Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors Influencing Industry Uptake of Marketing and Supply Chain Innovations Promoted by the Australian Seafood Cooperative Research Centre

This study identifies factors influencing the Australian seafood industry’s adoption of marketing and supply chain innovations created from public-private funded research and development (R&D). A grounded theory approach was followed by comparing and contrasting the evidence from 35 projects funded by the Australian Seafood Cooperative Research Centre (CRC). This research showed that: 1) the level of confidence in the value proposition of an innovation is a crucial condition in determining industry uptake of research outcomes and innovations, with organizational, seafood sector and environmental factors also playing a role; 2) to increase the industry level of confidence in a value proposition, researchers need to test hypotheses on benefits, costs and risks of an innovation through focused consumer and market research; and 3) to design effective consumer research, project managers need to establish clear, open and non-judgemental communication guidelines among project stakeholders during the project design stage. While focused on the Australian seafood industry the outcomes of this study could be applied through further research to other industries and countries to help construct and/or analyse the best environment for effective marketing and supply innovations to be adopted. Keynote: Innovation, public-private partnerships, marketing, seafood, project management, Australia.
Visibility Preprocessing Using Spherical Sampling of Polygonal Patches

A technique is presented that permits fast view-reconstruction of individual objects. This method improves a previous approach to solve the problem of approximated view reconstruction by combining clustering of polygons with visibility bitfields to determine visibility for novel viewpoints. The technique consists of three steps: patch creation, spherical sampling, and rendering. In the first stage, the input 3D model is tiled in polygonal patches. In the sampling stage images of the model are taken from several points on the surface of a viewing sphere. Patch-ID bitfields, which are structures that contain visibility information, are computed for each picture. In the rendering stage, a subset of the viewpoints computed for sampling is selected depending on the viewers position on the viewing sphere and the bitfields of the selected viewpoints are used to rebuild the visible parts of the model from the new viewpoint. The overall system presented here makes a very efficient use of memory resources, and involves practically no overhead during rendering while significantly improving frame rate during interaction with large models. Although the technique is not conservative, our results show that the reconstructed views are practically identical to the original views of the model.
8-5-2011 uService – Enabling user-driven fitness services onthe-go

User-centric developments are on the move, both in business and information technology. Especially in the mobile environment, personalization is of great importance . The concept of the mobile service super prosumer is core of the research carried out in the project uService. It aims at pro viding a platform for the creation, discovery and c onsumption of mobile services on-the-go. Tailoring fitness applications for mobile phones to the respective needs of patien ts a d hobby runners is the main goal of uService’s application scenario uR un. This use case enables hobby runners to create p rsonalized, contextaware versions of mobile services tailored to their specific personal preferences, health conditions a nd training plans. Based on these features, a semantic knowledge base allows for the context-aware search and recommendations f or ervice creation, discovery and usage. Compared to traditional consum er-centric health care systems, the depicted approa ch will be more personalized and context-aware and will empower phy sicians and personal trainers to act more timely th an before.
Feature analysis for detecting people from remotely sensed images

Abstract We propose a novel approach using airborne image sequences for detecting dense crowds and individuals. Although airborne images of this resolution range are not enough to see each person in detail, we can still notice a change of color and intensity components of the acquired image in the location where a person exists. Therefore, we propose a local feature detection-based probabilistic framework to detect people automatically. Extracted local features behave as observations of the probability density function (PDF) of the people locations to be estimated. Using an adaptive kernel density estimation method, we estimate the corresponding PDF. First, we use estimated PDF to detect boundaries of dense crowds. After that, using background information of dense crowds and previously extracted local features, we detect other people in noncrowd regions automatically for each image in the sequence. To test our crowd and people detection algorithm, we use airborne images taken over Munich during the Oktoberfest event, two different open-air concerts, and an outdoor festival. In addition, we apply tests on GeoEye-1 satellite images. Our experimental results indicate possible use of the algorithm in real-life mass events.
Relation between sleep and visuospatial skills in students from a public school

The relation between the sleep and the visuospatial skills was evaluated in 31 students from a public school. For the analysis of sleep, the parents of volunteers answered a sleep evaluation questionnaire and the sleep diary. The visuospatial performance was evaluated by Wechsler Intelligence Scale for Children (WISC-III), through the subtest Picture Completion, the Perceptual Organization Index and the Performance IQ Scale. In accordance with the results, 72% of the students presented regular sleep and good sleep length. The visuospatial performance was deficient in subtest Picture Completion for 56% of the students, and on the Performance IQ Scale for 60% of the students. Significant correlations were verified between early sleep onset (rho = -0.40, p < 0.05) and regular sleep (rho = -0.39, p < 0.05) with the visuospatial performance. It was concluded that sleeping early and having a regular sleep may contribute to a better visuospatial performance.
Undrained shear strength–water content relationship for sewage sludge

Micro-fibrous organic clays include sludges and residues derived from municipal and industrial treatment processes. This paper studies the relationship of water content w against remoulded undrained shear strength sur of one such material, namely sewage sludge (biosolids), and the factors affecting the coefficients a and b in the equation w=as⭑b−bur. Data for sur in fall-cone, vane shear and triaxial compression (TC) tests were examined, considering the material's mineralogical, physiochemical and biological properties. The effects of the different shearing modes, rates and confinement pressure on the mobilised strength were studied, since the different apparatuses approach the estimation of strength in different ways. The scalar relating the deduced sur values in vane shear to TC was not singular, but was particularly sensitive to the confining pressure (σ3) applied in TC tests, and also to the difference in strain rate between the different tests. The deduced sur from the miniature vane was between 1·19.
Applying instance-weighted support vector machines to class imbalanced datasets

Learning with class imbalance is always a challenging task in many real world applications such as the Internet, surveillance, security, and finance. Like many other successful machine learning algorithms, the success of the support vector machine (SVM) is limited when it is applied to the problem of learning from imbalanced datasets. SVM with different error costs has been widely used to deal with the class imbalanced problem. In this paper, we are trying to apply an instance-weighted variant of the SVM with both 1-norm and 2-norm format to deal with the class imbalance problem. We develop an asymmetric boosting method on the weights of the tradeoff parameters to optimize the instance-weighted SVM. The experimental results on the benchmark datasets show that the proposed algorithm is effective on the class imbalanced problem.
Efficient scanline visibility implementation

We sought a versatile renderer, one that could be used as a fast previewer and still provide high quality results when called upon to do so. The personal computers for which our implementation was intended imposed additional constraints: relatively modest processing power and a small amount of available memory. Having read papers describing several prior implementations [Watk70] [Fium83] [Croc84] [Fole84], we decided that a scanline visibility algorithm offered what we needed: an efficient means of generating complex images. The following is a discussion of our own scanline-based renderer, its background and implementation.
Why Statically Estimate Code Coverage is So Hard? A Report of Lessons Learned

The calculation of test coverage is often unfeasible for large-scale mining software repositories studies, as its computation requires building each project and executing their test suites. Because of that, we have been working on heuristics to calculate code coverage based on static code analysis. However, our results have been disappointing so far. In this paper, we present our approach to the problem and an evaluation involving 18 open source projects (around 2,700 classes) from the Apache Software Foundation. Results show that our approach provides acceptable results for only 50% of all classes. We believe researchers can learn from our mistakes and possibly derive a better approach. We advise researchers who need to use code coverage in their studies to select projects with a well-defined build system, such as Maven.
GPGPU Acceleration of Cryptographic Applications

Cryptographic algorithms are crucial to the security of modern computing systems. The peculiar nature of such algorithms leads them to be computationally intensive by design . Speeding up cryptographic algorithms through paralleliza tion can therefore prove effective especially when large amount f data are to be encrypted. At the same time, massive amounts of SIMD-like parallel computational power can speed up the breaking of cryptographic algorithms. In both cases, we show that software solutions targeting GPGPU devices can compete with dedicated hardware solutions on a performance/cost metric. To prove this, we provide two case studies: the breaking of the well-known DES algorithm, comparing a NVidia G200-based solution to the Copacobana FPGA-based solution; and disk volume encryption by means of the TrueCrypt suite, targeting both t he Serpent and Twofish algorithms in the XTS mode of operation. In both cases, we show how to correctly tune the design parameters, including data allocation, thread packing, an d parallelization strategy. Overall, our implementation of Tru eCrypt running on a NVidia GTX260 GPU outperforms by 67% the baseline implementation running on a four core CPU [2], whil e our implementation of DES breaking is able to find a DES key in about 18 days, at a cost equal to that of the Copacobana [3].
Three-Dimensional Binary-Uncoded Video Compression Using 3DSPIHT-ZTR

In conventional video coding, motion compensation is commonly being used to remove the temporal redundancy. But the computational complexity introduced by the motion compensation can be very high, especially when the full search is adopted. The 3DSPIHT resolves this problem by replacing the motion compensation with the temporal wavelet transform, which require lower computational complexity. However, the performance of the 3DSPIHT is optimal only when Arithmetic Coding (AC) is incorporated. This contradicts the initial idea of reducing the computational complexity with the wavelet transform, because the computational complexity introduced by AC is sufficiently high. In this paper, an efficient binary-uncoded algorithm for video coding called the 3DSPIHT-ZTR is proposed. The idea is to re-introduce the use of ZTR symbol, which is initially used in the Embedded Zerotree Wavelet (EZW) algorithm, into 3DSPIHT. In addition, the significant offspring are also encoded in a slightly different way to further enhance the performance. The performance of 3DSPIHT-ZTR is approximately 1.5 dB better than the conventional 3DSPIHT in terms of PSNR. Its performance is also comparable to 3DSPIHT with AC under certain circumstances.
Error type classification and word accuracy estimation using alignment features from word confusion network

This paper addresses error type classification in continuous speech recognition (CSR). In CSR, errors are classified into three types, namely, the substitution, insertion and deletion errors, by making an alignment between a recognized word sequence and its reference transcription with a dynamic programming (DP) procedure. We propose a method for deriving such alignment features from a word confusion network (WCN) without using the reference transcription. We show experimentally that the WCN-based alignment features steadily improve the performance of error type classification. They also improve the performance of out-of-vocabulary (OOV) word detection, since OOV word utterances are highly correlated with a particular alignment pattern. In addition, we show that the word accuracy can be estimated from the WCN-based alignment features and more accurately from the error type classification result without using the reference transcription.
Random phase updating algorithm for OFDM transmission with low PAPR

A novel random phase updating algorithm for reducing the peak-to-average power ratio (PAPR) of OFDM signals is addressed. The phase of each subcarrier is updated by a random increment until the PAPR goes below a certain threshold level. We investigate the influence of different distributions for the phase increments and the variance of distributions on the mean and variance of PAPR as well as the number of iterations to reach the threshold. Further, the random phase updating algorithm has been extended by dynamically reducing the threshold level. After successful updating of the phase shifts, the threshold level is reduced and the variance of the phase increments is changed. Simulation results of the algorithm are provided. It is shown that the random phase updating algorithm with dynamic threshold gives the best results and can reduce the mean power variance of an 8-carrier OFDM signal with BPSK modulation by a factor of 7 dB. In order to reduce the complexity, the random phase updating algorithm is investigated with quantization and grouping of the phase shifts. Results show that for a 16-carrier OFDM system, 2-level quantization of phase shifts in 8 groups of 2 carriers give no significant increase in the power variance while reducing complexity. Further, the impact of phasing on the bit error rate performance of the OFDM system is studied.
Empirical pathway analysis, without permutation

Resampling-based expression pathway analysis techniques have been shown to preserve type I error rates, in contrast to simple gene-list approaches that implicitly assume the independence of genes in ranked lists. However, resampling is intensive in computation time and memory requirements. We describe accurate analytic approximations to permutations of score statistics, including novel approaches for Pearson's correlation, and summed score statistics, that have good performance for even relatively small sample sizes. Our approach preserves the essence of permutation pathway analysis, but with greatly reduced computation. Extensions for inclusion of covariates and censored data are described, and we test the performance of our procedures using simulations based on real datasets. These approaches have been implemented in the new R package safeExpress.
Lifetime risk of dementia in the United States

Dementia is increasingly recognized as a major source of disease burden in the United States, on par with heart disease and cancer. Little research has evaluated the lifecycle implications of dementia. To address this research gap, this article uses the Aging, Demographics, and Memory Study (ADAMS) to provide the first nationally representative, longitudinal estimates of the probability that a dementia-free person will develop dementia later in life. I estimate that for the 1920 birth cohort, the average dementia-free 70 year old male had a 23.7% (SE: 2.9%) lifetime probability of developing dementia, and the average dementia-free 70 year old female had a 31.8% (SE: 3.6%) probability. These estimates of lifetime risk of dementia rise for younger cohorts, and they are higher than those found in local epidemiological studies in the U.S. They suggest a widespread need to prepare for a life stage with dementia.
Experiment and Spectral Analysis of a Low-Power  $Ka$-Band Heartbeat Detector Measuring From Four Sides of a Human Body

The accuracy of a Ka-band physiological movement detector was tested and compared for measurements from four different body orientations and at five different distances. A rigorous spectral analysis approach is developed when previously adopted small-angle approximation model is not applicable. This theory analyzes in detail the harmonics observed in phase-modulated Ka-band Doppler radar, explaining the reason for better heart-rate accuracy when detected from the back of the body. It also explains the advantage of double-sideband transmission in avoiding the null point problem. Simulations have been performed to illustrate this theory and provide design guidelines for the system. This theory has also been verified by experiments
Sketch-based Geometric Monitoring of Distributed Stream Queries

Emerging large-scale monitoring applications rely on continuous tracking of complex data-analysis queries over collections of massive, physically-distributed data streams. Thus, in addition to the space- and time-efficiency requirements of conventional stream processing (at each remote monitor site), effective solutions also need to guarantee communication efficiency (over the underlying communication network). The complexity of the monitored query adds to the difficulty of the problem -- this is especially true for nonlinear queries (e.g., joins), where no obvious solutions exist for distributing the monitor condition across sites. The recently proposed geometric method offers a generic methodology for splitting an arbitrary (non-linear) global threshold-monitoring task into a collection of local site constraints; still, the approach relies on maintaining the complete stream(s) at each site, thus raising serious efficiency concerns for massive data streams. In this paper, we propose novel algorithms for efficiently tracking a broad class of complex aggregate queries in such distributed-streams settings. Our tracking schemes rely on a novel combination of the geometric method with compact sketch summaries of local data streams, and maintain approximate answers with provable error guarantees, while optimizing space and processing costs at each remote site and communication cost across the network. One of our key technical insights for the effective use of the geometric method lies in exploiting a much lower-dimensional space for monitoring the sketch-based estimation query. Due to the complex, highly nonlinear nature of these estimates, efficiently monitoring the local geometric constraints poses challenging algorithmic issues for which we propose novel solutions. Experimental results on real-life data streams verify the effectiveness of our approach.
Advanced spectrum estimation methods for signal analysis in power electronics

Modern frequency power converters generate a wide spectrum of harmonic components. Large converters systems can also generate noncharacteristic harmonics and interharmonics. Standard tools of harmonic analysis based on the Fourier transform assume that only harmonics are present and the periodicity intervals are fixed, while periodicity intervals in the presence of interharmonics are variable and very long. A novel approach to harmonic and interharmonic analysis, based on the "subspace" methods, is proposed. Min-norm harmonic retrieval method is an example of high-resolution eigenstructure-based methods. The Prony method as applied for signal analysis was also tested for this purpose. Both high-resolution methods do not show the disadvantages of the traditional tools and allow exact estimation of the interharmonics frequencies. To investigate the methods several experiments were performed using simulated signals, current waveforms at the output of a simulated frequency converter, and current waveforms at the output of an industrial frequency converter. For comparison, similar experiments were repeated using the fast Fourier transform (FFT). The comparison proved the superiority of the new methods. However, their computation is much more complex than FFT.
KFCM Algorithm Based on the Source Code Mining Method Study

This paper provides a algorithm, which is based on that kernelized fuzzy C-means uses on the study of source code mining, to solve the problem that the large number of quantities, multiple attributes and most of them discrete of software engineering. By using this algorithm, we can improve the efficiency of mining and seek faster and more effective cluster approaches. Meanwhile, we can also solve the problem that the KFCM algorithm can not cluster text data directly. Then we can over the defect of only being able to obtain the minimum values by integrating KFCM and genetic algorithm. Finally, the experiment shows that the improved KFCM algorithm has a good clustering performance and high efficiency on data mining.
Homological perturbation theory for algebras over operads

We extend homological perturbation theory to encompass algebraic structures governed by operads and cooperads. The main difficulty is to find a suitable notion of algebra homotopy that generalizes to algebras over operads O . To solve this problem, we introduce thick maps of O ‐algebras and special thick maps that we call pseudo-derivations that serve as appropriate generalizations of algebra homotopies for the purposes of homological perturbation theory. As an application, we derive explicit formulas for transferring . C/‐algebra structures along contractions, where C is any connected cooperad in chain complexes. This specializes to transfer formulas for O1 ‐algebras for any Koszul operad O , in particular for A1 ‐, C1 ‐, L1 ‐ and G1 ‐algebras. A key feature is that our formulas are expressed in terms of the compact description of . C/‐algebras as coderivation differentials on cofree C ‐coalgebras. Moreover, we get formulas not only for the transferred structure and a structure on the inclusion, but also for structures on the projection and the homotopy. 18D50, 55P48