nils-herrmann/clean_scirepeval huggingface dataset:
Modeling, simulation and control of single actuator magnetic levitation system

This paper aims at Design, Fabrication and Control of a single actuator magnetic levitation system. A physical design model of Magnetic Levitation System have been presented at the initial phase. Modeling and Simulation of this non-linear magnetic levitation system is proposed with feedback linearization where a non linear state space transformation is used to linearize the system exactly. After this, experimental setup and construction of actual magnetic levitation system is presented. Experimental Levitation data is collected and compared to the theory. Magnetic levitation system considered in this study is taken as a neodymium magnet suspended in a voltage controlled magnetic field. Dynamic behavior of the system was modeled by the study of electromagnetic and mechanical subsystems. State space model was derived from the system equations. For high accuracy in position detection, Hall effect sensor SS49E was utilized. The successful operation of this system was obtained using relatively cheaper and simpler magnetic levitation subsystems and components.
Novel Concept of the Three-Dimensional Vertical FG nand Flash Memory Using the Separated-Sidewall Control Gate

Recently, we proposed a novel 3-D vertical floating gate (FG)-type nand Flash memory cell array using the separated-sidewall control gate (CG) (S-SCG). This novel cell consists of one cylindrical FG with line-type CG and S-SCG structures. For simplifying the process flow, we realized the common S-SCG lines by using the prestacked polysilicon layer, through which variable medium voltages are applied not only to control the electrically inverted S/D region but also to assist the program and erase operations. In this paper, we successfully demonstrate the normal Flash cell operation and show its superior performances in comparison with the recent 3-D FG nand cells by using the cylindrical device simulation. It is shown that the proposed cell can realize the highest CG coupling ratio, low-voltage cell operations of program with 15 V at Vth = 4V and erase with 14 V at Vth = -3V , good retention-mode electric field, and sufficient read-mode on-current margin. Moreover, the proposed S-SCG cell array can fully suppress both the interference effects and the disturbance problems at the same time by removing the direct coupling effects in the same cell string, which are the most critical problems of the recent 3-D vertical stacked cell structures. Above all, the proposed cell array has good potential for terabit 3-D vertical nand Flash cell array with highly reliable multilevel cell operation.
Cultural adaptation and validation of the Health Literacy Questionnaire (HLQ): robust nine-dimension Danish language confirmatory factor model

Health literacy is an important construct in population health and healthcare requiring rigorous measurement. The Health Literacy Questionnaire (HLQ), with nine scales, measures a broad perception of health literacy. This study aimed to adapt the HLQ to the Danish setting, and to examine the factor structure, homogeneity, reliability and discriminant validity. The HLQ was adapted using forward-backward translation, consensus conference and cognitive interviews (n = 15). Psychometric properties were examined based on data collected by face-to-face interview (n = 481). Tests included difficulty level, composite scale reliability and confirmatory factor analysis (CFA). Cognitive testing revealed that only minor re-wording was required. The easiest scale to respond to positively was 'Social support for health', and the hardest were 'Navigating the healthcare system' and 'Appraisal of health information'. CFA of the individual scales showed acceptably high loadings (range 0.49-0.93). CFA fit statistics after including correlated residuals were good for seven scales, acceptable for one. Composite reliability and Cronbach's α were >0.8 for all but one scale. A nine-factor CFA model was fitted to items with no cross-loadings or correlated residuals allowed. Given this restricted model, the fit was satisfactory. The HLQ appears robust for its intended application of assessing health literacy in a range of settings. Further work is required to demonstrate sensitivity to measure changes.
Approximation algorithms for data placement in arbitrary networks

We study approximation algorithms for placing replicated data in arbitrary networks. Consider a network of nodes with individual storage capacities and a metric communication cost function, in which each node periodically issues a request for an object drawn from a collection of uniform-length objects. We consider the problem of placing copies of the objects among the nodes such that the average access cost is minimized. Our main result is a polynomial-time constant-factor approximation algorithm for this placement problem. Our algorithm is based on a careful rounding of a linear programming relaxation of the problem. We also show that the data placement problem is MAXSNP-hard.
We extend our approximation result to a generalization of the data placement problem that models additional costs such as the cost of realizing the placement. We also show that when object lengths are non-uniform, a constant-factor approximation is achievable if the capacity at each node in the approximate solution is allowed to exceed that in the optimal solution by the length of the largest object.
Synergy-Driven Performance Enhancement of Vision-Based 3D Hand Pose Reconstruction

In this work we propose, for the first time, to improve the performance of a Hand Pose Reconstruction (HPR) technique from RGBD camera data, which is affected by self-occlusions, leveraging upon postural synergy information, i.e., a priori information on how human most commonly use and shape their hands in everyday life tasks. More specifically, in our approach, we ignore joint angle values estimated with low confidence through a vision-based HPR technique and fuse synergistic information with such incomplete measures. Preliminary experiments are reported showing the effectiveness of the proposed integration.
Systematic literature reviews in software engineering - A systematic literature review

In 2004 the concept of evidence-based software engineering (EBSE) was introduced at the ICSE04 conference.  This study assesses the impact of systematic literature reviews (SLRs) which are the recommended EBSE method for aggregating evidence.  We used the standard systematic literature review method employing a manual search of 10 journals and 4 conference proceedings.  Of 20 relevant studies, eight addressed research trends rather than technique evaluation. Seven SLRs addressed cost estimation. The quality of SLRs was fair with only three scoring less than 2 out of 4.  Currently, the topic areas covered by SLRs are limited. European researchers, particularly those at the Simula Laboratory appear to be the leading exponents of systematic literature reviews. The series of cost estimation SLRs demonstrate the potential value of EBSE for synthesising evidence and making it available to practitioners. ! 2008 Elsevier B.V. All rights reserved.
Overview of Generative Software Development

System family engineering seeks to exploit the commonalities among systems from a given problem domain while managing the variabilities among them in a systematic way. In system family engineering, new system variants can be rapidly created based on a set of reusable assets (such as a common architecture, components, models, etc.). Generative software development aims at modeling and implementing system families in such a way that a given system can be automatically generated from a specification written in one or more textual or graphical domainspecific languages. This paper gives an overview of the basic concepts and ideas of generative software development including DSLs, domain and application engineering, generative domain models, networks of domains, and technology projections. The paper also discusses the relationship of generative software development to other emerging areas such as Model Driven Development and Aspect-Oriented Software Development.
Cognitive Consequences of Trilingualism.

The objectives of the present research were to examine the cognitive consequences of trilingualism and explain them relative to the cognitive consequences of bilingualism.



A comparison of cognitive abilities in trilinguals and bilinguals was conducted. In addition, we proposed a cognitive plasticity framework to account for cognitive differences and similarities between trilinguals and bilinguals.



Three aspects of cognition were analyzed: (1) cognitive reserve in older adults, as measured by age of onset of Alzheimer's disease and mild cognitive impairment; (2) inhibitory control in children and younger adults, as measured by response times on behavioral Simon and flanker tasks; and (3) memory generalization in infants and toddlers, as measured by accuracy on behavioral deferred imitation tasks. Results were considered within a framework of cognitive plasticity, which took into account several factors that may affect plasticity, including the age of learning a third language and the extent to which additional cognitive resources are needed to learn the third language.



A mixed pattern of results was observed. In some cases, such as cognitive reserve in older adults, trilinguals showed larger advantages than bilinguals. On other measures, for example inhibitory control in children and younger adults, trilinguals were found to exhibit the same advantages as bilinguals. In still other cases, like memory generalization in infants and toddlers, trilinguals did not demonstrate the advantages seen in bilinguals.



This study is the first comprehensive analysis of how learning a third language affects the cognitive abilities that are modified by bilingual experience, and the first to propose a cognitive plasticity framework that can explain and predict trilingual-bilingual differences.



This research shows that the cognitive consequences of trilingualism are not simply an extension of bilingualism's effects; rather, trilingualism has distinct consequences, with theoretical implications for our understanding of linguistic and cognitive processes and their plasticity, as well as applied-science implications for using second and third language learning in educational and rehabilitative contexts to foster successful cognitive development and aging.
Fast and High Quality Illustration of Skinned Meshes in Image Space

Line drawings are widely used in conveying shape and meaning for a broad range of objects with a minimum visual representation of a scene. As for large scale animated skinned meshes, efficiency and the quality of surface deformation matters the most. Although image space method is much more efficient than the other line drawing method, i.e. object space method, it's precision on the line extraction is easily affected by noise on the rendered image. This paper provides a new illustration technique to get a well-depicted shaded model in image space which is suitable for large scale skin meshes. We firstly provide an efficient and robust algorithm to recover normals of skinned meshes. Then we apply a L0 gradient minimization to the deformed shading mesh before the suggestive contour detection in image space. The experimental results reveal that our method can illustrate large scale animated models with both accuracy and high-efficiency.
Multiclass Classification of Driver Perceived Workload Using Long Short-Term Memory based Recurrent Neural Network

Human sensing enables intelligent vehicles to provide driver-adaptive support by classifying perceived workload into multiple levels. Objective of this study is to classify driver workload associated with traffic complexity into five levels. We conducted driving experiments in systematically varied traffic complexity levels in a simulator. We recorded driver physiological signals including electrocardiography, electrodermal activity, and electroencephalography. In addition, we integrated driver performance and subjective workload measures. Deep learning based models outperform statistical machine learning methods when dealing with dynamic time-series data with variable sequence lengths. We show that our long short-term memory based recurrent neural network model can classify driver perceived-workload into five classes with an accuracy of 74.5%. Since perceived workload differ between individual drivers for the same traffic situation, our results further highlight the significance of including driver characteristics such as driving style and workload sensitivity to achieve higher classification accuracy.
A combined pose, object, and feature model for action understanding

Understanding natural human activity involves not only identifying the action being performed, but also locating the semantic elements of the scene and describing the person's interaction with them. We present a system that is able to recognize complex, fine-grained human actions involving the manipulation of objects in realistic action sequences. Our method takes advantage of recent advances in sensors and pose trackers in learning an action model that draws on successful discriminative techniques while explicitly modeling both pose trajectories and object manipulations. By combining these elements in a single model, we are able to simultaneously recognize actions and track the location and manipulation of objects. To showcase this ability, we introduce a novel Cooking Action Dataset that contains video, depth readings, and pose tracks from a Kinect sensor. We show that our model outperforms existing state of the art techniques on this dataset as well as the VISINT dataset with only video sequences.
Augmenting photographs with textures using the Laplacian pyramid

We introduce a method to stylize photographs with auxiliary textures, by means of the Laplacian pyramid. Laplacian pyramid coefficients from a synthetic texture are combined with the coefficients from the original image by means of a smooth maximum function. The final result is a stylized image which maintains the structural characteristics from the input, including edges, color, and existing texture, while enhancing the image with additional fine-scale details. Further, we extend patch-based texture synthesis to include a guidance channel so that texture structures are aligned with an orientation field, obtained through the image structure tensor.
Self-Regulation , Ego Depletion , and Motivation

Motivation is underappreciated in self-regulation theories (as is true in social personality psychology at large). This paper reviews the role of motivation in the context of the strength, or limited-resource, model of self-control in several domains. Sacrificing one desire in order to pursue another is more difficult when the incipient response is strongly motivated, a notion that highlights the struggle between urges and restraints. A reduction in ego resources can be temporarily overcome by strong motivation – nevertheless, ego depletion is not solely a loss of motivation: Recent experiments indicate that regulatory resources are rooted in physical energy stores. Motivational conflicts, especially the clash between selfish motives and behaviors that promote social acceptance, set the stage for the necessity of self-regulation and the circumstances in which ego depletion is most likely. Self-regulation is the self ’s capacity for altering its behaviors. It greatly increases the flexibility and adaptability of human behavior, enabling people to adjust their actions to a remarkably broad range of social and situational demands. It is an important basis for the popular conception of free will and for socially desirable behavior. It provides benefits to the individual and to society, and indeed good self-control seems to contribute to a great many desirable outcomes, including task performance, school and work success, popularity, mental health and adjustment, and good interpersonal relationships (Baumeister, Heatherton, & Tice, 1994; Duckworth & Seligman, 2005; Mischel, Shoda, & Peake, 1988; Shoda, Mischel, & Peake, 1990; Tangney, Baumeister, & Boone, 2004;Wolfe & Johnson, 1995). Motivation is underappreciated in psychology generally, no doubt partly because the cognitive revolution of recent decades has induced the majority of researchers to think in cognitive rather than motivational terms. ’s role in self-regulation has been similarly underestimated. This article seeks to remedy that deficiency. It will examine the multiple ways that motivation is relevant to self-regulation. The relevance to self-regulation spans a wide range, from the confluence of motivation and self-regulation (as in the motivation to engage in self-regulation) to their conflict (as when self-regulation is used to restrain motivation).
Nasal bone length, prenasal thickness, prenasal thickness-to-nasal bone length ratio and prefrontal space ratio in second- and third-trimester fetuses with Down syndrome.

To evaluate nasal bone length (NBL), prenasal thickness (PT), prenasal thickness-to-nasal bone length (PT-NBL) ratio and prefrontal space ratio (PFSR) as markers for Down syndrome in the second and third trimesters.



NBL, PT, PT-NBL ratio and PFSR were measured retrospectively in stored two-dimensional images or three-dimensional volumes (corrected to the mid-sagittal plane) of fetuses with Down syndrome, which were retrieved from the digital databases of participating units. Measurements were performed on the stored images and volumes by two experienced operators, and the values obtained were compared to our previously reported normal ranges for euploid fetuses in order to assess the detection rates for Down syndrome.



A total of 159 fetuses with Down syndrome were included in the analysis, six of which were excluded because of inadequate available images. Median maternal age was 36.0 years and median gestational age was 23 + 1 weeks. NBL and PT were correlated with gestational age (P < 0.001), but the PT-NBL ratio and PFSR were not. Mean NBL, PT, PT-NBL ratio and PFSR were 4.42 mm, 5.56 mm, 1.26 and 0.34, respectively. The nasal bone was absent in 23 (15.4%) cases. As a marker for Down syndrome, the PT-NBL ratio yielded the highest detection rate (86.2%), followed by PFSR (79.7%), PT (63.4%) and NBL (61.9%). All markers were abnormal in 33.6% of cases, whilst all were normal in 4.7%. At least one of the four markers was abnormal in 95.3%, and either the PT-NBL ratio or PFSR was abnormal in 93.8%. Detection rates were not related to gestational age.



The PT-NBL ratio and PFSR are robust second- and third-trimester markers for Down syndrome. Both provide high detection rates and are easy to use, as the cut-off for normality is constant throughout gestation.
Paper-Based Inkjet-Printed Tri-Band U-Slot Monopole Antenna for Wireless Applications

Realization of a U-slot tri-band monopole antenna on a low-cost paper substrate using inkjet-printed technology is presented for the first time. The U-shaped slot is optimized to enhance the bandwidth and to achieve tri-band operation of 1.57, 3.2, and 5 GHz with measured impedance bandwidths of 3.21%, 28.1%, and 36%, respectively. The antenna is fabricated through a metallic nanoparticle ink on a standard commercial paper. Thus, the antenna can be used to cover the GPS, WiMAX, HiperLAN/2, and WLAN. The antenna has a compact size of 12 × 37.3 × 0.44 mm3, leaving enough space for the driving electronics on the paper substrate. The impedance bandwidth, current distributions, radiation patterns, gain, and efficiency of the antenna have been studied through computer simulations and measurements.
A Three-Winding Coupled-Inductor DC–DC Converter Topology With High Voltage Gain and Reduced Switch Stress

This paper presents a dc–dc boost converter topology for low input and high output voltage applications, such as photovoltaic systems, fuel cell systems, high-intensity discharge lamp, and electric vehicles. The suggested configuration consists of a three-winding coupled-inductor, a single switch and two hybrid voltage multiplier cells. Furthermore, two independent hybrid voltage multiplier cells are in parallel when the single switch S is turned on, and they are in series when the switch S is turned off. So, the advantages of the proposed converter structure are summarized as follows: 1) A coupled inductor with three windings is introduced in the presented converter structure. The two secondary windings of the coupled inductor are, respectively, used to form a hybrid multiplier cell on the one hand, on the other hand, it increases the control freedom of the voltage gain, enhances the utility rate of magnetic core and power density, and reduces the stress of power components to provide a stable constant dc output voltage. 2) The two hybrid multiplier cells can absorb synchronously the energy of stray inductance, which not only reduces the current stress of corresponding diodes, but also greatly alleviates the spike voltage of the main switch, which improves the efficiency. 3) The two hybrid multiplier cells are connected in series to supply power energy for the load, so the voltage gain is extended greatly due to this particular structure. Thus, low-voltage low-conduction-loss devices can be selected and the reverse-recovery currents within the diodes are inhibited. The operating principles and the steady state analyses of the proposed converter are discussed in detail. Finally, a test prototype has been implemented in the laboratory, and the simulated and experimental results show satisfactory agreement with the theoretical analysis.
Emulation of Software Defined Networks Using Mininet in Different Simulation Environments

In this paper an evaluation of an SDN emulation tool called Mininet is conducted. Tests were conducted to study Mininnet limitations related to the simulation environment, resource capabilities. To evaluate the later, the scalability of Mininet in term of creating many topologies is tested with varying number of nodes and two different environment scenarios. Results show that the simulation environment has a remarkable effect on the required time for building a topology, for instance, the powerful resources scenario needed only 0.19 sec, whereas, 5.611 sec were needed when the resources were less. However, the required time were increased in both scenarios when the number of nodes was increased into 242.842 and 3718.117 sec for the powerful and less capabilities resources respectively.
Autonomous lift of a cable-suspended load by an unmanned aerial robot

In this paper, we address the problem of lifting from the ground a cable-suspended load by a quadrotor aerial vehicle. Furthermore, we consider that the mass of the load is unknown. The lift maneuver is a critical step before proceeding with the transportation of a given cargo. However, it has received little attention in the literature so far. To deal with this problem, we break down the lift maneuver into simpler modes which represent the dynamics of the quadrotor-load system at particular operating regimes. From this decomposition, we obtain a series of waypoints that the aerial vehicle has to reach to accomplish the task. We combine geometric control with a least-squares estimation method to design an adaptive controller that follows a prescribed trajectory planned based on the waypoints. The effectiveness of the proposed control scheme is demonstrated by numerical simulations.