nils-herrmann/clean_scirepeval huggingface dataset:
Data-driven depth map refinement via multi-scale sparse representation

Depth maps captured by consumer-level depth cameras such as Kinect are usually degraded by noise, missing values, and quantization. In this paper, we present a data-driven approach for refining degraded RAWdepth maps that are coupled with an RGB image. The key idea of our approach is to take advantage of a training set of high-quality depth data and transfer its information to the RAW depth map through multi-scale dictionary learning. Utilizing a sparse representation, our method learns a dictionary of geometric primitives which captures the correlation between high-quality mesh data, RAW depth maps and RGB images. The dictionary is learned and applied in a manner that accounts for various practical issues that arise in dictionary-based depth refinement. Compared to previous approaches that only utilize the correlation between RAW depth maps and RGB images, our method produces improved depth maps without over-smoothing. Since our approach is data driven, the refinement can be targeted to a specific class of objects by employing a corresponding training set. In our experiments, we show that this leads to additional improvements in recovering depth maps of human faces.
Simulating sensorimotor metaphors: Novel metaphors influence sensory judgments

Embodied cognition theory proposes that individuals' abstract concepts can be associated with sensorimotor processes. The authors examined the effects of teaching participants novel embodied metaphors, not based in prior physical experience, and found evidence suggesting that they lead to embodied simulation, suggesting refinements to current models of embodied cognition. Creating novel embodiments of abstract concepts in the laboratory may be a useful method for examining mechanisms of embodied cognition.
AFNI: software for analysis and visualization of functional magnetic resonance neuroimages.

A package of computer programs for analysis and visualization of three-dimensional human brain functional magnetic resonance imaging (FMRI) results is described. The software can color overlay neural activation maps onto higher resolution anatomical scans. Slices in each cardinal plane can be viewed simultaneously. Manual placement of markers on anatomical landmarks allows transformation of anatomical and functional scans into stereotaxic (Talairach-Tournoux) coordinates. The techniques for automatically generating transformed functional data sets from manually labeled anatomical data sets are described. Facilities are provided for several types of statistical analyses of multiple 3D functional data sets. The programs are written in ANSI C and Motif 1.2 to run on Unix workstations.
Working Memory Load Affects Processing Time in Spoken Word Recognition: Evidence from Eye-Movements

In daily life, speech perception is usually accompanied by other tasks that tap into working memory capacity. However, the role of working memory on speech processing is not clear. The goal of this study was to examine how working memory load affects the timeline for spoken word recognition in ideal listening conditions. We used the "visual world" eye-tracking paradigm. The task consisted of spoken instructions referring to one of four objects depicted on a computer monitor (e.g., "point at the candle"). Half of the trials presented a phonological competitor to the target word that either overlapped in the initial syllable (onset) or at the last syllable (offset). Eye movements captured listeners' ability to differentiate the target noun from its depicted phonological competitor (e.g., candy or sandal). We manipulated working memory load by using a digit pre-load task, where participants had to retain either one (low-load) or four (high-load) spoken digits for the duration of a spoken word recognition trial. The data show that the high-load condition delayed real-time target discrimination. Specifically, a four-digit load was sufficient to delay the point of discrimination between the spoken target word and its phonological competitor. Our results emphasize the important role working memory plays in speech perception, even when performed by young adults in ideal listening conditions.
Virtual anastylosis of Greek sculpture as museum policy for public outreach and cognitive accessibility

This paper deals with a virtual anastylosis of a Greek Archaic statue from ancient Sicily and the development of a public outreach protocol for those with visual impairment or cognitive disabilities through the application of three-dimensional (3-D) printing and haptic technology. The case study consists of the marble head from Leontinoi in southeastern Sicily, acquired in the 18th century and later kept in the collection of the Museum of Castello Ursino in Catania, and a marble torso, retrieved in 1904 and since then displayed in the Archaeological Museum of Siracusa. Due to similar stylistic features, the two pieces can be dated to the end of the sixth century BC. Their association has been an open problem, largely debated by scholars, who have based their hypotheses on comparisons between pictures, but the reassembly of the two artifacts was never attempted. As a result the importance of such an artifact, which could be the only intact Archaic statue of a kouros ever found in Greek Sicily, has not fully been grasped by the public. Consequently, the curatorial dissemination of the knowledge related with such artifacts is purely based on photographic material. As a response to this scenario, the two objects have been 3-D scanned and virtually reassembled. The result has been shared digitally with the public via a web platform and, in order to include increased accessibility for the public with physical or cognitive disabilities, copies of the reassembled statue have been 3-D printed and an interactive test with the 3-Dmodel has been carried out with a haptic device.
Hypoascorbemia induces atherosclerosis and vascular deposition of lipoprotein(a) in transgenic mice.

Lipoprotein(a), a variant of LDL carrying the adhesive glycoprotein apo(a), is a leading risk factor for cardiovascular disease. Lipoprotein(a) (Lp(a)) is found in humans and subhuman primates but rarely in lower mammals. Better understanding of the evolutionary advantage of this molecule should elucidate its physiological role. We developed a new mouse model with two characteristics of human metabolism: the expression of Lp(a) and the lack of endogenous ascorbate (vitamin C) production. We show that dietary deficiency of ascorbate increases serum levels of Lp(a). Moreover, chronic hypoascorbemia and complete depletion of ascorbate (scurvy) leads to Lp(a) accumulation in the vascular wall and parallels atherosclerotic lesion development. The results suggest that dietary ascorbate deficiency is a risk factor for atherosclerosis independent of dietary lipids. We provide support for the concept that Lp(a) functions as a mobile repair molecule compensating for the structural impairment of the vascular wall, a morphological hallmark of hypoascorbemia and scurvy.
Enhanced text steganography by changing word's spelling

Digitization of electronic signals has brought a stir in the telecommunication field. From copper wire to fiber optics, technology has gone through a mammoth change rendering a variety of communication media available for use by people, at the cheapest of rates possible, to communicate in a nearly perfect error-free environment. Consumers can now freely exchange or distribute digital contents at any time and anywhere in the world. The situation where a perfect replica of digital content can easily be made has raised serious security concerns prompting for the protection of rights of intellectual ownership and apprehension of unauthorized tampering of digital information for mala fide usage. On the other hand, the way multimedia contents are being tempered with has also made it an important subject of technological research.
 This paper suggests an enhanced method for secretly exchanging real time or off line information by using differently spelled words in British and American Language. The concept has been implemented via software applications developed in Visual Basic 6 programming language.
User-centered design and usability testing of a web site: An illustrative case study

Administrators at a large midwestern university recognized that their World Wide Web site was rapidly becoming an important factor in recruiting new students. They also expected this Web site to serve many different types of information needs for existing students,faculty, staff, and alumni. An interdisciplinary team of faculty, graduate students, and staff was formed to evaluate the existing Web site. A group from this teamfirst conducted a needs analysis to determine the kinds of irrfarmation the target population was seeking. This analysis led to the creation of a new information structure for the Web site. Usability tests of the both the new and old designs were conducted on paper. Users were able to f ind answers to frequently asked questions much more rapidly and successfully with the new information structure. This structure was further refined through additional usability tests conducted on the Web itself. This descriptive case study illustrates the value of user-centered design and usability testing of World Wide Web sites.  In this article, we emphasize rapid prototyping and usability testing as methods for design research. We begin with an overview of usercentered design and usability testing. Next we describe the entire Web design project, the iterative process of rapid prototyping and usability testing, and how the findings helped to improve the design. Finally, we discuss recommendations for university Web site design and reflect on problems faced in usability testing.
3D ancient mosaics

Digital 3D mosaics generation is a current trend of NPR (Non Photorealistic Rendering) field; in this demo we present an interactive system realized in JAVA where the user can simulate ancient mosaic in a 3D environment starting for any input image. Different simulation engines able to render the so-called "Opus Musivum"and "Opus Vermiculatum" are employed. Different parameters can be dynamically adjusted to obtain very impressive results.
Assessment of the hepatic veins in poor contrast conditions using dual energy CT: evaluation of a novel monoenergetic extrapolation software algorithm.

To evaluate a novel monoenergetic post-processing algorithm (MEI+) in patients with poor intrahepatic contrast enhancement.



25 patients were retrospectively included in this study. Late-phase imaging of the upper abdomen, which was acquired in dual-energy mode (100/140 kV), was used as a model for poor intrahepatic contrast enhancement. Traditional monoenergetic images (MEI), linearly weighted mixed images with different mixing ratios (MI), sole 100 and 140 kV and MEI+ images were calculated. MEI+ is a novel technique which applies frequency-based mixing of the low keV images and an image of optimal keV from a noise perspective to combine the benefits of both image stacks. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the intrahepatic vasculature (IHV) and liver parenchyma (LP) were objectively measured and depiction of IHV was subjectively rated and correlated with portal venous imaging by two readers in consensus.



MEI+ was able to increase the SNR of the IHV (5.7 ± 0.4 at 40keV) and LP (4.9 ± 1.0 at 90keV) and CNR (2.1 ± 0.6 at 40keV) greatly compared to MEI (5.1 ± 1.1 at 80keV, 4.7 ± 1.0 at 80keV, 1.0 ± 0.4 at 70keV), MI (5.2 ± 1.1 M5:5, 4.8 ± 1.0 M5:5, 1.0 ± 3.5 M9:1), sole 100 kV images (4.4 ± 1.0, 3.7 ± 0.8, 1.0 ± 0.3) and 140 kV images (2.8 ± 0.5, 3.1 ± 0.6, 0.1 ± 0.2). Subjective assessment rated MEI+ of virtual 40 keV superior to all other images.



MEI+ is a very promising algorithm for monoenergetic extrapolation which is able to overcome noise limitations associated with traditional monoenergetic techniques at low virtual keV levels and consequently does not suffer from a decline of SNR and CNR at low keV values. This algorithm allows an improvement of IHV depiction in the presence of poor contrast.



• The evaluated new image-based algorithm for virtual monoenergetic imaging allows calculating low virtual keV images from dual energy datasets with significantly improved contrast-to-noise ratios. • The image based novel monoenergetic extrapolation algorithm applies frequency-based mixing of the low keV images and an image of optimal keV from a noise perspective to combine the benefits of both image stacks.• When compared to traditional monoenergetic images, the novel monoenergetic algorithm has improved contrast-to-noise ratios for both low and high virtual keV images.• Contrast-enhanced dual energy images with poor contrast conditions can be significantly improved, e.g. late phase imaging of the liver.
An Event-Driven Ultra-Low-Power Smart Visual Sensor

In this paper, we present an ultra-low-power smart visual sensor architecture. A 10.6-μW low-resolution contrast-based imager featuring internal analog preprocessing is coupled with an energy-efficient quad-core cluster processor that exploits near-threshold computing within a few milliwatt power envelope. We demonstrate the capability of the smart camera on a moving object detection framework. The computational load is distributed among mixed-signal pixel and digital parallel processing. Such local processing reduces the amount of digital data to be sent out of the node by 91%. Exploiting context aware analog circuits, the imager only dispatches meaningful postprocessed data to the processing unit, lowering the sensor-to-processor bandwidth by 31× with respect to transmitting a full pixel frame. To extract high-level features, an event-driven approach is applied to the sensor data and optimized for parallel runtime execution. A 57.7× system energy saving is reached through the event-driven approach with respect to frame-based processing, on a low-power MCU node. The near-threshold parallel processor further reduces the processing energy cost by 6.64×, achieving an overall system energy cost of 1.79 μJ per frame, which results to be 21.8× and up to 383× lower than, respectively, an event-based imaging system based on an asynchronous visual sensor and a traditional frame-based smart visual sensor.
China Compared with the US : Cultural Differences and the Impacts on Advertising Appeals

An important first step to successful global marketing is to understand the similarities and dissimilarities of values between cultures. This task is particularly daunting for companies trying to do business with China because of the scarcity of research-based information. This study uses updated values of Hofstede’s (1980) cultural model to compare the effectiveness of Pollay’s advertising appeals between the U.S. and China. Nine of the twenty hypotheses predicting effective appeals based on cultural dimensions were supported. An additional hypothesis was significant, but in the opposite direction as predicted. These findings suggest that it would be unwise to use Hofstede’s cultural dimensions as a sole predictor for effective advertising appeals. The Hofstede dimensions may lack the currency and fine grain necessary to effectively predict the success of the various advertising appeals. Further, the effectiveness of advertising appeals may be moderated by other factors, such as age, societal trends, political-legal environment and product usage.
Multi-objective Architecture Search for CNNs

Architecture search aims at automatically finding neural architectures that are competitive with architectures designed by human experts. While recent approaches have come close to matching the predictive performance of manually designed architectures for image recognition, these approaches are problematic under constrained resources for two reasons: first, the architecture search itself requires vast computational resources for most proposed methods. Secondly, the found neural architectures are solely optimized for high predictive performance without penalizing excessive resource consumption. We address the first shortcoming by proposing NASH, an architecture search which considerable reduces the computational resources required for training novel architectures by applying network morphisms and aggressive learning rate schedules. On CIFAR10, NASH finds architectures with errors below 4% in only 3 days. We address the second shortcoming by proposing Pareto-NASH, a method for multi-objective architecture search that allows approximating the Pareto-front of architectures under multiple objective, such as predictive performance and number of parameters, in a single run of the method. Within 56 GPU days of architecture search, Pareto-NASH finds a model with 4M parameters and test error of 3.5%, as well as a model with less than 1M parameters and test error of 4.6%.
Extracting Optimal Performance from Dynamic Time Warping

Dynamic Time Warping (DTW) is a distance measure that compares two time series after optimally aligning them. DTW is being used for decades in thousands of academic and industrial projects despite the very expensive computational complexity, O(n2). These applications include data mining, image processing, signal processing, robotics and computer graphics among many others. In spite of all this research effort, there are many myths and misunderstanding about DTW in the literature, for example "it is too slow to be useful" or "the warping window size does not matter much." In this tutorial, we correct these misunderstandings and we summarize the research efforts in optimizing both the efficiency and effectiveness of both the basic DTW algorithm, and of the higher-level algorithms that exploit DTW such as similarity search, clustering and classification. We will discuss variants of DTW such as constrained DTW, multidimensional DTW and asynchronous DTW, and optimization techniques such as lower bounding, early abandoning, run-length encoding, bounded approximation and hardware optimization. We will discuss a multitude of application areas including physiological monitoring, social media mining, activity recognition and animal sound processing. The optimization techniques are generalizable to other domains on various data types and problems.
A fast source-oriented image clustering method for digital forensics

We present in this paper an algorithm that is capable of clustering images taken by an unknown number of unknown digital cameras into groups, such that each contains only images taken by the same source camera. It first extracts a sensor pattern noise (SPN) from each image, which serves as the fingerprint of the camera that has taken the image. The image clustering is performed based on the pairwise correlations between camera fingerprints extracted from images. During this process, each SPN is treated as a random variable and a Markov random field (MRF) approach is employed to iteratively assign a class label to each SPN (i.e., random variable). The clustering process requires no a priori knowledge about the dataset from the user. A concise yet effective cost function is formulated to allow different “neighbors” different voting power in determining the class label of the image in question depending on their similarities. Comparative experiments were carried out on the Dresden image database to demonstrate the advantages of the proposed clustering algorithm.
Fractional-N DPLL-Based Low-Power Clocking Architecture for 1–14 Gb/s Multi-Standard Transmitter

A low-power clocking solution is presented based on fractional-N highly digital LC-phase-locked loop (PLL) and sub-sampled ring PLL targeting multi-standard SerDes applications. The shared fractional-N digital LC-PLL covers 7–10 GHz frequency range consuming only 8-mW power and occupying 0.15 mm2 of silicon area with integrated jitter of 264 fs. Frequency resolution of the LC-PLL is 2 MHz. Per lane clock is generated using wide bandwidth ring PLL covering 800 MHz to 4 GHz to support the data rates between 1 and 14 Gb/s. The ring PLL supports dither-less fractional resolution of 250 MHz, corrects I/Q error with split tuning, and achieves less than 400-fs integrated jitter. Transmitter works at 14 Gb/s with power efficiency of 0.80 pJ/bit.
Timed Commitments

We introduce and construct timed commitment schemes, an extension to the standard notion of commitments in which a potential forced opening phase permits the receiver to recover (with effort) the committed value without the help of the committer. An important application of our timed-commitment scheme is contract signing: two mutually suspicious parties wish to exchange signatures on a contract. We show a two-party protocol that allows them to exchange RSA or Rabin signatures. The protocol is strongly fair: if one party quits the protocol early, then the two parties must invest comparable amounts of time to retrieve the signatures. This statement holds even if one party has many more machines than the other. Other applications, including honesty preserving auctions and collective coin-flipping, are discussed.
Yaw and pitch control of a twin rotor MIMO system

This paper addresses the control of the standard twin rotor multi-input-multi-output (MIMO) control system problem. First, nonlinear dynamic model of the system was derived using basic laws of physics. While it was possible to linearize some of the plant nonlinearities, some of them were not, such as squared input. In the conventional approach, this problem has been solved by linearizing the possible nonlinearities, while neglecting the others, at the cost of reduced performance. Most importantly, the latter partially linearized approach demands linearized plant model at every operating point, which makes the controller implementation complicated when considering a wide dynamic operating range. In order to overcome limitations of the partially linearized approach, we derive a nonlinear controller. In that we use the tracking error dynamics to arrive at a compromise between the tracking performances of the pitch and yaw axes control and the smoothness of the actuator input. Furthermore, one of the key features of twin rotor MIMO system is its dynamic cross coupling. Therefore, in order to get rid of the cross coupling a dynamic de-coupler was used. First the plant and the controller was simulated in MATLAB/Simulink™ environment. Then, it was implemented in the hardware to control the pitch and yaw of an actual Twin Rotor MIMO system. The performance assessed using Integrated Absolute Error (IAE) and Accumulated Squared Input (ASI) metrics which represents the tracking performance and the energy input respectively. The performance matrices of the controller were compared with a PID controller tuned to the partially linearized plant model and the results show approximately more than 25% improvement both in terms of IAE and ASI.
[Considerations about the nervous system phylogenetic evolution, behavior, and the emergence of consciousness].

This text reviews the generic aspects of the central nervous system evolutionary development, emphasizing the developmental features of the brain structures related with behavior and with the cognitive functions that finally characterized the human being. Over the limbic structures that with the advent of mammals were developed on the top of the primitive nervous system of their ancestrals, the ultimate cortical development with neurons arranged in layers constituted the structural base for an enhanced sensory discrimination, for more complex motor activities, and for the development of cognitive and intellectual functions that finally characterized the human being. The knowledge of the central nervous system phylogeny allow us particularly to infer possible correlations between the brain structures that were developed along phylogeny and the behavior of their related beings. In this direction, without discussing its conceptual aspects, this review ends with a discussion about the central nervous system evolutionary development and the emergence of consciousness, in the light of its most recent contributions.