nils-herrmann/clean_scirepeval huggingface dataset:
Learning to Refine Human Pose Estimation

Multi-person pose estimation in images and videos is an important yet challenging task with many applications. Despite the large improvements in human pose estimation enabled by the development of convolutional neural networks, there still exist a lot of difficult cases where even the state-of-the-art models fail to correctly localize all body joints. This motivates the need for an additional refinement step that addresses these challenging cases and can be easily applied on top of any existing method. In this work, we introduce a pose refinement network (PoseRefiner) which takes as input both the image and a given pose estimate and learns to directly predict a refined pose by jointly reasoning about the input-output space. In order for the network to learn to refine incorrect body joint predictions, we employ a novel data augmentation scheme for training, where we model "hard" human pose cases. We evaluate our approach on four popular large-scale pose estimation benchmarks such as MPII Single- and Multi-Person Pose Estimation, PoseTrack Pose Estimation, and PoseTrack Pose Tracking, and report systematic improvement over the state of the art.
Achieving effective cloud search services: multi-keyword ranked search over encrypted cloud data supporting synonym query

In recent years, consumer-centric cloud computing paradigm has emerged as the development of smart electronic devices combined with the emerging cloud computing technologies. A variety of cloud services are delivered to the consumers with the premise that an effective and efficient cloud search service is achieved. For consumers, they want to find the most relevant products or data, which is highly desirable in the "pay-as-you use" cloud computing paradigm. As sensitive data (such as photo albums, emails, personal health records, financial records, etc.) are encrypted before outsourcing to cloud, traditional keyword search techniques are useless. Meanwhile, existing search approaches over encrypted cloud data support only exact or fuzzy keyword search, but not semantics-based multi-keyword ranked search. Therefore, how to enable an effective searchable system with support of ranked search remains a very challenging problem. This paper proposes an effective approach to solve the problem of multi-keyword ranked search over encrypted cloud data supporting synonym queries. The main contribution of this paper is summarized in two aspects: multi-keyword ranked search to achieve more accurate search results and synonym-based search to support synonym queries. Extensive experiments on real-world dataset were performed to validate the approach, showing that the proposed solution is very effective and efficient for multikeyword ranked searching in a cloud environment.
Modeling and measuring a Moog voltage-controlled filter

The analog voltage-controlled filter used in historical music synthesizers by Moog is modeled using a digital system, which is then compared in terms of audio measurements with the original analog filter. The analog model is mainly borrowed from D'Angelo's previous work. The digital implementation of the filter incorporates a recently proposed antialiasing method. This method enhances the clarity of output signals in the case of large-level input signals, which cause harmonic distortion. The combination of these two ideas leads to a novel digital model, which represents the state of the art in virtual analog musical filters. It is shown that without the antialiasing, the output signals in the nonlinear regime may be contaminated by undesirable spectral components, which are the consequence of aliasing, but that the antialiasing technique suppresses these components sufficiently. Comparison of measurements of the analog and digital filters show that the digital model is accurate within a few dB in the linear regime and has very similar behavior in the nonlinear regime in terms of distortion. The proposed digital filter model can be used as a building block in virtual analog music synthesizers.
SpamBayes: Effective open-source, Bayesian based, email classification system

This paper introduces the SpamBayes classification engine and outlines the most important features and techniques which contribute to its success. The importance of using the indeterminate ‘unsure’ classification produced by the chi-squared combining technique is explained. It outlines a Robinson/Woodhead/Peters technique of ‘tiling’ unigrams and bigrams to produce better results than relying solely on either or other methods of using both unigrams and bigrams. It discusses methods of training the classifier, and evaluates the success of different methods. The paper focuses on highlighting techniques that might aid other classification systems rather than attempting to demonstrate the effectiveness of the SpamBayes classification engine.
Geometric features for voxel-based surface recognition

We introduce a library of geometric voxel features for CAD surface recognition/retrieval tasks. Our features include local versions of the intrinsic volumes (the usual 3D volume, surface area, integrated mean and Gaussian curvature) and a few closely related quantities. We also compute Haar wavelet and statistical distribution features by aggregating raw voxel features. We apply our features to object classification on the ESB data set and demonstrate accurate results with a small number of shallow decision trees.
A tertiary study: experiences of conducting systematic literature reviews in software engineering

The use of Systematic Literature Review (SLR) requires expertise and poses many challenges for novice researchers. The experiences of those who have used this research methodology can benefit novice researchers in effectively dealing with these challenges.  The aim of this study is to record the reported experiences of conducting Systematic Literature Reviews, for the benefit of new researchers. Such a review will greatly benefit the researchers wanting to conduct SLR for the very first time.  We conducted a tertiary study to gather the experiences published by researchers. Studies that have used the SLR research methodology in software engineering and have implicitly or explicitly reported their experiences are included in this review.  Our research has revealed 116 studies relevant to the theme. The data has been extracted by two researchers working independently and conflicts resolved after discussion with third researcher. Findings from these studies highlight Search Strategy, Online Databases, Planning and Data Extraction as the most challenging phases of SLR. Lack of standard terminology in software engineering papers, poor quality of abstracts and problems with search engines are some of the most cited challenges.  Further research and guidelines is required to facilitate novice researchers in conducting these phases properly.
MANIPULATOR CALIBRATION USING A SINGLE ENDPOINT CONTACT CONSTRAINT

Most manipulator calibration techniques require expensive and/or complicated pose measuring devices, such as theodolites. This paper investigates a calibration method where the manipulator endpoint is constrained to a single contact point and executes self-motions. From the easily measured joint angle readings, and an identification model, the manipulator is calibrated. Adding a wrist force sensor allows for the calibration of elastic effects due to end-point forces and moments. Optimization of the procedure is discussed. Experimental results are presented, showing the effectiveness of the method.  Physical errors, such as machining tolerances, assembly errors and elastic deformations, cause the geometric properties of a manipulator to be different from their ideal values. Model based error compensation of a robotic manipulator, also known as robot calibration, is a process to improve manipulator position accuracy using software. Classical calibration involves identifying an accurate functional relationship between the joint transducer readings and the workspace position of the end-effector in terms of parameters called generalized errors (Roth et al., 1987). This relationship is found from measured data and used to predict, and compensate for, the endpoint errors as a function of configuration. Considerable research has been performed to make manipulator calibration more effective both in terms of required number of measurements and computation by the procedure (Hollerbach, 1988; Hollerbach and Wampler, 1996; Roth et al., 1987). Several calibration techniques have been used to improve robot accuracy (Roth et al., 1987), including open and closed-loop methods (Everett and Lin, 1988). Open-loop methods require an external metrology system to measure the end-effector pose, such as theodolites. Obtaining open-loop measurements is generally very costly and time consuming, and must be performed regularly for very high precision systems. In contrast, closed-loop methods only need joint angle sensing, and the robot becomes self-calibrating. In closed-loop calibration, constraints are imposed on the end-effector of the robot, and the kinematic loop closure equations are adequate to calibrate the manipulator from joint readings alone. Past closed-loop methods have had the robot moving along an unsensed sliding joint at the endpoint, or constraining the endeffector to lie on a plane (Ikits and Hollerbach, 1997; Zhuang et al., 1999). This paper investigates a closed-loop calibration method that was among a number suggested by (Bennett and Hollerbach, 1991). In the method, called here Single Endpoint Contact (SEC) calibration, the robot endpoint is constrained to a single contact point. Using an end-effector fixture equivalent to a ball joint, the robot executes self-motions to move to different configurations. At each configuration, manipulator joint sensors provide data that is used in an SEC identification algorithm to estimate the robot’s parameters. A total least squares optimization procedure is used to improve the calibration accuracy (Hollerbach and Wampler, 1996).
Design of Variable-Flux Permanent-Magnet Machines Using Alnico Magnets

This paper proposes a novel design for variable-flux machines with Alnico magnets. The proposed design uses tangentially magnetized magnets to achieve high air-gap flux density and to avoid demagnetization by the armature field. Barriers are also inserted in the rotor to limit the armature flux and to allow the machine to utilize both reluctance and magnet torque components. An analytical procedure is first applied to obtain the initial machine design parameters. Then, several modifications are applied to the stator and rotor designs through finite-element analysis (FEA) simulations to improve machine efficiency and torque density. A prototype of the proposed design is built, and the experimental results are in good correlation with the FEA simulations, confirming the validity of the proposed machine design concept.
An Attributed Graph Mining Approach to Detect Transfer Pricing Fraud

This paper presents an attributed graph-based approach to an intricate data mining problem of revealing affiliated, interdependent entities that might be at risk of being tempted into fraudulent transfer pricing. We formalize the notions of controlled transactions and interdependent parties in terms of graph theory. We investigate the use of clustering and rule induction techniques to identify candidate groups (hot spots) of suspect entities. Further, we find entities that require special attention with respect to transfer pricing audits using network analysis and visualization techniques in IBM i2 Analyst's Notebook.
Ozonation of drinking water : Part I . Oxidation kinetics and product formation

The oxidation of organic and inorganic compounds during ozonation can occur via ozone or OH radicals or a combination thereof. The oxidation pathway is determined by the ratio of ozone and OH radical concentrations and the corresponding kinetics. A huge database with several hundred rate constants for ozone and a few thousand rate constants for OH radicals is available. Ozone is an electrophile with a high selectivity. The second-order rate constants for oxidation by ozone vary over 10 orders of magnitude, between o0.1M s 1 and about 7 10M s . The reactions of ozone with drinking-water relevant inorganic compounds are typically fast and occur by an oxygen atom transfer reaction. Organic micropollutants are oxidized with ozone selectively. Ozone reacts mainly with double bonds, activated aromatic systems and non-protonated amines. In general, electron-donating groups enhance the oxidation by ozone whereas electron-withdrawing groups reduce the reaction rates. Furthermore, the kinetics of direct ozone reactions depend strongly on the speciation (acid-base, metal complexation). The reaction of OH radicals with the majority of inorganic and organic compounds is nearly diffusion-controlled. The degree of oxidation by ozone and OH radicals is given by the corresponding kinetics. Product formation from the ozonation of organic micropollutants in aqueous systems has only been established for a few compounds. It is discussed for olefines, amines and aromatic compounds. r 2002 Elsevier
A Distributed Highway Velocity Model for Traffic State Reconstruction

This article is motivated by the practical problem of highwa y traffic estimation using velocity measurements from GPS enabled mobile devices such as cell phones. In order to simplify the estimation procedure, a velocity model for highway traffic is constructed, which results in a d ynamical system in which observation the operator is linear. This article presents a new scalar hyperbolic partial differential equation(PDE) model for traffic velocity evolution on highways, based on the seminal Lighthill-Whitham-Richards(LWR) PDE for density. Equivalence of the solution of the new velocity PDE and the solution of the LW R PDE is shown for quadratic flux functions. Because this equivalence does not hold for general flux funct io s, a discretized model of velocity evolution based on the Godunov scheme applied to the LWR PDE is proposed. Usin g an explicit instantiation of the weak boundary conditions of the PDE, the discrete velocity evolution mode l is generalized to a network, thus making the model applicable to arbitrary highway networks. The resulting ve locity model is a nonlinear and nondifferentiable discrete time dynamical system with a linear observation operator, w hich enables the use of a Monte-Carlo based ensemble Kalman filtering data assimilation algorithm. Accuracy of t he model and estimation technique is validated on experimental data obtained from a large-scale field experim ent.
Relational quality and media use in interpersonal relationships

This study examined the relationship between relational quality and media use in interpersonal relationships. In addition, the impacts of other potentially important variables such as sex and relationship type of participants and their partners were explored. College student participants focused on interaction experiences with an acquaintance, friend, romantic partner, or family member. Questions addressed the sex of relational partners, how much of participants’ total communication with relational partners is conducted in each of three media (i.e., face-to-face, phone, and internet), and the quality of relationships. Results indicated that participant sex and partner sex did not affect reported media use, whereas relationship type had significant effects on the extent to which face-to-face and telephone
Death following intentional ingestion of e-liquid.

Electronic cigarette (e-cigarette) use is growing within the United States, resulting in both intentional and unintentional exposures to concentrated liquid nicotine or "e-liquid." Nicotine has been culpable for severe poisoning and deaths in the past. However, sources of nicotine have traditionally been from cigarettes, cigars, or pesticides. Fatalities due to liquid nicotine are rare, and fatalities following ingestion of e-liquid are even scarcer.



We present a case of a 24-year-old woman who intentionally ingested up to 3000 mg of liquid nicotine intended for e-cigarette use. She was found in pulseless electrical activity and had return of spontaneous circulation (ROSC) after undergoing approximately 10 min of cardiopulmonary resuscitation with a blood pressure of 74/53 mmHg and a pulse rate of 106 beats/min. Despite aggressive supportive care, she ultimately died after she was found to have multiple acute infarcts, consistent with severe anoxic brain injury, on magnetic resonance imaging. The patient's toxicologic testing, obtained shortly after ROSC, was notable for plasma nicotine and cotinine levels each >1000 ng/mL.



This fatality highlights the potential toxicity associated with suicidal ingestion of liquid nicotine.
StrokeAggregator: consolidating raw sketches into artist-intended curve drawings

When creating line drawings, artists frequently depict intended curves using multiple, tightly clustered, or overdrawn, strokes. Given such sketches, human observers can readily envision these intended, aggregate, curves, and mentally assemble the artist's envisioned 2D imagery. Algorithmic stroke consolidation---replacement of overdrawn stroke clusters by corresponding aggregate curves---can benefit a range of sketch processing and sketch-based modeling applications which are designed to operate on consolidated, intended curves. We propose StrokeAggregator, a novel stroke consolidation method that significantly improves on the state of the art, and produces aggregate curve drawings validated to be consistent with viewer expectations. Our framework clusters strokes into groups that jointly define intended aggregate curves by leveraging principles derived from human perception research and observation of artistic practices. We employ these principles within a coarse-to-fine clustering method that starts with an initial clustering based on pairwise stroke compatibility analysis, and then refines it by analyzing interactions both within and in-between clusters of strokes. We facilitate this analysis by computing a common 1D parameterization for groups of strokes via common aggregate curve fitting. We demonstrate our method on a large range of line drawings, and validate its ability to generate consolidated drawings that are consistent with viewer perception via qualitative user evaluation, and comparisons to manually consolidated drawings and algorithmic alternatives.
A microwave frequency sensor for non-invasive blood-glucose measurement

A microwave sensor having features useful for the noninvasive determination of blood glucose levels is described. The sensor output is an amplitude only measurement of the standing wave versus frequency sampled at a fixed point on an open-terminated spiral-shaped microstrip line. Test subjects press their thumb against the line and apply contact pressure sufficient to fall within a narrow pressure range. Data are reported for test subjects whose blood glucose is independently measured using a commercial glucometer.
SCADA security: a review and enhancement for DNP3 based systems

Supervisory control and data acquisition (SCADA) systems are large-scale industrial control systems often spread across geographically dispersed locations that let human operators control entire physical systems, from a single control room. Early multi-site SCADA systems used closed networks and propriety industrial communication protocols like Modbus, DNP3 etc to reach remote sites. But with time it has become more convenient and more cost-effective to connect them to the Internet. However, internet connections to SCADA systems build in new vulnerabilities, as SCADA systems were not designed with internet security in mind. This can become matter of national security if these systems are power plants, water treatment facilities, or other pieces of critical infrastructure. Compared to IT systems, SCADA systems have a higher requirement concerning reliability, latency and uptime, so it is not always feasible to apply IT security measures deployed in IT systems. This paper provides an overview of security issues and threats in SCADA networks. Next, attention is focused on security assessment of the SCADA. This is followed by an overview of relevant SCADA security solutions. Finally we propose our security solution approach which is embedded in bump-in-the-wire is discussed.
Phytochemical, Antimicrobial, and Toxicological Evaluation of Traditional Herbs Used to Treat Sore Throat

The in vitro antibacterial activities of 29 traditional medicinal plants used in respiratory ailments were assessed on multidrug resistant Gram-positive and Gram-negative bacteria isolated from the sore throat patients and two reference strains. The methanolic, n-hexane, and aqueous extracts were screened by the agar well diffusion assay. Bioactive fractions of effective extracts were identified on TLC coupled with bioautography, while their toxicity was determined using haemolytic assay against human erythrocytes. Qualitative and quantitative phytochemical analysis of effective extracts was also performed. Methanolic extract of 18 plants showed antimicrobial activity against test strains. Adhatoda vasica (ZI = 17-21 mm, MIC: 7.12-62.5 μg/mL), Althaea officinalis (ZI = 16-20 mm, MIC: 15.62-31.25 μg/mL), Cordia latifolia (ZI = 16-20 mm, MIC: 12.62-62.5 μg/mL), Origanum vulgare (ZI = 20-22 mm, MIC: 3-15.62 μg/mL), Thymus vulgaris (ZI = 21-25 mm, MIC: 7.81-31.25 μg/mL), and Ziziphus jujuba (ZI = 14-20 mm, MIC: 7.81-31.25 μg/mL) showed significant antibacterial activity. Alkaloid fractions of Adhatoda vasica, Cordia latifolia, and Origanum vulgare and flavonoid fraction of the Althaea officinalis, Origanum vulgare, Thymus Vulgaris, and Ziziphus jujuba exhibited antimicrobial activity. Effective plant extracts show 0.93-0.7% erythrocyte haemolysis. The results obtained from this study provide a scientific rationale for the traditional use of these herbs and laid the basis for future studies to explore novel antimicrobial compounds.
Microemulsion-based media as novel drug delivery systems.

Microemulsions are clear, stable, isotropic mixtures of oil, water and surfactant, frequently in combination with a cosurfactant. These systems are currently of interest to the pharmaceutical scientist because of their considerable potential to act as drug delivery vehicles by incorporating a wide range of drug molecules. In order to appreciate the potential of microemulsions as delivery vehicles, this review gives an overview of the formation and phase behaviour and characterization of microemulsions. The use of microemulsions and closely related microemulsion-based systems as drug delivery vehicles is reviewed, with particular emphasis being placed on recent developments and future directions.
PeakVizor: Visual Analytics of Peaks in Video Clickstreams from Massive Open Online Courses

Massive open online courses (MOOCs) aim to facilitate open-access and massive-participation education. These courses have attracted millions of learners recently. At present, most MOOC platforms record the Web log data of learner interactions with course videos. Such large amounts of multivariate data pose a new challenge in terms of analyzing online learning behaviors. Previous studies have mainly focused on the aggregate behaviors of learners from a summative view; however, few attempts have been made to conduct a detailed analysis of such behaviors. To determine complex learning patterns in MOOC video interactions, this paper introduces a comprehensive visualization system called PeakVizor. This system enables course instructors and education experts to analyze the “peaks” or the video segments that generate numerous clickstreams. The system features three views at different levels: the overview with glyphs to display valuable statistics regarding the peaks detected; the flow view to present spatio-temporal information regarding the peaks; and the correlation view to show the correlation between different learner groups and the peaks. Case studies and interviews conducted with domain experts have demonstrated the usefulness and effectiveness of PeakVizor, and new findings about learning behaviors in MOOC platforms have been reported.