further process the matrices and produce the tendency curves. Possible cluster structure will be shown as peak-valley patterns on the curves, which can be caught not only by human eyes but also by the computer. Our numerical experiments showed that the computer can catch cluster structures from the tendency curves even in cases where the visual outputs of VAT are virtually useless.
Indoor mobile radio channel at 946 MHz: Measurements and modeling

The results of propagation measurements carried out in an office complex at 946 MHz are described. The objectives are to investigate the impact of desk population on the average propagation loss, to model average path loss, and to fit a statistical description to the measured results. The measurements are conducted on two identically structured floors, i.e., one fully occupied and the other completely empty. The loss in the fully occupied floor is found to be consistently higher, but the propagation loss factor is more uniform in different directions from the base. Fade margin statistics are obtained for mean signal power levels which are between 50 dB and 60 dB less than the signal power at the base. It is found that the Nakagami fading model fits the results better than the generally accepted model in Rayleigh fading.
Variable bit rate vector quantization of video images for packet-switched networks

The authors investigate a novel vector-quantized compression strategy that provides guaranteed image quality with variable bit rate and show its applicability to packet-switched networks. This preliminary study indicates that significant improvements in both picture quality and SNR value can be achieved. The technique can be refined by reducing the number of overhead bits for each block and by separating coding schemes and high/low detail thresholds for each block size. <<ETX>>
Foreground Object Segmentation in Dynamic Background Scenarios

Abstract In the paper research on foreground object segmentation in dynamic background scenarios (i.e. flowing water, moving leaves or shrubs) is described. The effectiveness of different algorithms: based on FIFO sample buffer, singlevariant, multi-variant (MOG, Clustering) and recently proposed ViBE and PBAS is evaluated. A post-processing method, that allows false detections reduction is also proposed. The solution was tested on sequences from the changedetection.net dataset. The obtained results indicate usefulness of the proposed approach.
Combining a wavelet transform with a channelized Hotelling observer for tumor detection in 3D PET oncology imaging

This study evaluates new observer models for 3D whole-body Positron Emission Tomography (PET) imaging based on a wavelet sub-band decomposition and compares them with the classical constant-Q CHO model. Our final goal is to develop an original method that performs guided detection of abnormal activity foci in PET oncology imaging based on these new observer models. This computer-aided diagnostic method would highly benefit to clinicians for diagnostic purpose and to biologists for massive screening of rodents populations in molecular imaging. Method: We have previously shown good correlation of the channelized Hotelling observer (CHO) using a constant-Q model with human observer performance for 3D PET oncology imaging. We propose an alternate method based on combining a CHO observer with a wavelet sub-band decomposition of the image and we compare it to the standard CHO implementation. This method performs an undecimated transform using a biorthogonal B-spline 4/4 wavelet basis to extract the features set for input to the Hotelling observer. This work is based on simulated 3D PET images of an extended MCAT phantom with randomly located lesions. We compare three evaluation criteria: classification performance using the signal-to-noise ratio (SNR), computation efficiency and visual quality of the derived 3D maps of the decision variable &lgr;. The SNR is estimated on a series of test images for a variable number of training images for both observers. Results: Results show that the maximum SNR is higher with the constant-Q CHO observer, especially for targets located in the liver, and that it is reached with a smaller number of training images. However, preliminary analysis indicates that the visual quality of the 3D maps of the decision variable &lgr; is higher with the wavelet-based CHO and the computation time to derive a 3D &lgr;-map is about 350 times shorter than for the standard CHO. This suggests that the wavelet-CHO observer is a good candidate for use in our guided detection method.
SHrinkage Covariance Estimation Incorporating Prior Biological Knowledge with Applications to High-Dimensional Data

In ``-omic data'' analysis, information on the structure of covariates are broadly available either from public databases describing gene regulation processes and functional groups such as the Kyoto encyclopedia of genes and genomes (KEGG), or from statistical analyses -- for example in form of partial correlation estimators. The analysis of transcriptomic data might benefit from the incorporation of such prior knowledge. In this paper we focus on the integration of structured information into statistical analyses in which at least one major step involves the estimation of a (high-dimensional) covariance matrix. More precisely, we revisit the recently proposed ``SHrinkage Incorporating Prior'' (SHIP) covariance estimation method which takes into account the group structure of the covariates, and suggest to integrate the SHIP covariance estimator into various multivariate methods such as linear discriminant analysis (LDA), global analysis of covariance (GlobalANCOVA), and regularized generalized canonical correlation analysis (RGCCA). We demonstrate the use of the resulting new methods based on simulations and discuss the benefit of the integration of prior information through the SHIP estimator. Reproducible R codes are available at http://www.ibe. med.uni-muenchen.de/organisation/mitarbeiter/020_professuren/boulesteix/shipproject/index.html.
Improved acoustic modeling for speaker independent large vocabulary continuous speech recognition

The authors report recent improvements to an HMM (hidden, Markov model)-based, continuous speech recognition system. These advances, which include the incorporation of interword context-dependent units and position-dependent units and an improved feature analysis, lead to a recognition system which gives a 95% word accuracy and 75% sentence accuracy for speaker independent recognition of the 1000-word, DARPA resource management task using the standard word pair grammar (with a perplexity of about 60). With the improved acoustic modeling of subword units, the overall error rate reduction was over 42% compared with the performance results reported in the baseline system. The best results obtained so far using the word pair grammar gave 95.2% average word accuracy for the three DARPA evaluation sets. <<ETX>>
In silico evaluation of multivariated methods to assess functional connectivity from EEG data

La tesi tratta della valutazione di metodi multivariati per lo studio della connettivita tra diverse aree cerebrali sfruttando dati simulati. Sono stati analizzati tre diversi modelli di rete ottenuti facendo interagire tra loro tre regioni corticali (ROI) simulate attraverso un modello di massa neurale. Di queste reti e stata stimata la topologia e l'intensita delle connessioni tra le ROI
Automatic detection of crystallization evaluation region by using image processing

Purpose – The purpose of this paper is to propose an imaging process method for automatically extracting assessment target regions in images of crystallization wells.Design/methodology/approach – The proposed method detects the target by image processing based on saturation variance in images of crystallization wells.Findings – The proposed method shows high accurate detection performance in a short time.Practical implications – The method is applicable to automatic crystallization machine. Especially, it is expected to implement to TERA system of RIKEN.Originality/value – The paper demonstrates target area detection from microscope images based on saturation variance in images of crystallization wells.
Extracting histological parameters from multi-spectral retinal images: a Bayesian inverse problem approach

Extracting histological parameters, especially macular pigment, from multispectral images of the ocular fundus is a potential technique for the assessment of age-related macular degeneration. Such approaches make use of a Monte Carlo radiation transport model relating spectral reflectance of the tissue to tissue histology. We develop a probabilistic surrogate for this computationally expensive physicalmodel using Gaussian processes (GP). Further, we present a Bayesian inversion algorithm that uses the surrogate model to recover model input parameters. This methodology is tested both on synthetic data generated from the Monte Carlo model and on real image data. It is shown that our inversion methods can recover macular pigment concentrations in human retina with good accuracy and the spatial distribution is consistent with known physiology.