nils-herrmann/clean_scirepeval huggingface dataset:
Mixture models, robustness, and sum of squares proofs

We use the Sum of Squares method to develop new efficient algorithms for learning well-separated mixtures of Gaussians and robust mean estimation, both in high dimensions, that substantially improve upon the statistical guarantees achieved by previous efficient algorithms. Our contributions are: 
 Mixture models with separated means: We study mixtures of poly(<i>k</i>)-many <i>k</i>-dimensional distributions where the means of every pair of distributions are separated by at least <i>k</i><sup>ε</sup>. In the special case of spherical Gaussian mixtures, we give a <i>k</i><sup><i>O</i>(1/ε)</sup>-time algorithm that learns the means assuming separation at least <i>k</i><sup>ε</sup>, for any ε> 0. This is the first algorithm to improve on greedy (“single-linkage”) and spectral clustering, breaking a long-standing barrier for efficient algorithms at separation <i>k</i><sup>1/4</sup>. 
 Robust estimation: When an unknown (1−ε)-fraction of <i>X</i><sub>1</sub>,…,<i>X</i><sub><i>n</i></sub> are chosen from a sub-Gaussian distribution with mean µ but the remaining points are chosen adversarially, we give an algorithm recovering µ to error ε<sup>1−1/<i>t</i></sup> in time <i>k</i><sup><i>O</i>(<i>t</i>)</sup>, so long as sub-Gaussian-ness up to <i>O</i>(<i>t</i>) moments can be certified by a Sum of Squares proof. This is the first polynomial-time algorithm with guarantees approaching the information-theoretic limit for non-Gaussian distributions. Previous algorithms could not achieve error better than ε<sup>1/2</sup>. As a corollary, we achieve similar results for robust covariance estimation. 
 Both of these results are based on a unified technique. Inspired by recent algorithms of Diakonikolas et al. in robust statistics, we devise an SDP based on the Sum of Squares method for the following setting: given <i>X</i><sub>1</sub>,…,<i>X</i><sub><i>n</i></sub> ∈ ℝ<sup><i>k</i></sup> for large <i>k</i> and <i>n</i> = poly(<i>k</i>) with the promise that a subset of <i>X</i><sub>1</sub>,…,<i>X</i><sub><i>n</i></sub> were sampled from a probability distribution with bounded moments, recover some information about that distribution.
On limit cycle oscillations in discrete-time digital linear regulators

Increasing level of transistor integration with multiple voltage domains and power states, ever decreasing decoupling capacitance, fast load transients and the need for fine-grained spatio-temporal power management provide impetus for embedding distributed point of load (PoL) linear regulators deep within digital functional blocks of microprocessors and Systems-on-Chip (SoCs). This demands modularity in design as well as process and voltage scalability of such linear regulators. Digital linear regulators have emerged as an attractive counterpart to the traditional analog solutions. This paper presents the circuit implementation and a steady state response model of a discrete-time digital regulator with simulations and hardware measurements with an emphasis on the steady state oscillations. We develop parametric models to demonstrate design trade-offs for a stable steady state response.
Nonlinear flicker compensation for archived film sequences using motion-compensated graylevel tracing

We present a novel approach for the compensation of temporal brightness variations (commonly referred to as flicker) in archived film sequences. The proposed method is motivated by fundamental principles of photographic image registration and provides a substantial level of adaptation to temporal but also spatial variations of picture brightness. Additionally, our scheme provides an efficient mechanism for the adaptive estimation of flicker compensation profile, which makes it suitable for the compensation of long duration film sequences while it addresses problems arising from scene motion and illumination using a novel motion-compensated graylevel tracing approach. We present experimental evidence which suggests that our method offers high levels of performance and compares favorably with competing state-of-the-art techniques for flicker compensation.
Comprehension and memory processes in translation and interpreting

Our research team has spent the last few years studying the cognitive processes involved in simultaneous interpreting. The results of this research have shown that professional interpreters develop specific ways of using their working memory, due to their work in simultaneous interpreting; this allows them to perform the processes of linguistic input, lexical and semantic access, reformulation and production of the segment translated both simultaneously and under temporal pressure (Bajo, Padilla & Padilla, 1998). This research led to our interest in the processes involved in the tasks of mediation in general. We understand that linguistic and cultural mediation involves not only translation but also the different forms of interpreting: consecutive and simultaneous. Our general objective in this project is to outline a cognitive theory of translation and interpreting and find empirical support for it. From the field of translation and interpreting there have been some attempts to create global and partial theories of the processes of mediation (Gerver, 1976; Moser-Mercer, 1997; Gile, 1997), but most of these attempts lack empirical support. On the other hand, from the field of psycholinguistics there have been some attempts to make an empirical study of the tasks of translation (De Groot, 1993; Sánchez-Casas Davis and GarcíaAlbea, 1992) and interpreting (McDonald and Carpenter, 1981), but these have always been partial, concentrating on very specific aspects of translation and interpreting. The specific objectives of this project are:
Computing Resource Allocation in Three-Tier IoT Fog Networks: A Joint Optimization Approach Combining Stackelberg Game and Matching

Fog computing is a promising architecture to provide economical and low latency data services for future Internet of Things (IoT)-based network systems. Fog computing relies on a set of low-power fog nodes (FNs) that are located close to the end users to offload the services originally targeting at cloud data centers. In this paper, we consider a specific fog computing network consisting of a set of data service operators (DSOs) each of which controls a set of FNs to provide the required data service to a set of data service subscribers (DSSs). How to allocate the limited computing resources of FNs to all the DSSs to achieve an optimal and stable performance is an important problem. Therefore, we propose a joint optimization framework for all FNs, DSOs, and DSSs to achieve the optimal resource allocation schemes in a distributed fashion. In the framework, we first formulate a Stackelberg game to analyze the pricing problem for the DSOs as well as the resource allocation problem for the DSSs. Under the scenarios that the DSOs can know the expected amount of resource purchased by the DSSs, a many-to-many matching game is applied to investigate the pairing problem between DSOs and FNs. Finally, within the same DSO, we apply another layer of many-to-many matching between each of the paired FNs and serving DSSs to solve the FN-DSS pairing problem. Simulation results show that our proposed framework can significantly improve the performance of the IoT-based network systems.
Natural Language Processing for Intelligent Access to Scientific Information

During the last decade the amount of scientific information available on-line increased at an unprecedented rate. As a consequence, nowadays researchers are overwhelmed by an enormous and continuously growing number of articles to consider when they perform research activities like the exploration of advances in specific topics, peer reviewing, writing and evaluation of proposals. Natural Language Processing Technology represents a key enabling factor in providing scientists with intelligent patterns to access to scientific information. Extracting information from scientific papers, for example, can contribute to the development of rich scientific knowledge bases which can be leveraged to support intelligent knowledge access and question answering. Summarization techniques can reduce the size of long papers to their essential content or automatically generate state-of-the-art-reviews. Paraphrase or textual entailment techniques can contribute to the identification of relations across different scientific textual sources. This tutorial provides an overview of the most relevant tasks related to the processing of scientific documents, including but not limited to the in-depth analysis of the structure of the scientific articles, their semantic interpretation, content extraction and summarization.
A modulo based LSB steganography method

Steganography is the art of hiding the very presence of communication by embedding secret messages into innocuous looking cover images. The Least Significant Bit (LSB) steganography that replaces the least significant bits of the host medium is a widely used technique with low computational complexity and high insertion capacity. Although it has good perceptual transparency, it is vulnerable to steganalysis which is based on histogram analysis. In all the existing schemes detection of a secret message in a cover image can be easily detected from the histogram analysis and statistical analysis. Therefore developing new LSB steganography algorithms against statistical and histogram analysis is the prime requirement.
The role of software processes and communication in offshore software development

Offshore software development is a new trend in the information technology (IT) outsourcing field, fueled by the globalization of IT and the improvement of telecommunication facilities. Countries such as India, Ireland, and Israel have established a significant presence in this market. In this article, we discuss how software processes affect offshore development projects. We use data from projects in India, and focus on three measures of project performance: effort, elapsed time, and software rework.
Collaborating through Social Media to Create Health Awareness

This paper examines the role that individuals and organizations can play in creating awareness through the use of social media. In the healthcare context, creating cancer awareness is key in early detection of cancer as well as cancer prevention altogether. Using a multiple case study analysis, we are able to understand how collaboration through social media is used to promote such awareness. We find that social media is used to create an online community that drives the creation of cancer awareness in many different ways. This research has implications for organizations looking to use social media to promote awareness as it explains the building process and role of social media grassroots communities.
A brief study and comparison of Snort and Bro Open Source Network Intrusion Detection Systems

Security administration plays a vital role in network management tasks. The intrusion detection systems are primarily designed to protect the availability, confidentiality and integrity of critical network information systems. There are plenty of IDSes to choose from, both commercial and open source. Since most of the commercial intrusion detection systems are at typically thousands of dollars and they tend to represent a significant resource requirement in themselves, for small networks, use of such IDS is not feasible. Therefore mostly open source IDS are being used. This paper provides a general working behaviour, features and comparison of two most popular open source network IDS SNORT & BRO. Keywords-alerts, intrusion, logging, network traffic, open source, packets
A low cross-polarized antipodal Vivaldi antenna array for wideband operation

An antipodal Vivaldi antenna gives good performance over a wide bandwidth, but the cross-polarization level is unfortunately high due to the slot flares on different layers. As a simple technique to reduce the cross-polarization level in the array, the antipodal antenna and its mirror image are placed alternately in the H-plane. The cross-polarization level is reduced more than 20 dB at broadside.
Ratings for emotion film clips.

Film clips are widely utilized to elicit emotion in a variety of research studies. Normative ratings for scenes selected for these purposes support the idea that selected clips correspond to the intended target emotion, but studies reporting normative ratings are limited. Using an ethnically diverse sample of college undergraduates, selected clips were rated for intensity, discreteness, valence, and arousal. Variables hypothesized to affect the perception of stimuli (i.e., gender, race-ethnicity, and familiarity) were also examined. Our analyses generally indicated that males reacted strongly to positively valenced film clips, whereas females reacted more strongly to negatively valenced film clips. Caucasian participants tended to react more strongly to the film clips, and we found some variation by race-ethnicity across target emotions. Finally, familiarity with the films tended to produce higher ratings for positively valenced film clips, and lower ratings for negatively valenced film clips. These findings provide normative ratings for a useful set of film clips for the study of emotion, and they underscore factors to be considered in research that utilizes scenes from film for emotion elicitation.
Interdisciplinary Communities and Research Issues in Music Information Retrieval

Music Information Retrieval (MIR) is an interdisciplinary research area that has grown out of the need to manage burgeoning collections of music in digital form. Its diverse disciplinary communities have yet to articulate a common research agenda or agree on methodological principles and metrics of success. In order for MIR to succeed, researchers need to work with real user communities and develop research resources such as reference music collections, so that the wide variety of techniques being developed in MIR can be meaningfully compared with one another. Out of these efforts, a common MIR practice can emerge.
Design of four-arm four-crawler disaster response robot OCTOPUS

We developed a four-arm four-crawler advanced disaster response robot called OCTOPUS. Disaster response robots are expected to be capable of both mobility, e.g., entering narrow spaces over very rough unstable ground, and workability, e.g., conducting complex debris-demolition work. However, conventional disaster response robots are specialized in either mobility or workability. Moreover, strategies to independently enhance the capability of crawlers for mobility and arms for workability will increase the robot size and weight. To balance environmental applicability with the mobility and workability, OCTOPUS is equipped with a mutual complementary strategy between its arms and crawlers. The four arms conduct complex tasks while ensuring stabilization when climbing steps. The four crawlers translate rough terrain while avoiding toppling over when conducting demolition work. OCTOPUS is hydraulic driven and teleoperated by two operators. To evaluate the performance of OCTOPUS, we conducted preliminary experiments involving climbing high steps and removing attached objects by using the four arms. The results showed that OCTOPUS completed the two tasks by adequately coordinating its four arms and four crawlers and improvement in operability needs.
Three Laws of Behavior Genetics and What They Mean

Behavior genetics has demonstrated that genetic variance is an important component of variation for all behavioral outcomes , but variation among families is not. These results have led some critics of behavior genetics to conclude that heritability is so ubiquitous as to have few consequences for scientific understanding of development , while some behavior genetic partisans have concluded that family environment is not an important cause of developmental outcomes. Both views are incorrect. Genotype is in fact a more systematic source of variability than environment, but for reasons that are methodological rather than substantive. Development is fundamentally nonlinear, interactive, and difficult to control experimentally. Twin studies offer a useful methodologi-cal shortcut, but do not show that genes are more fundamental than environments. The nature-nurture debate is over. The bottom line is that everything is heritable, an outcome that has taken all sides of the nature-nurture debate by surprise. Irving Gottesman and I have suggested that the universal influence of genes on behavior be enshrined as the first law of behavior genetics (Turkheimer & Gottesman, 1991), and at the risk of naming laws that I can take no credit for discovering, it is worth stating the nearly unanimous results of behavior genetics in a more formal manner. ● First Law. All human behavioral traits are heritable. ● Second Law. The effect of being raised in the same family is smaller than the effect of genes. ● Third Law. A substantial portion of the variation in complex human behavioral traits is not accounted for by the effects of genes or families. It is not my purpose in this brief article to defend these three laws against the many exceptions that might be claimed. The point is that now that the empirical facts are in and no longer a matter of serious controversy, it is time to turn attention to what the three laws mean, to the implications of the genetics of behavior for an understanding of complex human behavior and its development.  IN BEHAVIORAL DEVELOPMENT If the first two laws are taken literally , they seem to herald a great victory for the nature side of the old debate: Genes matter, families do not. To understand why such views are at best an oversimplification of a complex reality, it is necessary to consider the newest wave of opposition that behavior genetics has generated. These new critics , whose most …
The AHP approach for selecting an automobile purchase model

The analytic hierarchy process (AHP) provides a structure on decision-making processes where there are a limited numbers of choices but each has a number of attributes. This paper explores the use of AHP for deciding on car purchase. In the context of shopping, it is important to include elements that provide attributes that make consumer decision-making easier, comfortable and therefore, lead to a car purchase. As the car market becomes more competitive, there is a greater demand for innovation that provides better customer service and strategic competition in the business management. This paper presents a new methodological extension of the AHP by focusing on two issues. One combines pairwise comparison with a spreadsheet method using a 5-point rating scale. The other applies the group weight to a reciprocal consistency ratio. Three newly formed car models of midsize are used to show how the method allows choice to be prioritized and analyzed statistically.
Planar Magnetic Components in More Electric Aircraft: Review of Technology and Key Parameters for DC–DC Power Electronic Converter

The more electric aircraft (MEA) has motivated aircraft manufacturers since few decades. Indeed, their investigations lead to the increase of electric power in airplanes. The challenge is to decrease the weight of embedded systems and therefore, the fuel consumption. This is possible thanks to new efficient power electronic converters made of new components. As magnetic components represent a great proportion of their weight, planar components are an interesting solution to increase the power density of some switching mode power supplies. This paper presents the benefits and drawbacks of high-frequency planar transformers in dc/dc converters, different models developed for their design and different issues in MEA context related to planar’s specific geometry and technology.
Forest mapping and monitoring with interferometric Synthetic Aperture Radar ( InSAR )

8 9 10 A Synthetic Aperture Radar (SAR) is an active sensor transmitting pulses of polarized 11 electromagnetic waves and receiving the backscattered radiation. SAR sensors at different 12 wavelengths and with different polarimetric capabilities are being used in remote sensing of 13 the Earth. The value of an analysis of backscattered energy alone is limited due to ambiguities 14 in the possible ecological factor configurations causing the signal. From two SAR images 15 taken from similar viewing positions with a short time-lag, interference between the two 16 waves can be observed. By subtracting the two phases of the signals, it is feasible to eliminate 17 the random contribution of the scatterers to the phase. The interferometric correlation and the 18 interferometric phase contain additional information on the three-dimensional structure of the 19 scattering elements in the imaged area. 20 A brief review of SAR sensors is given, followed by an outline of the physical foundations of 21 SAR interferometry and the practical data processing steps involved. An overview of 22 applications of InSAR to forest mapping and monitoring is given, covering tree bole volume 23 and biomass, forest types and land cover, fire scars, forest thermal state and forest canopy 24
The Faces of Facebookers: Investigating Social Enhancement and Social Compensation Hypotheses; Predicting FacebookTM and Offline Popularity from Sociability and Self-Esteem, and Mapping the Meanings of Popularity with Semantic Networks

This research investigates two competing hypotheses from the literature: 1) the Social Enhancement (‘‘Rich Get Richer’’) hypothesis that those more popular offline augment their popularity by increasing it on Facebook , and 2) the ‘‘Social Compensation’’ (‘‘Poor Get Richer’’) hypothesis that users attempt to increase their Facebook popularity to compensate for inadequate offline popularity. Participants (n= 614) at a large, urban university in the Midwestern United States completed an online survey. Results are that a subset of users, those more extroverted and with higher self-esteem, support the Social Enhancement hypothesis, being more popular both offline and on Facebook . Another subset of users, those less popular offline, support the Social Compensation hypotheses because they are more introverted, have lower self-esteem and strive more to look popular on Facebook . Semantic network analysis of open-ended responses reveals that these two user subsets also have different meanings for offline and online popularity. Furthermore, regression explains nearly twice the variance in offline popularity as in Facebook popularity, indicating the latter is not as socially grounded or defined as offline popularity.
Wideband Radar Cross Section Reduction of Slot Antennas Arrays

A comprehensive analysis aimed at reducing the radar cross section (RCS) of array antennas, preserving at the same time their radiating performance, is presented. A microstrip slot array is considered as a test case to illustrate the proposed strategy for radar cross section reduction (RCSR). It is shown that a remarkable reduction of the radar signature can be accomplished over a frequency band as wide as two octaves by employing an array of periodic resistive elements in front of the radiating apertures. The monostatic and bistatic RCS of the proposed structures are investigated both for normal and oblique incidence. Different arrangements and geometries of the periodic resistive pattern are thoroughly analyzed showing the benefits and the drawbacks in terms of antenna gain and level of the scattered fields. Furthermore, the use of metallic parasitic elements for enhancing the antenna gain is considered, and the scattering phenomena caused by their presence are addressed, taking into account the appearance of grating lobes. The antenna designs are also analyzed by resorting to a bidimensional color plot presenting the variation of the reradiated field both in frequency and spatial domain. The guidelines illustrated by the proposed examples can be easily applied to other antenna architectures.