nils-herrmann/clean_scirepeval huggingface dataset:
An Augmented Reality X-Ray system based on visual saliency

In the past, several systems have been presented that enable users to view occluded points of interest using Augmented Reality X-ray visualizations. It is challenging to design a visualization that provides correct occlusions between occluder and occluded objects while maximizing legibility. We have previously published an Augmented Reality X-ray visualization that renders edges of the occluder region over the occluded region to facilitate correct occlusions while providing foreground context. While this approach is simple and works in a wide range of situations, it provides only minimal context of the occluder object.
Estimating vigilance level by using EEG and EMG signals

We developed a new method for estimation of vigilance level by using both EEG and EMG signals recorded during transition from wakefulness to sleep. Previous studies used only EEG signals for estimating the vigilance levels. In this study, it was aimed to estimate vigilance level by using both EEG and EMG signals for increasing the accuracy of the estimation rate. In our work, EEG and EMG signals were obtained from 30 subjects. In data preparation stage, EEG signals were separated to its subbands using wavelet transform for efficient discrimination, and chin EMG was used to verify and eliminate the movement artifacts. The changes in EEG and EMG were diagnosed while transition from wakefulness to sleep by using developed artificial neural network (ANN). Training and testing data sets consist of the subbanded components of EEG and power density of EMG signals were applied to the ANN for training and testing the system which gives three situations for the vigilance level of the subject: awake, drowsy, and sleep. The accuracy of estimation was about 98–99% while the accuracy of the previous study, which uses only EEG, was 95–96%.
Beyond Self-Management : Antecedents and Consequences of Team Empowerment

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Fine-Grained Access Control System Based on Outsourced Attribute-Based Encryption

As cloud computing becomes prevalent, more and more sensitive data is being centralized into the cloud for sharing, which brings forth new challenges for outsourced data security and privacy. Attributebased encryption (ABE) is a promising cryptographic primitive, which has been widely applied to design fine-grained access control system recently. However, ABE is being criticized for its high scheme overhead as the computational cost grows with the complexity of the access formula. This disadvantage becomes more serious for mobile devices because they have constrained computing resources. Aiming at tackling the challenge above, we present a generic and efficient solution to implement attribute-based access control system by introducing secure outsourcing techniques into ABE. More precisely, two cloud service providers (CSPs), namely key generation-cloud service provider (KG-CSP) and decryption-cloud service provider (D-CSP) are introduced to perform the outsourced key-issuing and decryption on behalf of attribute authority and users respectively. In order to outsource heavy computation to both CSPs without private information leakage, we formulize an underlying primitive called outsourced ABE (OABE) and propose several constructions with outsourced decryption and keyissuing. Finally, extensive experiment demonstrates that with the help of KG-CSP and D-CSP, efficient key-issuing and decryption are achieved in our constructions.
New zero-voltage-switching phase-shift full-bridge converter with low conduction losses

A new zero-voltage-switching (ZVS) phase-shift full-bridge (PSFB) converter with low conduction losses is proposed. It is based on the PSFB converter with series-connected two transformers, which features wide ZVS ranges. By adding a capacitor, the proposed converter overcomes the disadvantage of the based converter, such as the high circulating energy. Furthermore, the turns ratio of the transformers can be increased as well. Therefore, high efficiency of the proposed converter can be achieved. Operational principles and experimental results for a 100-W (5 V, 20 A) prototype are presented to validate the proposed converter.
Single-Pedestrian Detection Aided by Two-Pedestrian Detection

In this paper, we address the challenging problem of detecting pedestrians who appear in groups. A new approach is proposed for single-pedestrian detection aided by two-pedestrian detection. A mixture model of two-pedestrian detectors is designed to capture the unique visual cues which are formed by nearby pedestrians but cannot be captured by single-pedestrian detectors. A probabilistic framework is proposed to model the relationship between the configurations estimated by single- and two-pedestrian detectors, and to refine the single-pedestrian detection result using two-pedestrian detection. The two-pedestrian detector can integrate with any single-pedestrian detector. Twenty-five state-of-the-art single-pedestrian detection approaches are combined with the two-pedestrian detector on three widely used public datasets: Caltech, TUD-Brussels, and ETH. Experimental results show that our framework improves all these approaches. The average improvement is <inline-formula><tex-math>$9$</tex-math><alternatives> <inline-graphic xlink:type="simple" xlink:href="ouyang-ieq1-2377734.gif"/></alternatives></inline-formula> percent on the Caltech-Test dataset, <inline-formula><tex-math>$11$</tex-math><alternatives><inline-graphic xlink:type="simple" xlink:href="ouyang-ieq2-2377734.gif"/> </alternatives></inline-formula> percent on the TUD-Brussels dataset and <inline-formula><tex-math>$17$</tex-math> <alternatives><inline-graphic xlink:type="simple" xlink:href="ouyang-ieq3-2377734.gif"/></alternatives></inline-formula> percent on the ETH dataset in terms of average miss rate. The lowest average miss rate is reduced from <inline-formula><tex-math>$37$ </tex-math><alternatives><inline-graphic xlink:type="simple" xlink:href="ouyang-ieq4-2377734.gif"/></alternatives></inline-formula> to percent on the Caltech-Test dataset, from <inline-formula><tex-math>$55$</tex-math></inline-formula> to <inline-formula><tex-math>$50$</tex-math><alternatives><inline-graphic xlink:type="simple" xlink:href="ouyang-ieq6-2377734.gif"/> </alternatives></inline-formula> percent on the TUD-Brussels dataset and from <inline-formula><tex-math>$43$</tex-math> <alternatives><inline-graphic xlink:type="simple" xlink:href="ouyang-ieq7-2377734.gif"/></alternatives></inline-formula> to <inline-formula> <tex-math>$38$</tex-math><alternatives><inline-graphic xlink:type="simple" xlink:href="ouyang-ieq8-2377734.gif"/></alternatives> </inline-formula> percent on the ETH dataset.
Constructing a theory of the triple typology: Some (second) thoughts on nomothetic and idiographic approaches to personality.

Our fundamental scientific task is to convert observations of particular persons behaving in particular ways in particular situations into assertions that certain kinds of persons will behave in certain kinds of ways in certain kinds of situations, that is, to construct triple typologies or equivalence classes-of persons, of behaviors, and of situations-and to fashion theories of personality that relate these equivalence classes to one another. It is argued that the different approaches to the study of personality are distinguished from one another not by whether they are idiographic or nomothetic but by the strategies they employ for constructing-or ignoring-each of these three types of equivalence classes. The likely attributes of a successful interactional theory of personality-one that would embrace the entire triple typology-are proposed and discussed.
Automatic Nuclei Segmentation in H&E Stained Breast Cancer Histopathology Images

The introduction of fast digital slide scanners that provide whole slide images has led to a revival of interest in image analysis applications in pathology. Segmentation of cells and nuclei is an important first step towards automatic analysis of digitized microscopy images. We therefore developed an automated nuclei segmentation method that works with hematoxylin and eosin (H&E) stained breast cancer histopathology images, which represent regions of whole digital slides. The procedure can be divided into four main steps: 1) pre-processing with color unmixing and morphological operators, 2) marker-controlled watershed segmentation at multiple scales and with different markers, 3) post-processing for rejection of false regions and 4) merging of the results from multiple scales. The procedure was developed on a set of 21 breast cancer cases (subset A) and tested on a separate validation set of 18 cases (subset B). The evaluation was done in terms of both detection accuracy (sensitivity and positive predictive value) and segmentation accuracy (Dice coefficient). The mean estimated sensitivity for subset A was 0.875 (±0.092) and for subset B 0.853 (±0.077). The mean estimated positive predictive value was 0.904 (±0.075) and 0.886 (±0.069) for subsets A and B, respectively. For both subsets, the distribution of the Dice coefficients had a high peak around 0.9, with the vast majority of segmentations having values larger than 0.8.
Design of single-ridge SIW power dividers with over 75% bandwidth

Waveguide structures have a constrained bandwidth due to their cutoff frequencies and presence of higher order modes. Ridged substrate integrated waveguides (RSIW) are low profile, low cost and planar that can be designed for wider bandwidth. In this paper, a two-way power divider based on RSIW is designed to extend bandwidth beyond that of conventional guides. The design utilizes a developed low loss GCPW to RSIW transition to feed the structure. Design was successfully extended to eight way splitter as well. The developed divider has almost a 75% bandwidth with better than 15dB return loss from 5 to 11 GHz. In particular, the splitter demonstrated excellent amplitude and phase imbalance of less than ±0.35 dB and ±7° within 5.5 to 9 GHz, respectively. Theoretical and experimental results are in good agreement.
Teachers ' Beliefs and Educational Research : Cleaning up a Messy Construct

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The 2017 DAVIS Challenge on Video Object Segmentation

We present the 2017 DAVIS Challenge, a public competition specifically designed for the task of video object segmentation. Following the footsteps of other successful initiatives, such as ILSVRC  and PASCAL VOC , which established the avenue of research in the fields of scene classification and semantic segmentation, the DAVIS Challenge comprises a dataset, an evaluation methodology, and a public competition with a dedicated workshop co-located with CVPR 2017. The DAVIS Challenge follows up on the recent publication of DAVIS (Densely-Annotated VIdeo Segmentation ), which has fostered the development of several novel state-of-the-art video object segmentation techniques. In this paper we describe the scope of the benchmark, highlight the main characteristics of the dataset and define the evaluation metrics of the competition.
GREEN MARKETING , PUBLIC POLICY AND MANAGERIAL STRATEGIES

Green marketing subsumes greening products as well as greening firms. In addition to manipulating the 4Ps (product, price, place and promotion) of the traditional marketing mix, it requires a careful understanding of public policy processes. This paper focuses primarily on promoting products by employing claims about their environmental attributes or about firms that manufacture and/or sell them. Secondarily, it focuses on product and pricing issues. Drawing on multiple literatures, it examines issues such as what needs to be greened (products, systems or processes), why consumers purchase/do not purchase green products and how firms should think about information disclosure strategies on environmental claims.
Implanted antennas inside a human body: simulations, designs, and characterizations

Antennas implanted in a human body are largely applicable to hyperthermia and biotelemetry. To make practical use of antennas inside a human body, resonance characteristics of the implanted antennas and their radiation signature outside the body must be evaluated through numerical analysis and measurement setup. Most importantly, the antenna must be designed with an in-depth consideration given to its surrounding environment. In this paper, the spherical dyadic Green's function (DGF) expansions and finite-difference time-domain (FDTD) code are applied to analyze the electromagnetic characteristics of dipole antennas and low-profile patch antennas implanted in the human head and body. All studies to characterize and design the implanted antennas are performed at the biomedical frequency band of 402-405 MHz. By comparing the results from two numerical methodologies, the accuracy of the spherical DGF application for a dipole antenna at the center of the head is evaluated. We also consider how much impact a shoulder has on the performance of the dipole inside the head using FDTD. For the ease of the design of implanted low-profile antennas, simplified planar geometries based on a real human body are proposed. Two types of low-profile antennas, i.e., a spiral microstrip antenna and a planar inverted-F antenna, with superstrate dielectric layers are initially designed for medical devices implanted in the chest of the human body using FDTD simulations. The radiation performances of the designed low-profile antennas are estimated in terms of radiation patterns, radiation efficiency, and specific absorption rate. Maximum available power calculated to characterize the performance of a communication link between the designed antennas and an exterior antenna show how sensitive receivers are required to build a reliable telemetry link.
Design and Optimization of Neodymium-Free SPOKE-Type Motor With Segmented Wing-Shaped PM

This paper proposes a new design of SPOKE-type PM brushless direct current (BLDC) motor without using neodymium PM (Nd-PM). The proposed model has an improved output characteristic as it uses the properties of the magnetic flux effect of the SPOKE-type motor with an additional pushing assistant magnet and subassistant magnet in the shape of spoke. In this paper, ferrite PM (Fe-PM) is used instead of Nd-PM. First, the air-gap flux density and backelectromotive force (BEMF) are obtained based on the field model. Second, the analytical expressions of magnet field strength and magnet flux density are obtained in the air gap produced by Fe-PM. The developed analytical model is obtained by solving the magnetic scalar potential. Finally, the air-gap field distribution and BEMF of SPOKE-type motor are analyzed. The analysis works for internal rotor motor topologies. This paper validates results of the analytical model by finite-element analysis for wing-shaped SPOKE-type BLDC motors.
Microcontroller Based PWM Controlled Four Switch Three Phase Inverter Fed Induction Motor Drive

This paper presents PIC microcontroller based PWM inverter controlled four switch three phase inverter (FSTPI) fed Induction Motor drive. The advantage of this inverter that uses of 4 switches instead of conventional 6 switches is lesser switching losses, lower electromagnetic interference (EMI), less complexity of control algorithms and reduced interface circuits. Simulation and experimental work are carried out and results presented to demonstrate the feasibility of the proposed approach. Simulation is carried out using MATLAB SIMULINK and in the experimental work a prototype model is built to verify the simulation results. PIC microcontroller (PIC 16F877A) is used to generate the PWM pulses for FSTPI to drive the 0.5 hp 3-phase Induction Motor.
An open source tool for simulation and supervision of underwater intervention missions

This paper presents UWSim: a new software tool for visualization and simulation of underwater robotic missions. The software visualizes an underwater virtual scenario that can be configured using standard modeling software. Controllable underwater vehicles, surface vessels and robotic manipulators, as well as simulated sensors, can be added to the scene and accessed externally through network interfaces. This allows to easily integrate the simulation and visualization tool with existing control architectures, thus allowing hardware-in-the-loop simulations (HIL). UWSim has been successfully used for simulating the logics of underwater intervention missions and for reproducing real missions from the captured logs. The software is offered as open source, thus filling a gap in the underwater robotics community, where commercial simulators oriented to ROV pilot training predominate.
SGRank: Combining Statistical and Graphical Methods to Improve the State of the Art in Unsupervised Keyphrase Extraction

Keyphrase extraction is a fundamental technique in natural language processing. It enables documents to be mapped to a concise set of phrases that can be used for indexing, clustering, ontology building, auto-tagging and other information organization schemes. Two major families of unsupervised keyphrase extraction algorithms may be characterized as statistical and graph-based. We present a hybrid statistical-graphical algorithm that capitalizes on the heuristics of both families of algorithms and is able to outperform the state of the art in unsupervised keyphrase extraction on several datasets.
Bridging value modelling to ArchiMate via transaction modelling

The ArchiMate modelling language provides a coherent and a holistic view of an enterprise in terms of its products, services, business processes, actors, business units, software applications and more. Yet, ArchiMate currently lacks (1) expressivity in modelling an enterprise from a value exchange perspective, and (2) rigour and guidelines in modelling business processes that realize the transactions relevant from a value perspective. To address these issues, we show how to connect e $$^{3}$$ value, a technique for value modelling, to ArchiMate via transaction patterns from the DEMO methodology. Using ontology alignment techniques, we show a transformation between the meta models underlying e $$^{3}$$ value, DEMO and ArchiMate. Furthermore, we present a step-wise approach that shows how this model transformation is achieved and, in doing so, we also show the of such a transformation. We exemplify the transformation of DEMO and e $$^{3}$$ value into ArchiMate by means of a case study in the insurance industry. As a proof of concept, we present a software tool supporting our transformation approach. Finally, we discuss the functionalities and limitations of our approach; thereby, we analyze its and practical applicability.
Learned Spectral Super-Resolution

We describe a novel method for blind, single-image spectral super-resolution. While conventional superresolution aims to increase the spatial resolution of an input image, our goal is to spectrally enhance the input, i.e., generate an image with the same spatial resolution, but a greatly increased number of narrow (hyper-spectral) wavelength bands. Just like the spatial statistics of natural images has rich structure, which one can exploit as prior to predict high-frequency content from a low resolution image, the same is also true in the spectral domain: the materials and lighting conditions of the observed world induce structure in the spectrum of wavelengths observed at a given pixel. Surprisingly, very little work exists that attempts to use this diagnosis and achieve blind spectral super-resolution from single images. We start from the conjecture that, just like in the spatial domain, we can learn the statistics of natural image spectra, and with its help generate finely resolved hyper-spectral images from RGB input. Technically, we follow the current best practice and implement a convolutional neural network (CNN), which is trained to carry out the end-to-end mapping from an entire RGB image to the corresponding hyperspectral image of equal size. We demonstrate spectral super-resolution both for conventional RGB images and for multi-spectral satellite data, outperforming the state-of-the-art.
Security Improvement for Management Frames in IEEE 802.11 Wireless Networks

has gained popularity. WLANs use different security protocols like WEP, WPA and WPA2. The newly ratified WPA2 provides the highest level of security for data frames. However WPA2 does not really mention about protection of management frames. In other words IEEE 802.11 management frames are always sent in an unsecured manner. In fact the only security mechanism for management frames is CRC-32 bit algorithm. While useful for unintentional error detection, CRC-32 bit is not safe to completely verify data integrity in the face of intentional modifications. Therefore an unsecured management frame allows an attacker to start different kinds of attack. This paper proposes a new model to address these security problems in management frames. First we summarize security threats on management frames and their influences in WLANs. Then based on these security threats, we propose a new per frames security model to provide efficient security for these frames. Finally simulation methodology is presented and results are provided. Mathematical probabilities are discussed to demonstrate that the proposed security model is robust and efficient to secure management frames.