nils-herrmann/clean_scirepeval huggingface dataset:
A Piezoelectric Energy Harvester for Rotary Motion Applications: Design and Experiments

This paper investigates the analysis and design of a vibration-based energy harvester for rotary motion applications. The energy harvester consists of a cantilever beam with a tip mass and a piezoelectric ceramic attached along the beam that is mounted on a rotating shaft. Using this system, mechanical vibration energy is induced in the flexible beam due to the gravitational force applied to the tip mass while the hub is rotating. The piezoelectric transducer is used to convert the induced mechanical vibration energy into electricity. The equations of motion of the flexible structure are utilized along with the physical characteristics of the piezoelectric transducer to derive expressions for the electrical power. Furthermore, expressions for the optimum load resistance and maximum output power are obtained and validated experimentally using PVDF and PZT transducers. The results indicate that a maximum power of 6.4 mW at a shaft speed of 138 rad/s can be extracted by using a PZT transducer with dimensions 50.8 mm × 38.1 mm × 0.13 mm. This amount of power is sufficient to provide power for typical wireless sensors such as accelerometers and strain gauges.
Cycling Down Under : A Comparative Analysis of Bicycling Trends and Policies in Sydney and Melbourne

The purpose of this paper is to document and explain differences in cycling between Australia’s two largest cities. Our comparative case study analysis is based on a wide range of statistical datasets, secondary reports, and interviews with a panel of 22 bicycling policy and planning experts. The main finding is that cycling levels in Melbourne are roughly twice as high as in Sydney and have been growing three times as fast in recent years. The difference is due to Melbourne’s more favorable topography, climate, and road network as well as more supportive public policies. In particular, Melbourne has more and better integrated cycling infrastructure as well as more extensive cycling programs, advocacy, and promotional events. Melbourne also benefits from safer cycling than Sydney, which suffers from a lack of traffic-protected cycling facilities and aggressive motorist behavior toward cyclists on the road. While cycling has been increasing in Australia, it remains at very low levels relative to northern Europe, where both land use and transport policies are far more supportive of bicycling while discouraging car use through numerous restrictions and financial disincentives.
Studying Fake News via Network Analysis: Detection and Mitigation

Social media is becoming increasingly popular for news consumption due to its easy access, fast dissemination, and low cost. However, social media also enables the wide propagation of “fake news”, i.e., news with intentionally false information. Fake news on social media can have significant negative societal effects. Identifying and mitigating fake news also presents unique challenges. To tackle these challenges, many existing research efforts exploit various features of the data, including network features. In essence, a news dissemination ecosystem involves three dimensions on social media, i.e., a content dimension, a social dimension, and a temporal dimension. In this chapter, we will review network properties for studying fake news, introduce popular network types and propose how these networks can be used to detect and mitigate fake news on social media.
An analysis of electromagnetic characteristics and mechanical load characteristics of actuator for 4 pole MC

MC(Magnetic Contactor) is a widely used switch in power distribution systems for controlling electrical loads by making and breaking electric circuits using electromagnetic force of an actuator. MCs are classified as 3 and 4 pole MC according to the number of main contacts. 4 pole MC consists of 4 main contacts, which controls a three phase four wire system or two single phase systems. The type of the main contact affects not only the electric characteristics but also the mechanical load characteristics of the MC. In order to design the actuator for the 4 pole MC, it is important to analyze the mechanical load characteristics and the electromagnetic characteristics of the actuator precisely. In this paper, the analysis of mechanical load characteristics according to the formation types of main contacts is conducted and the electromagnetic characteristics are analyzed using 2-D FEM(Finite Element Method). Furthermore, the dynamic characteristics analysis of the actuator is conducted and its validity is verified by experiments.
TUTORIAL ON AGENT-BASED MODELING AND SIMULATION

Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of autonomous, interacting agents. ABMS promises to have far-reaching effects on the way that businesses use computers to support decision-making and researchers use electronic laboratories to support their research. Some have gone so far as to contend that ABMS is a third way of doing science besides deductive and inductive reasoning. Computational advances have made possible a growing number of agentbased applications in a variety of fields. Applications range from modeling agent behavior in the stock market and supply chains, to predicting the spread of epidemics and the threat of bio-warfare, from modeling consumer behavior to understanding the fall of ancient civilizations, to name a few. This tutorial describes the theoretical and practical foundations of ABMS, identifies toolkits and methods for developing ABMS models, and provides some thoughts on the relationship between ABMS and traditional modeling techniques.
VSP: A Virtual Smartphone Platform to Enhance the Capability of Physical Smartphone

Smart mobile devices have become ubiquitous, and people prefer to choose smartphone in daily life rather than use traditional personal computer. However, due to the hardware capability, performance of smartphones varies greatly and sometimes it cannot meet the demand of users. Furthermore, if smartphone is attacked by malicious application, the local private sensitive information will be leaked which in turn will cause huge losses. This paper proposes VSP, a Virtual Smartphone Platform. It offers a new way to enhance the capability of physical smartphone by providing virtual smartphone (VS) deployed in cloud. Users operate VS remotely through the thin-client of VSP on physical smartphones, and ignore the limits of physical mobile devices. The isolation of VS in cloud platform guarantees the security between VSes, and also prevents access to private sensitive information on physical devices. The evaluation indicates that average bandwidth cost with zlib is about 80 kBps and it is suitable for use in practice. Index Terms—Virtualization, Android, Remote Display, Cloud Computing, Ant Colony Optimization.
Parents with doubts about vaccines: which vaccines and reasons why.

The goals were (1) to obtain national estimates of the proportions of parents with indicators of vaccine doubt, (2) to identify factors associated with those parents, compared with parents reporting no vaccine doubt indicators, (3) to identify the specific vaccines that prompted doubt and the reasons why, and (4) to describe the main reasons parents changed their minds about delaying or refusing a vaccine for their child.



Data were from the National Immunization Survey (2003-2004). Groups included parents who ever got a vaccination for their child although they were not sure it was the best thing to do ("unsure"), delayed a vaccination for their child ("delayed"), or decided not to have their child get a vaccination ("refused").



A total of 3924 interviews were completed. Response rates were 57.9% in 2003 and 65.0% in 2004. Twenty-eight percent of parents responded yes to ever experiencing >or=1 of the outcome measures listed above. In separate analyses for each outcome measure, vaccine safety concern was a predictor for unsure, refused, and delayed parents. The largest proportions of unsure and refused parents chose varicella vaccine as the vaccine prompting their concern, whereas delayed parents most often reported "not a specific vaccine" as the vaccine prompting their concern. Most parents who delayed vaccines for their child did so for reasons related to their child's illness, unlike the unsure and refused parents. The largest proportion of parents who changed their minds about delaying or not getting a vaccination for their child listed "information or assurances from health care provider" as the main reason.



Parents who exhibit doubts about immunizations are not all the same. This research suggests encouraging children's health care providers to solicit questions about vaccines, to establish a trusting relationship, and to provide appropriate educational materials to parents.
Hand3D: Hand Pose Estimation using 3D Neural Network

We propose a novel 3D neural network architecture for 3D hand pose estimation from a single depth image. Different from previous works that mostly run on 2D depth image domain and require intermediate or post process to bring in the supervision from 3D space, we convert the depth map to a 3D volumetric representation, and feed it into a 3D convolutional neural network(CNN) to directly produce the pose in 3D requiring no further process. Our system does not require the ground truth reference point for initialization, and our network architecture naturally integrates both local feature and global context in 3D space. To increase the coverage of the hand pose space of the training data, we render synthetic depth image by transferring hand pose from existing real image datasets. We evaluation our algorithm on two public benchmarks and achieve the state-ofthe-art performance. The synthetic hand pose dataset will be available.
Advantages of longitudinal flux linear switched reluctance motor compared to transverse flux linear switched reluctance motor for levitation purposes

Linear switched reluctance motors (LSRMs) have great attractive force. This force can be used as levitation force. In general, LSRMs are divided in two types: 1) longitudinal flux LSRMs 2) transverse flux LSRMs. Two phase single-sided longitudinal flux and transverse flux LSRMs are considered. This paper presents that longitudinal flux LSRM produces greater attractive force and it needs lesser amount of steel in its secondary. The attractive force of the LSRM is calculated using the three-dimensional finite element method (3D-FEM).
Components for parametric urban design in Grasshopper from street network to building geometry

The main contribution of our work is in combining the methods for parametric urban design of highly specialized software such as CityEngine and general-purpose parametric modeling platform such as Grasshopper. Our work facilitates and prompts the use of parametric tools by architects and planners for urban design. In this paper we present a custom grasshopper component for street network generation and block subdivision. The component was developed in C# using the RhinoCommon SDK. We used Grasshopper for the development of an urban design proposal at a teaching exercise. To meet the requirements of the urban design project, additional functionalities had to be added to the range of existing Grasshopper components. In particular, we needed components for street network generation and block subdivision. To develop the component we implemented the street expansion strategies described in (Weber et al., 2009) and the methods for block subdivision described in (Vanegas et al., 2009). Additionally, we adapted and enhanced the strategies to meet the NURBS modeling capabilities of Rhinoceros.
Context-Aware Filtering and Visualization of Web Service Clusters

Web service filtering is an efficient approach to address some big challenges in service computing, such as discovery, clustering and recommendation. The key operation of the filtering process is measuring the similarity of services. Several methods are used in current similarity calculation approaches such as string-based, corpus-based, knowledge-based and hybrid methods. These approaches do not consider domain-specific contexts in measuring similarity because they have failed to capture the semantic similarity of Web services in a given domain and this has affected their filtering performance. In this paper, we propose a context-aware similarity method that uses a support vector machine and a domain dataset from a context-specific search engine query. Our filtering approach uses a spherical associated keyword space algorithm that projects filtering results from a three-dimensional sphere to a two-dimensional (2D) spherical surface for 2D visualization. Experimental results show that our filtering approach works efficiently.
Current limitation control technique for parallel operation of UPS inverters

This work presents a current limitation control technique for multimodule parallel UPS inverters. All inverter modules are with voltage and current control loops. However, only the voltage loop of the master module is active. The current command of the master module is generated by its voltage controller. Voltage loops of all slave modules are idle running. The slave module is only for sharing load current with its current command generated from the previous module. By limiting the output current command of each module and sending the difference between the limited and unlimited current commands to the next module, each module only has to share the load current not completely provided by all previous modules. Through circular chain connection of the modules, the number of control interconnection can be minimized. The master module also can be switched on-line with negligible disturbance for voltage regulation. Due to only one voltage loop is active at any time, the proposed method is the most stable one as compared with other methods with control interconnection. This paper also proposes a robust controller for maintaining good voltage regulating performance even when the parallel number of modules has a large change. Three 1 KVA modules are implemented. The effectiveness of the proposed technique is confirmed with experimental results.
Motion adaptation on a wheelchair driving simulator

The objective of the AccesSim project is to design a wheelchair simulator using Virtual Reality and a robotic platform to detect and illustrate accessibility issues in complex environments. In order to be efficient, the robotic platform must provide haptic and vestibular feedbacks to different profile of end users: urbanists to wheelchair users. It must be modular and adaptable to each one of them. In this paper we focus our robotic platform capable of adapting its configuration and feedback rendering based on the user. The design of the platform is described. The capacity of the platform to reproduce the motion of a wheelchair in a specific study case is tested experimen-tally. Finally the results introduce the possibility of adapting the dynamic feedback rendering based on a specific user and environmental situations.
Supervised LogEuclidean Metric Learning for Symmetric Positive Definite Matrices

Metric learning has been shown to be highly effective to improve the performance of nearest neighbor classification. In this paper, we address the problem of metric learning for symmetric positive definite (SPD) matrices such as covariance matrices, which arise in many real-world applications. Naively using standard Mahalanobis metric learning methods under the Euclidean geometry for SPD matrices is not appropriate, because the difference of SPD matrices can be a non-SPD matrix and thus the obtained solution can be uninterpretable. To cope with this problem, we propose to use a properly parameterized LogEuclidean distance and optimize the metric with respect to kernel-target alignment, which is a supervised criterion for kernel learning. Then the resulting non-trivial optimization problem is solved by utilizing the Riemannian geometry. Finally, we experimentally demonstrate the usefulness of our LogEuclidean metric learning algorithm on real-world classification tasks for EEG signals and texture patches.
A quasi-orthogonal space-time block code

It has been shown that a complex orthogonal design that provides full diversity and full transmission rate for a space–time block code is not possible for more than two antennas. Previous attempts have been concentrated in generalizing orthogonal designs which provide space–time block codes with full diversity and a high transmission rate. In this work, we design rate one codes which are quasi-orthogonal and provide partial diversity. The decoder of the proposed codes works with pairs of transmitted symbols instead of single symbols.
IoT based SCADA integrated with Fog for power distribution automation

Electrical Grid we have is more than 50 years old. The integration of information technology to the electric grid system is expected to address many shortcomings of the current and traditional electrical grids that have resulted in Smart Grid which is gaining lot of interest and momentum. In Smart Grid, Power Distribution is one part which requires monitoring and control. Lot of technologies and have been applied in Smart grid towards sensing and action.  There has been very less monitoring done on the distribution side due to the geographical distribution. Currently, Internet of Things has paved way for connecting huge number of devices to the Internet which would be very much effective and beneficial for power distribution and Automation. So accordingly, an IoT based SCADA integrated with Fog for Distribution Automation system has been proposed which takes care of the consumer utilization, outage management, power quality control and pole transformer health. This is supported by fog computing which does real-time streaming analytics. This helps in reducing the internet bandwidth and latency for immediate control action.
Complex-Valued Convolutional Neural Network and Its Application in Polarimetric SAR Image Classification

Following the great success of deep convolutional neural networks (CNNs) in computer vision, this paper proposes a complex-valued CNN (CV-CNN) specifically for synthetic aperture radar (SAR) image interpretation. It utilizes both amplitude and phase information of complex SAR imagery. All elements of CNN including input-output layer, convolution layer, activation function, and pooling layer are extended to the complex domain. Moreover, a complex backpropagation algorithm based on stochastic gradient descent is derived for CV-CNN training. The proposed CV-CNN is then tested on the typical polarimetric SAR image classification task which classifies each pixel into known terrain types via supervised training. Experiments with the benchmark data sets of Flevoland and Oberpfaffenhofen show that the classification error can be further reduced if employing CV-CNN instead of conventional real-valued CNN with the same degrees of freedom. The performance of CV-CNN is comparable to that of existing state-of-the-art methods in terms of overall classification accuracy.
Achievement Goals in the Classroom : Students ' Learning Strategies and Motivation Processes

We studied how specific motivational processes are related to the salience of mastery and performance goals in actual classroom settings. One hundred seventy-six students attending a junior high/high school for academically advanced students were randomly selected from one of their classes and responded to a questionnaire on their perceptions of the classroom goal orientation, use of effective learning strategies, task choices, attitudes, and causal attributions. Students who perceived an emphasis on mastery goals in the classroom reported using more effective strategies, preferred challenging tasks, had a more positive attitude toward the class, and had a stronger belief that success follows from one's effort. Students who perceived performance goals as salient tended to focus on their ability, evaluating their ability negatively and attributing failure to lack of ability. The pattern and strength of the findings suggest that the classroom goal orientation may facilitate the maintenance of adaptive motivation patterns when mastery goals are salient and are adopted by students.
Boot Attestation: Secure Remote Reporting with Off-The-Shelf IoT Sensors

A major challenge in computer security is about establishing the trustworthiness of remote platforms. Remote attestation is the most common approach to this challenge. It allows a remote platform to measure and report its system state in a secure way to a third party. Unfortunately, existing attestation solutions either provide low security, as they rely on unrealistic assumptions, or are not applicable to commodity low-cost and resource-constrained devices, as they require custom secure hardware extensions that are difficult to adopt across IoT vendors. In this work, we propose a novel remote attestation scheme, named Boot Attestation, that is particularly optimized for low-cost and resource-constrained embedded devices. In Boot Attestation, software integrity measurements are immediately committed to during boot, thus relaxing the traditional requirement for secure storage and reporting. Our scheme is very light on cryptographic requirements and storage, allowing efficient implementations, even on the most low-end IoT platforms available today. We also describe extensions for more flexible management of ownership and third party (public-key) attestation that may be desired in fully Internet-enabled devices. Our scheme is supported by many existing off-the-shelf devices. To this end, we review the hardware protection capabilities for a number of popular device types and present implementation results for two such commercially available platforms.
Hyperdimensional biosignal processing: A case study for EMG-based hand gesture recognition

The mathematical properties of high-dimensional spaces seem remarkably suited for describing behaviors produces by brains. Brain-inspired hyperdimensional computing (HDC) explores the emulation of cognition by computing with hypervectors as an alternative to computing with numbers. Hypervectors are high-dimensional, holographic, and (pseudo)random with independent and identically distributed (i.i.d.) components. These features provide an opportunity for energy-efficient computing applied to cyberbiological and cybernetic systems. We describe the use of HDC in a smart prosthetic application, namely hand gesture recognition from a stream of Electromyography (EMG) signals. Our algorithm encodes a stream of analog EMG signals that are simultaneously generated from four channels to a single hypervector. The proposed encoding effectively captures spatial and temporal relations across and within the channels to represent a gesture. This HDC encoder achieves a high level of classification accuracy (97.8%) with only 1/3 the training data required by state-of-the-art SVM on the same task. HDC exhibits fast and accurate learning explicitly allowing online and continuous learning. We further enhance the encoder to adaptively mitigate the effect of gesture-timing uncertainties across different subjects endogenously; further, the encoder inherently maintains the same accuracy when there is up to 30% overlapping between two consecutive gestures in a classification window.
Handbook of Multibiometrics (International Series on Biometrics)

Will reading habit influence your life? Many say yes. Reading handbook of multibiometrics 6 international series on biometrics is a good habit; you can develop this habit to be such interesting way. Yeah, reading habit will not only make you have any favourite activity. It will be one of guidance of your life. When reading has become a habit, you will not make it as disturbing activities or as boring activity. You can gain many benefits and importances of reading.