nils-herrmann/clean_scirepeval huggingface dataset:
SeaGlass: Enabling City-Wide IMSI-Catcher Detection

Cell-site simulators, also known as IMSIcatchers and stingrays, are used around the world by governments and criminals to track and eavesdrop on cell phones. Despite extensive public debate surrounding their use, few hard facts about them are available. For example, the richest sources of information on U.S. government cell-site simulator usage are from anonymous leaks, public records requests, and court proceedings. This lack of concrete information and the difficulty of independently obtaining such information hampers the public discussion. To address this deficiency, we build, deploy, and evaluate SeaGlass, a city-wide cellsite simulator detection network. SeaGlass consists of sensors that measure and upload data on the cellular environment to find the signatures of portable cell-site simulators. SeaGlass sensors are designed to be robust, low-maintenance, and deployable in vehicles for long durations. The data they generate is used to learn a city’s network properties to find anomalies consistent with cell-site simulators. We installed SeaGlass sensors into 15 ridesharing vehicles across two cities, collecting two months of data in each city. Using this data, we evaluate the system and show how SeaGlass can be used to detect signatures of portable cell-site simulators. Finally, we evaluate our signature detection methods and discuss anomalies discovered in the data.
Transformer-Less Converter Concept for a Grid-Connection of Thin-Film Photovoltaic Modules

A transformer-less converter concept for grid- connected photovoltaic systems is proposed that combines a DC/DC converter front-end with a DC/AC inverter. The converter system has an earth-connected DC input, as required from many thin-film photovoltaic modules. The DC/DC converter increases the positive photovoltaic DC-bus voltage by its negative DC output voltage to supply a grid-connected 3-phase inverter. This architecture extends today's power electronic converter topologies for thin-film photovoltaic modules considering their special requirements with the ambition to realize higher power conversion efficiencies at lower cost.
A CNN-based segmentation model for segmenting foreground by a probability map

This paper proposes a CNN-based segmentation model to segment foreground from an image and a prior probability map. Our model is constructed based on the FCN model that we simply replace the original RGB-based three channel input layer by a four channel, i.e., RGB and prior probability map. We then train the model by constructing various image, prior probability maps and the groundtruths from the PASCAL VOC dataset, and finally obtain a CNN-based foreground segmentation model that is suitable for general images. Our proposed method is motivated by the observation that the classical graphcut algorithm using GMM for modeling the priors can not capture the semantic segmentation from the prior probability, and thus leads to low segmentation performance. Furthermore, the efficient FCN segmentation model is for specific objects rather than general objects. We therefore improve the graph-cut like foreground segmentation by extending FCN segmentation model. We verify the proposed model by various prior probability maps such as artifical maps, saliency maps, and discriminative maps. The ICoseg dataset that is different from the PASCAL Voc dataset is used for the verification. Experimental results demonstrates the fact that our method obviously outperforms the graphcut algorithms and FCN models.
Thermoplastic Forming of Bulk Metallic Glass— A Technology for MEMS and Microstructure Fabrication

A technology for microelectromechanical systems (MEMS) and microstructure fabrication is introduced where the bulk metallic glass (BMG) is formed at a temperature where the BMG exist as a viscous liquid under an applied pressure into a mold. This thermoplastic forming is carried out under comparable forming pressure and temperatures that are used for plastics. The range of possible sizes in all three dimensions of this technology allows the replication of high strength features ranging from about 30 nm to centimeters with aspect ratios of 20 to 1, which are homogeneous and isotropic and free of stresses and porosity. Our processing method includes a hot-cutting technique that enables a clean planar separation of the parts from the BMG reservoir. It also allows to net-shape three-dimensional parts on the micron scale. The technology can be implemented into conventional MEMS fabrication processes. The properties of BMG as well as the thermoplastic formability enable new applications and performance improvements of existing MEMS devices and nanostructures
Theoretical frameworks and instruments for evaluation of critical thinking in nursing and education.

To identify theoretical frameworks and instruments for the evaluation of critical thinking to base studies in nursing and education.



Integrative review, with a selection of scientific articles in Portuguese, English and Spanish, in the LILACS, SCIELO, IBECS, MEDLINE/PubMed and SCOPUS databases, using the descriptors "thought", "teaching" and "nursing" in Portuguese and English. The search resulted in 3,147 articles, and 23 papers published between 2010 and 2015 were selected.



Fourteen (60.2%) studies used the Facione framework and eight (34.4%) resorted to different critical thinking assessment tools applied in nursing and education.



Most studies used the Facione framework. Among the evaluation tools, the California Critical Thinking Skills Test (CCTST) and the Watson-Glaser Critical Thinking Appraisal stood out as the most common instruments; both focus on cognitive skills in critical thinking.
Substrate Integrated Waveguide Quasi-Elliptic Filter Using Slot-Coupled and Microstrip-Line Cross-Coupled Structures

This paper proposes a quasi-elliptic filter with slot coupling and nonadjacent cross coupling based on the substrate integrated waveguide (SIW) cavity. The slots etched on the top metal plane of SIW cavity are used to produce electrical coupling, and the cross coupling is realized by the microstrip transmission line above the SIW cavity. The coupling strength is mainly controlled by the width and height of the slot. The length of the open-ended microstrip line controls the sign of the cross coupling. The cross coupling with different signs are used in the filter to produce a pair of transmission zeros (TZs) at both sides of the passband. In order to prove the validity, a fourth-order SIW quasi-elliptic filter with TZsat both sides of the passband is fabricated in a two-layer printed circuit board. The measured insertion loss at a center frequency of 3.7 GHz is 1.1 dB. The return loss within the passband is below -18 dB with a fractional bandwidth of 16%. The measured results are in good agreement with the simulated results.
Defending against sensor-sniffing attacks on mobile phones

Modern mobile phones possess three types of capabilities: computing, communication, and sensing. While these capabilities enable a variety of novel applications, they also raise serious privacy concerns. We explore the vulnerability where attackers snoop on users by sniffing on their mobile phone sensors, such as the microphone, camera, and GPS receiver. We show that current mobile phone platforms inadequately protect their users from this threat. To provide better privacy for mobile phone users, we analyze desirable uses of these sensors and discuss the properties of good privacy protection solutions. Then, we propose a general framework for such solutions and discuss various possible approaches to implement the framework's components.
Non invasive estimation of blood glucose using near infra red spectroscopy and double regression analysis

This paper presents a unique technique for noninvasive estimation of blood glucose concentration using near infra red spectroscopy. The spectroscopy has been performed at the second overtone of glucose which falls in the near infra red region. The near infra red spectroscopy has been performed using transmission photoplethsymography (PPG). The analog front end system has been implemented to get the PPG signal at the near infra red wavelengths of 1070nm, 950nm, 935nm. The PPG signal that has been obtained is processed and double regression analysis is carried out with the artificial neural network for estimating the glucose levels. The root mean square error of the prediction was 5.84mg/dL.
Schedulability Analysis Using Uppaal: Herschel-Planck Case Study

We propose a modeling framework for performing schedulability analysis by using Uppaal real-time model-checker . The framework is inspired by a case study where schedulability analysis of a satellite system is performed. The framework assumes a single CPU hardware where a fixed priority preemptive scheduler is used in a combination with two resource sharing protocols and in addition voluntary task suspension is considered. The contributions include the modeling framework, its application on an industrial case study and a comparison of results with classical response time analysis.
A unified framework of density-based clustering for semi-supervised classification

Semi-supervised classification is drawing increasing attention in the era of big data, as the gap between the abundance of cheap, automatically collected unlabeled data and the scarcity of labeled data that are laborious and expensive to obtain is dramatically increasing. In this paper, we introduce a unified framework for semi-supervised classification based on building-blocks from density-based clustering. This framework is not only efficient and effective, but it is also statistically sound. Experimental results on a large collection of datasets show the advantages of the proposed framework.
A novel integrated dielectric-and-conductive ink 3D printing technique for fabrication of microwave devices

In this work a novel combination of printed electronics using conductive nanoparticle ink together with 3D printing of dielectric material is presented as one integrated process. This allows fabrication of complicated 3D electromagnetic (EM) structures such as wide range of different antennas and microwave devices to simultaneously include printing of conductive nanoparticle ink within 3D dielectric configurations. Characterization of conductive ink and polymer based substrate has been done to ensure proper RF, electric, thermal and mechanical performance of both substrate and the ink. A meander line dipole antenna on a V-shaped substrate is printed and tested to demonstrate the efficiency and accuracy of proposed technique. The goal in this paper is to provide a low cost, environmentally friendly integrated process for the fabrication of geometrically complicated 3D electromagnetic structures.
Image Processing And Pattern Recognition Fundamentals And Techniques

It's coming again, the new collection that this site has. To complete your curiosity, we offer the favorite image processing and pattern recognition fundamentals and techniques book as the choice today. This is a book that will show you even new to old thing. Forget it; it will be right for you. Well, when you are really dying of image processing and pattern recognition fundamentals and techniques, just pick it. You know, this book is always making the fans to be dizzy if not to find.
Motivation and Second Language Acquisition 1

This paper posits four stages of language acquisition, identified as elemental, consolidation, conscious expression, and automaticity and thought, and considers the role of motivation in this process. It distinguishes between two types of motivation, language learning motivation and classroom motivation, indicating how these relate to two distinct contexts, the cultural and the educational through their influence on integrativeness and attitudes toward the learning situation. It discusses how the two types of motivation are differentially involved in the four stages, and empirical support for this perspective is presented in the form of path analyses of two samples of students from Catalonia.
Mediated parent-child contact in work-separated families

Parents and children in families living with regular separation due to work develop strategies to manage being apart. We interviewed 14 pairs of parents and children (ages 7 -- 13) from work-separated families to understand their experiences and the strategies that they use to keep their family together. Parents focus on combining scheduled synchronous and spontaneous asynchronous communication to maintain a constant presence in the life of the child. Children, on the other hand, focus on other sources of support, on other activities, and on the eventual reunion. Both the remote parent and the child rely heavily on a collocated adult to maintain aware-ness and contact. We compare work-separated families with other types of separation and highlight opportunities for new designs.
High codimensional bifurcation analysis to a six-neuron BAM neural network

In this article, the high codimension bifurcations of a six-neuron BAM neural network system with multiple delays are addressed. We first deduce the existence conditions under which the origin of the system is a Bogdanov–Takens singularity with multiplicities two or three. By choosing the connection coefficients as bifurcation parameters and using the formula derived from the normal form theory and the center manifold, the normal forms of Bogdanov–Takens and triple zero bifurcations are presented. Some numerical examples are shown to support our main results.
Does the Fragrance of Essential Oils Alleviate the Fatigue Induced by Exercise? A Biochemical Indicator Test in Rats

To study the effect of the essential oils of Citrus sinensis L., Mentha piperita L., Syzygium aromaticum L., and Rosmarinus officinalis L. on physical exhaustion in rats.



Forty-eight male Wistar rats were randomly divided into a control group, a fatigue group, an essential oil mixture (EOM) group, and a peppermint essential oil (PEO) group. Loaded swimming to exhaustion was used as the rat fatigue model. Two groups were nebulized with EOM and PEO after swimming, and the others were nebulized with distilled water. After continuous inhalation for 3 days, the swimming time, blood glucose, blood lactic acid (BLA), blood urea nitrogen (BUN), superoxide dismutase (SOD), glutathione peroxidase (GSH-PX), and malondialdehyde (MDA) in blood were determined.



While an increased time to exhaustion and SOD activity were apparent in both the EOM and PEO groups, the BLA and MDA were lower in both groups, in comparison with the fatigue group, and the changes in the EOM group were more dramatic. Additionally, the EOM group also showed marked changes of the rise of blood glucose and the decrease of BUN and GSH-PX.



The results suggested that the inhalation of an essential oil mixture could powerfully relieve exercise-induced fatigue.
A Liquid-to-Solid Phase Transition of the ALS Protein FUS Accelerated by Disease Mutation

Many proteins contain disordered regions of low-sequence complexity, which cause aging-associated diseases because they are prone to aggregate. Here, we study FUS, a prion-like protein containing intrinsically disordered domains associated with the neurodegenerative disease ALS. We show that, in cells, FUS forms liquid compartments at sites of DNA damage and in the cytoplasm upon stress. We confirm this by reconstituting liquid FUS compartments in vitro. Using an in vitro "aging" experiment, we demonstrate that liquid droplets of FUS protein convert with time from a liquid to an aggregated state, and this conversion is accelerated by patient-derived mutations. We conclude that the physiological role of FUS requires forming dynamic liquid-like compartments. We propose that liquid-like compartments carry the trade-off between functionality and risk of aggregation and that aberrant phase transitions within liquid-like compartments lie at the heart of ALS and, presumably, other age-related diseases.
Asymmetry-Aware Link Quality Services in Wireless Sensor Networks

Recent study in wireless sensor networks (WSN) has found that the irregular link quality is a common phenomenon. The irregular link quality, especially link asymmetry, has significant impacts on the design of WSN protocols, such as MAC protocols, neighborhood and topology discovery protocols, and routing protocols. In this paper, we propose asymmetryaware link quality services, including the neighborhood link quality service (NLQS) and the link relay service (LRS), to provide the timeliness link quality information of neighbors, and build a relay framework to alleviate effects of the link asymmetry. To demonstrate proposed link quality services, we design and implement two example applications, the shortest hops routing tree (SHRT) and the best path reliability routing tree (BRRT), in the TinyOS platform. To evaluate proposed link quality services, we have conducted both static analysis and simulation through the TOSSIM simulator, in terms of four performance metrics. We found that the performance of two example applications was improved substantially. More than 40% of nodes identify more outbound neighbors and the percentage of increased outbound neighbors is between 14% and 100%. In SHRT, more than 15% of nodes reduce hops of the routing tree and the percentage of reduced hops is between 14% and 100%. In BRRT, more than 16% of nodes improve the path reliability of the routing tree and the percentage of the improved path reliability is between 2% to 50%.
Skyline: an open source document editor for creating and analyzing targeted proteomics experiments

Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. It is open source and freely available for academic and commercial use. The Skyline user interface simplifies the development of mass spectrometer methods and the analysis of data from targeted proteomics experiments performed using selected reaction monitoring (SRM). Skyline supports using and creating MS/MS spectral libraries from a wide variety of sources to choose SRM filters and verify results based on previously observed ion trap data. Skyline exports transition lists to and imports the native output files from Agilent, Applied Biosystems, Thermo Fisher Scientific and Waters triple quadrupole instruments, seamlessly connecting mass spectrometer output back to the experimental design document. The fast and compact Skyline file format is easily shared, even for experiments requiring many sample injections. A rich array of graphs displays results and provides powerful tools for inspecting data integrity as data are acquired, helping instrument operators to identify problems early. The Skyline dynamic report designer exports tabular data from the Skyline document model for in-depth analysis with common statistical tools.


AVAILABILITY
Single-click, self-updating web installation is available at http://proteome.gs.washington.edu/software/skyline. This web site also provides access to instructional videos, a support board, an issues list and a link to the source code project.
Map-reduce-merge: simplified relational data processing on large clusters

Map-Reduce is a programming model that enables easy development of scalable parallel applications to process a vast amount of data on large clusters of commodity machines. Through a simple interface with two functions, map and reduce, this model facilitates parallel implementation of many real-world tasks such as data processing jobs for search engines and machine learning.
 However,this model does not directly support processing multiple related heterogeneous datasets. While processing relational data is a common need, this limitation causes difficulties and/or inefficiency when Map-Reduce is applied on relational operations like joins.
 We improve Map-Reduce into a new model called Map-Reduce-Merge. It adds to Map-Reduce a Merge phase that can efficiently merge data already partitioned and sorted (or hashed) by map and reduce modules. We also demonstrate that this new model can express relational algebra operators as well as implement several join algorithms.
NetSTAT: A Network-Based Intrusion Detection Approach

Network-based attacks have become common and sophisticated. For this reason, intrusion detection systems are now shifting their focus from the hosts and their operating systems to the network itself. Network-based intrusion detection is challenging because network auditing produces large amounts of data, and different events related to a single intrusion may be visible in different places on the network. This paper presents NetSTAT, a new approach to network intrusion detection. By using a formal model of both the network and the attacks, NetSTAT is able to determine which network events have to be monitored and where they can be monitored.
A 1.8-GHz CMOS Power Amplifier Using a Dual-Primary Transformer With Improved Efficiency in the Low Power Region

A 1.8-GHz CMOS power amplifier for a polar transmitter is implemented with a 0.18- RF CMOS process. The matching components, including the input and output transformers, were integrated. A dual-primary transformer is proposed in order to increase the efficiency in the low power region of the amplifier. The loss induced by the matching network for the low-output power region is minimized using the dual-primary transformer. The amplifier achieved a power-added efficiency of 40.7% at a maximum output power of 31.6 dBm. The dynamic range was 34 dB for a supply voltage that ranged from 0.5 to 3.3 V. The low power efficiency was 32% at the output power of 16 dBm.
Random Projection and Hashing

Random Projection is another class of methods used for low-rank matrix approximation. A random projection algorithm projects datapoints from a high-dimensional space R n onto a lower-dimensional subspace R r (r ⌧ n) using a random matrix S 2 R r⇥n. The key idea of random mapping comes from the Johnson-Lindenstrauss lemma[7] (we will explain later in detail) that says " if points in a vector space are projected onto a randomly selected subspace of suitably high dimension, then the distances between points are approximately preserved ". Random projection methods are computationally efficient and sufficiently accurate in practice for dimen-sionality reduction of high-dimensional datasets. Moreover, since complexity of many geometric algorithms depends significantly on the dimension, applying random projection as pre-processing is a common task in many data mining applications. As opposed to column sampling methods, that need to access data for approximating the low-rank subspace, random projections are data oblivious, as their computation involves only a random matrix S. We start with the basic concepts and definitions required to understand random projections techniques. Definition 1 (Column Space). Consider a matrix A 2 R n⇥d (n > d). Notice that as one ranges over all vectors x 2 R d , Ax ranges over all linear combinations of the columns of A and therefore defines a d-dimensional subspace of R n , which we refer to as the column space of A and denote it by C(A). Definition 2 (` 2-Subspace Embedding). A matrix S 2 R r⇥n provides a subspace embedding for C(A) if kSAxk 2 2 = (1 ± ")kAxk 2 2 , 8x 2 R d. Such matrix S provides a low distortion embedding, and is called a (1 ± ") ` 2-subspace embedding. Using an`2-subspace embedding, one can work with SA 2 R r⇥d instead of A 2 R n⇥d. Typically r ⌧ n, so we are working with a smaller matrix that reduces the time/space complexity of many algorithms. However note that definitely r needs to be larger than d if we are talking about the whole subspace R d [11]. Note that subspace embedding does not depend on a particular basis for C(A), that means if we have a matrix U that is an orthonormal basis for C(A), then Ux gives the same subspace as Ax. Therefore if S is an embedding for A, it will be an embedding for U too. Let's consider …