nils-herrmann/clean_scirepeval huggingface dataset:
ProvChain: A Blockchain-Based Data Provenance Architecture in Cloud Environment with Enhanced Privacy and Availability

Cloud data provenance is metadata that records the history of the creation and operations performed on a cloud data object. Secure data provenance is crucial for data accountability, forensics and privacy. In this paper, we propose a decentralized and trusted cloud data provenance architecture using blockchain technology. Blockchain-based data provenance can provide tamper-proof records, enable the transparency of data accountability in the cloud, and help to enhance the privacy and availability of the provenance data. We make use of the cloud storage scenario and choose the cloud file as a data unit to detect user operations for collecting provenance data. We design and implement ProvChain, an architecture to collect and verify cloud data provenance, by embedding the provenance data into blockchain transactions. ProvChain operates mainly in three phases: (1) provenance data collection, (2) provenance data storage, and (3) provenance data validation. Results from performance evaluation demonstrate that ProvChain provides security features including tamper-proof provenance, user privacy and reliability with low overhead for the cloud storage applications.
A wearable health care system based on knitted integrated sensors

A comfortable health monitoring system named WEALTHY is presented. The system is based on a textile wearable interface implemented by integrating sensors, electrodes, and connections in fabric form, advanced signal processing techniques, and modern telecommunication systems. Sensors, electrodes and connections are realized with conductive and piezoresistive yarns. The sensorized knitted fabric is produced in a one step process. The purpose of this paper is to show the feasibility of a system based on fabric sensing elements. The capability of this system to acquire simultaneously several biomedical signals (i.e. electrocardiogram, respiration, activity) has been investigated and compared with a standard monitoring system. Furthermore, the paper presents two different methodologies for the acquisition of the respiratory signal with textile sensors. Results show that the information contained in the signals obtained by the integrated systems is comparable with that obtained by standard sensors. The proposed system is designed to monitor individuals affected by cardiovascular diseases, in particular during the rehabilitation phase. The system can also help professional workers who are subject to considerable physical and psychological stress and/or environmental and professional health risks.
Overview of deep learning

In recent years, deep learning has achieved great success in many fields, such as computer vision and natural language processing. Compared to traditional machine learning methods, deep learning has a strong learning ability and can make better use of datasets for feature extraction. Because of its practicability, deep learning becomes more and more popular for many researchers to do research works. In this paper, we mainly introduce some advanced neural networks of deep learning and their applications. Besides, we also discuss the limitations and prospects of deep learning.
Semantic mapping relational to graph model

Making data to be more connected is one of the goals of Semantic Technology. Therefore, relational data model as one of important data resource type, is needed to be mapped and converted to graph model. In this paper we focus in mapping and converting without semantically loss, by considering semantic abstraction of the real world, which has been ignored in some previous researches. As a graph schema model, it can be implemented in graph database or linked data in RDF/OWL format. This approach studies that relationship should be paid more attention in mapping and converting because, often be found a gap semantic abstraction during those processes. In our small experiment shows that our idea can map and convert relational model to graph model without semantically loss.
Analysing Errors of Open Information Extraction Systems

We report results on benchmarking Open Information Extraction (OIE) systems using RelVis, a toolkit for benchmarking Open Information Extraction systems. Our comprehensive benchmark contains three data sets from the news domain and one data set from Wikipedia with overall 4522 labeled sentences and 11243 binary or n-ary OIE relations. In our analysis on these data sets we compared the performance of four popular OIE systems, ClausIE, OpenIE 4.2, Stanford OpenIE and PredPatt. In addition, we evaluated the impact of five common error classes on a subset of 749 n-ary tuples. From our deep analysis we unreveal important research directions for a next generation of OIE systems.
Characteristics Regulation for Manufacture of Permanent-Magnet Motors Using Post-Assembly Magnetization

This paper proposes a technique for manufacturing permanent-magnet (PM) motors by means of post-assembly magnetization (PAM) rather than assembling with the rotor premagnetized. This can be used to vary the operating characteristics of the motor. PAM utilizes the stator windings of the PM motor to magnetize the magnets after complete assembly, where large current pulses are applied to magnetize the machine. However, in this paper, it is shown that PAM can be used in a manner where a degree of unsaturated magnetization is allowed, so that the motor back EMF constant can be regulated without modifying windings or geometry. Various magnetizing current pulses are applied which result in a range of back EMFs. These are measured for verification. From the experimental results, the feasibility of this magnetizing technique is demonstrated for a rare-earth magnet motor. It is also suggested that the magnetizing efficiency can be improved and the copper ratings reduced since it is found that large magnetizing currents may not contribute to magnetization beyond a certain current level
Mathematical Modeling and Analysis of a Vehicle Crash

Because of the fact that vehicle crash tests are complex and complicated experiments it is advisable to establish their mathematical models. This paper contains an overview of the kinematic and dynamic relationships of a vehicle in a collision. There is also presented basic mathematical model representing a collision together with its analysis. The main part of this paper is devoted to methods of establishing parameters of the vehicle crash model and to real crash data investigation i.e. – creation of a Kelvin model for a real experiment, its analysis and validation. After model’s parameters extraction a quick assessment of an occupant crash severity is done.  Modeling, vehicle crash, Kelvin model, data processing.
Design of radome-covered substrate integrated waveguide slot antenna array

A design of a radome-covered slot antenna array based on Substrate Integrated Waveguide (SIW) technology is presented in this paper. The design method consists of the analysis of an isolated radiating element, the synthesis of a linear array, the optimization of a planar array, and the development of a power divider with a transition from a feeding metal waveguide to an SIW. The antenna array is designed using a full-wave electromagnetic solver (CST Microwave Studio) for the operating frequency band 26.5-27.5 GHz. The paper describes simulation results of the antenna array consisting of 10×10 longitudinal slots and simulated and measured results of a fabricated antenna array consisting of 4×4 slots.
Differential social perception and attribution of intergroup violence: testing the lower limits of sterotyping of blacks.

In a modified 4 X 4 factorial design with race (black-white) of the harm-doer and race (black-white) of the victim as the major factors, the phenomenon of differential social perception of intergroup violence was established. While subjects, observing a videotape of purported ongoing ineraction occuring in another room, labeled an act (ambiguous shove) as more violent when it was performed by a black than when the same act was perpetrated by a white. That is, the concept of violence was more accessible when viewing a black than when viewing a white committing the same act. Causal attributions were also found to be divergent. Situation attributions were preferred when the harm-doer was white, and person (dispositional) attributions were preferred in the black-protagonist conditions. The results are discussed in terms of perceptual threshold, sterotypy, and attributional biases.
BROADBAND ASYMMETRICAL MULTI-SECTION COUPLED LINE WILKINSON POWER DIVIDER WITH UNEQUAL POWER DIVIDING RATIO

The uniform asymmetrical microstrip parallel coupled line is used to design the multi-section unequal Wilkinson power divider with high dividing ratio. The main objective of the paper is to increase the trace widths in order to facilitate the construction of the power divider with the conventional photolithography method. The separated microstrip lines in the conventional Wilkinson power divider are replaced with the uniform asymmetrical parallel coupled lines. An even-odd mode analysis is used to calculate characteristic impedances and then the per-unit-length capacitance and inductance parameter matrix are used to calculate the physical dimension of the power divider. To clarify the advantages of this method, two three-section Wilkinson power divider with an unequal power-division ratio of 1 : 2.5 are designed and fabricated and measured, one in the proposed configuration and the other in the conventional configuration. The simulation and the measurement results show that not only the specified design goals are achieved, but also all the microstrip traces can be easily implemented in the proposed power divider.
A Distributed Demand Response Algorithm and Its Application to PHEV Charging in Smart Grids

This paper proposes a distributed framework for demand response and user adaptation in smart grid networks. In particular, we borrow the concept of congestion pricing in Internet traffic control and show that pricing information is very useful to regulate user demand and hence balance network load. User preference is modeled as a willingness to pay parameter which can be seen as an indicator of differential quality of service. Both analysis and simulation results are presented to demonstrate the dynamics and convergence behavior of the algorithm. Based on this algorithm, we then propose a novel charging method for plug-in hybrid electric vehicles (PHEVs) in a smart grid, where users or PHEVs can adapt their charging rates according to their preferences. Simulation results are presented to demonstrate the dynamic behavior of the charging algorithm and impact of different parameters on system performance.
The RAND Corporation Good News and Bad News : Representation Theorems and Applications

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Recursive Noise Adaptive Kalman Filtering by Variational Bayesian Approximations

This article considers the application of variational Bayesian methods to joint recursive estimation of the dynamic state and the time-varying measurement noise parameters in linear state space models. The proposed adaptive Kalman filtering method is based on forming a separable variational approximation to the joint posterior distribution of states and noise parameters on each time step separately. The result is a recursive algorithm, where on each step the state is estimated with Kalman filter and the sufficient statistics of the noise variances are estimated with a fixed-point iteration. The performance of the algorithm is demonstrated with simulated data.
Preventing pressure ulcers: a systematic review.

Pressure ulcers are common in a variety of patient settings and are associated with adverse health outcomes and high treatment costs.



To systematically review the evidence examining interventions to prevent pressure ulcers.



MEDLINE, EMBASE, and CINAHL (from inception through June 2006) and Cochrane databases (through issue 1, 2006) were searched to identify relevant randomized controlled trials (RCTs). UMI Proquest Digital Dissertations, ISI Web of Science, and Cambridge Scientific Abstracts were also searched. All searches used the terms pressure ulcer, pressure sore, decubitus, bedsore, prevention, prophylactic, reduction, randomized, and clinical trials. Bibliographies of identified articles were further reviewed.



Fifty-nine RCTs were selected. Interventions assessed in these studies were grouped into 3 categories, ie, those addressing impairments in mobility, nutrition, or skin health. Methodological quality for the RCTs was variable and generally suboptimal. Effective strategies that addressed impaired mobility included the use of support surfaces, mattress overlays on operating tables, and specialized foam and specialized sheepskin overlays. While repositioning is a mainstay in most pressure ulcer prevention protocols, there is insufficient evidence to recommend specific turning regimens for patients with impaired mobility. In patients with nutritional impairments, dietary supplements may be beneficial. The incremental benefit of specific topical agents over simple moisturizers for patients with impaired skin health is unclear.



Given current evidence, using support surfaces, repositioning the patient, optimizing nutritional status, and moisturizing sacral skin are appropriate strategies to prevent pressure ulcers. Although a number of RCTs have evaluated preventive strategies for pressure ulcers, many of them had important methodological limitations. There is a need for well-designed RCTs that follow standard criteria for reporting nonpharmacological interventions and that provide data on cost-effectiveness for these interventions.
A regression model for predicting optimal purchase timing for airline tickets

Optimal timing for airline ticket purchasing from the consumer’s perspective is challenging principally because buyers have insufficient information for reasoning about future price movements. This paper presents a model for computing expected future prices and reasoning about the risk of price changes. The proposed model is used to predict the future expected minimum price of all available flights on specific routes and dates based on a corpus of historical price quotes. Also, we apply our model to predict prices of flights with specific desirable properties such as flights from a specific airline, non-stop only flights, or multi-segment flights. By comparing models with different target properties, buyers can determine the likely cost of their preferences. We present the expected costs of various preferences for two high-volume routes. Performance of the prediction models presented is achieved by including instances of time-delayed features, by imposing a class hierarchy among the raw features based on feature similarity, and by pruning the classes of features used in prediction based on in-situ performance. Our results show that purchase policy guidance using these models can lower the average cost of purchases in the 2 month period prior to a desired departure. The proposed method compares favorably with a deployed commercial web site providing similar purchase policy recommendations.
Privately Evaluating Decision Trees and Random Forests

Decision trees and random forests are common classifiers with widespread use. In this paper, we develop two protocols for privately evaluating decision trees and random forests. We operate in the standard two-party setting where the server holds a model (either a tree or a forest), and the client holds an input (a feature vector). At the conclusion of the protocol, the client learns only the model’s output on its input and a few generic parameters concerning the model; the server learns nothing. The first protocol we develop provides security against semi-honest adversaries. Next, we show an extension of the semi-honest protocol that obtains one-sided security against malicious adversaries. We implement both protocols and show that both variants are able to process trees with several hundred decision nodes in just a few seconds and a modest amount of bandwidth. Compared to previous semi-honest protocols for private decision tree evaluation, we demonstrate tenfold improvements in computation and bandwidth.
Wireless Power Transfer via Strongly Coupled Magnetic Resonance

The efficiency of an energy transferring system is the percentage of energy sent which reaches the destination. Sending energy through wires is often more efficient because wires represent a low loss way to confine and guide the energy to where it is needed. Still, generally, wireless energy transfer works very well at short range; and efficient long-distance transfer is possible if the transmitters and receivers are physically large, or if the energy can be formed into a tight beam. A great concern has been voiced in recent years over the extensive use of energy, the limited supply of resources, and the pollution of the environment from the use of present energy conversion systems. Electrical power accounts for much of the energy consumed. Much of this power is wasted during transmission from power plant generators to the consumer. The resistance of the wire used in the electrical grid distribution system causes a loss of 26-30% of the energy generated. This loss implies that our present system of electrical distribution is only 70-74% efficient. There are areas of the World where the need for electrical power exists. Yet there is no method for delivering power. Africa is in need of power to run pumps to tap into the vast resources of water under the Sahara Desert. Rural areas such as those in China require the electrical power necessary to bring them into the 20th Century and to equal standing with Western nations. Wireless power transmission (WPT) can be used for applications where either an instantaneous amount or a continuous delivery of energy is needed, but where conventional wires are unaffordable, inconvenient, expensive, hazardous, unwanted or impossible. The power can be transmitted using microwaves, millimeter waves or lasers. WPT is a technology that can transport power to locations, which are otherwise not possible or impractical to reach.The aim of this work is to identify the difficulties during wireless power transmission (WPT) and to propose suitable model for overcoming these difficulties. The main difficulty of WPT is the short range and low efficiency. Different aspects of strongly coupled magnetic resonance are analysed in this paper. The main parameters of self-resonance coil such as Quality factor, coupling co-efficient and Decay constant are optimised and a theoretical model is proposed. The model is also implemented practically
PM-Huber: PatchMatch with Huber Regularization for Stereo Matching

Most stereo correspondence algorithms match support windows at integer-valued disparities and assume a constant disparity value within the support window. The recently proposed Patch Match stereo algorithm by Bleyer et al. overcomes this limitation of previous algorithms by directly estimating planes. This work presents a method that integrates the Patch Match stereo algorithm into a variational smoothing formulation using quadratic relaxation. The resulting algorithm allows the explicit regularization of the disparity and normal gradients using the estimated plane parameters. Evaluation of our method in the Middlebury benchmark shows that our method outperforms the traditional integer-valued disparity strategy as well as the original algorithm and its variants in sub-pixel accurate disparity estimation.
Empathic Robots for Long-term Interaction - Evaluating Social Presence, Engagement and Perceived Support in Children

As a great number of robotic products are entering people’s lives, the question of how can they behave in order to sustain long-term interactions with users becomes increasingly more relevant. In this paper, we present an empathic model for social robots that aim to interact with children for extended periods of time. The application of this model to a scenario where a social robot plays chess with children is described. To evaluate the proposed model, we conducted a long-term study in an elementary school and measured children’s perception of social presence, engagement and social support.
Fast Model Predictive Control for Redistributive Lithium-Ion Battery Balancing

Energy storage systems with Lithium-ion batteries require balancing due to individual cells having manufacturing inconsistencies, different self-discharge rates, internal resistances, and temperature variations. Nondissipative redistributive balancing further improves on the pack capacity and efficiency over a dissipative approach where energy is consumed across shunt resistors. This paper presents a high-level fast model predictive control (MPC) in continuous time. The optimization problem uses performance metrics to balance the state of charge (SoC) in the battery pack. It is shown in simulation that MPC achieves a single point convergence of the SoC when compared against a common rule-based algorithm. This improves the efficiency of the power electronics and prolongs the life of each battery cell since frequent switching between charging and discharging of intermediate cells is avoided. Experimental results are presented to show a redistributive battery balancing system that achieves a balanced state in the minimum amount of time by coupling the fast MPC with microcontrollers available on todays market.
Dissociable prefrontal networks for cognitive and affective theory of mind: A lesion study

The underlying mechanisms and neuroanatomical correlates of theory of mind (ToM), the ability to make inferences on others' mental states, remain largely unknown. While numerous studies have implicated the ventromedial (VM) frontal lobes in ToM, recent findings have questioned the role of the prefrontal cortex. We designed two novel tasks that examined the hypothesis that affective ToM processing is distinct from that related to cognitive ToM and depends in part on separate anatomical substrates. The performance of patients with localized lesions in the VM was compared to responses of patients with dorsolateral lesions, mixed prefrontal lesions, and posterior lesions and with healthy control subjects. While controls made fewer errors on affective as compared to cognitive ToM conditions in both tasks, patients with VM damage showed a different trend. Furthermore, while affective ToM was mostly impaired by VM damage, cognitive ToM was mostly impaired by extensive prefrontal damage, suggesting that cognitive and affective mentalizing abilities are partly dissociable. By introducing the concept of 'affective ToM' to the study of social cognition, these results offer new insights into the mediating role of the VM in the affective facets of social behavior that may underlie the behavioral disturbances observed in these patients.
Technological Discontinuities and Organizational Environments

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