nils-herrmann/clean_scirepeval huggingface dataset:
Computer shogi

This paper describes the current state of the art in computer shogi. Shogi (Japanese chess) promises to be a good vehicle for future research into game-playing programs that are based on tree-searching paradigms. This paper shows where chess and shogi are similar, and details the important areas that make shogi programming of particular interest. A crucial difference is the game-tree complexity, which is significantly higher in shogi than in chess. Three important differences are the “drop” rule, the diverging character of the game, and the slow build-up of forces. They make it difficult to have effective opening and endgame procedures. After a short summary of the rules of shogi and an outline of the main areas of current work in computer shogi, we provide an overview of the history of computer shogi, in which computershogi activities both in human tournaments and in exhibition events are given. We conjecture that by the year 2010 a computer will be comparable in strength to the best human players. The most important techniques used in computer shogi are described. We focus on issues such as opening play, selective search, quiescence search, solving tactical exchanges without tree searching, position evaluation and endgame play. At the end the key challenges in computer shogi are enumerated, and finally, concluding remarks are given.
Aerial acoustic communications

This paper describes experiments in using audible sound as a means for wireless device communications. The direct application of standard modulation techniques to sound, without further improvements, results in sounds that are immediately perceived as digital communications and that are fairly aggressive and intrusive. We observe that some parameters of the modulation that have an impact in the data rate, the error probability and the computational overhead at the receiver also have a tremendous impact in the quality of the sound as perceived by humans. This paper focuses on how to vary those parameters in standard modulation techniques such as ASK, FSK and Spread-Spectrum to obtain communication systems in which the messages are musical and other familiar sounds, rather than modem sounds. A prototype called Digital Voices demonstrates the feasibility of this music-based communication technology. Our goal is to lay out the basis of sound design for aerial acoustic communications so that the presence of such communications, though noticeable, is not intrusive and can even be considered as part of musical compositions and sound tracks.
Synthesizing the preferred inputs for neurons in neural networks via deep generator networks

Deep neural networks (DNNs) have demonstrated state-of-the-art results on many pattern recognition tasks, especially vision classification problems. Understanding the inner workings of such computational brains is both fascinating basic science that is interesting in its own right—similar to why we study the human brain—and will enable researchers to further improve DNNs. One path to understanding how a neural network functions internally is to study what each of its neurons has learned to detect. One such method is called activation maximization (AM), which synthesizes an input (e.g. an image) that highly activates a neuron. Here we dramatically improve the qualitative state of the art of activation maximization by harnessing a powerful, learned prior: a deep generator network (DGN). The algorithm (1) generates qualitatively state-of-the-art synthetic images that look almost real, (2) reveals the features learned by each neuron in an interpretable way, (3) generalizes well to new datasets and somewhat well to different network architectures without requiring the prior to be relearned, and (4) can be considered as a high-quality generative method (in this case, by generating novel, creative, interesting, recognizable images).
Multimodal Local Perception Bilinear Pooling for Visual Question Answering

Visual question answering is a challenging multimodal task, which has received increasing attention in recent years. One key solution to visual question answering is how to fuse the visual and textual features extracted from the image and questions, and thus, we can comprehensively employ the information from both modals and deliver correct answers. Bilinear pooling has been a powerful fusion approach owing to its exhausting interaction of each element of two modals, but its overuse of parameters limits its practical application. In this paper, we aim to retain the advantages of bilinear pooling for feature interaction and propose a novel multimodal feature fusion approach named multimodal local perception bilinear (MLPB) pooling, which can retain the second-order interactions between visual and textual features with limited learning parameters. To be specific, the MLPB utilizes local perception mechanism, which transforms the bilinear pooling between two high-dimensional raw features into multiple low-dimensional part features. To further reduce the computational cost, we propose to share the learning parameters of each local bilinear pooling. In this way, MLPB can achieve the complex interactions of the bilinear pooling without taking up too much computational resource. Extensive experiments show that the proposed method can achieve competitive or better performance than the state of the art.
More than touch: understanding how people use skin as an input surface for mobile computing

This paper contributes results from an empirical study of on-skin input, an emerging technique for controlling mobile devices. Skin is fundamentally different from off-body touch surfaces, opening up a new and largely unexplored interaction space. We investigate characteristics of the various skin-specific input modalities, analyze what kinds of gestures are performed on skin, and study what are preferred input locations. Our main findings show that (1) users intuitively leverage the properties of skin for a wide range of more expressive commands than on conventional touch surfaces; (2) established multi-touch gestures can be transferred to on-skin input; (3) physically uncomfortable modalities are deliberately used for irreversible commands and expressing negative emotions; and (4) the forearm and the hand are the most preferred locations on the upper limb for on-skin input. We detail on users' mental models and contribute a first consolidated set of on-skin gestures. Our findings provide guidance for developers of future sensors as well as for designers of future applications of on-skin input.
A finger on the pulse: temporal rhythms and information seeking in medical work

Most cooperative work takes place in information-rich environments. However, studies of "information work" tend to focus on the decontextualized access and retrieval problems faced by individual information seekers. Our work is directed towards understanding how information management is seamlessly integrated into the course of everyday activities. Drawing on an ethnographic study of medical work, we explore the relationship between information and temporal coordination and discuss the role of temporal patterns or "rhythms" in providing individuals with the means to coordinate information and work.
Review of Inflatable Booms for Deployable Space Structures : Packing and Rigidization

Inflatable structures offer the potential of compactly stowing lightweight structures, which assume a fully deployed state in space. An important category of space inflatables are cylindrical booms, which may form the structural members of trusses or the support structure for solar sails. Two critical and interdependent aspects of designing inflatable cylindrical booms for space applications are i) packaging methods that enable compact stowage and ensure reliable deployment, and ii) rigidization techniques that provide long-term structural ridigity after deployment. The vast literature in these two fields is summarized to establish the state of the art.
Generalized expectancies for internal versus external control of reinforcement.

The effects of reward or reinforcement on preceding behavior depend in part on whether the person perceives the reward as contingent on his own behavior or independent of it. Acquisition and performance differ in situations perceived as determined by skill versus chance. Persons may also differ in generalized expectancies for internal versus external control of reinforcement. This report summarizes several experiments which define group differences in behavior when Ss perceive reinforcement as contingent on their behavior versus chance or experimenter control. The report also describes the development of tests of individual differences in a generalized belief in internal-external control and provides reliability, discriminant validity and normative data for 1 test, along with a description of the results of several studies of construct validity.
Ultrawideband All-Metal Flared-Notch Array Radiator

Simulations and measurements are presented for an all-metal flared-notch array element in both single and dual-polarization configurations. The ultrawideband radiator exhibits an operational bandwidth of 12:1 for broadside scan and 8:1 bandwidth at a 45-degree scan in all planes, maintaining active VSWR<;2. The feed consists of a direct coax-to-slot-line transition that mounts directly into the base of the radiator. The all-metal flared-notches are machined from common metal stock and fed via SMA coaxial connectors. No soldering is required for any part of the design-including the feed-and assembly is simple and modular. The array parts are machined using a high-precision wire-EDM cutting technology, ensuring that measurements (in the 700 MHz-9 GHz range) are repeatable and give close agreement with theory, even through multiple assembly cycles of the modular construction system. This paper presents results for a 32-element linear array of horizontal elements and also an 8 × 8 planar array of dual-polarized elements, comparing measurements with full-wave simulations of the complete finite array structures.
A Data Quality Metric (DQM): How to Estimate the Number of Undetected Errors in Data Sets

Data cleaning, whether manual or algorithmic, is rarely perfect leaving a dataset with an unknown number of false positives and false negatives after cleaning. In many scenarios, quantifying the number of remaining errors is challenging because our data integrity rules themselves may be incomplete, or the available gold-standard datasets may be too small to extrapolate. As the use of inherently fallible crowds becomes more prevalent in data cleaning problems, it is important to have estimators to quantify the extent of such errors. We propose novel species estimators to estimate the number of distinct remaining errors in a dataset after it has been cleaned by a set of crowd workers – essentially, quantifying the utility of hiring additional workers to clean the dataset. This problem requires new estimators that are robust to false positives and false negatives, and we empirically show on three real-world datasets that existing species estimators are unstable for this problem, while our proposed techniques quickly converge.
Collar Line Segments for fast odometry estimation from Velodyne point clouds

We present a novel way of odometry estimation from Velodyne LiDAR point cloud scans. The aim of our work is to overcome the most painful issues of Velodyne data - the sparsity and the quantity of data points - in an efficient way, enabling more precise registration. Alignment of the point clouds which yields the final odometry is based on random sampling of the clouds using Collar Line Segments (CLS). The closest line segment pairs are identified in two sets of line segments obtained from two consequent Velodyne scans. From each pair of correspondences, a transformation aligning the matched line segments into a 3D plane is estimated. By this, significant planes (ground, walls, ...) are preserved among aligned point clouds. Evaluation using the KITTI dataset shows that our method outperforms publicly available and commonly used state-of-the-art method GICP for point cloud registration in both accuracy and speed, especially in cases where the scene lacks significant landmarks or in typical urban elements. For such environments, the registration error of our method is reduced by 75% compared to the original GICP error.
Social Media and Firm Equity Value

Companies have increasingly advocated social media technologies and platforms to improve and ultimately transform business performance. This study examines whether social media has a predictive relationship with firm equity value, which metric of social media has the strongest relationship, and the dynamics of the relationship. The results derived from the vector autoregressive models suggest that social media-based metrics (blogs and reviews) are significant leading indicators of firm stock market performance. We also find a faster predictive value of social media, i.e., a shorter “wear-in” effect compared with conventional online behavior metrics, such as web traffic and search. Interestingly, conventional digital user metrics (Google search and web traffic), which have been widely adopted to measure online consumer behavior, are found to have significant yet substantially weaker predictive relationships with firm equity value than social media. The results provide new insights for social media managers and firm equity valuations.
Characterising the Behaviour of IEEE 802.11 Broadcast Transmissions in Ad Hoc Wireless LANs

This paper evaluates the performance of the IEEE 802.11 broadcast traffic under both saturation and nonsaturation conditions. The evaluation highlights some important characteristics of IEEE 802.11 broadcast traffic as compared to corresponding unicast traffic. Moreover, it underlines the inaccuracy of the broadcast saturation model proposed by Ma and Chen due to the absence of backoff counter freeze process when channel is busy. Computer simulations are used to validate the accuracy of the new model and demonstrate the importance of capturing the freezing of backoff counter in the analytical study of IEEE 802.11 broadcast.
AprilTag: A robust and flexible visual fiducial system

While the use of naturally-occurring features is a central focus of machine perception, artificial features (fiducials) play an important role in creating controllable experiments, ground truthing, and in simplifying the development of systems where perception is not the central objective. We describe a new visual fiducial system that uses a 2D bar code style “tag”, allowing full 6 DOF localization of features from a single image. Our system improves upon previous systems, incorporating a fast and robust line detection system, a stronger digital coding system, and greater robustness to occlusion, warping, and lens distortion. While similar in concept to the ARTag system, our method is fully open and the algorithms are documented in detail.
An optimal method for stochastic composite optimization

This paper considers an important class of convex programming (CP) problems, namely, the stochastic composite optimization (SCO), whose objective function is given by the summation of general nonsmooth and smooth stochastic components. Since SCO covers non-smooth, smooth and stochastic CP as certain special cases, a valid lower bound on the rate of convergence for solving these problems is known from the classic complexity theory of convex programming. Note however that the optimization algorithms that can achieve this lower bound had never been developed. In this paper, we show that the simple mirror-descent stochastic approximation method exhibits the best-known rate of convergence for solving these problems. Our major contribution is to introduce the accelerated stochastic approximation (AC-SA) algorithm based on Nesterov’s optimal method for smooth CP [32,34], and show that the AC-SA algorithm can achieve the aforementioned lower bound on the rate of convergence for SCO. To the best of our knowledge, it is also the first universally optimal algorithm in the literature for solving non-smooth, smooth and stochastic CP problems. We illustrate the significant advantages of the AC-SA algorithm over existing methods in the context of solving a special but broad class of stochastic programming problems.
Control of the switching transients of IGBT series strings by high-performance drive units

In the field of power electronics, the use of series-connected insulated gate devices, such as insulated gate bipolar transistors or power MOSFETs, is interesting in order to obtain fast and efficient power switches in medium-range power converters. In this kind of application, the control of the voltage sharing across the series strings of devices is an important aspect to be considered. The proposed technique allows obtaining safe commutations of the switches by simple and effective control circuits acting on the gate side of the power devices. In particular, the gate drive units are arranged in order to ensure good performance during the switching transients, while preventing overvoltage peaks on the devices. Both the design criteria and analysis of the control circuit are developed. Several experimental tests are reported in order to demonstrate the validity and correctness of the proposed approach.
A review of process fault detection and diagnosis: Part II: Qualitative models and search strategies

In this part of the paper, we review qualitative model representations and search strategies used in fault diagnostic systems. Qualitative models are usually developed based on some fundamental understanding of the physics and chemistry of the process. Various forms of qualitative models such as causal models and abstraction hierarchies are discussed. The relative advantages and disadvantages of these representations are highlighted. In terms of search strategies, we broadly classify them as topographic and symptomatic search techniques. Topographic searches perform malfunction analysis using a template of normal operation, whereas, symptomatic searches look for symptoms to direct the search to the fault location. Various forms of topographic and symptomatic search strategies are discussed.
Diplomat: Using Delegations to Protect Community Repositories

Community repositories, such as Docker Hub, PyPI, and RubyGems, are bustling marketplaces that distribute software. Even though these repositories use common software signing techniques (e.g., GPG and TLS), attackers can still publish malicious packages after a server compromise. This is mainly because a community repository must have immediate access to signing keys in order to certify the large number of new projects that are registered each day. This work demonstrates that community repositories can offer compromise-resilience and real-time project registration by employing mechanisms that disambiguate trust delegations. This is done through two delegation mechanisms that provide flexibility in the amount of trust assigned to different keys. Using this idea we implement Diplomat, a software update framework that supports security models with different security / usability tradeoffs. By leveraging Diplomat, a community repository can achieve near-perfect compromise-resilience while allowing real-time project registration. For example, when Diplomat is deployed and configured to maximize security on Python’s community repository, less than 1% of users will be at risk even if an attacker controls the repository and is undetected for a month. Diplomat is being integrated by Ruby, CoreOS, Haskell, OCaml, and Python, and has already been deployed by Flynn, LEAP, and Docker.
Anatomical Variants in Prostate Artery Embolization: A Pictorial Essay

Prostate artery embolization (PAE) has emerged as a new treatment option for patients with symptomatic benign prostatic hyperplasia. The main challenges related to this procedure are navigating arteries with atherosclerosis and anatomical variations, and the potential risk of non-target embolization to pelvic structures due to the presence of collateral shunts and reflux of microparticles. Knowledge of classical vascular anatomy and the most common variations is essential for safe embolization, good clinical practice, and optimal outcomes. The aim of this pictorial essay is to illustrate the pelvic vascular anatomy relevant to PAE in order to provide a practical guide that includes the most common anatomical variants as well as to discuss the technical details related to each.
An Embedded Declarative Language for Hierarchical Object Structure Traversal

A common challenge in processing large domain-specific models and in-memory object structures (e.g., complex XML documents) is writing traversals and queries on them. Object-oriented (OO) designs, particularly those based on the Visitor pattern, are commonly used for developing traversals. However, such OO designs limit the reusability and independent evolution of visitation actions (i.e., the actions to be performed at each traversed node) due to tight coupling between the traversal logic and visitation actions, particularly when a variety of different traversals are needed. Code generators developed for traversal specification languages alleviate some of these problems but their high cost of development is often prohibitive. This paper presents Language for Embedded quEry and traverSAl (LEESA), which provides a generative programming approach for embedding object structure queries and traversal specifications within a host language, C++. By virtue of being declarative, LEESA significantly reduces the development cost of programs operating on complex object structures compared to the traditional techniques.
Meme extraction and tracing in crisis events

The proliferation of social media has increased the competition among different memes, which can be free texts, trending catchphrases, or micro media. As human attention is limited, these memes compete with each other, and go in and out of popularity at a rapid pace, sometimes even faster than we can recognize. Popular memes often shape the mindsets of online communities, and also shed light on their future tendencies. Considering the huge volume of memes generated and their continuous mutations, extracting and tracing online memes automatically is rather challenging. In this paper, we propose an automatic meme extraction algorithm. The proposed algorithm extracts massive memes based on phrases independency, and clusters phrase variants of a single meme efficiently. Evaluation on measles outbreak in the USA in 2015 indicates that the proposed algorithm could extract typical memes reflecting the fierce campaign between the pro-vaccination community and the anti-vaccination community. In both communities, memes are power-law distributed, and popular ones have many variants that appear more frequently. By tracing the evolution of online memes, we uncover that popular memes converge and generate peaks at times. Though the pro-vaccination community and the anti-vaccination community may focus on similar memes, they comprehend memes from totally different perspectives and deliver opposing opinions of measles vaccination.
SeCURITy AnAlySIS oF MobIle Two-FACToR AUThenTICATIon SCheMeS

Two-factor authentication (2FA) schemes aim at strengthening the security of login-password–based authentication by deploying secondary authentication tokens. In this context, mobile 2FA schemes require no additional hardware (such as a smartcard) to store and handle the secondary authentication token, and hence are considered as a reasonable tradeoff between security, usability, and cost. They are widely used in online banking and increasingly deployed by Internet service providers.