nils-herrmann/clean_scirepeval huggingface dataset:
A Scripted Printable Quadrotor: Rapid Design and Fabrication of a Folded MAV

Robotic systems hold great promise to assist with household, educational, and research tasks, but the difficulties of designing and building such robots often are an inhibitive barrier preventing their development. This paper presents a framework in which simple robots can be easily designed and then rapidly fabricated and tested, paving the way for greater proliferation of robot designs. The Python package presented in this work allows for the scripted generation of mechanical elements, using the principles of hierarchical structure and modular reuse to simplify the design process. These structures are then manufactured using an origami-inspired method in which precision cut sheets of plastic film are folded to achieve desired geometries. Using these processes, lightweight, low cost, rapidly built quadrotors were designed and fabricated. Flight tests compared the resulting robots against similar micro air vehicles (MAVs) generated using other processes. Despite lower tolerance and precision, robots generated using the process presented in this work took significantly less time and cost to design and build, and yielded lighter, lower power MAVs.
Convergent, discriminant, and incremental validity of competing measures of emotional intelligence.

This study investigated the convergent, discriminant, and incremental validity of one ability test of emotional intelligence (EI)--the Mayer-Salovey-Caruso-Emotional Intelligence Test (MSCEIT)--and two self-report measures of EI--the Emotional Quotient Inventory (EQ-i) and the self-report EI test (SREIT). The MSCEIT showed minimal relations to the EQ-i and SREIT, whereas the latter two measures were moderately interrelated. Among EI measures, the MSCEIT was discriminable from well-studied personality and well-being measures, whereas the EQ-i and SREIT shared considerable variance with these measures. After personality and verbal intelligence were held constant, the MSCEIT was predictive of social deviance, the EQ-i was predictive of alcohol use, and the SREIT was inversely related to academic achievement. In general, results showed that ability EI and self-report EI are weakly related and yield different measurements of the same person.
Classification of blasts in acute leukemia blood samples using k-nearest neighbour

The k-nearest neighbor (k-NN) is a traditional method and one of the simplest methods for classification problems. Even so, results obtained through k-NN had been promising in many different fields. Therefore, this paper presents the study on blasts classifying in acute leukemia into two major forms which are acute myelogenous leukemia (AML) and acute lymphocytic leukemia (ALL) by using k-NN. 12 main features that represent size, color-based and shape were extracted from acute leukemia blood images. The k values and distance metric of k-NN were tested in order to find suitable parameters to be applied in the method of classifying the blasts. Results show that by having k = 4 and applying cosine distance metric, the accuracy obtained could reach up to 80%. Thus, k-NN is applicable in the classification problem.
A deep learning approach to detection of splicing and copy-move forgeries in images

In this paper, we present a new image forgery detection method based on deep learning technique, which utilizes a convolutional neural network (CNN) to automatically learn hierarchical representations from the input RGB color images. The proposed CNN is specifically designed for image splicing and copy-move detection applications. Rather than a random strategy, the weights at the first layer of our network are initialized with the basic high-pass filter set used in calculation of residual maps in spatial rich model (SRM), which serves as a regularizer to efficiently suppress the effect of image contents and capture the subtle artifacts introduced by the tampering operations. The pre-trained CNN is used as patch descriptor to extract dense features from the test images, and a feature fusion technique is then explored to obtain the final discriminative features for SVM classification. The experimental results on several public datasets show that the proposed CNN based model outperforms some state-of-the-art methods.
Modified CMOS Cherry-Hooper amplifiers with source follower feedback in 0.35/spl mu/m technology

A CMOS Cherry-Hooper amplifier that is modified to include source follower feedback is described. A small signal model that uses only the most dominant capacitances is used to derive the transfer function of the circuit. The gain is significantly higher than that of the standard MOS Cherry-Hooper stage. Design techniques based on the analysis are suggested for broadband applications. A test circuit, fabricated in a 0.35 /spl mu/m CMOS technology, has 9.4dB gain and 880 MHz bandwidth while consuming 6.0 mA from a 3.3 V supply. Eye diagrams of the test chip at 630 MS/s show good eye opening, giving confidence to the new amplifier's large signal performance. In addition, a six stage main amplifier using the modified Cherry-Hooper stages was fabricated in a 0.18 /spl mu/m CMOS technology. It draws 44mA from a 1.8 V supply. It has 39 dB single-ended gain, 2.1 GHz bandwidth, and 14.2 dB noise figure.
Planar square quadrifilar spiral antenna for mobile RFID reader

A compact planar square quadrifilar spiral antenna (QSA) for passive UHF radio frequency identification (RFID) reader is proposed and experimentally investigated. The presented RFID reader antenna consists of four spiral antennas which are fed by microstrip feed network and the 4-port antenna matching technique for QSA is used to improve radiation efficiency. Experimental results shows the proposed antenna has peak gain of 0.06 dBic, axial ratio under 3 dB in wanted frequency band, 3-dB beamwidth of 124° with good right hand circular polarization (RHCP) characteristics.
Discovery of everyday human activities from long-term visual behaviour using topic models

Human visual behaviour has significant potential for activity recognition and computational behaviour analysis, but previous works focused on supervised methods and recognition of predefined activity classes based on short-term eye movement recordings. We propose a fully unsupervised method to discover users' everyday activities from their long-term visual behaviour. Our method combines a bag-of-words representation of visual behaviour that encodes saccades, fixations, and blinks with a latent Dirichlet allocation (LDA) topic model. We further propose different methods to encode saccades for their use in the topic model. We evaluate our method on a novel long-term gaze dataset that contains full-day recordings of natural visual behaviour of 10 participants (more than 80 hours in total). We also provide annotations for eight sample activity classes (outdoor, social interaction, focused work, travel, reading, computer work, watching media, eating) and periods with no specific activity. We show the ability of our method to discover these activities with performance competitive with that of previously published supervised methods.
Full body gait analysis with Kinect

Human gait is an important indicator of health, with applications ranging from diagnosis, monitoring, and rehabilitation. In practice, the use of gait analysis has been limited. Existing gait analysis systems are either expensive, intrusive, or require well-controlled environments such as a clinic or a laboratory. We present an accurate gait analysis system that is economical and non-intrusive. Our system is based on the Kinect sensor and thus can extract comprehensive gait information from all parts of the body. Beyond standard stride information, we also measure arm kinematics, demonstrating the wide range of parameters that can be extracted. We further improve over existing work by using information from the entire body to more accurately measure stride intervals. Our system requires no markers or battery-powered sensors, and instead relies on a single, inexpensive commodity 3D sensor with a large preexisting install base. We suggest that the proposed technique can be used for continuous gait tracking at home.
Application of Extreme Learning Machine Method for Time Series Analysis

In this paper, we study the application of Extreme Learning Machine (ELM) algorithm for single layered feedforward neural networks to non-linear chaotic time series problems. In this algorithm the input weights and the hidden layer bias are randomly chosen. The ELM formulation leads to solving a system of linear equations in terms of the unknown weights connecting the hidden layer to the output layer. The solution of this general system of linear equations will be obtained using Moore-Penrose generalized pseudo inverse. For the study of the application of the method we consider the time series generated by the Mackey Glass delay differential equation with different time delays, Santa Fe A and UCR heart beat rate ECG time series. For the choice of sigmoid, sin and hardlim activation functions the optimal values for the memory order and the number of hidden neurons which give the best prediction performance in terms of root mean square error are determined. It is observed that the results obtained are in close agreement with the exact solution of the problems considered which clearly shows that ELM is a very promising alternative method for time series prediction. Chaotic time series, Extreme learning machine, Generalization performance.
Optimal Operation of Residential Energy Hubs in Smart Grids

This paper presents mathematical optimization models of residential energy hubs which can be readily incorporated into automated decision making technologies in smart grids, and can be solved efficiently in a real-time frame to optimally control all major residential energy loads, storage and production components while properly considering the customer preferences and comfort level. Novel mathematical models for major household demand, i.e., fridge, freezer, dishwasher, washer and dryer, stove, water heater, hot tub, and pool pumps are formulated. Also, mathematical models of other components of a residential energy system including lighting, heating, and air-conditioning are developed, and generic models for solar PV panels and energy storage/generation devices are proposed. The developed mathematical models result in Mixed Integer Linear Programming (MILP) optimization problems with the objective functions of minimizing energy consumption, total cost of electricity and gas, emissions, peak load, and/or any combination of these objectives, while considering end-user preferences. Several realistic case studies are carried out to examine the performance of the mathematical model, and experimental tests are carried out to find practical procedures to determine the parameters of the model. The application of the proposed model to a real household in Ontario, Canada is presented for various objective functions. The simulation results show that savings of up to 20% on energy costs and 50% on peak demand can be achieved, while maintaining the household owner's desired comfort levels.
The pls Package: Principal Component and Partial Least Squares Regression in R

The pls package implements principal component regression (PCR) and partial least squares regression (PLSR) in R (R Development Core Team 2006b), and is freely available from the Comprehensive R Archive Network (CRAN), licensed under the GNU General Public License (GPL). The user interface is modelled after the traditional formula interface, as exemplified by lm. This was done so that people used to R would not have to learn yet another interface, and also because we believe the formula interface is a good way of working interactively with models. It thus has methods for generic functions like predict, update and coef. It also has more specialised functions like scores, loadings and RMSEP, and a flexible crossvalidation system. Visual inspection and assessment is important in chemometrics, and the pls package has a number of plot functions for plotting scores, loadings, predictions, coefficients and RMSEP estimates. The package implements PCR and several algorithms for PLSR. The design is modular, so that it should be easy to use the underlying algorithms in other functions. It is our hope that the package will serve well both for interactive data analysis and as a building block for other functions or packages using PLSR or PCR. We will here describe the package and how it is used for data analysis, as well as how it can be used as a part of other packages. Also included is a section about formulas and data frames, for people not used to the R modelling idioms.
Low-Power Wearable ECG Monitoring System for Multiple-Patient Remote Monitoring

Many devices and solutions for remote electrocardiogram (ECG) monitoring have been proposed in the literature. These solutions typically have a large marginal cost per added sensor and are not seamlessly integrated with other smart home solutions. Here, we propose an ECG remote monitoring system that is dedicated to non-technical users in need of long-term health monitoring in residential environments and is integrated in a broader Internet-of-Things (IoT) infrastructure. Our prototype consists of a complete vertical solution with a series of advantages with respect to the state of the art, considering both the prototypes with integrated front end and prototypes realized with off-the-shelf components: 1) ECG prototype sensors with record-low energy per effective number of quantized levels; 2) an architecture providing low marginal cost per added sensor/user; and 3) the possibility of seamless integration with other smart home systems through a single IoT infrastructure.
IoT enabled environmental monitoring system for smart cities

A smart city enables the effective utilization of resources and better quality of services to the citizens. To provide services such as air quality management, weather monitoring and automation of homes and buildings in a smart city, the basic parameters are temperature, humidity and CO2. This paper presents a customised design of an Internet of Things (IoT) enabled environment monitoring system to monitor temperature, humidity and CO2. In developed system, data is sent from the transmitter node to the receiver node. The data received at the receiver node is monitored and recorded in an excel sheet in a personal computer (PC) through a Graphical User Interface (GUI), made in LabVIEW. An Android application has also been developed through which data is transferred from LabVIEW to a smartphone, for monitoring data remotely. The results and the performance of the proposed system is discussed.
E-tribalized marketing ? : the strategic implicat ions of virtual communit ies of consumption

On the Internet, electronic tribes structured around consumer interests have been growing rapidly. To be effective in this new environment, managers must consider the strategic implications of the existence of different types of both virtual community and community participation. Contrasted with database-driven relationship marketing, marketers seeking success with consumers in virtual communities should consider that they: (1) are more active and discerning; (2) are less accessible to one-on-one processes, and (3) provide a wealth of valuable cultural information. Strategies for effectively targeting more desirable types of virtual communities and types of community members include: interaction-based segmentation, fragmentation-based segmentation, co-opting communities, paying-for-attention, and building networks by giving product away. Purchase Export Previous article Next article Check if you have access through your login credentials or your institution.
Why pay?: exploring how financial incentives are used for question & answer

Electronic commerce has enabled a number of online pay-for-answer services. However, despite commercial interest, we still lack a comprehensive understanding of how financial incentives support question asking and answering. Using 800 questions randomly selected from a pay-for-answer site, along with site usage statistics, we examined what factors impact askers' decisions to pay. We also explored how financial rewards affect answers, and if question pricing can help organize Q&A exchanges for archival purposes. We found that askers' decisions are two-part--whether or not to pay and how much to pay. Askers are more likely to pay when requesting facts and will pay more when questions are more difficult. On the answer side, our results support prior findings that paying more may elicit a higher number of answers and answers that are longer, but may not elicit higher quality answers (as rated by the askers). Finally, we present evidence that questions with higher rewards have higher archival value, which suggests that pricing can be used to support archival use.
Labia Majora Augmentation with De-epithelialized Labial Rim (Minora) Flaps as an Auxiliary Procedure for Labia Minora Reduction

Esthetic surgery of external female genitalia remains an uncommon procedure. This article describes a novel, de-epithelialized, labial rim flap technique for labia majora augmentation using de-epithelialized labia minora tissue otherwise to be excised as an adjunct to labia minora reduction. Ten patients were included in the study. The protruding segments of the labia minora were de-epithelialized with a fine scissors or scalpel instead of being excised, and a bulky section of subcutaneous tissue was obtained. Between the outer and inner surfaces of the labia minora, a flap with a subcutaneous pedicle was created in continuity with the de-epithelialized marginal tissue. A pocket was dissected in the labium majus, and the flap was transposed into the pocket to augment the labia majora. Mean patient age was 39.9 (±13.9) years, mean operation time was 60 min, and mean follow-up period was 14.5 (±3.4) months. There were no major complications (hematoma, wound dehiscence, infection) following surgery. No patient complained of postoperative difficulty with coitus or dyspareunia. All patients were satisfied with the final appearance. Several methods for labia minora reduction have been described. Auxiliary procedures are required with labia minora reduction for better results. Nevertheless, few authors have taken into account the final esthetic appearance of the whole female external genitalia. The described technique in this study is indicated primarily for mild atrophy of the labia majora with labia minora hypertrophy; the technique resulted in perfect patient satisfaction with no major complications or postoperative coital problems. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .
Clinical Outcomes of Impending Nasal Skin Necrosis Related to Nose and Nasolabial Fold Augmentation with Hyaluronic Acid Fillers.

Although there are several case reports of facial skin ischemia/necrosis caused by hyaluronic acid filler injections, no systematic study of the clinical outcomes of a series of cases with this complication has been reported.



The authors report a study of 20 consecutive patients who developed impending nasal skin necrosis as a primary concern, after nose and/or nasolabial fold augmentation with hyaluronic acid fillers. The authors retrospectively reviewed the clinical outcomes and the risk factors for this complication using case-control analysis.



Seven patients (35 percent) developed full skin necrosis, and 13 patients (65 percent) recovered fully after combination treatment with hyaluronidase. Although the two groups had similar age, sex, filler injection sites, and treatment for the complication, 85 percent of the patients in the full skin necrosis group were late presenters who did not receive the combination treatment with hyaluronidase within 2 days after the vascular complication first appeared. In contrast, just 15 percent of the patients in the full recovery group were late presenters (p = 0.004).



Nose and nasolabial fold augmentations with hyaluronic acid fillers can lead to impending nasal skin necrosis, possibly caused by intravascular embolism and/or extravascular compression. The key for preventing the skin ischemia from progressing to necrosis is to identify and treat the ischemia as early as possible. Early (<2 days) combination treatment with hyaluronidase is associated with the full resolution of the complication.



Therapeutic, IV.
Cultural competence models and cultural competence assessment instruments in nursing: a literature review.

The author reviewed cultural competence models and cultural competence assessment instruments developed and published by nurse researchers since 1982. Both models and instruments were examined in terms of their components, theoretical backgrounds, empirical validation, and psychometric evaluation. Most models were not empirically tested; only a few models developed model-based instruments. About half of the instruments were tested with varying levels of psychometric properties. Other related issues were discussed, including the definition of cultural competence and its significance in model and instrument development, limitations of existing models and instruments, impact of cultural competence on health disparities, and further work in cultural competence research and practice.
Syntax tree fingerprinting for source code similarity detection

Numerous approaches based on metrics, token sequence pattern-matching, abstract syntax tree (AST) or program dependency graph (PDG) analysis have already been proposed to highlight similarities in source code: in this paper we present a simple and scalable architecture based on AST fingerprinting. Thanks to a study of several hashing strategies reducing false-positive collisions, we propose a framework that efficiently indexes AST representations in a database, that quickly detects exact (w.r.t source code abstraction) clone clusters and that easily retrieves their corresponding ASTs. Our aim is to allow further processing of neighboring exact matches in order to identify the larger approximate matches, dealing with the common modification patterns seen in the intra-project copy-pastes and in the plagiarism cases.
Security Metrics and Security Investment Models

Planning information security investment is somewhere between art and science. This paper reviews and compares existing scientific approaches and discusses the relation between security investment models and security metrics. To structure the exposition, the high-level security production function is decomposed into two steps: cost of security is mapped to a security level, which is then mapped to benefits. This allows to structure data sources and metrics, to rethink the notion of security productivity, and to distinguish sources of indeterminacy as measurement error and attacker behavior. It is further argued that recently proposed investment models, which try to capture more features specific to information security, should be used for all strategic security investment decisions beneath defining the overall security budget.