nils-herrmann/clean_scirepeval huggingface dataset:
Analysis and comparison of classical and flex-PCB slotless windings in BLDC motors

Slotless brushless DC motors find more and more applications due to their high performance and their low production cost. This paper focuses on the windings inserted in the airgap of these motors, and particularly, to an original production technique which consists in printing the windings on a flexible printed circuit board. It shows that this technique, when coupled with an optimization of the winding shape, can improve the power density of about 30 % compared with classical skewed and rhombic windings made of round wire.
Across the Digital Divide: A Cross-Country Multi-Technology Analysis of the Determinants of IT Penetration

This paper studies the country-level digital divide across successive generations of IT, providing detailed insights into the magnitude and changing nature of the divide. We examine a panel of 40 countries from 1985-2001, based on data from three distinct generations of IT: mainframes, personal computers, and the Internet. Using two measures of IT penetration, we conduct an empirical investigation of socio-economic factors driving the digital divide. We find that IT penetration is positively associated with national income for all three technology generations, and the association between penetration and income is stronger for countries with higher levels of IT penetration. We also examine other demographic and economic factors, going beyond income, and find significant differences in the nature of their effects across countries at different stages of IT adoption. Importantly, factors that previously may have been expanding the divide with earlier technologies are narrowing the gap as the Internet becomes the defining technology of the Information Age.
Phase unwrapping in three dimensions with application to InSAR time series.

The problem of phase unwrapping in two dimensions has been studied extensively in the past two decades, but the three-dimensional (3D) problem has so far received relatively little attention. We develop here a theoretical framework for 3D phase unwrapping and also describe two algorithms for implementation, both of which can be applied to synthetic aperture radar interferometry (InSAR) time series. We test the algorithms on simulated data and find both give more accurate results than a two-dimensional algorithm. When applied to actual InSAR time series, we find good agreement both between the algorithms and with ground truth.
The Work Design Questionnaire (WDQ): developing and validating a comprehensive measure for assessing job design and the nature of work.

Although there are thousands of studies investigating work and job design, existing measures are incomplete. In an effort to address this gap, the authors reviewed the work design literature, identified and integrated previously described work characteristics, and developed a measure to tap those work characteristics. The resultant Work Design Questionnaire (WDQ) was validated with 540 incumbents holding 243 distinct jobs and demonstrated excellent reliability and convergent and discriminant validity. In addition, the authors found that, although both task and knowledge work characteristics predicted satisfaction, only knowledge characteristics were related to training and compensation requirements. Finally, the results showed that social support incrementally predicted satisfaction beyond motivational work characteristics but was not related to increased training and compensation requirements. These results provide new insight into how to avoid the trade-offs commonly observed in work design research. Taken together, the WDQ appears to hold promise as a general measure of work characteristics that can be used by scholars and practitioners to conduct basic research on the nature of work or to design and redesign jobs in organizations.
CBAM: Convolutional Block Attention Module

We propose Convolutional Block Attention Module (CBAM), a simple yet effective attention module for feed-forward convolutional neural networks. Given an intermediate feature map, our module sequentially infers attention maps along two separate dimensions, channel and spatial, then the attention maps are multiplied to the input feature map for adaptive feature refinement. Because CBAM is a lightweight and general module, it can be integrated into any CNN architectures seamlessly with negligible overheads and is end-to-end trainable along with base CNNs. We validate our CBAM through extensive experiments on ImageNet-1K, MS COCO detection, and VOC 2007 detection datasets. Our experiments show consistent improvements in classification and detection performances with various models, demonstrating the wide applicability of CBAM. The code and models will be publicly available.
Verhoef Understanding the Effect of Customer Relationship Management Efforts on Customer Retention and Customer Share Development

Scholars have questioned the effectiveness of several customer relationship management strategies. The author investigates the differential effects of customer relationship perceptions and relationship marketing instruments on customer retention and customer share development over time. Customer relationship perceptions are considered evaluations of relationship strength and a supplier’s offerings, and customer share development is the change in customer share between two periods. The results show that affective commitment and loyalty programs that provide economic incentives positively affect both customer retention and customer share development, whereas direct mailings influence customer share development. However, the effect of these variables is rather small. The results also indicate that firms can use the same strategies to affect both customer retention and customer share development.
A Wide-Range Model for Metal-Oxide Surge Arrester

This paper presents an electric model of a metal-oxide surge arrester (MOSA). The proposed electric model accurately represents the MOSA in a wide range of frequencies and amplitudes. The model was developed and validated based on MOSA electrical behavior in each one of the three operating regions of the zinc-oxide (ZnO) surge arresters, and in a database composed of voltage and current waveforms measured from tests performed in 12 ZnO varistors having different physical dimensions and electrical characteristics—from five different manufacturers. These varistors were subjected to different voltage levels in the low current region, and multilevel amplitude of switching current impulses (30/60 <inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>s), lightning current impulses (8/20 <inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>s), high current impulses (4/10 <inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>s), and fast-front current impulses (1.5/26 <inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>s and 3/6 <inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>s) encompass the three regions of operation and a wide range of frequencies and amplitudes. The results provided by the MOSA wide-range (MWR) model were compared with those obtained in the laboratory. The MWR model has shown good agreement in terms of waveform, peak value, and absorbed energy for the evaluated cases.
Clinical narrative classification using discriminant word embeddings with ELM

Clinical texts are inherently complex due to the medical domain expertise required for content comprehension. In addition, the unstructured nature of these narratives poses a challenge for automatically extracting information. In natural language processing, the use of word embeddings are an effective approach to generate word representations (vectors) in a low dimensional space. In this paper we use a log-linear model (a type of neural language model) and Linear Discriminant Analysis with a kernel-based Extreme Learning Machine (ELM) to map the clinical texts to the medical code. Experimental results on clinical texts indicate improvement with ELM in comparison to SVM and neural network approaches.
Virtual Community Success: A Uses and Gratifications Perspective

In this study we report the findings of a survey on a virtual community of knowledge and interest for end-users. We approach a community participant both as a member and a user, who is also a virtual value initiator for other members. The central issue raised in this study is: what factors motivate a member to participate in a virtual community of knowledge? We utilize uses and gratifications theoretical framework which is grounded in the functionalist and communication research paradigm to develop scales to be empirically tested in the virtual community environment. We use member need satisfaction as a proxy measure for virtual community success. With the help of a community organizer, we posted our survey to develop the constructs and test the relationship with user satisfaction in a virtual community.
Wideband Multi-Mode CMOS VCO Design Using Coupled Inductors

Coupled inductors can create multiple resonant frequencies in a compact high-order resonator. Together with proper nonlinear active circuitry, such a high-order resonator realizes a multi-mode oscillator covering a wide frequency range. Compared with conventional switched-resonator-based approaches that consume the same chip area, the proposed coupled-inductor-based resonator results in larger quality-factor, and hence, lower oscillator phase noise. In the proposed multi-mode oscillator that uses the multi-port coupled inductors, mode switching is achieved using independent active cores without using lossy switches in the resonator path. The behavior of the multi-mode resonator as a multi-port network in an oscillator, design trade-offs, and switching transient response of the multi-mode oscillator have been studied analytically. As a proof of concept, an integrated voltage-controlled oscillator (VCO) with a 1.28-6.06 GHz tuning range is designed and fabricated in a 0.13 mum CMOS technology. The triple-mode VCO uses a sixth-order resonator based on three coupled inductors with a compact common-centric layout. Depending on the oscillation frequency, the VCO current consumption is automatically adjusted from 2.9 to 6.1 mA to achieve a low phase noise throughout the frequency range. The measured phase noises at 1 MHz offset from carrier frequencies of 1.76, 2.26, 3.3, 4.5, and 5.6 GHz are -119.3 , -120.15 , -118.1 , -117 , and -113.5 dBc/Hz , respectively. The chip area, including the pads, is 1 mm times 1 mm and the supply voltage is 1.5 V.
Grounding New Words on the Physical World in Multi-Domain Human-Robot Dialogues

This paper summarizes our ongoing project on developing an architecture for a robot that can acquire new words and their meanings while engaging in multidomain dialogues. These two functions are crucial in making conversational service robots work in real tasks in the real world. Household robots and office robots need to be able to work in multiple task domains and they also need to engage in dialogues in multiple domains corresponding to those task domains. Lexical acquisition is necessary because speech understanding cannot be done without enough knowledge on words that are possibly spoken in the task domain. Our architecture is based on a multi-expert model in which multiple domain experts are employed and one of them is selected based on the user utterance and the situation to engage in the control of the dialogue and physical behaviors. We incorporate experts that have an ability to acquire new lexical entries and their meanings grounded on the physical world through spoken interactions. By appropriately selecting those experts, lexical acquisition in multi-domain dialogues becomes possible. An example robotic system based on this architecture that can acquire object names and location names demonstrates the viability of the architecture.
Levels of Processing : A Framework for Memory Research 1

Over the past decade, models of human memory have been dominated by the concept of stores and the transfer of information among them. One major criterion for distinguishing between stores has been their different retention characteristics. The temporal properties of stored information have, thus, played a dual role: Besides constituting the basic phenomenon to be explained, they have also been used to generate the theoretical constructs in terms o f which the explanation is formulated. The apparent circularity has been avoided by the specification of additional properties of the stores (such as their capacity and coding characteristics) thereby characterizing them independently of the phenomena to be explained. The constructs, thus formulated, have been used to account for data across a variety of paradigms and experimental conditions. The essential concept underlying such explanations is that of information being transferred from one store to another, and the store-to-store transfer models may be distinguished, at least in terms of emphasis, from explanations which associate different retention characteristics with qualitative changes in the memory code. In the present paper we will do three things: (a) examine the reasons for proposing multi-
Algebraic MACs and Keyed-Verification Anonymous Credentials

We consider the problem of constructing anonymous credentials for use in a setting where the issuer of credentials is also the verifier, or more generally where the issuer and verifier have a shared key. In this setting we can use message authentication codes (MACs) instead of public key signatures as the basis for the credential system.
 To this end, we construct two algebraic MACs in prime-order groups, along with efficient protocols for issuing credentials, asserting possession of a credential, and proving statements about hidden attributes (e.g., the age of the credential owner). We prove the security of the first scheme in the generic group model, and prove the security of the second scheme\dash using a dual-system-based approach\dash under decisional Diffie-Hellman (DDH). Our MACs are of independent interest, as they are the only uf-cmva-secure MACs with efficient proofs of knowledge.
 Finally, we compare the efficiency of our new systems to two existing constructions of anonymous credentials: U-Prove and Idemix. We show that the performance of the new schemes is competitive with U-Prove (which does not have multi-show unlinkability), and many times faster than Idemix.
An exact algorithm for a vehicle routing problem with time windows and multiple use of vehicles

The vehicle routing problem with multiple use of vehicles is a variant of the classical vehicle routing problem. It arises when each vehicle performs several routes during the workday due to strict time limits on route duration (e.g., when perishable goods are transported). The routes are defined over customers with a revenue, a demand and a time window. Given a fixed-size fleet of vehicles, it might not be possible to serve all customers. Thus, the customers must be chosen based on their associated revenue minus the traveling cost to reach them. We introduce a branch-and-price approach to address this problem where lower bounds are computed by solving the linear programming relaxation of a set packing formulation, using column generation. The pricing subproblems are elementary shortest path problems with resource constraints. Computational results are reported on euclidean problems derived from well-known benchmark instances for the vehicle routing problem with time windows.
Color based vehicle classification using road surveillance camera images

In this study, we propose novel methods for color based vehicle classification using roadway surveillance camera images. Proposed approach utilizes single shot multibox detector to localize the vehicle and parts of the vehicle within roadway surveillance camera images. Next, color features are extracted around the detected regions to infer the color of the vehicle. Experiments are conducted using 437 images that contain a large variation in terms of reflection, shadow and other illumination effects. We achieved an overall accuracy of % 80 using test dataset.
Matching Real Fabrics with Micro-Appearance Models

Micro-appearance models explicitly model the interaction of light with microgeometry at the fiber scale to produce realistic appearance. To effectively match them to real fabrics, we introduce a new appearance matching framework to determine their parameters. Given a micro-appearance model and photographs of the fabric under many different lighting conditions, we optimize for parameters that best match the photographs using a method based on calculating derivatives during rendering. This highly applicable framework, we believe, is a useful research tool because it simplifies development and testing of new models.
 Using the framework, we systematically compare several types of micro-appearance models. We acquired computed microtomography (micro CT) scans of several fabrics, photographed the fabrics under many viewing/illumination conditions, and matched several appearance models to this data. We compare a new fiber-based light scattering model to the previously used microflake model. We also compare representing cloth microgeometry using volumes derived directly from the micro CT data to using explicit fibers reconstructed from the volumes. From our comparisons, we make the following conclusions: (1) given a fiber-based scattering model, volume- and fiber-based microgeometry representations are capable of very similar quality, and (2) using a fiber-specific scattering model is crucial to good results as it achieves considerably higher accuracy than prior work.
Schenkerian Analysis by Computer : A Proof of Concept

A system for automatically deriving a Schenkerian reduction of an extract of tonal music is described. Schenkerian theory is formalised in a quasi-grammatical manner, expressing a reduction as a binary-tree structure. Computer software which operates in the manner of a chart parser using this grammar has been implemented, capable of deriving a matrix of reduction possibilities, in polynomial time, from a representation of the score. A full reduction of the extract can be discovered by selecting a tree from this matrix. The number of possible valid reductions for even short extracts is found to be extremely large, so criteria are required to distinguish good reductions from bad ones. To find such criteria, themes from five Mozart piano sonatas are analysed and samples of  ̳good‘ reductions (defined by reference to pre-existing analyses of these themes) are compared with randomly sampled reductions. Nine criteria are thereby derived, which can be applied in the process of parsing and selecting a reduction. The results are promising, but the process is still too computationally expensive—only extracts of a few bars in length can be reduced—and more extensive testing is required before the system can be properly claimed to perform automatic Schenkerian analysis.
License Plate Recognition and Super-resolution from Low-Resolution Videos by Convolutional Neural Networks

The paper proposes Convolutional Neural Network (CNN) for License Plate Recognition (LPR) from low-resolution videos. The CNN accepts arbitrary long sequence of geometrically registered license plate (LP) images and outputs a distribution over a set of strings with an admissible length. Evaluation on 31k low-resolution videos shows that the proposed CNN significantly outperforms both baseline methods and humans by a large margin. Our second contribution is a CNN based super-resolution generator of LP images. The generator converts input low-resolution LP image into its high-resolution counterpart which i) preserves the structure of the input and ii) depicts a string that was previously recognized from video.
WOMEN ’ S VIOLENCE TO MEN IN INTIMATE RELATIONSHIPS Working on a Puzzle

Different notions among researchers about the nature of intimate partner violence have long been the subjects of popular and academic debate. Research findings are contradictory and point in two directions, with some revealing that women are as likely as men to perpetrate violence against an intimate partner (symmetry) and others showing that it is overwhelmingly men who perpetrate violence against women partners (asymmetry). The puzzle about who perpetrates intimate partner violence not only concerns researchers but also policy makers and community advocates who, in differing ways, have a stake in the answer to this question, since it shapes the focus of public concern, legislation, public policy and interventions for victims and offenders. The question of who are the most usual victims and perpetrators rests, to a large extent, on ‘what counts’ as violence. It is here that we begin to try to unravel the puzzle, by focusing on concept formation, definitions, forms of measurement, context, consequences and approaches to claim-making, in order better to understand how researchers have arrived at such apparently contradictory findings and claims. The question also turns on having more detailed knowledge about the nature, extent and consequences of women’s violence, in order to consider the veracity of these contradictory findings. To date, there has been very little in-depth research about women’s violence to male partners and it is difficult, if not impossible, to consider this debate without such knowledge. We present quantitative and qualitative findings from 190 interviews with 95 couples in which men and women reported separately upon their own violence and upon that of their partner. Men’s and women’s violence are compared. The findings suggest that intimate partner violence is primarily an asymmetrical problem of men’s violence to women, and women’s violence does not equate to men’s in terms of frequency, severity, consequences and the victim’s sense of safety and well-being. But why bother about the apparent contradictions in findings of research? For those making and implementing policies and expending public and private resources, the apparent contradiction about the very nature of this problem has real consequences for what might be done for those who are its victims and those who
Judgment Before Emotion: People Access Moral Evaluations Faster than Affective States

Theories about the role of emotions in moral cognition make different predictions about the relative speed of moral and affective judgments: those that argue that felt emotions are causal inputs to moral judgments predict that recognition of affective states should precede moral judgments; theories that posit emotional states as the output of moral judgment predict the opposite. Across four studies, using a speeded reaction time task, we found that self-reports of felt emotion were delayed relative to reports of event-directed moral judgments (e.g. badness) and were no faster than persondirected moral judgments (e.g. blame). These results pose a challenge to prominent theories arguing that moral judgments are made on the basis of reflecting on affective states.