nils-herrmann/clean_scirepeval huggingface dataset:
Efficient GPU Screen-Space Ray Tracing

We present an efficient GPU solution for screen-space 3D ray tracing against a depth buffer by adapting the perspective-correct DDA line rasterization algorithm. Compared to linear ray marching, this ensures sampling at a contiguous set of pixels and no oversampling. This paper provides for the first time full implementation details of a method that has been proven in production of recent major game titles. After explaining the optimizations, we then extend the method to support multiple depth layers for robustness. We include GLSL code and examples of pixel-shader ray tracing for several applications.
ECG Measurement Using Capacitive Coupling Electrodes for Man-Machine Emotional Communication

We have studied the capacitive coupling ECG measurement as a new emotional communication between man and machine. In this capacitive coupling measurement a metal plate is placed outside the body and this plate and the electric signal source inside body forms a condenser and the electric biosignal can be derived through this condenser. In this paper, we studied ECG measurement using two or only one capacitive coupling electrodes without any ground electrode for more convenient ECG monitoring. Three ECG measurement methods different in the setting of capacitive coupling electrodes and ground electrode were tested as follows; two isolated signal electrodes with an isolated ground electrode, two isolated signal electrodes without any ground electrode and one isolated signal electrode without any ground electrode. As a result, two isolated electrodes are enough to measure ECG whether with a ground electrode or not. Moreover ECG can be measured with only one signal electrode. Of course ECG waveform was noisy but "R" peak of ECG could be detected. Same tendencies were confirmed in all five subjects participated in experiments.
Relationship Between Visual-Motor Integration , Eye-Hand Coordination , and Quality of Handwriting

If the influence of visual-motor integration (copying forms) on the quality of handwriting has been widely investigated, the influence of eye-hand coordination (tracing item) has been less well analyzed. The Concise Assessment Scale for Children’s Handwriting (BHK), the Developmental Test of Visual Perception (DTVP-2), and the section “Manual Dexterity” of the Movement Assessment Battery for Children (M-ABC) were administered to a group of second grade children (N = 75; 8.1-year-olds). The association of visual-motor integration and eye-hand coordination are predictive of the quality of handwriting (p < . 001). These two skills should be taken into consideration when children are referred to occupational therapy for difficulties in handwriting.
Locational marginal pricing basics for restructured wholesale power markets

Although Locational Marginal Pricing (LMP) plays an important role in many restructured wholesale power markets, the detailed derivation of LMPs as actually used in industry practice is not readily available. This lack of transparency greatly hinders the efforts of researchers to evaluate the performance of these markets. In this paper, different AC and DC optimal power flow (OPF) models are presented to help understand the derivation of LMPs. As a byproduct of this analysis, the paper provides a rigorous explanation of the basic LMP and LMP-decomposition formulas (neglecting real power losses) presented without derivation in the business practice manuals of the U.S. Midwest Independent System Operator (MISO).
Risk Management: A Maturity Model Based on ISO 31000

Risk Management, according with the ISO Guide 73 is the set of "coordinated activities to direct and control an organization with regard to risk". In a nutshell, Risk Management is the business process used to manage risk in organizations. ISO 31000 defines a framework and process for risk management. However, implementing this standard without a detailed plan can become a burden on organizations. This paper presents a maturity model for the risk management process based on ISO 31000. The purpose of this model is to provide an assessment tool for organizations to use in order to get their current risk management maturity level. The results can then be used to create an improvement plan which will guide organizations to reach their target maturity level. This maturity model allows organizations to assess a risk management process according to the best practices defined in risk management references. The maturity model can also be used as a reference for improving this process since it sets a clear path of how a risk management process should be performed.
Adversarial Frontier Stitching for Remote Neural Network Watermarking

The state of the art performance of deep learning models comes at a high cost for companies and institutions, due to the tedious data collection and the heavy processing requirements. Recently, Uchida et al. (2017) proposed to watermark convolutional neural networks by embedding information into their weights. While this is a clear progress towards model protection, this technique solely allows for extracting the watermark from a network that one accesses locally and entirely. This is a clear impediment, as leaked models can be re-used privately, and thus not released publicly for ownership inspection. Instead, we aim at allowing the extraction of the watermark from a neural network (or any other machine learning model) that is operated remotely, and available through a service API. To this end, we propose to operate on the model’s action itself, tweaking slightly its decision frontiers so that a set of specific queries convey the desired information. In present paper, we formally introduce the problem and propose a novel zerobit watermarking algorithm that makes use of adversarial model examples (called adversaries for short). While limiting the loss of performance of the protected model, this algorithm allows subsequent extraction of the watermark using only few remote queries. We experiment this approach on the MNIST dataset with three types of neural networks, demonstrating that e.g., watermarking with 100 images incurs a slight accuracy degradation, while being resilient to most removal attacks.
Use of a gesture user interface as a touchless image navigation system in dental surgery: Case series report

The purposes of this study were to develop a workstation computer that allowed intraoperative touchless control of diagnostic and surgical images by a surgeon, and to report the preliminary experience with the use of the system in a series of cases in which dental surgery was performed.



A custom workstation with a new motion sensing input device (Leap Motion) was set up in order to use a natural user interface (NUI) to manipulate the imaging software by hand gestures. The system allowed intraoperative touchless control of the surgical images.



For the first time in the literature, an NUI system was used for a pilot study during 11 dental surgery procedures including tooth extractions, dental implant placements, and guided bone regeneration. No complications were reported. The system performed very well and was very useful.



The proposed system fulfilled the objective of providing touchless access and control of the system of images and a three-dimensional surgical plan, thus allowing the maintenance of sterile conditions. The interaction between surgical staff, under sterile conditions, and computer equipment has been a key issue. The solution with an NUI with touchless control of the images seems to be closer to an ideal. The cost of the sensor system is quite low; this could facilitate its incorporation into the practice of routine dental surgery. This technology has enormous potential in dental surgery and other healthcare specialties.
Social Balance on Networks : The Dynamics of Friendship and Enmity

How do social networks evolve when both friendly and unfriendly relations exist? Here we propose a simple dynamics for social networks in which the sense of a relationship can change so as to eliminate imbalanced triads—relationship triangles that contains 1 or 3 unfriendly links. In this dynamics, a friendly link changes to unfriendly or vice versa in an imbalanced triad to make the triad balanced. Such networks undergo a dynamic phase transition from a steady state to “utopia”—all friendly links—as the amount of network friendliness is changed. Basic features of the long-time dynamics and the phase transition are discussed.
Multi-Objective Optimization for the Joint Disambiguation of Nouns and Named Entities

In this paper, we present a novel approach to joint word sense disambiguation (WSD) and entity linking (EL) that combines a set of complementary objectives in an extensible multi-objective formalism. During disambiguation the system performs continuous optimization to find optimal probability distributions over candidate senses. The performance of our system on nominal WSD as well as EL improves state-ofthe-art results on several corpora. These improvements demonstrate the importance of combining complementary objectives in a joint model for robust disambiguation.
Structured Time Series Analysis for Human Action Segmentation and Recognition

We address the problem of structure learning of human motion in order to recognize actions from a continuous monocular motion sequence of an arbitrary person from an arbitrary viewpoint. Human motion sequences are represented by multivariate time series in the joint-trajectories space. Under this structured time series framework, we first propose Kernelized Temporal Cut (KTC), an extension of previous works on change-point detection by incorporating Hilbert space embedding of distributions, to handle the nonparametric and high dimensionality issues of human motions. Experimental results demonstrate the effectiveness of our approach, which yields realtime segmentation, and produces high action segmentation accuracy. Second, a spatio-temporal manifold framework is proposed to model the latent structure of time series data. Then an efficient spatio-temporal alignment algorithm Dynamic Manifold Warping (DMW) is proposed for multivariate time series to calculate motion similarity between action sequences (segments). Furthermore, by combining the temporal segmentation algorithm and the alignment algorithm, online human action recognition can be performed by associating a few labeled examples from motion capture data. The results on human motion capture data and 3D depth sensor data demonstrate the effectiveness of the proposed approach in automatically segmenting and recognizing motion sequences, and its ability to handle noisy and partially occluded data, in the transfer learning module.
Uniplanar Printed Coupled-Fed PIFA With a Band-Notching Slit for WLAN/WiMAX Operation in the Laptop Computer

A small-size uniplanar printed antenna suitable for 2.4/5.2/5.8 GHz WLAN and 2.5/3.5/5.5 GHz WiMAX operations is presented. The antenna is a coupled-fed PIFA and shows a height of 9 mm and a width of 13 mm only, when mounted at the top edge of the display panel in the laptop computer. The multiband operation is achieved by using the coupling feed and further embedding a band-notching slit in the radiating arm of the PIFA. With the coupling feed, two wide operating bands can be generated at about 2.5 and 5.5 GHz for the PIFA. By further embedding the slit of length about a quarter-wavelength at about 4 GHz, a band-notching characteristic at about 4 GHz is obtained, which leads to an additional resonance at about 3.5 GHz and shows very small effects on the desired 2.5 and 5.5 GHz bands. This behavior results in successful excitation of an additional resonant mode for 3.5 GHz WiMAX operation. Hence, with no increase in the antenna size, three wide operating bands for covering all the desired operating bands of WLAN/WiMAX systems are achieved for the proposed PIFA. Details of the design considerations are presented, and results of the fabricated prototype are discussed.
Artificial sweeteners produce the counterintuitive effect of inducing metabolic derangements

The negative impact of consuming sugar-sweetened beverages on weight and other health outcomes has been increasingly recognized; therefore, many people have turned to high-intensity sweeteners like aspartame, sucralose, and saccharin as a way to reduce the risk of these consequences. However, accumulating evidence suggests that frequent consumers of these sugar substitutes may also be at increased risk of excessive weight gain, metabolic syndrome, type 2 diabetes, and cardiovascular disease. This paper discusses these findings and considers the hypothesis that consuming sweet-tasting but noncaloric or reduced-calorie food and beverages interferes with learned responses that normally contribute to glucose and energy homeostasis. Because of this interference, frequent consumption of high-intensity sweeteners may have the counterintuitive effect of inducing metabolic derangements.
Description of an Electrodynamic Self-Bearing Permanent Magnet Machine

This paper aims to give a description of a passively levitated self-bearing permanent magnet motor principle. The windings of a permanent magnet motor are connected in such a way that they are also coupled to the p ± 1 harmonics due to a rotor off-centering. They allow for eddy currents to flow inside a short-circuit path when the rotor is out-centered, and in consequence to generate radial force according to the principle of radial heteropolar electrodynamic bearings. The general principles are described, and a 2-D-FE time-dependent model illustrates those principles on two application cases. The theoretical feasibility of this passively levitated permanent magnet motor is shown on a slotless application case.
Equilibrium Points in N-Person Games.

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Blowing in the wind

We present an approach for simulating the natural dynamics that emerge from the coupling of a flow field to lightweight, mildly deformable objects immersed within it. We model the flow field using a Lattice Boltzmann Model (LBM) extended with a subgrid model and accelerate the computation on commodity graphics hardware to achieve real-time simulations. We demonstrate our approach using soap bubbles and a feather blown by wind fields, yet our approach is general enough to apply to other light-weight objects. The soap bubbles illustrate Fresnel reflection, reveal the dynamics of the unseen flow field in which they travel, and display spherical harmonics in their undulations. The free feather floats and flutters in response to lift and drag forces. Our single bubble simulation allows the user to directly interact with the wind field and thereby influence the dynamics in real time.
Industrial Management & Data Systems Transformational leadership and innovative work behavior

The purpose of this paper is to explore the mediating role of psychological empowerment and the moderating role of self-construal (independent and interdependent) on the relationship between transformational leadership and employees’ innovative work behavior (IWB).  A total of 639 followers and 87 leaders filled out questionnaires from cross-industry sample of five most innovative companies of China. Structural equation modeling was used to analyze the relations.  Results revealed that psychological empowerment mediated the relationship between transformational leadership and IWB. The research established that transformational leadership positively influences IWB which includes idea generation as well as idea implementation. The results also showed that the relationship between transformational leadership and IWB was stronger among employees with a higher interdependent self-construal and a lower independent self-construal.  This study adds to IWB literature by empirically testing the moderating role of self-construal and the mediating role of psychological empowerment on transformational leadership-IWB link.
Style in the Age of Instagram: Predicting Success within the Fashion Industry using Social Media

Fashion is a multi-billion dollar industry with social and economic implications worldwide. To gain popularity, brands want to be represented by the top popular models. As new faces are selected using stringent (and often criticized) aesthetic criteria, a priori predictions are made difficult by information cascades and other fundamental trend-setting mechanisms. However, the increasing usage of social media within and without the industry may be affecting this traditional system. We therefore seek to understand the ingredients of success of fashion models in the age of Instagram. Combining data from a comprehensive online fashion database and the popular mobile image-sharing platform, we apply a ma- chine learning framework to predict the tenure of a cohort of new faces for the 2015 Spring/Summer season throughout the subsequent 2015-16 Fall / Winter season. Our framework successfully predicts most of the new popular models who appeared in 2015. In particular, we find that a strong social media presence may be more important than being under contract with a top agency, or than the aesthetic standards sought after by the industry.
Iterative Refinement for Machine Translation

Existing machine translation decoding algorithms generate translations in a strictly monotonic fashion and never revisit previous decisions. As a result, earlier mistakes cannot be corrected at a later stage. In this paper, we present a translation scheme that starts from an initial guess and then makes iterative improvements that may revisit previous decisions. We parameterize our model as a convolutional neural network that predicts discrete substitutions to an existing translation based on an attention mechanism over both the source sentence as well as the current translation output. By making less than one modification per sentence, we improve the output of a phrase-based translation system by up to 0.4 BLEU on WMT15 German-English translation.
Rated aspect summarization of short comments

Web 2.0 technologies have enabled more and more people to freely comment on different kinds of entities (e.g. sellers, products, services). The large scale of information poses the need and challenge of automatic summarization. In many cases, each of the user-generated short comments comes with an overall rating. In this paper, we study the problem of generating a ``rated aspect summary'' of short comments, which is a decomposed view of the overall ratings for the major aspects so that a user could gain different perspectives towards the target entity. We formally define the problem and decompose the solution into three steps. We demonstrate the effectiveness of our methods by using eBay sellers' feedback comments. We also quantitatively evaluate each step of our methods and study how well human agree on such a summarization task. The proposed methods are quite general and can be used to generate rated aspect summary automatically given any collection of short comments each associated with an overall rating.
A vision based onboard approach for landing and position control of an autonomous multirotor UAV in GPS-denied environments

We describe our work on multirotor UAVs and focus on our method for autonomous landing and position control. The paper describes the design of our landing pad and the vision based detection algorithm that estimates the 3D-position of the UAV relative to the landing pad. A cascaded controller structure stabilizes velocity and position in the absence of GPS signals by using a dedicated optical flow sensor. Practical experiments prove the quality of our approach.
Measuring Computer Performance: A Practitioner's Guide

A practitioner's guide Measuring computer performance sets out the fundamental techniques used in analyzing and understanding the performance of computer systems. Throughout the book, the emphasis is on practical methods of measurement, simulation and analytical modeling. The author discusses performance metrics and provides detailed coverage of the strategies used in benchmark programs. He gives intuitive explanations of the key statistical tools needed to interpret measured performance data. He also describes the generaìdesign of experiments' technique, and shows how the maximum amount of information can be obtained for the minimum effort. The book closes with a chapter on the technique of queueing analysis. Appendices listing common probability distributions and statistical tables are included, along with a glossary of important technical terms. This practically oriented book will be of great interest to anyone who wants a detailed, yet intuitive, understanding of computer systems performance analysis.
An Analysis of Security and Privacy Issues in Smart Grid Software Architectures on Clouds

Power utilities globally are increasingly upgrading to Smart Grids that use bi-directional communication with the consumer to enable an information-driven approach to distributed energy management. Clouds offer features well suited for Smart Grid software platforms and applications, such as elastic resources and shared services. However, the security and privacy concerns inherent in an information-rich Smart Grid environment are further exacerbated by their deployment on Clouds. Here, we present an analysis of security and privacy issues in a Smart Grids software architecture operating on different Cloud environments, in the form of a taxonomy. We use the Los Angeles Smart Grid Project that is underway in the largest U.S. municipal utility to drive this analysis that will benefit both Cloud practitioners targeting Smart Grid applications, and Cloud researchers investigating security and privacy.
Deconstructing Dynamic Symbolic Execution

Dynamic symbolic execution (DSE) is a well-known technique for automatically generating tests to achieve higher levels of coverage in a program. Two keys ideas of DSE are to: (1) seed symbolic execution by executing a program on an initial input; (2) using concrete values from the program execution in place of symbolic expressions whenever symbolic reasoning is hard or not desired. We describe DSE for a simple core language and then present a minimalist implementation of DSE for Python (in Python) that follows this basic recipe. The code is available at https://www.github.com/thomasjball/PyExZ3/ (tagged “v1.0”) and has been designed to make it easy to experiment with and extend.
Ridges and Valleys Detection in Images Using Difference of Rotating Half Smoothing Filters

In this paper we propose a new ridge/valley detection method in images based on the difference of rotating Gaussian semi filters. The novelty of this approach resides in the mixing of ideas coming both from directional filters and DoG method. We obtain a new ridge/valley anisotropic DoG detector enabling very precise detection of ridge/valley points. Moreover, this detector performs correctly at crest lines even if highly bended, and is precise on junctions. This detector has been tested successfully on various image types presenting difficult problems for classical ridges/valleys detection methods.