nils-herrmann/clean_scirepeval huggingface dataset:
Confirmatory model of mathematics self efficacy, problem solving skills and prior knowledge on mathematics achievement: a structural equation model

The purpose of the current study was to determine the effects of mathematical problem solving skills and prior mathematics knowledge on mathematics achievement and mathematics self efficacy. Also the effect of mathematics self efficacy on mathematics achievement was demonstrated. The subjects of the study were middle school students (males and females) of the academic year 2013. 400 of 8th graders were selected from four public schools of Shiraz in Iran. A two stage Cluster Random Sampling Method was utilized. Structural Equation Model was used to analyze the data. The estimate of Structural Equation Model revealed that mathematical problem solving skills and prior mathematics knowledge had a direct and an indirect effect through mathematics self efficacy on mathematics achievement. The high goodness of fit indices that model had a good fit to the given data (kh2=2.520 5) Additionally, Confirmatory Factor Analysis was used for validity and reliability of instruments. The results showed the Construct Reliability value for all of subscales were more than .70. Furthermore, the finding of this study indicated the significant relationship between predictor's variables (problem solving skills, prior mathematics knowledge) mathematics self efficacy as mediator, and mathematics achievement as criterion variable. The findings supported the hypothesized role of self efficacy in Bandura's (1986) social cognitive theory and Schoenfeld's (1985) mathematical problem solving theory. This study hopes to accomplish a perfect framework for educators, students, and the Ministry of Education. The obtained results of the current study will bring advantages to the researchers and educators.
Anatomy of the Antarctic Circumpolar Current volume transports through Drake Passage

The 20 year (October 1992 to August 2013) observation based volume transport time series of the Antarctic Circumpolar Current (ACC) through Drake Passage (DP) across the Jason altimeter track #104 is analyzed to better understand the ACC transport variability and its potential causes. The time series of three transport components (total (TT) barotropic (BT) and baroclinic (BC) referenced to 3000 m present energetic intraseasonal fluctuations, with a salient spectral peak at 50 and 36 days, with the largest (least) variance being associated with the BT (BC) component. Low frequency variations are much less energetic with a significant variance limited to the annual and biannual timescales and show a nonstationary intermittent link with the Southern Annular Mode and the Nino 3.4 index for interannual timescales. The region around 57degS in the Yaghan Basin appears to be a strategic point for a practical monitoring of the ACC transport as the whole track TT is significantly correlated with the local TT (r=5 0.53) and BT (r=5 0.69) around 57degS. These local BT (and TT) variations are associated with a well defined tripole pattern in altimetric sea level anomaly (SLA) There is evidence that the tripole pattern associated with BT is locally generated when the BC associated mesoscale SLAs, which have propagated eastward from an upstream area of DP, cross the Shackleton Fracture Zone to penetrate into the Yaghan Basin. Barotropic basin modes excited within the Yaghan Basin are discussed as a plausible mechanism for the observed energy containing intra seasonal spectral peaks found in the transport variability.
A secure and efficient authenticated encryption for electronic payment systems using elliptic curve cryptography
Venue: Electron. Commer. Res.

The use of e payment system for electronic trade is on its way to make daily life more easy and convenient. Contrarily, there are a number of security issues to be addressed, user anonymity and fair exchange have become important concerns along with authentication, confidentiality, integrity and non repudiation. In a number of existing e payment schemes, the customer pays for the product before acquiring it. Furthermore, many such schemes require very high computation and communication costs. To address such issues recently Yang et al. proposed an authenticated encryption scheme and an e payment scheme based on their authenticated encryption. They excluded the need of digital signatures for authentication. Further they claimed their schemes to resist replay, man in middle, impersonation and identity theft attack while providing confidentiality, authenticity, integrity and privacy protection. However our analysis exposed that Yang et al.'s both authenticated encryption scheme and e payment system are vulnerable to impersonation attack. An adversary just having knowledge of public parameters can easily masquerade as a legal user. Furthermore, we proposed improved authenticated encryption and e payment schemes to overcome weaknesses of Yang et al.'s schemes. We prove the security of our schemes using automated tool ProVerif. The improved schemes are more robust and more lightweight than Yang et al.'s schemes which is evident from security and performance analysis.
The Future of the Mobile Payment as Electronic Payment System

The development of the Internet and the arrival of e commerce fostered digitalization in the payment processes by providing a variety of electronic payment options including payment cards (credit and debit) digital and mobile wallets, electronic cash, contactless payment methods etc. Mobile payment services with their increasing popularity are presently under the phase of transition, heading towards a promising future of tentative possibilities along with the innovation in technology. In this paper, we will evaluate the current state and growth of mobile payments and other electronic payment systems in markets around the world and take a look at the future of this industry. We analyze various systems of electronic payment services, security issues related to them and the future of the mobile payment mode. This paper will also examines the factors affecting adoption of mobile payment methods by consumers. With all the security and convenience provided by mobile electronic payment method, we can expect further growth of mobile payments worldwide even surpassing payments made by credit and debit cards. However, there are several barriers identified to the adoption of this payment method; so certain measures should be taken to grant this industry a promising future ahead.
Computers And Intractability A Guide To The Theory Of Np Completeness

Thank you for downloading computers and intractability a guide to the theory of np completeness. As you may know, people have search numerous times for their favorite books like this computers and intractability a guide to the theory of np completeness, but end up in harmful downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they juggled with some harmful bugs inside their desktop computer.
Computers And Intractability A Guide To The Theory Of Np Completeness

Thank you very much for reading computers and intractability a guide to the theory of np completeness. As you may know, people have look hundreds times for their favorite novels like this computers and intractability a guide to the theory of np completeness, but end up in infectious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they juggled with some harmful virus inside their desktop computer.
Implementation of Circular Economy Business Models by Small and Medium Sized Enterprises (SMEs) Barriers and Enablers

Small and medium sized enterprises (SMEs) are increasingly aware of the benefits of closing loops and improving resource efficiency, such as saving material costs, creating competitive advantages, and accessing new markets. At the same time, however, various barriers pose challenges to small businesses in their transition to a circular economy, namely a lack of financial resources and lack of technical skills. The aim of this paper is to increase knowledge and understanding about the barriers and enablers experienced by SMEs when implementing circular economy business models. Looking first at the barriers that prevent SMEs from realising the benefits of the circular economy, an investigation is carried out in the form of a literature review and an analysis of a sample of SME case studies that are featured on the GreenEcoNet EU funded web platform. Several enabling factors that help SMEs adopt circular economy practices are then identified. The paper concludes that although various policy instruments are available to help SMEs incorporate circular economy principles into their business models, several barriers remain. The authors recommend that European and national policies strengthen their focus on greening consumer preferences, market value chains and company cultures, and support the recognition of SMEs' green business models. This can be achieved through the creation of dedicated marketplaces and communities of practice, for example.
Joint visual denoising and classification using deep learning
Venue: 2016 IEEE International Conference on Image Processing (ICIP)

Visual restoration and recognition are traditionally addressed in pipeline fashion, i.e. denoising followed by classification. Instead, observing correlations between the two tasks, for example clearer image will lead to better categorization and vice visa, we propose a joint framework for visual restoration and recognition for handwritten images, inspired by advances in deep autoencoder and multi modality learning. Our model is a 3 pathway deep architecture with a hidden layer representation which is shared by multi inputs and outputs, and each branch can be composed of a multi layer deep model. Thus, visual restoration and classification can be unified using shared representation via non linear mapping, and model parameters can be learnt via backpropagation. Using MNIST and USPS data corrupted with structured noise, the proposed framework performs at least 20% better in classification than separate pipelines, as well as clearer recovered images.
Deep Learning for Surface Material Classification Using Haptic and Visual Information
Venue: IEEE Transactions on Multimedia

When a user scratches a hand held rigid tool across an object surface, an acceleration signal can be captured, which carries relevant information about the surface material properties. More importantly, such haptic acceleration signals can be used together with surface images to jointly recognize the surface material. In this paper, we present a novel deep learning method dealing with the surface material classification problem based on a fully convolutional network, which takes the aforementioned acceleration signal and a corresponding image of the surface texture as inputs. Compared to the existing surface material classification solutions which rely on a careful design of hand crafted features, our method automatically extracts discriminative features utilizing advanced deep learning methodologies. Experiments performed on the TUM surface material database demonstrate that our method achieves state of the art classification accuracy robustly and efficiently.
Enjoyment, resistance to change and mlearning acceptance among pre service teachers
Venue: TEEM

This communication presents the results derived from a study carried out in the University of Salamanca to analyze the intention to use mobile devices in the future teaching practice of the student from the Pre primary Education Teacher Bachelor's Degree from said university. In order to do so, we developed a TAM model expanded with the constructs of perceived enjoyment and resistance to change, both adapted to the abovementioned object of study. The sample was composed of 382 students from the University of Salamanca who participated willingly. The results reflect a good disposition towards the use of mobile technology in the future teaching practice of the students. The hypothesis testing barely shows any significant differences according to the course year of the students, although we can observe some differences according to the branch of the university that the students attend to.
Analisis Framing dalam Riset Public Relations

This paper aims to give description about how to use frame analysis in Public Relations (PR) research. The author use two framing models: Entman and Pan Kosicki. The object is organization official statement about particular issue. Frame analysis method rarely used in Public Relations research. This methods commonly use in journalism study, to analyse the news in media. Meanwhile, the key word of framing is the social construction of reality. Organization can make social construction of realty in their official statement. In acacemic term, frame analysis in PR research is useful to know how organization positioned themselves in particular situation. Other benefit is use to evaluat whether the organization frame is conformable with the public opinion or agenda setting media or not. In practical term, frame analysis give benefit for PR practitioner to create the message that can be undserstood by public, also give positive image for organization.
Profile Image: Ways of Self (re )presentation on the Facebook Social Network

This chapter focuses on the description of the profile image and the entire communicative ecosystem on the Facebook social network. In doing so, it presents the results of the inventory and classification of 7200 profile pictures of Facebook users from 24 different cities around the world. The classification criteria were initially based on a model which includes entity, treatment and framing (ETF) of the image. Although our study does not focus specifically on youth, we also present a number of results in relation to this demographic group, as it experiences digital technologies as an answer to its expressive needs and the kinds of identity exploration which characterise our modern social life. Finally, we introduce some conclusions about the integration of digital technologies into everyday life.
The MaxQuant computational platform for mass spectrometry based shotgun proteomics
Venue: Nature Protocols

MaxQuant is one of the most frequently used platforms for mass spectrometry (MS) based proteomics data analysis. Since its first release in 2008, it has grown substantially in functionality and can be used in conjunction with more MS platforms. Here we present an updated protocol covering the most important basic computational workflows, including those designed for quantitative label free proteomics, MS1 level labeling and isobaric labeling techniques. This protocol presents a complete description of the parameters used in MaxQuant, as well as of the configuration options of its integrated search engine, Andromeda. This protocol update describes an adaptation of an existing protocol that substantially modifies the technique. Important concepts of shotgun proteomics and their implementation in MaxQuant are briefly reviewed, including different quantification strategies and the control of false discovery rates (FDRs) as well as the analysis of post translational modifications (PTMs) The MaxQuant output tables, which contain information about quantification of proteins and PTMs, are explained in detail. Furthermore, we provide a short version of the workflow that is applicable to data sets with simple and standard experimental designs. The MaxQuant algorithms are efficiently parallelized on multiple processors and scale well from desktop computers to servers with many cores. The software is written in C# and is freely available at http:/www.maxquant.org.
Supplier Involvement in New Product Development: A Case Study from the Semiconductor Industry

SUPPLIER INVOLVEMENT IN NEW PRODUCT  A CASE STUDY FROM THE SEMICONDUCTOR INDUSTRY Ozalp Vayvay, Maria Manuela Cruz Cunha The global competition requires that the companies adapt themselves to technological changes rapidly, develop new products, reduce the cost, shorten the time to market, and increase the quality. In this context, supplier involvement in New Product Development (NPD) is determinant for a company to respond to the requirements of the increasingly dynamic markets. The main purpose of the paper is to demonstrate the importance of supplier involvement in NPD, buyersupplier relationships and their effects on buyer's NPD process, highlighting the benefi ts of supplier involvement, the barriers, the strategic aspects and industry aspects. These issues are addressed with a case study from the semiconductor industry. Besides helping to understand NPD in the semiconductor industry, the contribution and fi ndings of this work are clear: the results achieved confi rm the fi ndings of studies referred in the literature review, and confi rm that the semiconductor industry sector requires a closer and more complex relationship structure with suppliers, given the specifi cities and challenges of the sector, such as rapid technological changes, permanent innovation, global competition, reduction of cost and time to market cycle, increased capacity, among other. The main contribution of the paper to the scientifi c literature and to managers is the better understanding of the buyer supplier relationships in NPD in the semiconductor industry.
DIRECT TORQUE CONTROL OF WIND TURBINE DRIVEN DOUBLY FED INDUCTION GENERATOR

1 Universite de Bejaia, Faculte de Technologie, Laboratoire de Technologie Industriel et de l'Information, 06000, Algerie,  idjdarene@yahoo.fr, to_reki@yahoo.fr 2 Universite de Batna, Faculte de Technologie, Laboratoire d'Electrotechnique de Batna, 05000, Algerie, E mail: rachid.abdessemed@gmail.com. DIRECT TORQUE CONTROL OF WIND TURBINE DRIVEN DOUBLY FED INDUCTION GENERATOR
STUDY ON SLIDING MODE VIRTUAL FLUX ORIENTED CONTROL FOR THREE PHASE PWM RECTIFIERS

This paper presents the design of the sliding mode control technique for three phase boost type PWM rectifier based on virtual flux vector orientation. A sliding mode control algorithm on synchronous rotating reference frame is employed for each current and dc voltage control loops. The Lyapunov direct method is used to ensure the reaching and sustaining of the sliding mode. The logic control signals (Sa, Sb, Sc) are calculated by using the space vector modulation (SVM) technique. To alleviate chattering phenomenon without compromising system robustness, a tangent hyperbolic function is used in the dc voltage loop instead of a conventionally sign function. The proposed sliding mode control system has been simulated using MATLAB SIMULINK Software and compared with traditional PI controller. The comparison shows that the sliding mode control scheme is more robust against load changes and power supply variations. Furthermore, it confers better dynamic performance.
A precise BP neural network based online model predictive control strategy for die forging hydraulic press machine
Venue: Neural Computing and Applications

The time variance and nonlinearity of forging processes pose great challenges to high quality production. In this study, a one step ahead model predictive control (MPC) strategy based on backpropagation (BP) neural network is proposed for the precise forging processes. Two online updated BP neural networks, predictive neural network (PNN) and control neural network (CNN) are developed to accurately control the die forging hydraulic press machine. The PNN and CNN are utilized to predict the output (the velocity of upper die) and determine the input (the oil pressure of driven cylinders) respectively. The weights of neural networks are initially trained offline and then updated online according to an error backpropagation algorithm. In the proposed control strategy, only the input and output are required, which makes the forging process easy to be controlled. In addition, because of the generalized ability and adaptability of neural networks, the proposed predictive controller can well deal with the time variance and nonlinearity of forging process. Two forging experiments demonstrate the feasibility and effectiveness of the proposed strategy. Moreover, comparing the proposed MPC strategy with the traditional MPC approach and PID controller, it can be found that the proposed MPC strategy is the most effective control approach for the practical forging process.
An energy saving method to solve the mismatch between installed and demanded power in hydraulic press

Improving the energy efficiency of hydraulic presses has become an important field of research in low carbon manufacturing systems. The mismatch between installed and demanded power is the main cause of low energy efficiency among hydraulic presses. This study presents an energy saving method to solve the problem, where a single drive system composed of several motor pumps, is partitioned into several drive zones corresponding to load profiles. The system is used to supply power to several hydraulic presses with approximately same installed power. Each drive zone is shared by grouped hydraulic presses in the same operation. Furthermore, a method for scheduling drive zones is presented to share drive zone with no conflict and shorten their idle time. The composition of each drive zone is optimized to match the power demand of each operation to achieve the scheduling schemes. The proposed energy saving method is applied to a hydraulic press group in the case study. Results show that the energy efficiency of a single hydraulic press in the group is increased by approximately 20% and the average energy consumption can be reduced by 43% compared with the traditional setup.
Greenhouse gases (GHG) emissions analysis of manufacturing of the hydraulic press slider within forging machine in China

Product manufacturing stage is one of the main contributors for greenhouse gases (GHG) emissions in China. The study aims to find the potential to control GHG emissions during forging machine's manufacturing stage in China for substantially reducing energy consumption and GHG emissions. Taking hydraulic press slider, a typical part of forging machines, as the research object, a complete GHG emission calculation method is proposed for its manufacturing stage, and the key factors affecting the GHG emissions are analyzed in order to provide support for the low carbon design and manufacturing of forging machines. The results show that the use of raw material of steel sheet is the largest contributor to GHG emissions in the manufacturing stage of forging machines, followed by welding. Some possible solutions to reduce the GHG emissions are also discussed.