nils-herrmann/clean_scirepeval huggingface dataset:
Nonnegative Matrix Factorization with the Itakura-Saito Divergence: With Application to Music Analysis

This letter presents theoretical, algorithmic, and experimental results about nonnegative matrix factorization (NMF) with the Itakura-Saito (IS) divergence. We describe how IS-NMF is underlaid by a well-defined statistical model of superimposed gaussian components and is equivalent to maximum likelihood estimation of variance parameters. This setting can accommodate regularization constraints on the factors through Bayesian priors. In particular, inverse-gamma and gamma Markov chain priors are considered in this work. Estimation can be carried out using a space-alternating generalized expectation-maximization (SAGE) algorithm; this leads to a novel type of NMF algorithm, whose convergence to a stationary point of the IS cost function is guaranteed. We also discuss the links between the IS divergence and other cost functions used in NMF, in particular, the Euclidean distance and the generalized Kullback-Leibler (KL) divergence. As such, we describe how IS-NMF can also be performed using a gradient multiplicative algorithm (a standard algorithm structure in NMF) whose convergence is observed in practice, though not proven. Finally, we report a furnished experimental comparative study of Euclidean-NMF, KL-NMF, and IS-NMF algorithms applied to the power spectrogram of a short piano sequence recorded in real conditions, with various initializations and model orders. Then we show how IS-NMF can successfully be employed for denoising and upmix (mono to stereo conversion) of an original piece of early jazz music. These experiments indicate that IS-NMF correctly captures the semantics of audio and is better suited to the representation of music signals than NMF with the usual Euclidean and KL costs.
Will NoSQL Databases Live Up to Their Promise?

Many organizations collect vast amounts of customer, scientific, sales, and other data for future analysis. Traditionally, most of these organizations have stored structured data in relational databases for subsequent access and analysis. However, a growing number of developers and users have begun turning to various types of nonrelational, now frequently called NoSQL-databases. Nonrelational databases, including hierarchical, graph, and object-oriented databases-have been around since the late 1960s. However, new types of NoSQL databases are being developed. And only now are they beginning to gain market traction. Different NoSQL databases take different approaches. What they have in common is that they're not relational. Their primary advantage is that, unlike relational databases, they handle unstructured data such as word-processing files, e-mail, multimedia, and social media efficiently. This paper discuss issues such as limitations, advantages, concerns and doubts regarding NoSQL databases.
Shortest-path kernels on graphs

Data mining algorithms are facing the challenge to deal with an increasing number of complex objects. For graph data, a whole toolbox of data mining algorithms becomes available by defining a kernel function on instances of graphs. Graph kernels based on walks, subtrees and cycles in graphs have been proposed so far. As a general problem, these kernels are either computationally expensive or limited in their expressiveness. We try to overcome this problem by defining expressive graph kernels which are based on paths. As the computation of all paths and longest paths in a graph is NP-hard, we propose graph kernels based on shortest paths. These kernels are computable in polynomial time, retain expressivity and are still positive definite. In experiments on classification of graph models of proteins, our shortest-path kernels show significantly higher classification accuracy than walk-based kernels.
Multiscale Rotation-Invariant Convolutional Neural Networks for Lung Texture Classification

We propose a new multiscale rotation-invariant convolutional neural network (MRCNN) model for classifying various lung tissue types on high-resolution computed tomography. MRCNN employs Gabor-local binary pattern that introduces a good property in image analysis—invariance to image scales and rotations. In addition, we offer an approach to deal with the problems caused by imbalanced number of samples between different classes in most of the existing works, accomplished by changing the overlapping size between the adjacent patches. Experimental results on a public interstitial lung disease database show a superior performance of the proposed method to state of the art.
Semantic Sensor Web

Sensors are distributed across the globe leading to an avalanche of data about our environment. It is possible today to utilize networks of sensors to detect and identify a multitude of observations, from simple phenomena to complex events and situations. The lack of integration and communication between these networks, however, often isolates important data streams and intensifies the existing problem of too much data and not enough knowledge. With a view to addressing this problem, the semantic sensor Web (SSW) proposes that sensor data be annotated with semantic metadata that will both increase interoperability and provide contextual information essential for situational knowledge.
A meta-analytic review of the effects of acute cortisol administration on human memory

Adrenal glucocorticoids (GC) secreted during stress modulate memory. Animal and human studies investigating the effects of acute GC treatment on memory have reported conflicting (enhancing as well as impairing) results. Several theories have been proposed to integrate these contradictory findings. Among the variables discussed are the timing of the GC treatment (before learning or before retrieval) and the time of day (morning versus afternoon). Here we review meta-analytically the results of 16 studies, which experimentally investigated the acute impact of cortisol treatment on human memory. The results revealed that the timing of GC application in the course of a study is a relevant variable which explains a substantial amount of the significant heterogeneity within the effect sizes. The studies which administered cortisol before retrieval (n = 4) reported a significant decrease (average effect size of d = -.49) in memory performance. Studies which administered cortisol before learning (n =12) found on average no effect (d = .08), but there is heterogeneity within these effect sizes. Further analysis on these experiments indicated that studies, which administered cortisol in the morning found a significant memory impairment (d = -.40), while studies conducted in the afternoon observed a small but significant memory enhancement (d = .22). This meta-analysis supports the idea that the timing of GC administration (before learning or before retrieval) is a major determinant of the effects of GCs on human memory. We discuss methodological limitations of the current analysis and suggest several areas for future research.
COMBINE: leveraging the power of wireless peers through collaborative downloading

Mobile devices are increasingly equipped with multiple network interfaces: Wireless Local Area Network (WLAN) interfaces for local connectivity and Wireless Wide Area Network (WWAN) interfaces for wide-area connectivity. The WWAN typically provides much wider coverage but much lower speeds than the WLAN. To address this dichotomy, we present COMBINE, a system for collaborative downloading wherein devices that are within WLAN range pool together their WWAN links, significantly increasing the effective speed available to them.
 COMBINE makes a number of novel contributions overprior work in this area, including: (a) a framework of incentives for collaboration that addresses several practical issues including the unification of monetary and energy costs, and on-the-fly estimation of the energy cost of communication in a system in operation; (b) a protocol for collaborative group formation and workload distribution that is energy efficient and adaptive to fluctuations in network conditions; and (c) an application-level striping procedure that eases deployment by avoiding the need for special-purpose proxies in the infrastructure. We present experimental results based on the prototype we have implemented that showen couraging speeds-ups with COMBINE.
4-points congruent sets for robust pairwise surface registration

We introduce 4PCS, a fast and robust alignment scheme for 3D point sets that uses wide bases, which are known to be resilient to noise and outliers. The algorithm allows registering raw noisy data, possibly contaminated with outliers, without pre-filtering or denoising the data. Further, the method significantly reduces the number of trials required to establish a reliable registration between the underlying surfaces in the presence of noise, without any assumptions about starting alignment. Our method is based on a novel technique to extract all coplanar 4-points sets from a 3D point set that are approximately congruent, under rigid transformation, to a given set of coplanar 4-points. This extraction procedure runs in roughly O(n2 + k) time, where n is the number of candidate points and k is the number of reported 4-points sets. In practice, when noise level is low and there is sufficient overlap, using local descriptors the time complexity reduces to O(n + k). We also propose an extension to handle similarity and affine transforms. Our technique achieves an order of magnitude asymptotic acceleration compared to common randomized alignment techniques. We demonstrate the robustness of our algorithm on several sets of multiple range scans with varying degree of noise, outliers, and extent of overlap.
The Technology Acceptance Model: A Meta-Analysis of Empirical Findings

The technology acceptance model proposes that perceived ease of use and perceived usefulness predict the acceptance of information technology. Since its inception, the model has been tested with various applications in tens of studies and has become a most widely applied model of user acceptance and usage. Nevertheless, the reported findings on the model are mixed in terms of statistical significance, direction, and magnitude. In this study, we conducted a meta-analysis based on 26 selected empirical studies in order to synthesize the empirical evidence. The results suggest that both the correlation between usefulness and acceptance and between usefulness and ease of use are somewhat strong. However, the relationship between ease of use and acceptance is weak, and its significance does not pass the fail-safe test. IDEA GROUP PUBLISHING This chapter appears in the book, Advanced Topics in End User Computing, vol. 4 edited by M. Adam Mahmood  Fax 717/533-8661; URL-http://www.idea-group.com ITB11300
A Faster and More Realistic Flush+Reload Attack on AES

Cloud’s unrivaled cost effectiveness and on the fly operation versatility is attractive to enterprise and personal users. However, the cloud inherits a dangerous behavior from virtualization systems that poses a serious security risk: resource sharing. This work exploits a shared resource optimization technique called memory deduplication to mount a powerful known-ciphertext only cache side-channel attack on a popular OpenSSL implementation of AES. In contrast to the other cross-VM cache attacks, our attack does not require synchronization with the target server and is fully asynchronous, working in a more realistic scenario with much weaker assumption. Also, our attack succeeds in just 15 seconds working across cores in the cross-VM setting. Our results show that there is strong information leakage through cache in virtualized systems and the memory deduplication should be approached with caution.
Expanding cellular coverage via cell-edge deployment in heterogeneous networks: spectral efficiency and backhaul power consumption perspectives

Heterogeneous small-cell networks (HetNets) are considered to be a standard part of future mobile networks where operator/consumer deployed small-cells, such as femto-cells, relays, and distributed antennas (DAs), complement the existing macrocell infrastructure. This article proposes the need-oriented deployment of small-cells and device-to-device (D2D) communication around the edge of the macrocell such that the small-cell base stations (SBSs) and D2D communication serve the cell-edge mobile users, thereby expanding the network coverage and capacity. In this context, we present competitive network configurations, namely, femto-on-edge, DA-one-dge, relay-on-edge, and D2D-communication on- edge, where femto base stations, DA elements, relay base stations, and D2D communication, respectively, are deployed around the edge of the macrocell. The proposed deployments ensure performance gains in the network in terms of spectral efficiency and power consumption by facilitating the cell-edge mobile users with small-cells and D2D communication. In order to calibrate the impact of power consumption on system performance and network topology, this article discusses the detailed breakdown of the end-to-end power consumption, which includes backhaul, access, and aggregation network power consumptions. Several comparative simulation results quantify the improvements in spectral efficiency and power consumption of the D2D-communication-on-edge configuration to establish a greener network over the other competitive configurations.
Mobile Media Use, Multitasking and Distractibility

Portable media devices are ubiquitous and their use has become a core component of many people’s daily experience, but to what effect? In this paper, the authors review research on the ways in which media use and multitasking relate to distraction, distractibility and impulsivity. They review recent research on the effects of media multitasking on driving, walking, work, and academic performance. The authors discuss earlier research concerning the nature of media’s impact on attention and review cognitive and neuropsychological findings on the effects of divided attention. Research provides clear evidence that mobile media use is distracting, with consequences for safety, efficiency and learning. Greater use of media is correlated with higher levels of trait impulsivity and distractibility, but the direction of causality has not been established. Individuals may become more skilled at media multitasking over time, but intervention is currently required to improve the safe and effective use of mobile media.  10.4018/ijcbpl.2012070102 16 International Journal of Cyber Behavior, Psychology and Learning, 2(3), 15-29, July-September 2012  Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. and neuropsychological research on the effects of divided attention. Finally, we explore how high levels of media multitasking might alter our general responses to experience in ways that are marked by changes in distractibility and impulsivity. THE DISTRACTING EFFECTS OF MULTITASKING WITH MOBILE MEDIA
Design of Dielectric Lens Loaded Double Ridged Horn Antenna for Millimetre Wave Application

In this paper, designs of Dielectric Lens Loaded Double Ridged Horn Antenna for Millimetre Wave Applications is investigated. Firstly a double ridged horn antenna is designed and simulated in CST environment. After that, 2 dielectric lens architecture are designed and placed at the aperture of the antenna. It is seen that by placing spherical shaped dielectric lens, it is possible to achieve improvement in return loss and farfield gain of the antennas design in a 20–40 GHz bandwidth.
A New Sampling Technique for Tensors

In this paper we propose new techniques to sample arbitrary third-order tensors, with an objective of speeding up tensor algorithms that have recently gained popularity in machine learning. Our main contribution is a new way to select, in a biased random way, only O(n/ǫ) of the possible n elements while still achieving each of the three goals: (a) tensor sparsification: for a tensor that has to be formed from arbitrary samples, compute very few elements to get a good spectral approximation, and for arbitrary orthogonal tensors (b) tensor completion: recover an exactly low-rank tensor from a small number of samples via alternating least squares, or (c) tensor factorization: approximating factors of a low-rank tensor corrupted by noise. Our sampling can be used along with existing tensor-based algorithms to speed them up, removing the computational bottleneck in these methods.
Non-uniformity Correction of Infrared Images by Midway Equalization

The non-uniformity is a time-dependent noise caused by the lack of sensor equalization. We present here the detailed algorithm and online demo of the non-uniformity correction method by midway infrared equalization. This method was designed to suit infrared images. Nevertheless, it can be applied to images produced for example by scanners, or by push-broom satellites. This single image method works on static images, is fully automatic, has no user parameter, and requires no registration. It needs no camera motion compensation, no closed aperture sensor equalization and is able to correct for a fully non-linear non-uniformity.
Cytokines in atherosclerosis: pathogenic and regulatory pathways.

Atherosclerosis is a chronic disease of the arterial wall where both innate and adaptive immunoinflammatory mechanisms are involved. Inflammation is central at all stages of atherosclerosis. It is implicated in the formation of early fatty streaks, when the endothelium is activated and expresses chemokines and adhesion molecules leading to monocyte/lymphocyte recruitment and infiltration into the subendothelium. It also acts at the onset of adverse clinical vascular events, when activated cells within the plaque secrete matrix proteases that degrade extracellular matrix proteins and weaken the fibrous cap, leading to rupture and thrombus formation. Cells involved in the atherosclerotic process secrete and are activated by soluble factors, known as cytokines. Important recent advances in the comprehension of the mechanisms of atherosclerosis provided evidence that the immunoinflammatory response in atherosclerosis is modulated by regulatory pathways, in which the two anti-inflammatory cytokines interleukin-10 and transforming growth factor-beta play a critical role. The purpose of this review is to bring together the current information concerning the role of cytokines in the development, progression, and complications of atherosclerosis. Specific emphasis is placed on the contribution of pro- and anti-inflammatory cytokines to pathogenic (innate and adaptive) and regulatory immunity in the context of atherosclerosis. Based on our current knowledge of the role of cytokines in atherosclerosis, we propose some novel therapeutic strategies to combat this disease. In addition, we discuss the potential of circulating cytokine levels as biomarkers of coronary artery disease.
Older Adults' Experiences Using a Commercially Available Monitor to Self-Track Their Physical Activity.

Physical activity contributes to older adults' autonomy, mobility, and quality of life as they age, yet fewer than 1 in 5 engage in activities as recommended. Many older adults track their exercise using pencil and paper, or their memory. Commercially available physical activity monitors (PAM) have the potential to facilitate these tracking practices and, in turn, physical activity. An assessment of older adults' long-term experiences with PAM is needed to understand this potential.



To assess short and long-term experiences of adults >70 years old using a PAM (Fitbit One) in terms of acceptance, ease-of-use, and usefulness: domains in the technology acceptance model.



This prospective study included 95 community-dwelling older adults, all of whom received a PAM as part of randomized controlled trial piloting a fall-reducing physical activity promotion intervention. Ten-item surveys were administered 10 weeks and 8 months after the study started. Survey ratings are described and analyzed over time, and compared by sex, education, and age.



Participants were mostly women (71/95, 75%), 70 to 96 years old, and had some college education (68/95, 72%). Most participants (86/95, 91%) agreed or strongly agreed that the PAM was easy to use, useful, and acceptable both 10 weeks and 8 months after enrolling in the study. Ratings dropped between these time points in all survey domains: ease-of-use (median difference 0.66 points, P=.001); usefulness (median difference 0.16 points, P=.193); and acceptance (median difference 0.17 points, P=.032). Differences in ratings by sex or educational attainment were not statistically significant at either time point. Most participants 80+ years of age (28/37, 76%) agreed or strongly agreed with survey items at long-term follow-up, however their ratings were significantly lower than participants in younger age groups at both time points.



Study results indicate it is feasible for older adults (70-90+ years of age) to use PAMs when self-tracking their physical activity, and provide a basis for developing recommendations to integrate PAMs into promotional efforts.
Distributed access control on IoT ledger-based architecture

Due to increased number of attacks on the Internet of Things (IoT) devices, the security of IoT networks became critical. Some recent researches proposed the adoption of blockchain in IoT networks without a thorough discussion on the impact of the solution on the devices performance. Furthermore, blockchain employment in the context of IoT can be challenging due to the devices hardware limitations. To fill this gap, this paper proposes an IoT ledger-based architecture to ensure access control on heterogeneous scenarios. This research applies conventional devices used on IoT networks, such as Arduino, Raspberry and Orange Pi boards. Finally, we perform performance evaluation focused on access control of IoT devices and on information propagation through peers on a private IoT network scenario.
User perception of adapting video quality

In general, video quality adaptation and video quality evaluation are distinct activities. Most adaptive delivery mechanisms for streaming multimedia content do not explicitly consider user-perceived quality when making adaptation decisions. Equally, video quality evaluation techniques are not designed to evaluate instantaneous quality where the quality is changing over time. We propose that an Optimal Adaptation Trajectory (OAT) through the set of possible encoding exists, and that it indicates how to adapt encoding quality in response to changes in network conditions in order to maximize user-perceived quality. The subjective and objective tests carried out to find such trajectories for a number of different MPEG-4 video clips are described. Experimental subjective testing results are presented that demonstrate the dynamic nature of user perception with adapting multimedia. The results demonstrate that adaptation using the OAT out-performs conventional adaptation strategies in which only a single aspect of the video quality is adapted. In contrast, the OAT provides a mechanism to adapt multiple aspects of the video quality thereby giving better user-perceived quality in both the short and long term.