nils-herrmann/clean_scirepeval huggingface dataset:
When Professionals Become Mothers , Warmth Doesn ’ t Cut the Ice

Working moms risk being reduced to one of two subtypes: homemakers—viewed as warm but incompetent, or female professionals—characterized as competent but cold. The current study ( N = 122 college students) presents four important findings. First, when working women become mothers, they trade perceived competence for perceived warmth. Second, working men don’t make this trade; when they become fathers, they gain perceived warmth and maintain perceived competence. Third, people report less interest in hiring, promoting, and educating working moms relative to working dads and childless employees. Finally, competence ratings predict interest in hiring, promoting, and educating workers. Thus, working moms’ gain in perceived warmth does not help them, but their loss in perceived competence does hurt them.
Perceptions of Sex, Gender, and Puberty Suppression: A Qualitative Analysis of Transgender Youth

International guidelines recommend the use of Gonadotropin-Releasing Hormone (GnRH) agonists in adolescents with gender dysphoria (GD) to suppress puberty. Little is known about the way gender dysphoric adolescents themselves think about this early medical intervention. The purpose of the present study was (1) to explicate the considerations of gender dysphoric adolescents in the Netherlands concerning the use of puberty suppression; (2) to explore whether the considerations of gender dysphoric adolescents differ from those of professionals working in treatment teams, and if so in what sense. This was a qualitative study designed to identify considerations of gender dysphoric adolescents regarding early treatment. All 13 adolescents, except for one, were treated with puberty suppression; five adolescents were trans girls and eight were trans boys. Their ages ranged between 13 and 18 years, with an average age of 16 years and 11 months, and a median age of 17 years and 4 months. Subsequently, the considerations of the adolescents were compared with views of clinicians treating youth with GD. From the interviews with the gender dysphoric adolescents, three themes emerged: (1) the difficulty of determining what is an appropriate lower age limit for starting puberty suppression. Most adolescents found it difficult to define an appropriate age limit and saw it as a dilemma; (2) the lack of data on the long-term effects of puberty suppression. Most adolescents stated that the lack of long-term data did not and would not stop them from wanting puberty suppression; (3) the role of the social context, for which there were two subthemes: (a) increased media-attention, on television, and on the Internet; (b) an imposed stereotype. Some adolescents were positive about the role of the social context, but others raised doubts about it. Compared to clinicians, adolescents were often more cautious in their treatment views. It is important to give voice to gender dysphoric adolescents when discussing the use of puberty suppression in GD. Otherwise, professionals might act based on assumptions about adolescents' opinions instead of their actual considerations. We encourage gathering more qualitative research data from gender dysphoric adolescents in other countries.
Social-information-processing factors in reactive and proactive aggression in children's peer groups.

We examined social-information-processing mechanisms (e.g., hostile attributional biases and intention-cue detection deficits) in chronic reactive and proactive aggressive behavior in children's peer groups. In Study 1, a teacher-rating instrument was developed to assess these behaviors in elementary school children (N = 259). Reactive and proactive scales were found to be internally consistent, and factor analyses partially supported convergent and discriminant validities. In Study 2, behavioral correlates of these forms of aggression were examined through assessments by peers (N = 339). Both types of aggression related to social rejection, but only proactively aggressive boys were also viewed as leaders and as having a sense of humor. In Study 3, we hypothesized that reactive aggression (but not proactive aggression) would occur as a function of hostile attributional biases and intention-cue detection deficits. Four groups of socially rejected boys (reactive aggressive, proactive aggressive, reactive-proactive aggressive, and nonaggressive) and a group of average boys were presented with a series of hypothetical videorecorded vignettes depicting provocations by peers and were asked to interpret the intentions of the provocateur (N = 117). Only the two reactive-aggressive groups displayed biases and deficits in interpretations. In Study 4, attributional biases and deficits were found to be positively correlated with the rate of reactive aggression (but not proactive aggression) displayed in free play with peers (N = 127). These studies supported the hypothesis that attributional biases and deficits are related to reactive aggression but not to proactive aggression.
Rush: repeated recommendations on mobile devices

We present rush as a recommendation-based interaction and visualization technique for repeated item selection from large data sets on mobile touch screen devices. Proposals and choices are intertwined in a continuous finger gesture navigating a two-dimensional canvas of recommended items. This provides users with more flexibility for the resulting selections. Our design is based on a formative user study regarding orientation and occlusion aspects. Subsequently, we implemented a version of rush for music playlist creation. In an experimental evaluation we compared different types of recommendations based on similarity, namely the top 5 most similar items, five random selections from the list of similar items and a hybrid version of the two. Participants had to create playlists using each condition. Our results show that top 5 was too restricting, while random and hybrid suggestions had comparable results.
Towards optimal bag-of-features for object categorization and semantic video retrieval

Bag-of-features (BoF) deriving from local keypoints has recently appeared promising for object and scene classification. Whether BoF can naturally survive the challenges such as reliability and scalability of visual classification, nevertheless, remains uncertain due to various implementation choices. In this paper, we evaluate various factors which govern the performance of BoF. The factors include the choices of detector, kernel, vocabulary size and weighting scheme. We offer some practical insights in how to optimize the performance by choosing good keypoint detector and kernel. For the weighting scheme, we propose a novel soft-weighting method to assess the significance of a visual word to an image. We experimentally show that the proposed soft-weighting scheme can consistently offer better performance than other popular weighting methods. On both PASCAL-2005 and TRECVID-2006 datasets, our BoF setting generates competitive performance compared to the state-of-the-art techniques. We also show that the BoF is highly complementary to global features. By incorporating the BoF with color and texture features, an improvement of 50% is reported on TRECVID-2006 dataset.
Steering with eyes closed: Mm-Wave beam steering without in-band measurement

Millimeter-wave communication achieves multi-Gbps data rates via highly directional beamforming to overcome pathloss and provide the desired SNR. Unfortunately, establishing communication with sufficiently narrow beamwidth to obtain the necessary link budget is a high overhead procedure in which the search space scales with device mobility and the product of the sender-receiver beam resolution. In this paper, we design, implement, and experimentally evaluate Blind Beam Steering (BBS) a novel architecture and algorithm that removes in-band overhead for directional mm-Wave link establishment. Our system architecture couples mm-Wave and legacy 2.4/5 GHz bands using out-of-band direction inference to establish (overhead-free) multi-Gbps mm-Wave communication. Further, BBS evaluates direction estimates retrieved from passively overheard 2.4/5 GHz frames to assure highest mm-Wave link quality on unobstructed direct paths. By removing in-band overhead, we leverage mm-Wave's very high throughput capabilities, beam-width scalability and provide robustness to mobility. We demonstrate that BBS achieves 97.8% accuracy estimating direction between pairing nodes using at least 5 detection band antennas. Further, BBS successfully detects unobstructed direct path conditions with an accuracy of 96.5% and reduces the IEEE 802.11ad beamforming training overhead by 81%.
Coverage criteria for GUI testing

A widespread recognition of the usefulness of graphical user interfaces (GUIs) has established their importance as critical components of today's software. GUIs have characteristics different from traditional software, and conventional testing techniques do not directly apply to GUIs. This paper's focus is on coverage critieria for GUIs, important rules that provide an objective measure of test quality. We present new coverage criteria to help determine whether a GUI has been adequately tested. These coverage criteria use events and event sequences to specify a measure of test adequacy. Since the total number of permutations of event sequences in any non-trivial GUI is extremely large, the GUI's hierarchical structure is exploited to identify the important event sequences to be tested. A GUI is decomposed into GUI components, each of which is used as a basic unit of testing. A representation of a GUI component, called an event-flow graph, identifies the interaction of events within a component and intra-component criteria are used to evaluate the adequacy of tests on these events. The hierarchical relationship among components is represented by an integration tree, and inter-component coverage criteria are used to evaluate the adequacy of test sequences that cross components. Algorithms are given to construct event-flow graphs and an integration tree for a given GUI, and to evaluate the coverage of a given test suite with respect to the new coverage criteria. A case study illustrates the usefulness of the coverage report to guide further testing and an important correlation between event-based coverage of a GUI and statement coverage of its software's underlying code.
Making Arabic PDF books accessible using gamification

Most of online Arabic books are not accessible to Arab people with visual impairments. They cannot read online books because they are usually scanned images of the original ones. There is also a problem in PDF encoding of some of the textual books. One of the solutions is to use an Arabic OCR to convert scanned books into text; however Arabic OCR is still in its early stages and suffers from many limitations. In this paper we propose the use of human recognition skills to replace OCR limitations by incorporating the concepts of crowdsourcing and gamification. Our proposed system is in the form of a mobile recall game that presents players with word images segmented from the books to be converted into text. The players' answers are checked using techniques similar to what is used in word spotting. We initially implemented two components of the system; the segmentation, and the feature extraction and matching components. For the feature extraction and matching component, which is used to verify the player's answers, we performed four tests to choose a similarity measure threshold for accepting an entered word as a correct answer. Future work will consider other means of input correctness assurance.
Analyzing the Network for AWS Distributed Cloud Computing

Cloud computing is a global service. Cloud Service Providers, such as AWS, allow users to launch VM instances on multiple data centers (regions) around the world. However, the network connectivity and bandwidth between these different geographically distributed regions varies significantly depending on the user's location. In this paper, we analyze the network performance between pairs of AWS instances hosted on all available regions. We leverage our analysis to derive the optimal hosting region for web service providers depending on the customer locations.
Biomechanical Properties of Insect Wings: The Stress Stiffening Effects on the Asymmetric Bending of the Allomyrina dichotoma Beetle's Hind Wing

Although the asymmetry in the upward and downward bending of insect wings is well known, the structural origin of this asymmetry is not yet clearly understood. Some researchers have suggested that based on experimental results, the bending asymmetry of insect wings appears to be a consequence of the camber inherent in the wings. Although an experimental approach can reveal this phenomenon, another method is required to reveal the underlying theory behind the experimental results. The finite element method (FEM) is a powerful tool for evaluating experimental measurements and is useful for studying the bending asymmetry of insect wings. Therefore, in this study, the asymmetric bending of the Allomyrina dichotoma beetle's hind wing was investigated through FEM analyses rather than through an experimental approach. The results demonstrated that both the stressed stiffening of the membrane and the camber of the wing affect the bending asymmetry of insect wings. In particular, the chordwise camber increased the rigidity of the wing when a load was applied to the ventral side, while the spanwise camber increased the rigidity of the wing when a load was applied to the dorsal side. These results provide an appropriate explanation of the mechanical behavior of cambered insect wings, including the bending asymmetry behavior, and suggest an appropriate approach for analyzing the structural behavior of insect wings.
On-Line Multi-View Video Summarization for Wireless Video Sensor Network

Battery lifetime is critical for wireless video sensors. To enable battery-powered wireless video sensors, low-power design is required. In this paper, we consider applying multi-view summarization to wireless video sensors to remove redundant contents such that the compression and transmission power can be reduced. A low-complexity online multi-view video summarization scheme is proposed. Experiments show that the proposed summarization method successfully reduces the video content while keeping important events. A power analysis of the system also shows that a significant amount of energy can be saved.
Investigating Players' Engagement, Immersion, and Experiences in Playing Pokémon Go

In recent years, Augmented Reality (AR) based mobile games have become popular among players. The Pokémon Go is one of the well-known examples. Although Pokémon Go game has become a global phenomenon, there is a limited study about players' experiences in the gameplay. Especially, little is known about players' engagement and immersion in playing AR-based mobile games in which physical movements in the real world are largely required to play the game. In this study, we conducted a pilot study with eight participants to investigate players' engagement, immersion, and experiences in the Pokémon Go gameplay. We report and discuss the preliminary findings from the study, which can help game designers understand players' experiences in the gameplay so that they can design more creative AR games in the future. Furthermore, the findings are also useful for future studies with larger sample size.
Mean-field theory for scale-free random networks

Random networks with complex topology are common in Nature, describing systems as diverse as the world wide web or social and business networks. Recently, it has been demonstrated that most large networks for which topological information is available display scale-free features. Here we study the scaling properties of the recently introduced scale-free model, that can account for the observed power-law distribution of the connectivities. We develop a mean-field method to predict the growth dynamics of the individual vertices, and use this to calculate analytically the connectivity distribution and the scaling exponents. The mean-field method can be used to address the properties of two variants of the scale-free model, that do not display power-law scaling.
Thesis for the degree of Doctor of Philosophy Knowledge-Based Speech Enhancement

Speech is a fundamental means of human communication. In the last several decades, much effort has been devoted to the efficient transmission and storage of speech signals. With advances in technology making mobile communication ubiquitous, communications anywhere has become a reality. The freedom and flexibility offered by mobile technology brings with it new challenges, one of which is robustness to acoustic background noise. Speech enhancement systems form a vital front-end for mobile telephony in noisy environments such as in cars, cafeterias, subway stations, etc., in hearing aids, and to improve the performance of speech recognition systems. In this thesis, which consists of four research articles, we discuss both single and multi-microphone approaches to speech enhancement. The main contribution of this thesis is a framework to exploit available prior knowledge about both speech and noise. The physiology of speech production places a constraint on the possible shapes of the speech spectral envelope, and this information is captured using codebooks of speech linear predictive (LP) coefficients obtained from a large training database. Similarly, information about commonly occurring noise types is captured using a set of noise codebooks, which can be combined with sound environment classification to treat different environments differently. In paper A, we introduce maximum-likelihood estimation of the speech and noise LP parameters using the codebooks. The codebooks capture only the spectral shape. The speech and noise gain factors are obtained through a frame-byframe optimization, providing good performance in practical nonstationary noise environments. The estimated parameters are subsequently used in a Wiener filter. Paper B describes Bayesian minimum mean squared error estimation of the speech and noise LP parameters and functions there-of, while retaining the instantaneous gain computation. Both memoryless and memory-based estimators are derived. While papers A and B describe single-channel techniques, paper C describes a multi-channel Bayesian speech enhancement approach, where, in addition to temporal processing, the spatial diversity provided by multiple microphones is also exploited. In paper D, we introduce a multi-channel noise reduction technique motivated by blind source separation (BSS) concepts. In contrast to standard BSS approaches, we use the knowledge that one of the signals is speech and that the other is noise, and exploit their different characteristics.
A pole-zero matching method for EBG surfaces composed of a dipole FSS printed on a grounded dielectric slab

A method is presented, for the efficient derivation of the dispersion equation associated with electromagnetic bandgap (EBG) structures composed by lossless frequency selective surfaces (FSS) printed on stratified dielectric media. The method, valid for the range of frequency where a single propagating Floquet mode occurs, is based on Foster's reactance theorem applied to an equivalent transmission line network. This theorem implies that the admittance functions of frequency which represent the FSS satisfy the pole-zero analytical properties of the driving point LC admittance functions. By these basic properties and by the full-wave identification of the FSS resonances, an analytical form of the dispersion equation is obtained. This equation is next solved for both surface wave and leaky wave modes by a conventional numerical technique. The results are successfully compared with those from a full-wave analysis.
Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights

This paper presents incremental network quantization (INQ), a novel method, targeting to efficiently convert any pre-trained full-precision convolutional neural network (CNN) model into a low-precision version whose weights are constrained to be either powers of two or zero. Unlike existing methods which are struggled in noticeable accuracy loss, our INQ has the potential to resolve this issue, as benefiting from two innovations. On one hand, we introduce three interdependent operations, namely weight partition, group-wise quantization and re-training. A wellproven measure is employed to divide the weights in each layer of a pre-trained CNN model into two disjoint groups. The weights in the first group are responsible to form a low-precision base, thus they are quantized by a variable-length encoding method. The weights in the other group are responsible to compensate for the accuracy loss from the quantization, thus they are the ones to be re-trained. On the other hand, these three operations are repeated on the latest re-trained group in an iterative manner until all the weights are converted into low-precision ones, acting as an incremental network quantization and accuracy enhancement procedure. Extensive experiments on the ImageNet classification task using almost all known deep CNN architectures including AlexNet, VGG-16, GoogleNet and ResNets well testify the efficacy of the proposed method. Specifically, at 5-bit quantization (a variable-length encoding: 1 bit for representing zero value, and the remaining 4 bits represent at most 16 different values for the powers of two) , our models have improved accuracy than the 32-bit floating-point references. Taking ResNet-18 as an example, we further show that our quantized models with 4-bit, 3-bit and 2-bit ternary weights have improved or very similar accuracy against its 32-bit floating-point baseline. Besides, impressive results with the combination of network pruning and INQ are also reported. We believe that our method sheds new insights on how to make deep CNNs to be applicable on mobile or embedded devices. The code is available at https://github.com/Zhouaojun/IncrementalNetwork-Quantization.
Receptive fields of single neurones in the cat's striate cortex.

In the central nervous system the visual pathway from retina to striate cortex provides an opportunity to observe and compare single unit responses at several distinct levels. Patterns of light stimuli most effective in influencing units at one level may no longer be the most effective at the next. From differences in responses at successive stages in the pathway one may hope to gain some understanding of the part each stage plays in visual perception. By shining small spots of light on the light-adapted cat retina Kuffler (1953) showed that ganglion cells have concentric receptive fields, with an 'on' centre and an 'off ' periphery, or vice versa. The 'on' and 'off' areas within a receptive field were found to be mutually antagonistic, and a spot restricted to the centre of the field was more effective than one covering the whole receptive field (Barlow, FitzHugh & Kuffler, 1957). In the freely moving lightadapted cat it was found that the great majority of cortical cells studied gave little or no response to light stimuli covering most of the animal's visual field, whereas small spots shone in a restricted retinal region often evoked brisk responses (Hubel, 1959). A moving spot of light often produced stronger responses than a stationary one, and sometimes a moving spot gave more activation for one direction than for the opposite. The present investigation, made in acute preparations, includes a study of receptive fields of cells in the cat's striate cortex. Receptive fields of the cells considered in this paper were divided into separate excitatory and inhibitory ('on' and 'off') areas. In this respect they resembled retinal ganglion-cell receptive fields. However, the shape and arrangement of excitatory and inhibitory areas differed strikingly from the concentric pattern found in retinal ganglion cells. An attempt was made to correlate responses to moving stimuli