nils-herrmann/clean_scirepeval huggingface dataset:
Evaluation of an Automated Reading Tutor that Listens: Comparison to Human Tutoring and Classroom Instruction.

A year-long study of 131 second and third graders in 12 classrooms compared three daily 20-minute treatments. (a) 58 students in 6 classrooms used the 1999-2000 version of Project LISTEN’s Reading Tutor, a computer program that uses automated speech recognition to listen to a child read aloud, and gives spoken and graphical assistance. Students took daily turns using one shared Reading Tutor in their classroom while the rest of their class received regular instruction. (b) 34 students in the other 6 classrooms were pulled out daily for one-on-one tutoring by certified teachers. To control for materials, the human tutors used the same set of stories as the Reading Tutor. (c) 39 students served as in-classroom controls, receiving regular instruction without tutoring. We compared students’ preto post-test gains on the Word Identification, Word Attack, Word Comprehension, and Passage Comprehension subtests of the Woodcock Reading Mastery Test, and in oral reading fluency. Surprisingly, the human-tutored group significantly outgained the Reading Tutor group only in Word Attack (main effects p<.02, effect size .55). Third graders in both the computerand human-tutored conditions outgained the control group significantly in Word Comprehension (p<.02, respective effect sizes .56 and .72) and suggestively in Passage Comprehension (p=.14, respective effect sizes .48 and .34). No differences between groups on gains in Word Identification or fluency were significant. These results are consistent with an earlier study in which students who used the 1998 version of the Reading Tutor outgained their matched classmates in Passage Comprehension (p=.11, effect size .60), but not in Word Attack, Word Identification, or fluency. To shed light on outcome differences between tutoring conditions and between individual human tutors, we compared process variables. Analysis of logs from all 6,080 human and computer tutoring sessions showed that human tutors included less rereading and more frequent writing than the Reading Tutor. Micro-analysis of 40 videotaped sessions showed that students who used the Reading Tutor spent considerable time waiting for it to respond, requested help more frequently, and picked easier stories when it was their turn. Human tutors corrected more errors, focussed more on individual letters, and provided assistance more interactively, for example getting students to sound out words rather than sounding out words themselves as the Reading Tutor did.
Modular ATRON: modules for a self-reconfigurable robot

This paper describes the mechanical and electrical design of a new lattice based self-reconfigurable robot, called the ATRON. The ATRON system consists of several fully self-contained robot modules, each having their own processing power, power supply, sensors and actuators. The ATRON modules are roughly spheres with equatorial rotation. Each module can be connected to up to eight neighbors through four male and four female connectors. In this paper, we describe the realization of the design, both the mechanics and the electronics. Details on power sharing and power consumption is given. Finally, this paper includes a brief outline of our future work on the ATRON system.
Clinical anatomy of the coccyx: A systematic review.

The coccyx has been relatively neglected in anatomical research which is surprising given the population prevalence of coccydynia and our inadequate understanding of its etiology. This systematic review analyzes available information on the clinical anatomy of the coccyx. A literature search using five electronic databases and standard anatomy reference texts was conducted yielding 61 primary and 7 secondary English-language sources. This was supplemented by a manual search of selected historical foreign language articles. The coccygeal vertebrae, associated joints, ligaments and muscles, coccygeal movements, nerves, and blood supply were analyzed in detail. Although the musculoskeletal aspects of the coccyx are reasonably well described, the precise anatomy of the coccygeal plexus and its distribution, the function of the coccygeal body, and the anatomy of the sacrococcygeal zygapophyseal joints are poorly documented. Further research into the anatomy of the coccyx may clarify the etiopathogenesis of coccydynia which remains uncertain in one-third of affected patients.
Marrying Uncertainty and Time in Knowledge Graphs

The management of uncertainty is crucial when harvesting structured content from unstructured and noisy sources. Knowledge Graphs (KGs) are a prominent example. KGs maintain both numerical and non-numerical facts, with the support of an underlying schema. These facts are usually accompanied by a confidence score that witnesses how likely is for them to hold. Despite their popularity, most of existing KGs focus on static data thus impeding the availability of timewise knowledge. What is missing is a comprehensive solution for the management of uncertain and temporal data in KGs. The goal of this paper is to fill this gap. We rely on two main ingredients. The first is a numerical extension of Markov Logic Networks (MLNs) that provide the necessary underpinning to formalize the syntax and semantics of uncertain temporal KGs. The second is a set of Datalog constraints with inequalities that extend the underlying schema of the KGs and help to detect inconsistencies. From a theoretical point of view, we discuss the complexity of two important classes of queries for uncertain temporal KGs: maximum a-posteriori and conditional probability inference. Due to the hardness of these problems and the fact that MLN solvers do not scale well, we also explore the usage of Probabilistic Soft Logics (PSL) as a practical tool to support our reasoning tasks. We report on an experimental evaluation comparing the MLN and PSL approaches.
Answering the Call for a Standard Reliability Measure for Coding Data

In content analysis and similar methods, data are typically generated by trained human observers who record or transcribe textual, pictorial, or audible matter in terms suitable for analysis. Conclusions from such data can be trusted only after demonstrating their reliability. Unfortunately, the content analysis literature is full of proposals for so-called reliability coefficients, leaving investigators easily confused, not knowing which to choose. After describing the criteria for a good measure of reliability, we propose Krippendorff’s alpha as the standard reliability measure. It is general in that it can be used regardless of the number of observers, levels of measurement, sample sizes, and presence or absence of missing data. To facilitate the adoption of this recommendation, we describe a freely available macro written for SPSS and SAS to calculate Krippendorff’s alpha and illustrate its use with a simple example.
Implementation and Performance Analysis of Firewall on Open vSwitch

Software Defined Networking (SDN) is a current research trend that follows the ideology of physical separation of the control and data plane of the forwarding devices. SDN mainly advocates with two types of devices: (1) Controllers, that implement the control plane and (2) Switches, that perform the data plane operations. OpenFlow protocol (OFP) is the current standard through which controllers and switches can communicate with each other. Using OpenFlow, SDN controllers can manage forwarding behaviors of SDN switches by managing Flow Table entries. Switches use these low-level Flow Table entries to forward packets to appropriate hosts. Firewalls are integral part of today’s networks. We can’t imagine our network without a Firewall which protects our network from potential threats. As SDN is getting pace in replacing traditional architecture, it would be very interesting to see how much security features can be provided by OpenFlow-enabled switches. Hence, it will be very important to see if SDN, on the top of OpenFlow, can efficiently implement Firewalls and provides support for an advanced feature like connection tracking. The task is straightforward: Controller will add Flow Table entries on switches based upon Firewall rules. Such way, we can enhance packet-processing by providing security. In this Document, one strategy for implementing Firewall on SDN is presented. We can write some controller applications that work as Firewall and inspect incoming packets against the Firewall rules. These applications are also able to implement connection tracking mechanism. As SDN devices for the experiments, we selected Ryu controller and Open vSwitch. Initially, such applications are tested on local machine with small Firewall ruleset. Later, they are tested with real-world traffic and comparatively large Firewall ruleset. The testing results present that such strategy can be used as a first step in implementing security features (including connection tracking) in SDN environment.
Automatic Generation of Visual-Textual Presentation Layout

Visual-textual presentation layout (e.g., digital magazine cover, poster, Power Point slides, and any other rich media), which combines beautiful image and overlaid readable texts, can result in an eye candy touch to attract users’ attention. The designing of visual-textual presentation layout is therefore becoming ubiquitous in both commercially printed publications and online digital magazines. However, handcrafting aesthetically compelling layouts still remains challenging for many small businesses and amateur users. This article presents a system to automatically generate visual-textual presentation layouts by investigating a set of aesthetic design principles, through which an average user can easily create visually appealing layouts. The system is attributed with a set of topic-dependent layout templates and a computational framework integrating high-level aesthetic principles (in a top-down manner) and low-level image features (in a bottom-up manner). The layout templates, designed with prior knowledge from domain experts, define spatial layouts, semantic colors, harmonic color models, and font emotion and size constraints. We formulate the typography as an energy optimization problem by minimizing the cost of text intrusion, the utility of visual space, and the mismatch of information importance in perception and semantics, constrained by the automatically selected template and further preserving color harmonization. We demonstrate that our designs achieve the best reading experience compared with the reimplementation of parts of existing state-of-the-art designs through a series of user studies.
AUTOMATIC GENERATION OF PRESENTATION SLIDES FOR ACADEMIC PAPERS USING INTEGER LINEAR PROGRAMMING

Presentations are one of the most common and effective ways of communicating the overview of a work to the audience. Given a specialized paper, programmed era of introduction slides diminishes the exertion of the moderator and aides in making an organized synopsis of the paper. In this Project, we propose the structure of another framework that does this assignment. Any paper that has a theoretical and whose segments can be ordered under presentation, related work, model, examinations and conclusions can be given as info. This XML record is parsed and data in it is extricated. An inquiry particular extractive summarizer has been utilized to create slides. In numerous meetings and social occasions, a moderator takes the guide of slides to present his work deliberately (pictorial). The introduction slides for the paper are then made by utilizing the Integer Linear Programming (ILP) demonstrate with complicatedly organized target breaking points and goals to pick and adjust key expressions and sentences. The framework removed theme and non subject parts from the article in light of the basic talk structure. The isolated subject and non-topic parts were determined to the slides by giving fitting indents in perspective of the examination of their syntactic structure.  Abstracting methods, Integer Linear Programming, Support Vector Regression model, text mining.
Differential diagnosis and treatment strategies for biologic complications and failing oral implants: a review of the literature.

The aim of this article was to review the literature on differential diagnosis and treatment of biologic complications and failing implants. All types of publications, with the exception of abstracts, published in English up to December 1998, were included. A multi-layered search strategy was used. Controlled clinical trials (CCTs) were searched in the Cochrane Oral Health Group's Specialized Register of Trials. This database contains all CCTs identified in MEDLINE and EMBASE. PubMed was searched using various key words and the "related articles" feature. All identified publications were obtained and none were excluded. Infection, impaired healing, and overload are considered the major etiologic factors for the loss of oral implants. Only a few clinical and animal investigations were found that tested the validity of the proposed therapeutic approaches. The treatment of failing implants is still based mainly on empirical considerations, often derived from periodontal research, from data extrapolated from in vitro findings, or from anecdotal case reports performed on a trial-and-error basis.
VisiCon: a robot control interface for visualizing manipulation using a handheld projector

The miniaturization of image projectors leads to the expectation that projectors could be embedded in mobile devices such as cellular phones and PDAs. A projector mounted on a mobile device, freely movable in 3D space under user control, could operate not only as an output device but also as an input device for enabling humans to manipulate mobile robots. We therefore explore the possibilities of human-robot interaction techniques using handheld projectors. For this purpose, we propose an innovative interface called VisiCon. We have also developed a cooperative game, CoGAME, in which players guide a simple robot using handheld projectors. In this game, users can connect projected maps together, and cooperatively lead a robot to a specified goal. In this paper, we explain the techniques used in CoGAME, and present an evaluation.
Accurate mobile malware detection and classification in the cloud

As the dominator of the Smartphone operating system market, consequently android has attracted the attention of s malware authors and researcher alike. The number of types of android malware is increasing rapidly regardless of the considerable number of proposed malware analysis systems. In this paper, by taking advantages of low false-positive rate of misuse detection and the ability of anomaly detection to detect zero-day malware, we propose a novel hybrid detection system based on a new open-source framework CuckooDroid, which enables the use of Cuckoo Sandbox's features to analyze Android malware through dynamic and static analysis. Our proposed system mainly consists of two parts: anomaly detection engine performing abnormal apps detection through dynamic analysis; signature detection engine performing known malware detection and classification with the combination of static and dynamic analysis. We evaluate our system using 5560 malware samples and 6000 benign samples. Experiments show that our anomaly detection engine with dynamic analysis is capable of detecting zero-day malware with a low false negative rate (1.16 %) and acceptable false positive rate (1.30 %); it is worth noting that our signature detection engine with hybrid analysis can accurately classify malware samples with an average positive rate 98.94 %. Considering the intensive computing resources required by the static and dynamic analysis, our proposed detection system should be deployed off-device, such as in the Cloud. The app store markets and the ordinary users can access our detection system for malware detection through cloud service.
A Simple and Reliable PDMS and SU-8 Irreversible Bonding Method and Its Application on a Microfluidic-MEA Device for Neuroscience Research

Polydimethylsiloxane (PDMS) and SU-8 are currently two very commonly used polymeric materials in the microfluidics field for biological applications. However, there is a pressing need to find a simple, reliable, irreversible bonding method between these two materials for their combined use in innovative integrated microsystems. In this paper, we attempt to investigate the aminosilane-mediated irreversible bonding method for PDMS and SU-8 with X-Ray Photoelectron Spectroscopy (XPS) surface analysis and bonding strength tests. Additionally, the selected bonding method was applied in fabricating a microelectrode array (MEA) device, including microfluidic features, which allows electrophysiological observations on compartmentalized neuronal cultures. As there is a growing trend towards microfluidic devices for neuroscience research, this type of integrated microdevice, which can observe functional alterations on compartmentalized neuronal culture, can potentially be used for neurodegenerative disease research and pharmaceutical development.
Efficient GPU path rendering using scanline rasterization

We introduce a novel GPU path rendering method based on scan-line rasterization, which is highly work-efficient but traditionally considered as GPU hostile. Our method is parallelized over boundary fragments, i.e., pixels directly intersecting the path boundary. Non-boundary pixels are processed in bulk as horizontal spans like in CPU scanline rasterizers, which saves a significant amount of winding number computation workload. The distinction also allows the majority of our algorithmic steps to focus on boundary fragments only, which leads to highly balanced workload among the GPU threads. In addition, we develop a ray shooting pattern that minimizes the global data dependency when computing winding numbers at anti-aliasing samples. This allows us to shift the majority of winding-number-related workload to the same kernel that consumes its result, which saves a significant amount of GPU memory bandwidth. Experiments show that our method gives a consistent 2.5X speedup over state-of-the-art alternatives for high-quality rendering at Ultra HD resolution, which can increase to more than 30X in extreme cases. We can also get a consistent 10X speedup on animated input.
Patch Based Multiple Instance Learning Algorithm for Object Tracking

To deal with the problems of illumination changes or pose variations and serious partial occlusion, patch based multiple instance learning (P-MIL) algorithm is proposed. The algorithm divides an object into many blocks. Then, the online MIL algorithm is applied on each block for obtaining strong classifier. The algorithm takes account of both the average classification score and classification scores of all the blocks for detecting the object. In particular, compared with the whole object based MIL algorithm, the P-MIL algorithm detects the object according to the unoccluded patches when partial occlusion occurs. After detecting the object, the learning rates for updating weak classifiers' parameters are adaptively tuned. The classifier updating strategy avoids overupdating and underupdating the parameters. Finally, the proposed method is compared with other state-of-the-art algorithms on several classical videos. The experiment results illustrate that the proposed method performs well especially in case of illumination changes or pose variations and partial occlusion. Moreover, the algorithm realizes real-time object tracking.
Identifying patterns in combat that are predictive of success in MOBA games

Multiplayer Online Battle Arena (MOBA) games rely primarily on combat to determine the ultimate outcome of the game. Combat in these types of games is highly-dynamic and can be difficult for novice players to learn. Typically, mastery of combat requires that players obtain expert knowledge through practice, which can be difficult to concisely describe. In this paper, we present a data-driven approach for discovering patterns in combat tactics that are common among winning teams in MOBA games. We model combat as a sequence of graphs and extract patterns that predict successful outcomes not just of combat, but of the entire game. To identify those patterns, we attribute features to these graphs using well known graph metrics. These features allow us to describe, in meaningful terms, how different combat tactics contribute to team success. We also present an evaluation of our methodology on the popular MOBA game, DotA 2 (Defense of the Ancients 2). Experiments show that extracted patterns achieve an 80% prediction accuracy when testing on new game logs.
GPU Passthrough Performance: A Comparison of KVM, Xen, VMWare ESXi, and LXC for CUDA and OpenCL Applications

As more scientific workloads are moved into the cloud, the need for high performance accelerators increases. Accelerators such as GPUs offer improvements in both performance and power efficiency over traditional multi-core processors, however, their use in the cloud has been limited. Today, several common hypervisors support GPU passthrough, but their performance has not been systematically characterized. In this paper we show that low overhead GPU passthrough is achievable across 4 major hypervisors and two processor microarchitectures. We compare the performance of two generations of NVIDIA GPUs within the Xen, VMWare ESXi, and KVM hypervisors, and we also compare the performance to that of Linux Containers (LXC). We show that GPU passthrough to KVM achieves 98 -- 100\% of the base system's performance across two architectures, while Xen and VMWare achieve 96 -- 99\% of the base systems performance, respectively. In addition, we describe several valuable lessons learned through our analysis and share the advantages and disadvantages of each hypervisor/GPU passthrough solution.
Pulse glucometry: A new approach for noninvasive blood glucose measurement using instantaneous differential near-infrared spectrophotometry.

We describe a new optical method for noninvasive blood glucose (BGL) measurement. Optical methods are confounded by basal optical properties of tissues, especially water and other biochemical species, and by the very small glucose signal. We address these problems by using fast spectrophotometric analysis in a finger, deriving 100 transmittance spectra per second, to resolve optical spectra (900 to 1700 nm) of blood volume pulsations throughout the cardiac cycle. Difference spectra are calculated from the pulsatile signals, thereby eliminating the effects of bone, other tissues, and nonpulsatile blood. A partial least squares (PLS) model is used with the measured spectral data to predict BGL levels. Using glucose tolerance tests in 27 healthy volunteers, periodic optical measurements were made simultaneously with collection of blood samples for in vitro glucose analysis. Altogether, 603 paired data sets were obtained in all subjects and two-thirds of the data or of the subjects randomly selected were used for the PLS calibration model and the rest for the prediction. Bland-Altman and error-grid analyses of the predicted and measured BGL levels indicated clinically acceptable accuracy. We conclude that the new method, named pulse glucometry, has adequate performance for safe, noninvasive estimation of BGL.