nils-herrmann/clean_scirepeval huggingface dataset:
Concentrating Correctly on Cybercrime Concentration

We review the cybercrime literature to draw attention to the many occasions on which authors have identified concentrations within criminal activity. We note that the existence of concentrations often leads authors to suggest that concentrations, or ‘choke points’ are amenable to effective intervention. We then discuss the reasons that concentrations are observed – it is often the result of the criminals being economically efficient, but there are other possible explanations. We then set out a methodology for establishing whether a specific concentration might be the opportunity for a successful intervention. We also argue that the mere possibility of a successful intervention on a specific concentration point does not necessarily mean that incentives of the various stakeholders will be sufficiently well aligned for that intervention to occur.
Cities and complexity - understanding cities with cellular automata, agent-based models, and fractals

Title Type cities and complexity understanding cities with cellular automata agent-based models and fractals PDF the complexity of cooperation agent-based models of competition and collaboration PDF party competition an agent-based model princeton studies in complexity PDF sharing cities a case for truly smart and sustainable cities urban and industrial environments PDF global metropolitan globalizing cities in a capitalist world questioning cities PDF state of the worlds cities 201011 cities for all bridging the urban divide PDF new testament cities in western asia minor light from archaeology on cities of paul and the seven churches of revelation PDF
In-hand manipulation in young children: rotation of an object in the fingers.

The purpose of this study was to look at the development of two in-hand skills of rotation. Three questions were asked: (a) Do boys' and girls' performance differ significantly? (b) Does performance improve with age? and (c) Can periods of rapid improvement with age be seen on the tasks presented?



The in-hand manipulation skill of rotation was measured in 154 right-handed children between the ages of 3-0 years and 6-11 years as well as in 13 adults. The participants were videotaped as they either turned over small pegs in a pegboard or rotated a peg in their fingertips. The number of pegs dropped when turning and placing them back in the board, the number of times a peg could be rotated in the fingertips, the time it took to complete each task, and the methods participate used to accomplish the two tasks were recorded from the videotapes.



The results indicated no differences between the performance of boys and girls on any of the variables studied, but performance did change with age, and periods of rapid change were identified. Further, when compared on methods used, the children did not achieve the same speed or consistency as the adult participants.



The development of in-hand manipulation skills of rotation involves improvement in the dimension of speed, method, and consistency. Observation of these skills in a child can add to a therapist's understanding of the child's fine motor abilities. The variability in children's performance needs to be considered in both evaluation and treatment planning.
Binary Patterns Encoded Convolutional Neural Networks for Texture Recognition and Remote Sensing Scene Classification

Designing discriminative powerful texture features robust to realistic imaging conditions is a challenging computer vision problem with many applications, including material recognition and analysis of satellite or aerial imagery. In the past, most texture description approaches were based on dense orderless statistical distribution of local features. However, most recent approaches to texture recognition and remote sensing scene classification are based on Convolutional Neural Networks (CNNs). The de facto practice when learning these CNN models is to use RGB patches as input with training performed on large amounts of labeled data (ImageNet). In this paper, we show that Local Binary Patterns (LBP) encoded CNN models, codenamed TEX-Nets, trained using mapped coded images with explicit LBP based texture information provide complementary information to the standard RGB deep models. Additionally, two deep architectures, namely early and late fusion, are investigated to combine the texture and color information. To the best of our knowledge, we are the first to investigate Binary Patterns encoded CNNs and different deep network fusion architectures for texture recognition and remote sensing scene classification. We perform comprehensive experiments on four texture recognition datasets and four remote sensing scene classification benchmarks: UC-Merced with 21 scene categories, WHU-RS19 with 19 scene classes, RSSCN7 with 7 categories and the recently introduced large scale aerial image dataset (AID) with 30 aerial scene types. We demonstrate that TEX-Nets provide complementary information to standard RGB deep model of the same network architecture. Our late fusion TEX-Net architecture always improves the overall performance compared to the standard RGB network on both recognition problems. Furthermore, our final combination leads to consistent improvement over the state-of-the-art for remote sensing scene classification.
Kinematic controllability for decoupled trajectory planning in underactuated mechanical systems

We introduce the notion of kinematic controllability for second-order underactuated mechanical systems. For systems satisfying this property, the problem of planning fast collision-free trajectories between zero velocity states can be decoupled into the computationally simpler problems of path planning for a kinematic system followed by time-optimal time scaling. While this approach is well known for fully actuated systems, until now there has been no way to apply it to underactuated dynamic systems. The results in this paper form the basis for efficient collision-free trajectory planning for a class of underactuated mechanical systems including manipulators and vehicles in space and underwater environments.
Comparison of permanent magnet drive motor with a cage induction motor design for a hybrid electric vehicle

In this paper the design for the 2004 Prius electric drive machine is investigated in detail to assess its characteristics. It takes the form a fluid-cooled interior permanent magnet machine. This information is used to generate a complete operating profile. This information is then utilized to produce a design for an alternative induction motor. The specification is found to be demanding however a design is produced for the application which is found to be operationally close to that of the current permanent magnet design and should, in theory, be cheaper to manufacture due to the absence of permanent magnets.
Surviving the Web: A Journey into Web Session Security

In this article, we survey the most common attacks against web sessions, that is, attacks that target honest web browser users establishing an authenticated session with a trusted web application. We then review existing security solutions that prevent or mitigate the different attacks by evaluating them along four different axes: protection, usability, compatibility, and ease of deployment. We also assess several defensive solutions that aim at providing robust safeguards against multiple attacks. Based on this survey, we identify five guidelines that, to different extents, have been taken into account by the designers of the different proposals we reviewed. We believe that these guidelines can be helpful for the development of innovative solutions approaching web security in a more systematic and comprehensive way.
Computational Stereo

Perception of depth is a central problem m machine vision. Stereo is an attractive technique for depth perception because, compared with monocular techniques, it leads to more direct, unambiguous, and quantitative depth measurements, and unlike "active" approaches such as radar and laser ranging, it is suitable in almost all application domains. Computational stereo is broadly defined as the recovery of the three-dimensional characteristics of a scene from multiple images taken from different points of view. First, each of the functional components of the computational stereo paradigm--image acquLsition, camera modeling, feature acquisition, image matching, depth determination, and interpolation--is identified and discussed. Then, the criteria that are important for evaluating the effectiveness of various computational stereo techniques are presented. Finally a representative sampling of computational stereo research is provided.
Latent Factor Representations for Cold-Start Video Recommendation

Recommending items that have rarely/never been viewed by users is a bottleneck for collaborative filtering (CF) based recommendation algorithms. To alleviate this problem, item content representation (mostly in textual form) has been used as auxiliary information for learning latent factor representations. In this work we present a novel method for learning latent factor representation for videos based on modelling the emotional connection between user and item. First of all we present a comparative analysis of state-of-the art emotion modelling approaches that brings out a surprising finding regarding the efficacy of latent factor representations in modelling emotion in video content. Based on this finding we present a method visual-CLiMF for learning latent factor representations for cold start videos based on implicit feedback. Visual-CLiMF is based on the popular collaborative less-is-more approach but demonstrates how emotional aspects of items could be used as auxiliary information to improve MRR performance. Experiments on a new data set and the Amazon products data set demonstrate the effectiveness of visual-CLiMF which outperforms existing CF methods with or without content information.
Design of joint torque sensor and joint structure of a robot arm to minimize crosstalk and torque ripple

Torque control of a robot arm often requires joint torques which are measured using joint torque sensors. However, a joint torque sensor installed at a robot joint suffers from crosstalk errors and torque ripple. The crosstalk error generated by a moment load induces an offset to the torque sensor output. Furthermore, torque ripple noise generated by a harmonic drive interferes with accurate torque measurement as its amplitude is much higher than electric noise. In this study, novel methods are proposed to reduce crosstalk and torque ripple. The crosstalk is dealt with by specially designing the structure of a robot joint. Torque ripple is reduced by taking an average of two Wheatstone bridges outputs. The performance of the proposed robot joint was verified through various experiments.
Hand rehabilitation following stroke: a pilot study of assisted finger extension training in a virtual environment.

The purpose of this pilot study was to investigate the impact of assisted motor training in a virtual environment on hand function in stroke survivors.



Fifteen volunteer stroke survivors (32-88 years old) with chronic upper extremity hemiparesis (1-38 years post incident) took part.



Participants had 6 weeks of training in reach-to-grasp of virtual and actual objects. They were randomized to one of three groups: assistance of digit extension provided by a novel cable orthosis, assistance provided by a novel pneumatic orthosis, or no assistance provided. Hand performance was evaluated at baseline, immediately following training, and 1 month after completion of training. Clinical assessments included the Wolf Motor Function Test (WMFT), Box and Blocks Test (BB), Upper Extremity Fugl-Meyer Test (FM), and Rancho Los Amigos Functional Test of the Hemiparetic Upper Extremity (RLA). Biomechanical assessments included grip strength, extension range of motion and velocity, spasticity, and isometric strength.



Participants demonstrated a significant decrease in time to perform functional tasks for the WMFT (p = .02), an increase in the number of blocks successfully grasped and released during the BB (p = .09), and an increase for the FM score (p = .08). There were no statistically significant changes in time to complete tasks on the RLA or any of the biomechanical measures. Assistance of extension did not have a significant effect.



After the training period, participants in all 3 groups demonstrated a decrease in time to perform some of the functional tasks. Although the overall gains were slight, the general acceptance of the novel rehabilitation tools by a population with substantial impairment suggests that a larger randomized controlled trial, potentially in a subacute population, may be warranted.
Perception , Planning , and Execution for Mobile Manipulation in Unstructured Environments

Unstructured human environments present a substantial challenge to effective robotic operation. Mobile manipulation in typical human environments requires dealing with novel unknown objects, cluttered workspaces, and noisy sensor data. We present an approach to mobile pick and place in such environments using a combination of 2D and 3D visual processing, tactile and proprioceptive sensor data, fast motion planning, reactive control and monitoring, and reactive grasping. We demonstrate our approach by using a two-arm mobile manipulation system to pick and place objects. Reactive components allow our system to account for uncertainty arising from noisy sensors, inaccurate perception (e.g. object detection or registration) or dynamic changes in the environment. We also present a set of tools that allow our system to be easily configured within a short time for a new robotic system.
The insulated gate rectifier (IGR): A new power switching device

A new power semiconductor device called the Insulated Gate Rectifier (IGR) is described in this paper. This device has the advantages of operating at high current densities while requiring low gate drive power. The devices exhibit relatively slow switching speeds due to bipolar operation. The results of two dimensional computer modelling of the device structure are compared with measurements taken on devices fabricated with 600 volt forward and reverse blocking capability.
A Survey of Small-Scale Unmanned Aerial Vehicles : Recent Advances and Future Development Trends

This paper provides a brief overview on the recent advances of small-scale unmanned aerial vehicles (UAVs) from the perspective of platforms, key elements, and scientific research. The survey starts with an introduction of the recent advances of small-scale UAV platforms, based on the information summarized from 132 models available worldwide. Next, the evolvement of the key elements, including onboard processing units, navigation sensors, mission-oriented sensors, communication modules, and ground control station, is presented and analyzed. Third, achievements of small-scale UAV research, particularly on platform design and construction, dynamics modeling, and flight control, are introduced. Finally, the future of small-scale UAVs' research, civil applications, and military applications are forecasted.
Expressing computer science concepts through Kodu game lab

Educational programming environments such as Microsoft Research's Kodu Game Lab are often used to introduce novices to computer science concepts and programming. Unlike many other educational languages that rely on scripting and Java-like syntax, the Kodu language is entirely event-driven and programming takes the form of "when" do' clauses. Despite this simplistic programing model, many computer science concepts can be expressed using Kodu. We identify and measure the frequency of these concepts in 346 Kodu programs created by users, and find that most programs exhibit sophistication through the use of complex control flow and boolean logic. Through Kodu's non-traditional language, we show that users express and explore fundamental computer science concepts.
Mediators of the long-term impact of child sexual abuse: perceived stigma, betrayal, powerlessness, and self-blame.

Using a community sample of 192 adult women who had been sexually abused during childhood, the present study tested the hypothesis that perceived stigma, betrayal, powerlessness, and self-blame mediate the long-term effects of child sexual abuse. A path analysis indicated that the level of psychological distress currently experienced by adult women who had been sexually abused in childhood was mediated by feelings of stigma and self-blame. This result provides partial support for Finkelhor and Browne's (1985) traumagenic dynamics model of child sexual abuse. The limitations of the study are discussed.
Snapchat Elicits More Jealousy than Facebook: A Comparison of Snapchat and Facebook Use

Recent news in the media has suggested that younger people are using popular social media such as Facebook less and are quickly adopting newer media, such as the self-destructing app Snapchat. Snapchat is unique in that it erases messages several seconds after they have been sent, affording its users a higher level of privacy. Yet, little research exists on Snapchat use in general, let alone its broader psychological implications. This article offers a preliminary comparison of Snapchat and Facebook use and psychological effects on romantic jealousy. General motives for using Snapchat and Facebook are examined, as well as the nature of the content that Snapchat users most frequently share. Further, because of the differences in privacy and persistence of information, potential psychological effects in the domain of romantic jealousy are also examined, which has been widely studied on Facebook in the last few years. Findings show that the main difference in motives were that Snapchat was used more for flirting and finding new love interests, whereas Facebook was still the main social networking site used for keeping in touch with friends. Further, when presenting users with a series of potentially jealousy provoking scenarios, Snapchat elicited higher levels of jealousy than did Facebook. These findings are explained based on an affordance approach.
Wide-Loading-Range Fully Integrated LDR With a Power-Supply Ripple Injection Filter

A low-dropout regulator for on-chip application with a power-supply rejection (PSR) boosting filter circuit for enhancing supply noise rejection at middle-to-high frequency over a wide loading range is presented in this brief. The idea has been analytically modeled and experimentally verified with a standard 0.13- μm CMOS process. The on-chip compensation capacitance is 1 pF. For the PSR filter design, the total on-chip capacitance is 20 pF. From the experimental results, the implemented regulator can operate with supply voltage of 1.2 V with nominal dropout voltage of 0.2 V at maximum load of 50 mA and IQ of 37.32 μA.
Improving Decision Analytics with Deep Learning: The Case of Financial Disclosures

Decision analytics commonly focuses on the text mining of financial news sources in order to provide managerial decision support and to predict stock market movements. Existing predictive frameworks almost exclusively apply traditional machine learning methods, whereas recent research indicates that traditional machine learning methods are not sufficiently capable of extracting suitable features and capturing the non-linear nature of complex tasks. As a remedy, novel deep learning models aim to overcome this issue by extending traditional neural network models with additional hidden layers. Indeed, deep learning has been shown to outperform traditional methods in terms of predictive performance. In this paper, we adapt the novel deep learning technique to financial decision support. In this instance, we aim to predict the direction of stock movements following financial disclosures. As a result, we show how deep learning can outperform the accuracy of random forests as a benchmark for machine learning by 5.66 %.
The DLR MIRO: a versatile lightweight robot for surgical applications

The paper presents a new torque-controlled lightweight robot for medical procedures developed at the Institute of Robotics and Mechatronics of the German Aerospace Center. Based on the experiences in lightweight robotics and anthropomorphic robotic hands, a small robot arm with 7 axis and torque-controlled joints tailored to surgical procedures has been designed. With an optimized anthropomorphic kinematics, integrated multi-modal sensors and flexible robot control architecture, the first prototype KINEMEDIC and the new generation MIRO, enhanced for endoscopic surgery, can easily be adapted to a wide range of different medical procedures and scenarios by the use of specialized instruments and compiling workflows within the robot control. With the options of both, Cartesian impedance and position control, MIRO is suited for tele-manipulation, shared autonomy and completely autonomous procedures. This paper focuses on system and hardware design of the robot, supplemented with a brief description on new specific control methods for the MIRO robot.
A Compact Dual-Band Fork-Shaped Monopole Antenna for Bluetooth and UWB Applications

A simple, low-cost, and compact printed dual-band fork-shaped monopole antenna for Bluetooth and ultrawideband (UWB) applications is proposed. Dual-band operation covering 2.4-2.484 GHz (Bluetooth) and 3.1-10.6 GHz (UWB) frequency bands are obtained by using a fork-shaped radiating patch and a rectangular ground patch. The proposed antenna is fed by a 50-Ω microstrip line and fabricated on a low-cost FR4 substrate having dimensions 42 (<i>L</i><sub>sub</sub>) × 24 (<i>W</i><sub>sub</sub>) × 1.6 (<i>H</i>) mm<sup>3</sup>. The antenna structure is fabricated and tested. Measured <i>S</i><sub>11</sub> is ≤ -10 dB over 2.3-2.5 and 3.1-12 GHz. The antenna shows acceptable gain flatness with nearly omnidirectional radiation patterns over both Bluetooth and UWB bands.
Visual SLAM for Handheld Monocular Endoscope

Simultaneous localization and mapping (SLAM) methods provide real-time estimation of 3-D models from the sole input of a handheld camera, routinely in mobile robotics scenarios. Medical endoscopic sequences mimic a robotic scenario in which a handheld camera (monocular endoscope) moves along an unknown trajectory while observing an unknown cavity. However, the feasibility and accuracy of SLAM methods have not been extensively validated with human in vivo image sequences. In this work, we propose a monocular visual SLAM algorithm tailored to deal with medical image sequences in order to provide an up-to-scale 3-D map of the observed cavity and the endoscope trajectory at frame rate. The algorithm is validated over synthetic data and human in vivo sequences corresponding to 15 laparoscopic hernioplasties where accurate ground-truth distances are available. It can be concluded that the proposed procedure is: 1) noninvasive, because only a standard monocular endoscope and a surgical tool are used; 2) convenient, because only a hand-controlled exploratory motion is needed; 3) fast, because the algorithm provides the 3-D map and the trajectory in real time; 4) accurate, because it has been validated with respect to ground-truth; and 5) robust to inter-patient variability, because it has performed successfully over the validation sequences.