Miracle-dz/UniFAR-FTUs huggingface dataset:
MEMR: A Margin Equipped Monotone Retargeting Framework for Ranking

We bring to bear the tools of convexity, margins and the newly proposed technique of monotone retargeting upon the task of learning permutations from examples. This leads to novel and efficient algorithms with guaranteed prediction performance in the online setting and on global optimality and the rate of convergence in the batch setting. Monotone retargeting efficiently optimizes over all possible monotone transformations as well as the finite dimensional parameters of the model. As a result we obtain an effective algorithm to learn transitive relationships over items. It captures the inherent combinatorial characteristics of the output space yet it has a computational burden not much more than that of a generalized linear model.
Computationally efficient target classification in multispectral image data with Deep Neural Networks

Detecting and classifying targets in video streams from surveillance cameras is a cumbersome, error-prone and expensive task. Often, the incurred costs are prohibitive for real-time monitoring. This leads to data being stored locally or transmitted to a central storage site for post-incident examination. The required communication links and archiving of the video data are still expensive and this setup excludes preemptive actions to respond to imminent threats. An effective way to overcome these limitations is to build a smart camera that analyzes the data on-site, close to the sensor, and transmits alerts when relevant video sequences are detected. Deep neural networks (DNNs) have come to outperform humans in visual classifications tasks and are also performing exceptionally well on other computer vision tasks. The concept of DNNs and Convolutional Networks (ConvNets) can easily be extended to make use of higher-dimensional input data such as multispectral data. We explore this opportunity in terms of achievable accuracy and required computational effort. To analyze the precision of DNNs for scene labeling in an urban surveillance scenario we have created a dataset with 8 classes obtained in a field experiment. We combine an RGB camera with a 25-channel VIS-NIR snapshot sensor to assess the potential of multispectral image data for target classification. We evaluate several new DNNs, showing that the spectral information fused together with the RGB frames can be used to improve the accuracy of the system or to achieve similar accuracy with a 3x smaller computation effort. We achieve a very high per-pixel accuracy of 99.1%. Even for scarcely occurring, but particularly interesting classes, such as cars, 75% of the pixels are labeled correctly with errors occurring only around the border of the objects. This high accuracy was obtained with a training set of only 30 labeled images, paving the way for fast adaptation to various application scenarios.
Eye Tracking Based on the Template Matching and the Pyramidal Lucas-Kanade Algorithm

Eyes are important facial organs and play an important role in face recognition, human-computer interactions and other areas. In order to locate and track eyes accurately, in this paper, we used the Adaboost algorithm to detect face, then located the eyes in the first frame using the Template Matching algorithm, finally combined the Pyramid algorithm and Lucas-Kanade optical flow algorithm to track eyes. At the same time, by using the OTSU algorithm and integral projection, we got the state of the eyes. The experimental results show that the algorithm has certain advantages in speed and accuracy relative to other algorithms.
Performance evaluation of HDD and SSD on 10GigE, IPoIB & RDMA-IB with Hadoop Cluster Performance Benchmarking System

Hadoop and Map reduce today are facing huge amounts of data and are moving towards ubiquitous for big data storage and processing. Benchmarking tools available are not capable of analyzing performance of the Hadoop cluster system and are made to either run in a single node system. HiBench is an essential part of Hadoop. It is a comprehensive benchmark suit that consists of a complete deposit of Hadoop applications having micro bench marks & real time applications for benchmarking the performance of Hadoop on the available type of storage device (i.e. HDD and SSD) and machine configuration. This is helpful to optimize the performance and improve the support towards the limitations of Hadoop system. In this paper we will present the Performance evaluation of HDD and SSD with 10GigE, IPoIB & RDMA-IB on Hadoop Cluster Performance Benchmarking System. In addition, we will also demonstrate that the traditional servers and old Cloud systems can be upgraded by software and hardware up gradations to perform at par with the modern technologies to handle these loads, without spending ruthlessly on up gradations or complete changes in the system with the use of Modern storage devices and interconnect networking systems.
Improved Linked Data Interaction through an Automatic Information Architecture

Thanks to Open Data initiatives the amount of data available on the Web is rapidly increasing. Unfortunately, most of these initiatives only publish raw tabular data, which makes its analysis and reuse very difficult. Linked Data principles allow for a more sophisticated approach by making explicit both the structure and semantics of the data. However, from the user experience viewpoint, published datasets continue to be monolithic files which are completely opaque or difficult to explore by making complex semantic queries. Our objective is to facilitate the user to grasp what kind of entities are in the dataset, how they are interrelated, which are their main properties and values, etc. Rhizomer is a data publishing tool whose interface provides a set of components borrowed from Information Architecture (IA) that facilitate getting an insight of the dataset at hand. Rhizomer automatically generates navigation menus and facets based on the kinds of things in the dataset and how they are described through metadata properties and values. This tool is currently being evaluated with end users that discover a whole new perspective of the Web of Data.
Testing circumstellar disk lifetimes in young embedded clusters associated with the Vela Molecular Ridge

Context. The Vela Molecular Ridge hosts a number of young embedded star clusters at the same evolutionary stage. Aims. We test whether the fraction of members with a circumstellar disk in a sample of clusters in the cloud D of the Vela Molecular Ridge, is consistent with relations derived for larger samples of star clusters with an age spread. In addition, we constrain the age of the young embedded star clusters associated with cloud D. Methods. We carried out L (3.78 μm) photometry using images of six young embedded star clusters associated with cloud D of the Vela Molecular Ridge, taken with ISAAC at the VLT. These data are complemented with the available HKs photometry. The 6 clusters are of roughly the same size and appear to be at the same evolutionary stage. The fraction of stars with a circumstellar disk was measured in each cluster by counting the fraction of sources found to have a NIR excess in colour-colour (HKsL )d iagrams. Results. The L photometry allowed us to identify the NIR counterparts of the IRAS sources associated with the clusters. The fraction of stars with a circumstellar disk appears to be constant within the errors for the 6 clusters. There is a hint that this is lower for the most massive stars. The age of the clusters is constrained to be ∼1‐2 Myr. Conclusions. The fraction of stars with a circumstellar disk in the observed sample is consistent with the relations derived from larger samples of star clusters and with other age estimates for cloud D. The fraction may be lower for the most massive stars. Our results agree with a scenario where all intermediate and low-mass stars form with a disk, whose lifetime is shorter for higher mass stars.
Adaptive Gaussian Predictive Process Approximation

We address the issue of knots selection for Gaussian predictive process methodology. Predictive process approximation provides an effective solution to the cubic order computational complexity of Gaussian process models. This approximation crucially depends on a set of points, called knots, at which the original process is retained, while the rest is approximated via a deterministic extrapolation. Knots should be few in number to keep the computational complexity low, but provide a good coverage of the process domain to limit approximation error. We present theoretical calculations to show that coverage must be judged by the canonical metric of the Gaussian process. This necessitates having in place a knots selection algorithm that automatically adapts to the changes in the canonical metric affected by changes in the parameter values controlling the Gaussian process covariance function. We present an algorithm toward this by employing an incomplete Cholesky factorization with pivoting and dynamic stopping. Although these concepts already exist in the literature, our contribution lies in unifying them into a fast algorithm and in using computable error bounds to finesse implementation of the predictive process approximation. The resulting adaptive predictive process offers a substantial automatization of Guassian process model fitting, especially for Bayesian applications where thousands of values of the covariance parameters are to be explored.
Automatic implementation of evolutionary algorithms on GPUs using ESDL

Modern computer processing units tend towards simpler cores in greater numbers, favouring the development of data-parallel applications. Evolutionary algorithms are ideal for taking full advantage of SIMD (Single Instruction, Multiple Data) processing, which is available on both CPUs and GPUs. Creating software that runs on a GPU requires the use of specialised programming languages or styles, forcing practitioners to acquire new skills and limiting the portability of their developments. In this paper, we present an automatic translation from ESDL, a domain-specific language for composing evolutionary algorithms from arbitrary operators, to C++ AMP, a C++ extension for targeting heterogeneous hardware. Generating executable code from a simple platform-independent description allows practitioners with varying levels of programming expertise to take advantage of data-parallel execution, and enables those with strong expertise to further optimise their implementations. The automatic transformation is shown to produce code less optimal than a manual implementation but with significantly less developer effort. A secondary result is that GPU implementations require a large population, large individuals or an expensive evaluation function to achieve performance benefits over the CPU. All code developed for this paper is freely available online from http://stevedower.id. au/esdl/amp.
A systematic investigation of absorptive capacity and external information search in groups

Purpose This paper aims to test the influence of external information search (EIS) on knowledge elaboration and group cognitive complexity (GCC) under the moderating effect of absorptive capacity (AC is indicated by prior knowledge base and gender diversity). Design/methodology/approach The results of three studies (one field study and two experimental studies) are reported. The first study tests the interaction between EIS and the two dimensions of AC on group knowledge elaboration in a sample of 65 organizational groups. In the second study, EIS was directly manipulated and the interaction with AC in a sample of 65 groups was tested. In the last experimental study, the AC of the boundary spanner (highest level of expertise versus lowest level of expertise) was manipulated and the effects of EIS in a sample of 37 groups were tested. Findings The first study reveals a significant interaction between EIS and prior knowledge base on knowledge elaboration and points toward a compensatory interplay of EIS and AC on GCC. The results of the second study indicate that EIS increases the time spent on task, as well as the efficiency of knowledge integration (GCC per unit of time). Furthermore, EIS has the strongest positive effect on GCC in groups in which at least one of the AC dimensions is average or high. The results of the last study show that the AC of the boundary spanner compensates for the lack of absorptive capacity of the group and also show that the cognitive distance between the boundary spanner and the rest of the group has a negative influence on the efficiency of knowledge integration in groups. Research limitations/implications The limitations of Study 1, common to non-experimental research (related to causality), are dealt with in the second and third studies that establish causality between EIS and GCC. Practical implications The paper has important implications for the management of information search effort in organizational groups, in particular the groups are advised to: engage in EIS to increase their cognitive repertoire and cognitive complexity, delegate, when possible, their most competent members to engage in boundary spanning activities as they will maximize the cognitive benefits of EIS and finally minimize the cognitive dissimilarity between the boundary spanner and the rest of the group to facilitate the effective integration of novel insights into the group cognition. Originality/value This study is among the first empirical attempts to uncover the causal effect of EIS on knowledge elaboration and GCC in groups and to uncover the role of the boundary spanner in the EIS efforts.
Benchmarking the dependability of Windows NT4, 2000 and XP

The aim of this paper is to compare the dependability of three operating systems (Windows NT4, Windows 2000 and Windows XP) with respect to erroneous behavior of the application layer. The results show a similar behavior of the three OSs with respect to robustness and a noticeable difference in OS reaction and restart times. They also show that the application state (mainly the hang and abort states) significantly impacts the restart time for the three OSs.
Single-channel Speech Separation Using Orthogonal Matching Pursuit

In this paper, we propose a new sparse decomposition based single-channel speech separation method using orthogonal matching pursuit (OMP). The separation is performed using source-individual dictionaries consisting of time-domain training frames as atoms. OMP is used to compute sparse coefficients to estimate sources. We report the separation results of our proposed method and compare them with a separation method based on sparse non-negative matrix factorization (SNMF) which is a classical sparse decomposition based separation method. Experiments show that our proposed method results in higher signal-to-noise ratio (SNR) and signal-to-interference ratio (SIR).
On the stability of black strings / branes

Some issues on the stability of black string or brane solutions are summarized briefly. The stability of dS/AdS-Schwarzschild black strings has been investigated. Interestingly, the AdS-Schwarzschild black strings turn out to be stable as the horizon size becomes larger than the AdS scale. It is also shown that BTZ black strings in four dimensions are stable regardless of the horizon size. Such stable feature seems to be common for several known black strings in dimensions lower than five. Some implications of our results on the role of non-uniformity in stable black string configurations are also discussed.
On the use of POMDP for spectrum selection in cognitive Radio networks

Dynamic Spectrum Access is a key capability of Cognitive Radio (CR) networks to increase the efficiency in the use of the available spectrum resources. In this respect, this paper focuses on the spectrum selection problem when a number of radio links has to be established in a CR network to support applications with different bit rate requirements. A novel strategy based on a Partially Observable Markov Decision Process (POMDP) is proposed, whose target is to maximize a reward function that reflects the suitability of the available spectrum blocks to the application requirements. The proposed strategy combines partial observations of the interference state in the different spectrum blocks together with a statistical characterization of the interference dynamics. Thanks to this feature, the performance comparison of the algorithm against different reference strategies reveals that it achieves a very similar performance than a strategy operating under full knowledge of the real interference state of all the spectrum blocks, while at the same time it has much less requirements in terms of measurement needs and associated signaling.
Decreased Copper in Alzheimer's Disease Brain Is Predominantly in the Soluble Extractable Fraction

Alzheimer's disease (AD) is the leading cause of dementia and represents a significant burden on the global economy and society. The role of transition metals, in particular copper (Cu), in AD has become of significant interest due to the dyshomeostasis of these essential elements, which can impart profound effects on cell viability and neuronal function. We tested the hypothesis that there is a systemic perturbation in Cu compartmentalization in AD, within the brain as well as in the periphery, specifically within erythrocytes. Our results showed that the previously reported decrease in Cu within the human frontal cortex was confined to the soluble (P < 0.05) and total homogenate (P < 0.05) fractions. No differences were observed in Cu concentration in erythrocytes. Our data indicate that there is a brain specific alteration in Cu levels in AD localized to the soluble extracted material, which is not reflected in erythrocytes. Further studies using metalloproteomics approaches will be able to elucidate the metabolic mechanism(s) that results in the decreased brain Cu levels during the progression of AD.
Comparing different treatment schedules of Zomen (zofenopril).

BACKGROUND Chronotherapy of hypertension became, during the last years, a main target in optimal BP values control, during 24 hours. Many clinical studies have demonstrated a different effect on blood pressure of the majority of angiotensin-converting enzyme inhibitors (ACEIs), studied as function of the moment of their administration. Until now, the majority of clinical proofs sustain the greater benefit offered by bedtime administration of ACEIs, concerning especially a significantly greater efficacy in reducing BP during the asleep period, thus increasing the prevalence of "dippers", the circadian profile considered to offer the best cardio-vascular prognosis, compared to at awakening administration. MATERIALS AND METHODS This study investigated time-dependent effects of zofenopril (Zomen, 30 mg, Berlin-Chemie, Menarini Group, Romania) administration on ambulatory blood pressure values. We studied 33 consecutive untreated hypertensive patients (19 men, 14 women), 56 +/- 12.7 years old, with grade 1 or 2 uncomplicated essential hypertension (according to the European Society of Hypertension-European Society of Cardiology guidelines) (diagnostic formulated by casual determination and confirmed by an ABPM session at baseline), using zofenopril as monotherapy. The drug was initially administered in a single dose, at bedtime, during one month; after that period, we performed for all of them a new ABPM session, and, after that, for another month we administered the same drug, in single dose, at awakening. Blood pressure was measured for 48 hours before and after one month of treatment. RESULTS The blood pressure reduction during diurnal activity was similar for both treatment schedules. Bedtime administration of zofenopril, however, was significantly more efficient than at awakening administration in reducing asleep blood pressure. The awake:asleep blood pressure ratio was decreased after zofenopril on awakening but significantly increased towards a more dipping pattern, (from 60.60% to 90.90%) after at bedtime administration. The proportion of patients with controlled ambulatory BP increased from 51.51% to 84.84% (p < 0.001) by bedtime administration. CONCLUSIONS Nocturnal blood pressure regulation is significantly better achieved at bedtime as compared with at awakening administration of zofenopril, without any loss in efficacy during diurnal active hours; this might be clinically important, because nighttime blood pressure has been shown to be a more relevant marker of cardiovascular risks than diurnal mean values. The change in the dose-response curve, the increased proportion of controlled patients, and improved efficacy on nighttime BP values by bedtime administration of zofenopril should be taken into account when prescribing this ACEI for treatment of essential hypertension.
Combined area of mechatronics and computer science Mechanics

This overall plan will give some background to the platform from a historical point of view and present the platform in its relation to the main activities of the University of Skövde, both from the education and research point of views. Furthermore, it will present the potential of the platform, with a special focus on its relation to future external (both academic and industrial) projects, to master and doctoral level studies and development of the surrounding region. Finally, it contains the budget for 1999. The University of Skövde is an academic institution with a strong profile towards engineering, natural and computer sciences, and particularly their integration. The university is focused towards areas which are characterized by growth and a need for academic professional competence, e.g., information technology and bioinformatics. The university received academic status as recently as 1983, at which time it had about 500 students. Today, the highest degree that can be awarded is at the master level (computer science, automation, electronics, mechanics, German). Since the University of Skövde is so young it has until now not had the right to issue diplomas at the doctoral level, but an application for this level will shortly be handed in to the government. The area for which the university applies for this right is the combination of computer science and a part of engineering science, namely the area of mechatronics. Computer science is here seen as the science about how the surrounding world can be analyzed, modeled, represented and processed in an automated system where the human is regarded as a natural component. Mechatronics is here seen as a multidisciplinary area which synergistically integrates the classic areas of mechanics and electronics with intelligent program control in products and processes. The main bulk of research carried out at the university is located within this combination, including:
Design of a compact synchrotron for medical applications

An optimal design of a low energy (300 MeV) proton synchrotron for medical applications is addressed. The machine has the following properties: (1) The transition energy is higher than the targets final proton beam energy of 300 MeV; (2) the betatron tunes are chosen such that the machine is free of systematic resonances; (3) the machine can accommodate both slow and fast extraction systems; and (4) the machine can provide rapid cycling operations depending on the rf cavity voltage. Applications of this low energy synchrotron are discussed.