nils-herrmann/clean_scirepeval huggingface dataset:
A new verification approach for subjective evaluation of actions in HMD VR with EEG
Venue: Other Conferences
Year: 2021

We propose a new verification approach for subjective evaluation of actions and reactions in virtual reality. We have been working on subject behavior analysis in VR. A head tracking HMD allows users to move around and make actions up to a room size, and their experiences can be measured by their head position, motion estimation, and gaze tracking when they are available. But in most cases, subjective evaluation for total VR experience are conducted after their experiences are over. We have succeeded in integrating a new EEG device that can measure EEG and mind indexes in real time with gaze trackable and head trackable HMD. By referring the gaze tracking results and EEG analysis and/or mind indexes when a situation is presented in VR, we can check the subject is surely watching the objects with their attention in the situation and their attention level in his/her mind. It may support the reliability of the score of subjective evaluation. This is very important when we need to conduct a number of subjective evaluations with a fewer number of subjects. We have developed our preliminary system for two applications sport action analysis and traffic safety evaluation and confirmed that it is a promising approach.
Synthesis for Robots: Guarantees and Feedback for Robot Behavior
Year: 2018

Robot control for tasks such as moving around obstacles or grasping objects has advanced significantly in the last few decades. However, controlling robots to perform complex tasks is still accomplished largely by highly trained programmers in a manual, time consuming, and error prone process that is typically validated only through extensive testing. Formal methods are mathematical techniques for reasoning about systems, their requirements, and their guarantees. Formal synthesis for robotics refers to frameworks for specifying tasks in a mathematically precise language and automatically transforming these specifications into correct by construction robot controllers or into a proof that the task cannot be done. Synthesis allows users to reason about the task specification rather than its implementation, reduces implementation error, and provides behavioral guarantees for the resulting controller. This article reviews the current state of formal synthesis for robotics and surveys the landscape of abstract.
Percutaneous Posterolateral Transforaminal Endoscopic Discectomy: Clinical Outcome, Complications, and Learning Curve Evaluation.
Venue: Surgical technology international
Year: 2011

Ongoing technological development combined with better understanding of endoscopic anatomy has made posterolateral endoscopic discectomy an appealing surgical option for the management of herniated lumbar disc. We evaluated clinical outcomes, complication rates, and surgical learning curve with the percutaneous posterolateral transforaminal endoscopic discectomy technique (PPTED) PPTED was performed on 150 patients from 2004 to 2008. And 124 patients were available for follow up. Data regarding pain, postoperative complications, neurological status, operation time, and subjective patient satisfaction were recorded. A satisfactory clinical outcome as reflected in the VAS (mean 3.6) and ODI improvement (mean 21% scores was reported; 20.9% of the patients required additional surgery. Learning curve assessment showed a significant difference (p 0.043) for fewer revision surgeries as surgeons became more experienced. Patients who had endoscopic discectomy as a primary surgery achieved significantly lower VAS (p 0.04) and ODI improvement (p 0.004) scores compared with patients having transforaminal endoscopic discectomy as revision surgery. The complication rate was 1.6% including one case of post surgery hypoesthesia and one deep wound infection. The percutaneous posterolateral transforaminal endoscopic discectomy technique has a satisfactory clinical outcome with a low complication rate. Results for endoscopic surgery for revision or recurrent disc herniation are comparable to those of open revision surgery; the steep learning curve can be overcome with training and suitable patient selection.
Analise do estilo de vida de usuarias com sofrimento psiquico do grupo "movimente se" atraves do pentaculo do bem estar
Year: 2019

O objetivo deste estudo foi analisar o estilo de vida de usuarias do SUS com sofrimento psiquico que fazem parte do grupo "Movimente se" Trata se de estudo descritivo, transversal e abordagem quantitativa com dados secundarios, cuja amostra foi selecionada de um grupo de 50 usuarios do grupo "Movimente se" que faz parte da rede de atendimento do SUS. Entre os resultados destacam se: a amostra majoriatarimente feminina, alto percentual de pessoas com ansiedade (67% a presenca de outras doencas associadas tais como: Hipertensao (33% depressao(33% e insonia (33% Acerca da qualidade de vida observa se que os itens alimentacao, atividade fisica, relacionamento e controle do estresse sao reproduzidos pela maioria dos entrevistados entre os escores que representam a ausencia total ou parcial deste comportamento. Por outro lado, no comportamento preventivo a maioria apontou que conhece controla doencas preexistentes. Conclui se que a presenca dos usuarios no grupo de atividade fisica pode ser favoravel a reducao destes comportamento nocivos a saude geral, bem como na diminuicao do sofrimento psiquico.
Strategic Approach Towards Organizational Performance: Modern Practices over Human Resource Management
Year: 2020

The research study identifies the connection among Contemporary Practices of HRM and their effect over organizational Performance. However, the purpose of this research is to create the importance of HRM practices for employees' to perform its operations more efficiently and their impacts on organizational performance. This study underlines the value to any organization concerned about its performance that runs from management intentions through HRM practices and employee responses to organizational outcomes. Whereas, the study intend to evaluate the scope of general HRM practices that might contribute to enhance the employee performance. Finally SEM analysis is computed to identify the relationship among the SHRM, Organizational performance and environment with the mediation of employee attitude. The study values the organizational to overcome the employee inefficiency and upcoming challenges in organization turbulence to facilitate further debate on intangible resource utilization, potential enhancement in organizational performance.
Feature Integration Via Geometrical Supervised Multi View Multi Label Canonical Correlation For Incomplete Label Assignment
Venue: 2020 IEEE International Conference on Image Processing (ICIP)
Year: 2020

This paper presents feature integration via geometrical supervised multi view multi label canonical correlation analysis (GSM2CCA) for incomplete label assignment. The problem of incomplete labels is frequently encountered in the multi label classification problem where the training labels are obtained via crowd sourcing. In such a situation, consideration of only the label correlation, which is the basic approach, is not suitable for improvement of representation ability of features. For dealing with the incomplete label assignment, GSM2CCA constructs effective feature embedding space providing the discriminant ability by introducing both the multi label correlation and feature similarity of the original feature space into its objective function. Since novel integrated features with high discriminant ability can be calculated by our GSM2CCA, performance improvement of multi label classification with the incomplete label assignment is realized. The main contribution of this paper is the realization of the effective feature integration via the adoption of the combination use of label similarity and locality preserving projection of heterogeneous features for solving the problem of the incomplete label assignment. The effectiveness of GSM2CCA by applying GSM2CCA based feature integration to heterogeneous features calculated from various convolutional neural network models is verified via experimental results.
Linear codes with few weights from cyclotomic classes and weakly regular bent functions
Venue: Des. Codes Cryptogr.
Year: 2020

Linear codes with few weights constructed from defining sets have been extensively studied due to their applications in data storage systems, secret sharing schemes and authentication codes. In this paper, inspired by the works of Li et al. ( 2017) and Jian et al. (Finite Fields Appl 57:92 107, 2019) we propose a class of five weight linear codes by choosing the defining set from cyclotomic classes, which includes a class of two weight linear codes as a special case, and we also present two classes of two or three weight linear codes by employing weakly regular bent functions. Besides, we obtain a class of two weight optimal punctured codes with respect to the Griesmer bound.
Kinematics and timing of shear zone deformation in the western Coast Belt: evidence for mid Cretaceous orogen parallel extension
Year: 2014

Northwest striking sinistral shear zones characterize mid Cretaceous deformation in the western Coast Belt south of Prince Rupert in north coastal British Columbia. Structurally focused mapping and geochronology have revealed a component of lateral extension to this deformation. General flow characteristics of the shear zones are identified by comparison of fabric patterns to published models for fabric development in shear zones. U Pb ages from synkinematic dykes constrain motion on northwest striking sinistral transpressional shear zones, including the Useless, Barrett and Salt Lagoon shear zones, to ca. 104 96 Ma, and dextral transpression on the north striking Telegraph Passage shear zone to ca. 97 Ma. The geometry, kinematics, and coeval nature of these shear zones suggest that they formed in part as a ductile conjugate set. The orientation of these conjugate sets indicates ENE WSW (orogen perpendicular) shortening and NNW ESE (orogen parallel) extension. The conjugate shear zones merge together into the Grenville Channel shear zone, a sinistral transpressional shear zone with high strike parallel stretch indicating the same strain field. This local strain regime is consistent with large scale mid Cretaceous tectonic escape as proposed for the northern Cordillera at that time, expressed in coeval sinistral faulting in the Coast Belt and dextral faulting in the northern Omineca belt.
TECHNOLOGY AN EFFICIENT COMPRESSION ALGORITHM FOR FINGERPRINT IMAGES USING SPARSE REPRESENTATION
Year: 2015

Recognition of person by means of their biometric characteristics is very popular among the society. Among this, for personal identification fingerprint recognition is an important technology due to its unique structure. Human fingerprints are rich in details called minutiae. This can be used for identification marks for fingerprint verification. Large volume of fingerprint images are collected and stored day by day from a wider range of applications. Compression of data is commanding of under certain circumstances due to large amount of data transmission and efficient memory utilization. A new and efficient fingerprint compression algorithm using sparse representation is proposed. Obtaining an over complete dictionary from a set of fingerprint patches allows us to represent them as a sparse linear combination of dictionary atoms. In the algorithm, first construct a dictionary for predefined fingerprint image patches. For a new given fingerprint images, represent its patches according to the dictionary by computing l0 minimization and then quantize and encode the coefficients and other related information using lossless coding methods. A fast Fourier filtering transformation for image post processing helped to improve the contrast ratio of the regenerated image The effect of various factors on compression results robust to extract minutiae, better PSNR, verbosity for reconstructed images and better compression ratio.
Feature Selection Methods for Cost Constrained Classification in Random Forests
Venue: ArXiv
Year: 2020

Cost sensitive feature selection describes a feature selection problem, where features raise individual costs for inclusion in a model. These costs allow to incorporate disfavored aspects of features, e.g. failure rates of as measuring device, or patient harm, in the model selection process. Random Forests define a particularly challenging problem for feature selection, as features are generally entangled in an ensemble of multiple trees, which makes a post hoc removal of features infeasible. Feature selection methods therefore often either focus on simple pre filtering methods, or require many Random Forest evaluations along their optimization path, which drastically increases the computational complexity. To solve both issues, we propose Shallow Tree Selection, a novel fast and multivariate feature selection method that selects features from small tree structures. Additionally, we also adapt three standard feature selection algorithms for cost sensitive learning by introducing a hyperparameter controlled benefit cost ratio criterion (BCR) for each method. In an extensive simulation study, we assess this criterion, and compare the proposed methods to multiple performance based baseline alternatives on four artificial data settings and seven real world data settings. We show that all methods using a hyperparameterized BCR criterion outperform the baseline alternatives. In a direct comparison between the proposed methods, each method indicates strengths in certain settings, but no one fits all solution exists. On a global average, we could identify preferable choices among our BCR based methods. Nevertheless, we conclude that a practical analysis should never rely on a single method only, but always compare different approaches to obtain the best results.
Construction of Optimum Composite Field Architecture for Compact High Throughput AES S Boxes
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Year: 2012

In this work, we derive three novel composite field arithmetic (CFA) Advanced Encryption Standard (AES) S boxes of the field GF((22)2)2) The best construction is selected after a sequence of algorithmic and architectural optimization processes. Furthermore, for each composite field constructions, there exists eight possible isomorphic mappings. Therefore, after the exploitation of a new common subexpression elimination algorithm, the isomorphic mapping that results in the minimal implementation area cost is chosen. High throughput hardware implementations of our proposed CFA AES S boxes are reported towards the end of this paper. Through the exploitation of both algebraic normal form and seven stages fine grained pipelining, our best case achieves a throughput 3.49 Gbps on a Cyclone II EP2C5T144C6 field programmable gate array.
Dynamic Representation Learning for Video Action Recognition Using Temporal Residual Networks
Venue: 2018 IEEE SmartWorld, Ubiquitous Intelligence Computing, Advanced Trusted Computing, Scalable Computing Communications, Cloud Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)
Year: 2018

Recent progresses in video action recognition are driven by the great success of convolutional neural networks (ConvNets) Many researches have investigated modeling spatiotemporal architecture with ConvNets to take full advantage of video information. However, the quality of video representations that serve as the network inputs, is often insufficient due to significant background motion. In this paper, we propose an Improved Dynamic Image (IDI) to describe videos by applying salient object detection and rank pooling on sequence of still images. Saliency detection aims to segment objects of interest which can be viewed as image level background motion removal, while rank pooling is used to construct dynamic images as input to ConvNets. We also present a temporal Residual Network (ResNet) architecture which directly operates on multiple IDIs for long term video representations learning. Experiments on two standard action recognition benchmarks demonstrate that our method achieves state of the art performance without combining video level representations (e.g. dense optical flow) as well as hand designed features (e.g. improved dense trajectories)
A community driven hypertension treatment group in rural Honduras
Venue: Global health action
Year: 2015

We formed a self funded hypertension treatment group in a resource poor community in rural Honduras. After training community health workers and creating protocols for standardized treatment, we used group membership fees to maintain the group, purchase generic medications in bulk on the local market, and hire a physician to manage treatment. We then assessed whether participation in the group improved treatment, medication adherence, and hypertension control.  This is a program evaluation using quasi experimental design and no control group. Using data from the 86 members of the hypertension treatment group, we analyzed baseline and follow up surveys of members, along with 30 months of clinical records of treatment, medication adherence, and blood pressure readings.  Our initial hypertension needs assessment revealed that at baseline, community hypertensives relied on the local Ministry of Health clinic as their source of anti hypertensive medications and reported that irregular supply interfered with medication adherence. At baseline, hypertension group members were mainly female, overweight or obese, physically active, non smoking, and non drinking. After 30 months of managing the treatment group, we found a significant increase in medication adherence, from 54.8 to 76.2% (p<0.01) and hypertension control <140/90 mmHg) from 31.4 to 54.7% (p<0.01) We also found a mean monthly decrease of 0.39 mmHg in systolic blood pressure (p<0.01) At the end of the 30 month observation period, the local Ministry of Health system had increased provision of low cost anti hypertensive medications and adopted the hypertension treatment group's treatment protocols.  Formation of a self funded, community based hypertension treatment group in a rural, resource poor community is feasible, and group participation may improve treatment, medication adherence, and hypertension control and can serve as a political driver for improving hypertension treatment services provided by the public system.
Preload on draft gear in freight trains
Year: 2018

Adjusting draft gear preloads requires minimum or no structural changes to the existing coupler systems. Better or optimal preloads are more promising to be implemented than modifying other parameters such as wedge angles and spring stiffness. This paper presents a method to model draft gear preloads and investigates the numerical step size requirements for the simulations of draft gear preloads. The implications of preloads on the draft gear impact performance, longitudinal train dynamics performance and coupler fatigue damage were also investigated. The results show that step sizes of less than 2.5 and 0.2 ms (with the fourth Runge Kutta solver) are recommended to simulate preloads during the simulations of longitudinal train dynamics and wagon impacts, respectively. Wagon impact simulations indicate that the increase of draft gear preloads can noticeably decrease the maximum draft gear deflection during wagon impacts. Longitudinal train dynamics simulations for a distributed power train with 214 vehicles on a 320 km long track were conducted. The longitudinal train dynamics simulations indicate that, when the preload is increased from 0 to 100 kN, the difference of maximum vehicle accelerations is insignificant. When the draft gear preload is further increased to 200 or 300 kN, maximum vehicle accelerations are evidently increased. Draft gear preloads do not noticeably influence the maximum tensile coupler forces. However, preloads have evident implications for maximum compressive coupler forces, especially for the second half of the train. Coupler fatigue damage calculations show that the sum of coupler fatigue damage evidently decreases with the increase of draft gear preload. The damage for the zero preload case is 8.7 times than that of the 300 kN preload case.
MATHEMATICAL PREDICTIONS FOR COVID 19 AS A GLOBAL PANDEMIC
Venue: medRxiv
Year: 2020

This study shows that the disease free equilibrium (E_0 for COVID 19 coronavirus does not satisfy the criteria for a locally or globally asymptotic stability. This implies that as a pandemic as declared by WHO (2020) the COVID 19 coronavirus does not have a curative vaccine yet and precautionary measures are advised through quarantine and observatory procedures. Also, the Basic Reproductive number (R_0<1) by Equation (33) shows that there is a chance of decline of secondary infections when the ratio between the incidence rate in the population and the total number of infected population quarantined with observatory procedure. The effort to evaluate the disease equilibrium shows that unless there is a dedicated effort from government, decision makers and stakeholders, the world would hardly be reed of the COVID 19 coronavirus and further spread is eminent and the rate of infection will continue to increase despite the increased rate of recovery because of the absence of vaccine at the moment.
Implementation of Secure Hash Algorithm 256
Year: 2017

Hash functions play a significant ro le in today's cryptographic applications. SHA (Secure Hash Algorithm) is famous message compress standard used in computer cryptography, it can compress a long message to become a short message abstract. In this paper, SHA256 is implemented using Verilog HDL (Hardware Description Language) The SHA 256 Verilog source code is divided into three modules, namely Init ial, Round and Top module. The Verilog code is synthesized on Spartan 3E FPGA using Xilinx Chipscope Pro software tool. The test vectors have been applied to verify the correctness of the SHA 256 functionality. A comparison between the proposed SHA 256 hash function implementation with other related works shows that it achieves the introduced system can working higher operation frequency and needs less silicon area resources. The achieved performance in t he term of throughput of the proposed system/architecture is much higher than the other hardware implementations. The proposed system could be used for the implementation of integrity units, and in many other sensitive cryptographic applications, such as, digital signatures, message authentication codes and random number generators.
Economics, adoption determinants, and impacts of micro irrigation technologies: empirical results from India
Venue: Irrigation Science
Year: 2007

Micro irrigation technologies are promoted for various reasons in India. Despite the reported significant economic advantages, and the concerted support of the government and NGOs, the current micro irrigation area in India remains an insignificant proportion of its potential.  the economics of alternative micro irrigation technologies, (2) the determinants of adoption, (3) the poverty outreach of the different micro irrigation systems, and (4) the sustainability implications of micro irrigation adoption. In line with the findings of other studies, this study indicates that micro irrigation technologies result in a significant productivity and economic gains. The most important determinants of micro irrigation adoption include access to groundwater, cropping pattern, availability of cash, and level of education, the social status and poverty status of the farmer. Contrary to the expectations, the majority of the current adopters of low cost micro irrigation systems are the better off farmers. The study indicates that the impact of micro irrigation systems on the sustainability of groundwater resources depends upon the magnitude of the overall productivity gain following the shift from traditional irrigation method to micro irrigation system, the pattern of use of the saved water, and the type and potential number of adopters.