nils-herrmann/clean_scirepeval huggingface dataset:
Learning Hierarchical Features for Automated Extraction of Road Markings From 3-D Mobile LiDAR Point Clouds

This paper presents a novel method for automated extraction of road markings directly from three dimensional (3-D) point clouds acquired by a mobile light detection and ranging (LiDAR) system. First, road surface points are segmented from a raw point cloud using a curb-based approach. Then, road markings are directly extracted from road surface points through multisegment thresholding and spatial density filtering. Finally, seven specific types of road markings are further accurately delineated through a combination of Euclidean distance clustering, voxel-based normalized cut segmentation, large-size marking classification based on trajectory and curb-lines, and small-size marking classification based on deep learning, and principal component analysis (PCA). Quantitative evaluations indicate that the proposed method achieves an average completeness, correctness, and F-measure of 0.93, 0.92, and 0.93, respectively. Comparative studies also demonstrate that the proposed method achieves better performance and accuracy than those of the two existing methods.
An Exploratory Study of Calendar Use

In this paper, we report on findings from an ethnographic study of how people use their calendars for personal information management (PIM). Our participants were faculty, staff and students who were not required to use or contribute to any specific calendaring solution, but chose to do so anyway. The study was conducted in three parts: first, an initial survey provided broad insights into how calendars were used; second, this was followed up with personal interviews of a few participants which were transcribed and content-analyzed; and third, examples of calendar artifacts were collected to inform our analysis. Findings from our study include the use of multiple reminder alarms, the reliance on paper calendars even among regular users of electronic calendars, and wide use of calendars for reporting and life-archival purposes. We conclude the paper with a discussion of what these imply for designers of interactive calendar systems and future work in PIM research.
Deep Descriptor Transforming for Image Co-Localization

Reusable model design becomes desirable with the rapid expansion of machine learning applications. In this paper, we focus on the reusability of pre-trained deep convolutional models. Specifically, different from treating pre-trained models as feature extractors, we reveal more treasures beneath convolutional layers, i.e., the convolutional activations could act as a detector for the common object in the image colocalization problem. We propose a simple but effective method, named Deep Descriptor Transforming (DDT), for evaluating the correlations of descriptors and then obtaining the category-consistent regions, which can accurately locate the common object in a set of images. Empirical studies validate the effectiveness of the proposed DDT method. On benchmark image co-localization datasets, DDT consistently outperforms existing state-of-the-art methods by a large margin. Moreover, DDT also demonstrates good generalization ability for unseen categories and robustness for dealing with noisy data.
Pedestrian Behavior Modeling From Stationary Crowds With Applications to Intelligent Surveillance

Pedestrian behavior modeling and analysis is important for crowd scene understanding and has various applications in video surveillance. Stationary crowd groups are a key factor influencing pedestrian walking patterns but was mostly ignored in the literature. It plays different roles for different pedestrians in a crowded scene and can change over time. In this paper, a novel model is proposed to model pedestrian behaviors by incorporating stationary crowd groups as a key component. Through inference on the interactions between stationary crowd groups and pedestrians, our model can be used to investigate pedestrian behaviors. The effectiveness of the proposed model is demonstrated through multiple applications, including walking path prediction, destination prediction, personality attribute classification, and abnormal event detection. To evaluate our model, two large pedestrian walking route datasets are built. The walking routes of around 15 000 pedestrians from two crowd surveillance videos are manually annotated. The datasets will be released to the public and benefit future research on pedestrian behavior analysis and crowd scene understanding.
Beamforming Lens Antenna on a High Resistivity Silicon Wafer for 60 GHz WPAN

Wafer-scale beamforming lenses for future IEEE802.15.3c 60 GHz WPAN applications are presented. An on-wafer fabrication is of particular interest because a beamforming lens can be fabricated with sub-circuits in a single process. It means that the beamforming lens system would be compact, reliable, and cost-effective. The Rotman lens and the Rotman lens with antenna arrays were fabricated on a high-resistivity silicon (HRS) wafer in a semiconductor process, which is a preliminary research to check the feasibility of a Rotman lens for a chip scale packaging. In the case of the Rotman lens only, the efficiency is in the range from 50% to 70% depending on which beam port is excited. Assuming that the lens is coupled with ideal isotropic antennas, the synthesized beam patterns from the S-parameters shows that the beam directions are -29.3°, -15.1°, 0.2°, 15.2°, and 29.5 °, and the beam widths are 15.37°, 15.62°, 15.46°, 15.51°, and 15.63°, respectively. In the case of the Rotman lens with antenna array, the patterns were measured by using on-wafer measurement setup. It shows that the beam directions are -26.6°, -21.8°, 0°, 21.8°, and 26.6° . These results are in good agreement with the calculated results from ray-optic. Thus, it is verified that the lens antenna implemented on a wafer can be feasible for the system-in-package (SiP) and wafer-level package technologies.
Diagnosis of canine monocytotropic ehrlichiosis (Ehrlichia canis): an overview.

Canine monocytotropic ehrlichiosis (CME), caused by the rickettsia Ehrlichia canis, an important canine disease with a worldwide distribution. Diagnosis of the disease can be challenging due to its different phases and multiple clinical manifestations. CME should be suspected when a compatible history (living in or traveling to an endemic region, previous tick exposure), typical clinical signs and characteristic hematological and biochemical abnormalities are present. Traditional diagnostic techniques including hematology, cytology, serology and isolation are valuable diagnostic tools for CME, however a definitive diagnosis of E. canis infection requires molecular techniques. This article reviews the current literature covering the diagnosis of infection caused by E. canis.
Scaling Up Programming by Demonstration for Intelligent Tutoring Systems Development: An Open-Access Web Site for Middle School Mathematics Learning

Intelligent tutoring systems (ITSs), which provide step-by-step guidance to students in complex problem-solving activities, have been shown to enhance student learning in a range of domains. However, they tend to be difficult to build. Our project investigates whether the process of authoring an ITS can be simplified, while at the same time maintaining the characteristics that make ITS effective, and also maintaining the ability to support large-scale tutor development. Specifically, our project tests whether authoring tools based on programming-by-demonstration techniques (developed in prior research) can support the development of a large-scale, real-world tutor. We are creating an open-access Web site, called Mathtutor (http://webmathtutor.org), where middle school students can solve math problems with step-by-step guidance from ITS. The Mathtutor site fields example-tracing tutors, a novel type of ITS that are built "by demonstration," without programming, using the cognitive tutor authoring tools (CTATs). The project's main contribution will be that it represents a stringent test of large-scale tutor authoring through programming by demonstration. A secondary contribution will be that it tests whether an open-access site (i.e., a site that is widely and freely available) with software tutors for math learning can attract and sustain user interest and learning on a large scale.
Effects of faking on self-deception and impression management scales

To investigate the effects of self-presentation on the construct validity of the impression management (IM) and self-deceptive enhancement (SDE) scales of the Balanced Inventory of Social Desirable Responding Version 7 (BIDR-7), 155 participants completed the IM and SDE scales combined with standard instructions. IM and SDE were also presented with three self-presentation instructions: fake good, Agency, and Communion instructions. In addition, selfand social desirability ratings were assessed for a list of 190 personality-trait words. It could be shown that not only IM, but also SDE can be faked if participants are appropriately instructed to do so. In addition, personality-trait words related to IM were rated as socially more desirable than those related to SDE. BIDR scales were more highly related in the faking conditions than in the standard instruction condition. In addition, faked BIDR scores were not related to undistorted BIDR scores. These results implicate that both SDE and IM are susceptible to faking like any other personality questionnaire, and that both SDE and IM loose their original meaning under faking. Therefore, at least under faking social desirability scales do not seem to provide additional diagnostic information beyond that derived from personality scales.
A Privacy Analysis of Cross-device Tracking

Online tracking is evolving from browserand devicetracking to people-tracking. As users are increasingly accessing the Internet from multiple devices this new paradigm of tracking—in most cases for purposes of advertising—is aimed at crossing the boundary between a user’s individual devices and browsers. It establishes a person-centric view of a user across devices and seeks to combine the input from various data sources into an individual and comprehensive user profile. By its very nature such cross-device tracking can principally reveal a complete picture of a person and, thus, become more privacy-invasive than the siloed tracking via HTTP cookies or other traditional and more limited tracking mechanisms. In this study we are exploring cross-device tracking techniques as well as their privacy implications. Particularly, we demonstrate a method to detect the occurrence of cross-device tracking, and, based on a cross-device tracking dataset that we collected from 126 Internet users, we explore the prevalence of cross-device trackers on mobile and desktop devices. We show that the similarity of IP addresses and Internet history for a user’s devices gives rise to a matching rate of F-1 = 0.91 for connecting a mobile to a desktop device in our dataset. This finding is especially noteworthy in light of the increase in learning power that cross-device companies may achieve by leveraging user data from more than one device. Given these privacy implications of cross-device tracking we also examine compliance with applicable self-regulation for 40 cross-device companies and find that some are not transparent about their practices.
Developmental timing of trauma exposure and emotion dysregulation in adulthood: Are there sensitive periods when trauma is most harmful?

This study aimed to determine whether there were sensitive periods when a first exposure to trauma was most associated with emotion dysregulation symptoms in adulthood.



Adult participants came from a public urban hospital in Atlanta, GA (n = 1944). Lifetime trauma exposure was assessed using the Traumatic Events Inventory (TEI). Multiple linear regression models were used to assess the association between the developmental timing of first trauma exposure, classified as early childhood (ages 0-5), middle childhood (ages 6-10), adolescence (ages 11-18), and adulthood (ages 19+), on adult emotion dysregulation symptoms, measured using the abbreviated Emotion Dysregulation Scale.



Participants exposed to trauma at any age had higher emotion dysregulation scores than their unexposed peers. However, participants first exposed to child maltreatment or interpersonal violence during middle childhood had higher emotion dysregulation scores relative to those first exposed during other developmental stages; these developmental timing differences were detected even after controlling for sociodemographic factors, exposure to other trauma, and frequency of exposure to trauma. Further, after controlling for current psychiatric symptoms, the effect of other interpersonal trauma exposure in middle childhood was diminished and first exposure to other interpersonal violence in early childhood was associated with significantly lower emotion dysregulation symptoms.



Limitations of this study include the use of retrospective reports and absence of complete information about trauma severity or duration.



These findings should be replicated in other population-based samples with prospective designs to confirm the importance of developmental timing of trauma on later emotion dysregulation.
Corneal Topography: An Emerging Biometric System for Person Authentication

Corneal topography is a non-invasive medical imaging techniqueto assess the shape of the cornea in ophthalmology. In this paper we demonstrate that in addition to its health care use, corneal topography could provide valuable biometric measurements for person authentication. To extract a feature vector from these images (topographies), we propose to fit the geometry of the corneal surface with Zernike polynomials, followed by a linear discriminant analysis (LDA) of the Zernike coefficients to select the most discriminating features. The results show that the proposed method reduced the typical d-dimensional Zernike feature vector (d=36) into a much lower r-dimensional feature vector (r=3), and improved the Equal Error Rate from 2.88% to 0.96%, with the added benefit of faster computation time.
A compact 1.7 - 2.1 GHz three-way power combiner using microstrip technology with better than 93.8% combining efficiency

This letter presents the design and measured performance of a microstrip three-way power combiner. The combiner is designed using the conventional Wilkinson topology with the extension to three outputs, which has been rarely considered for the design and fabrication of V-way combiners. It is shown that with an appropriate design approach, the main drawback reported with this topology (nonplanarity of the circuit when N > 2) can be minimized to have a negligible effect on the circuit performance and still allow an easy MIC or MHMIC fabrication.
Direct-Manipulation Visualization of Deep Networks

The recent successes of deep learning have led to a wave of interest from non-experts. Gaining an understanding of this technology, however, is difficult. While the theory is important, it is also helpful for novices to develop an intuitive feel for the effect of different hyperparameters and structural variations. We describe TensorFlow Playground, an interactive, open sourced visualization that allows users to experiment via direct manipulation rather than coding, enabling them to quickly build an intuition about neural nets.
Web metrics for managing quality and auditing Croatian hotel web sites – cluster analysis

Intensive use of e-business can provide number of opportunities and actual benefits to companies of all activities and sizes. In general, through the use of web sites companies can create global presence and widen business boundaries. Many organizations now have websites to complement their other activities, but it is likely that a smaller proportion really know how successful their sites are and in what extent they comply with business objectives. A key enabler of web sites measurement is web site analytics and metrics. Web sites analytics especially refers to the use of data collected from a web site to determine which aspects of the web site work towards the business objectives. Advanced web analytics must play an important role in overall company strategy and should converge to web intelligence – a specific part of business intelligence which collect and analyze information collected from web sites and apply them in relevant ‘business’ context. This paper examines the importance of measuring the web site quality of the Croatian hotels. Wide range of web site metrics are discussed and finally a set of 8 dimensions and 44 attributes chosen for the evaluation of Croatian hotel’s web site quality. The objective of the survey conducted on the 30 hotels was to identify different groups of hotel web sites in relation to their quality measured with specific web metrics. Key research question was: can hotel web sites be placed into meaningful groups by consideration of variation in web metrics and number of hotel stars? To confirm the reliability of chosen metrics a Cronbach's alpha test was conducted. Apart from descriptive statistics tools, to answer the posed research question, clustering analysis was conducted and the characteristics of the three clusters were considered. Experiences and best practices of the hotel web sites clusters are taken as the prime source of recommendation for improving web sites quality level.  web metrics, hotel web sites, web analytics, web site audit, web site quality, cluster analysis
Video games and prosocial behavior: A study of the effects of non-violent, violent and ultra-violent gameplay

Experimental evidence has pointed toward a negative effect of violent video games on social behavior. Given that the availability and presence of video games is pervasive, negative effects from playing them have potentially large implications for public policy. It is, therefore, important that violent video game effects are thoroughly and experimentally explored, with the current experiment focusing on prosocial behavior. 120 undergraduate volunteers (Mage = 19.01, 87.5% male) played an ultra-violent, violent, or non-violent video game and were then assessed on two distinct measures of prosocial behavior: how much they donated to a charity and how difficult they set a task for an ostensible participant. It was hypothesized that participants playing the ultra-violent games would show the least prosocial behavior and those playing the non-violent game would show the most. These hypotheses were not supported, with participants responding in similar ways, regardless of the type of game played. While null effects are difficult to interpret, samples of this nature (undergraduate volunteers, high male skew) may be problematic, and participants were possibly sensitive to the hypothesis at some level, this experiment adds to the growing body of evidence suggesting that violent video game effects are less clear than initially
Intensive vs Standard Blood Pressure Control and Cardiovascular Disease Outcomes in Adults Aged ≥75 Years: A Randomized Clinical Trial.

The appropriate treatment target for systolic blood pressure (SBP) in older patients with hypertension remains uncertain.



To evaluate the effects of intensive (<120 mm Hg) compared with standard (<140 mm Hg) SBP targets in persons aged 75 years or older with hypertension but without diabetes.



A multicenter, randomized clinical trial of patients aged 75 years or older who participated in the Systolic Blood Pressure Intervention Trial (SPRINT). Recruitment began on October 20, 2010, and follow-up ended on August 20, 2015.



Participants were randomized to an SBP target of less than 120 mm Hg (intensive treatment group, n = 1317) or an SBP target of less than 140 mm Hg (standard treatment group, n = 1319).



The primary cardiovascular disease outcome was a composite of nonfatal myocardial infarction, acute coronary syndrome not resulting in a myocardial infarction, nonfatal stroke, nonfatal acute decompensated heart failure, and death from cardiovascular causes. All-cause mortality was a secondary outcome.



Among 2636 participants (mean age, 79.9 years; 37.9% women), 2510 (95.2%) provided complete follow-up data. At a median follow-up of 3.14 years, there was a significantly lower rate of the primary composite outcome (102 events in the intensive treatment group vs 148 events in the standard treatment group; hazard ratio [HR], 0.66 [95% CI, 0.51-0.85]) and all-cause mortality (73 deaths vs 107 deaths, respectively; HR, 0.67 [95% CI, 0.49-0.91]). The overall rate of serious adverse events was not different between treatment groups (48.4% in the intensive treatment group vs 48.3% in the standard treatment group; HR, 0.99 [95% CI, 0.89-1.11]). Absolute rates of hypotension were 2.4% in the intensive treatment group vs 1.4% in the standard treatment group (HR, 1.71 [95% CI, 0.97-3.09]), 3.0% vs 2.4%, respectively, for syncope (HR, 1.23 [95% CI, 0.76-2.00]), 4.0% vs 2.7% for electrolyte abnormalities (HR, 1.51 [95% CI, 0.99-2.33]), 5.5% vs 4.0% for acute kidney injury (HR, 1.41 [95% CI, 0.98-2.04]), and 4.9% vs 5.5% for injurious falls (HR, 0.91 [95% CI, 0.65-1.29]).



Among ambulatory adults aged 75 years or older, treating to an SBP target of less than 120 mm Hg compared with an SBP target of less than 140 mm Hg resulted in significantly lower rates of fatal and nonfatal major cardiovascular events and death from any cause.
Photoacoustic imaging reveals hidden underdrawings in paintings

A novel, non-invasive, imaging methodology, based on the photoacoustic effect, is introduced in the context of artwork diagnostics with emphasis on the uncovering of hidden features such as underdrawings or original sketch lines in paintings. Photoacoustic microscopy, a rapidly growing imaging method widely employed in biomedical research, exploits the ultrasonic acoustic waves, generated by light from a pulsed or intensity modulated source interacting with a medium, to map the spatial distribution of absorbing components. Having over three orders of magnitude higher transmission through strongly scattering media, compared to light in the visible and near infrared, the photoacoustic signal offers substantially improved detection sensitivity and achieves excellent optical absorption contrast at high spatial resolution. Photoacoustic images, collected from miniature oil paintings on canvas, illuminated with a nanosecond pulsed Nd:YAG laser at 1064 nm on their reverse side, reveal clearly the presence of pencil sketch lines coated over by several paint layers, exceeding 0.5 mm in thickness. By adjusting the detection bandwidth of the optically induced ultrasonic waves, photoacoustic imaging can be used for looking into a broad variety of artefacts having diverse optical properties and geometrical profiles, such as manuscripts, glass objects, plastic modern art or even stone sculpture.