Miracle-dz/UniFAR-FTUs huggingface dataset:
ROOT CAUSES OF THE MAIN DIFFICULTIES FOUND BY THE ENGINEERING DEGREE STUDENTS IN THE SUBJECT NUMERICAL METHODS

This research is part of the Teaching Innovation Project of the University of Oviedo “Reinforcement of basic mathematical concepts throughout engineering degrees. Detection of conceptual errors" (PINN18-A-087) Several authors note that certain errors are made by a high percentage of students in mathematics subjects, as has also been detected in this paper. This circumstance seems to be widespread not only in Spain, but also in several European countries. In the case of engineering students, several researchers have verified the existence of a deficient previous mathematical formation. The reasons why students make mistakes in math can be very diverse. But when these errors are very similar between very different students, from different schools and without having had previous contact, the reason or reasons for these errors may be more limited. From this study we intend to study these errors. In the studies carried out during the academic year 2018-19 by the Bacunimat group, formed by the teachers who applied for the Project referred to above, we highlight one of the conclusions obtained: "The first-year students of the Engineering degree in the first four-month period come from high schools with some lack of conceptual knowledge of mathematical analysis. In the present Project it is verified that these insufficiencies improve after taking the subject of Calculus. In addition, no significant differences have been detected by the type of centre of origin, although they do depend on gender". This paper analyzes the mathematical knowledge acquired by students of engineering degrees currently being studied at the Polytechnic School of Gijón (University of Oviedo), at the beginning of the second quarter of the first year. These students, therefore, have already taken the subjects of Calculus and Algebra and during the second term, they are taking Numerical Methods. The research carried out is based on the analysis of the results of a questionnaire. The questionnaire consisted of a test on basic mathematical concepts, consisting of a total of 8 questions, which was passed on to the students in the first sessions of the Numerical Methods subject (January 2019). A total of 89 students responded to the questionnaire. The results obtained have made it possible to carry out an analysis of the degree of assimilation of the subjects of Calculus and Algebra by these students. In addition, this paper also analyzes the relationship between the errors in fundamental concepts shown by students and the way in which these concepts are taught in high school courses.
Developing and validating a questionnaire for evaluating the EFL ‘Total PACKage’: Technological Pedagogical Content Knowledge (TPACK) for English as a Foreign Language (EFL)

ABSTRACT This paper introduces a new self-report questionnaire for the assessment of TPACK for English language teaching which does not prescribe a particular approach to language teaching or the use of particular technologies. Development and validation of the questionnaire involved: (1) creation of an initial item pool based on a review of the literature on Pedagogical Content Knowledge (PCK) and the use of technology in EFL, (2) evaluation of the content validity of the initial items with a panel of 36 international experts in computer-assisted language learning, (3) exploration and validation of the underlying factor structure through the administration of the questionnaire to 542 EFL practitioners and Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). A six-factor solution, comprising PCK, TK, CK, Technological Pedagogical Knowledge (TPK), Technological Content Knowledge (TCK), and Technological Pedagogical Content Knowledge (TPCK), emerged from the EFA and was subsequently confirmed through CFA. The results provide support for approaches to English language teacher education which attempt to integrate TK, PK, and CK, rather than introduce them separately, and which highlight the ways in which emerging and established technologies can be employed to represent language and provide opportunities for communication that are known to promote language acquisition.
Proceedings of the 2004 ACM SIGMM Workshop on Effective Telepresence, ETP '04, New York, NY, USA, October 15, 2004

It gives us great pleasure to welcome you to the 2nd ACM International Workshop on Effective Telepresence. This workshop builds upon the ACM SIGMM 2003 Workshop on Experiential Telepresence (ETP03) held in conjunction with ACM Multimedia last year. Last year's workshop and panel involved a lively debate on what the notion of an experience implies. One of the conclusions was that we are in need of models for knowledge spaces that facilitate new forms of creativity, knowledge exploration and social relationships. We would like this workshop to facilitate a more focused debate, namely about the means of experience in the context of seamless remote interaction. While sophisticated systems for distributed collaboration and immersive presence have emerged from time to time, their acceptance has been limited. The most commonly cited problems with such systems are that they are too difficult to set up and use, and that their value is not commensurate with cost. The challenge, then, is to develop effective telepresence systems that offer appropriate interfaces and tools to enable seamless interaction with remote people and events. This has been recognized as one of the "grand challenges" for the multimedia community. The design and measures of performance of such systems should be centred on end-user experience. The goal of this workshop is to foster a community of researchers advancing the various technical and socio-technical aspects of telepresence. This workshop aims to bring together a good mix of people from academia, industry, and government, and spanning various disciplines including the sciences, engineering, and the arts. An event of this kind is only as good as the quality of the people it can bring together. We have been fortunate to have a diverse program committee of research leaders of the highest expertise and reputation, who showed enthusiasm and support for this workshop. Our program this year includes six papers for oral presentation and nine papers for demo presentation. Together, they should provide an excellent snapshot of the state of research today in telepresence and we hope you like this mix of presentations. We also have three special sessions - two keynote talks and a panel session - based on invitations to some world-renowned people. The keynote talks by Jaron Lanier and Duffie White, and the panel on "Directions and frameworks for effective telepresence" should go a long way in stimulating and guiding future research in this area. This year, we invited workshop participants to post questions and discussions to the workshop website starting several weeks before the workshop. We hope participants find this leading to a more interesting debate in the panel session.
Influence of Gibberellic acid (GA3) on seed germination and seedling growth of Kagzi Lime

A study was conducted to estimate the influence of gibberellic acid (GA3) at different concentrations in different time intervals on seed germination and seedling growth of kagzi lime. The results revealed that Maximum germination percentage (95%) was recorded under treatment with GA3 80 ppm for 12 hours, rate of germination of seeds (25 days), height of plant (18.79 cm) at 120 DAS, number of leaves per plant (26.53), fresh and dry weight of shoot (25.84 g and 14.44 g), tap root (17.44 cm), secondary and fibrous roots (5.98 and 85.99), fresh as well as dry weight (7.04 and 4.95 g), survival percentage (85 percent) in similar treatment. Therefore, it may be concluded that the GA3 at 80 ppm has a significant effect on the seed germination and seedling growth of Kagzi Lime and can be recommended to the grower for obtaining better growth and yield.
Model Risk in Cryptocurrency Governance Reliability Assessments

Cryptocurrencies have entered the economy as alternative money, as speculation objects, and as utility tokens for innovative service-platforms. Cryptocurrencies are based on cryptography-based asset disposals validated by decentralized operators of distributed ledgers according to consented protocols. The integrity of the decentralized operations – that is, the operators’ compliance with the protocol – relies on checks and balances based on, inter alia, insight from game theory. Models are often used to inform the reliability of the governance structures. This paper addresses model risk associated with these models. As the role of cryptocurrencies in the economy increases, such model risk is likely to be a concern for regulators. The regulatory implications of model risk are also discussed in this paper.
Efficient extraction of semantic information from medical images in large datasets using random forests

Large datasets of unlabelled medical images are increasingly becoming available; however only a small subset tend to be manually semantically labelled as it is a tedious and extremely timeconsuming task to do for large datasets. This thesis aims to tackle the problem of efficiently extracting semantic information in the form of image segmentations and organ localisations from large datasets of unlabelled medical images. To do so, we investigate the suitability of supervoxels and random classification forests for the task. The first contribution of this thesis is a novel method for efficiently estimating coarse correspondences between pairs of images that can handle difficult cases that exhibit large variations in fields of view. The proposed methods adapts the random forest framework, which is a supervised learning algorithm, to work in an unsupervised manner by automatically generating labels for training via the use of supervoxels. The second contribution of this thesis is a method that extends our first contribution so as to be applicable efficiently on a large dataset of images. The proposed method is efficient and can be used to obtain correspondences between a large number of object-like supervoxels that are representative of organ structures in the images. The method is evaluated for the applications of organ-based image retrieval and weakly-supervised image segmentation using extremely minimal user input. While the method does not achieve image segmentation accuracies for all organs in an abdominal CT dataset compared to current fully-supervised state-of-the-art methods, it does provide a promising way for efficiently extracting and parsing a large dataset of medical images for the purpose of further processing.
Solar star projects SAM version 2017.9.5 PVwats version 5 model case study & validation

Very Large Photovoltaic Solar Power Plants (VLPVPPs) are a major revolutionary step up not only for economies of scale, but also for %100 renewable power Global Grid. Their designs and investments should be performed in an environmentally friendly, fair, open to very large to small private investors, transparent and reducing relative income inequality approaches. Their investments will easily be possible with new investment models (%0 interest load, %100 private equity, open investment for ordinary people, project developers, private companies etc. with a constraint-based shareholder structuring). These revolutionary investment models will play an important and game changing role. VLPVPPs’ early engineering and investment analysis can be performed on many software. Therefore, validation and verification efforts of those software in advance on the operational PVPPs are essential. This research study aims to present a validation and verification accomplishment of the Solar Star Projects (597 MW AC , 747,3 MW DC ) (Solar Star I: 318 MW AC , 397,8 MW DC & Solar Star II: 279 MW AC , 349,5 MW DC ) in Antelope Valley near Rosamond, Kern and Los Angeles counties, California, United States with the PVWatts Version 5 model of the National Renewable Energy Laboratory (NREL) System Advisor Model (SAM) Version 2017.9. 5. The location and resource, system design data and information of the Solar Star Projects (I & II) are presented based on open source information and personal communications. The Solar Star Projects SAM software models' are simulated on a personal computer (PC) (Windows 10 Pro, Intel(R) Core(TM) i5 CPU 650 @ 3.20 GHZ, 6,00 GB RAM) with the internet connection. The results of eight simple simulations, one parametric simulation and one stochastic simulation are compared with the actual generation data by help of some statistical performance measures (e.g. annual model/actual: 100,0%, annual model/actual: 100,1%, absolute maximum forecast error 39.276 MWh, mean absolute error 11.554 MWh, geometric mean absolute error 8.924 MWh, mean square error 2.662.330.229 MWh, root mean square error 51.597 MWh).
Automatic extraction of constraints in manipulation tasks for autonomy and interaction

T asks routinely executed by humans involve sequences of actions performed with high dexterity and coordination. Fully specifying these actions such that a robot could replicate the task is often difficult. Furthermore the uncertainties introduced by the use of different tools or changing configurations demand the specification to be generic, while enhancing the important task aspects, i.e. the constraints. Therefore the first challenge of this thesis is inferring these constraints from repeated demonstrations. In addition humans explaining a task to another person rely on the persons ability to apprehend missing or implicit information. Therefore observations contain user-specific cues, alongside knowledge on performing the task. Thus our second challenge is correlating the task constraints with the user behavior for improving the robots performance. We address these challenges using a Programming by Demonstration framework. In the first part of the thesis we describe an approach for decomposing demonstrations into actions and extracting task-space constraints as continuous features that apply throughout each action. The constraints consist of: (1) the reference frame for performing manipulation, (2) the variables of interest relative to this frame, allowing a decomposition in force and position control, and (3) a stiffness gain modulating the contribution of force and position. We then extend this approach to asymmetrical bimanual tasks by extracting features that enable arm coordination: the master–slave role that enables precedence, and the motion–motion or force–motion coordination that facilitates the physical interaction through an object. The set of constraints and the time–independent encodings of each action form a task prototype, used to execute the task. In the second part of the thesis we focus on discovering additional features implicit in the demonstrations with respect to two aspects of the teaching interactions: (1) characterizing the user performance and (2) improving the user behavior. For the first goal we assess the skill of the user and implicitly the quality of the demonstrations by using objective task–specific metrics, related directly to the constraints. We further analyze ways of making the user aware of the robot’s state during teaching by providing task–related feedback. The feedback has a direct influence on both the teaching efficiency and the user’s perception of the interaction. We evaluated our approaches on robotic experiments that encompass daily activities using two 7 degrees of freedom Kuka LWR robotic arms, and a 53 degrees of freedom iCub humanoid robot.
The effect of escalation of commitment and project risk in resources allocation decision

This research aims to examine the causal relationship between escalation of commitment and project risk with decision making in resource allocation (production cost). In this research the allocation of resources is in determining the cost of direct labor and material costs. To trigger cognitive dissonance, the determination of higher labor costs will increase the bonus of individuals working as production managers. When kos production has been set in a certain number, labor costs are high, while factory overhead costs is fixed, cause material costs to be low. The lower the material cost, the lower the product quality. Escalation of commitment is a condition when individuals already know the potential risks in the future, but still take risks for their decisions. This study proposes that the production cost allocation decision in conditions of high commitment escalation will tend to choose decisions that benefit themselves compared to when the escalation of commitment is low (choosing a labor cost allocation is higher than the material cost). This research also predicts that individuals in the face of high-risk projects will tend to allocate resources that benefit themselves. In addition, the interaction of the existence of a low level of escalation of commitment and a low risk project level will reduce the allocation of production costs to direct labor costs. This research uses a laboratory experiment design with 102 accounting students at a private university in Central Java who act as production managers with paper and pencil test. This experiment uses a 2x2 between subject. The results of the research show that there is a causal relationship between the escalation of commitment and the allocation of human resources and there is a causal relationship between the escalation of commitment and project risk. This finding also shows that there is an interaction between escalation of commitment, project risk and resource allocation decisions.
ICTs and online resources used for meeting information needs by agricultural researchers and extension workers in Edo State, Nigeria

The study ascertained ICTs and online resources used for meeting information needs by agricultural researchers and extension workers in Edo State, Nigeria. Survey design was used in the study. ICTs /online resources used by respondents to meet their information needs were: computers (95.1%), internet (90.2%), mobile/cell phones (86.3%), dictionaries (79.4%), electronic books (e-books) (78.4%), and electronic journals (e-journals) (77.5%). The majority (82.4%) indicated their purpose of using ICTS/online resources was for research purposes. Researchers acquired their e-resources majorly from the internet (83.9%) and extension workers acquired their e-resources through subscriptions made through the consortium for university and research libraries (87.5%). The study recommends that Edo State ministry of agriculture and agricultural research institutes in the state, should subscribe for online resources for the benefit of respondents who desire to use relevant online resources but are hindered by cost and technical issues.
The moderating impact of gender on the acceptance of peer-to-peer mobile payment systems

Purpose The purpose of this paper is to determine the significant antecedents of peer-to-peer (P2P) m-payment acceptance and explore the moderating effects of gender on the influence of these predictors with regards to intention of using the system. Design/methodology/approach The research was conducted on a sample comprised of 701 Spanish smartphone users. A multi-group structural equation modeling analysis was used to test the moderating effect of gender with a particular focus on the relationships between the latent variables of the research model. Findings The study identified significant differences between the two observed groups – the results show that men are more likely to use mobile payments than women and are therefore less influenced by the potential risks involved. In addition, men are more easily influenced by their social environment, whereas women are more influenced by their personal innovativeness. Originality/value The study proposes a three-level model, based on an extended TAM model. It is a pioneering study, exploring the effects of gender on P2P m-payment acceptance. Due to its novel value and the potential involved, the results of the study may be of great importance for m-payment providers, particularly in marketing strategy planning and customer segmentation.
A cost-effective and reliable measurement strategy for 3D printed parts by integrating low- and high-resolution measurement systems

ABSTRACT Metrology data are crucial to quality control of three-dimensional (3D) printed parts. Low-cost measurement systems are often unreliable due to their low resolutions, whereas high-resolution measurement systems usually induce high measurement costs. To balance the measurement cost and accuracy, a new cost-effective and reliable measurement strategy is proposed in this article, which jointly uses two-resolution measurement systems. Specifically, only a small sample of base parts are measured by both the low- and high-resolution measurement systems in order to save costs. The measurement accuracy of most parts with only low-resolution metrology data is improved by effectively integrating high-resolution metrology data of the base parts. A Bayesian generative model parameterizes a part-independent bias and variance pattern of the low-resolution metrology data and facilitates a between-part data integration via an efficient Markov chain Monte Carlo sampling algorithm. This multi-part two-resolution metrology data integration highlights the novelty and contribution of this article compared with the existing one-part data integration methods in the literature. Finally, an intensive experimental study involving a laser scanner and a machine visual system has validated the effectiveness of our measurement strategy in acquisition of reliable metrology data of 3D printed parts.
Communication Costs and Incentives to Acquire Soft and Hard Knowledge

We study a multiple tasking principal-agent model where the agent gathers soft and hard knowledge for operational purposes. Within this set-up, we model communication from the agent to the principal as the process of hardening and transmitting soft knowledge, in the spirit of Dewatripont and Tirole (2005), and we assume that soft information, once hardened, can be used by the principal as a measure of the agent contribution to production (e.g., for incentive purposes). The assumption that hard and soft knowledge are complements in the communication technology, which naturally reflects the non-depletable nature of hard knowledge, leads to the following results. Under full delegation of information gathering choices, the agent’s private incentives to gather hard information fall short of social incentives; therefore, in the second best, the principal imposes the agent to gather more hard information than he would freely do were his decision reflect market prices (e.g., under full delegation).
Impact of Behavioral Factors in Making Investment Decisions and Performance: Study on Investors of National Stock Exchange

Market anomalies and irrational behavior caused investors changes in the stock market, and this has led to an investigation into the impact of various behavioral biases and factors affecting decision-making for individual investors. The purpose of this study was to find out the effect of the four factors, heuristic, prospect, market, herding on decisions of investors at NSE. Data are collected from the questionnaire on the basis of a likert scale. To determine the reliability of the questionnaire, the Cronbach alpha factor, which was 0.728, was used. EFA and multiple regression tests have been applied. Cronbach-alpha was used to check the interal consistency of the element. Cronbach alpha emphasized to each factor: Heuristic, Prospect, Market, Herding, Investment performance and Investors decisions that consistency at an acceptable level. The result of the analysis is that the four variables have greatly influenced the investment decision and return on investment. All behavioral variables have a significant impact on the decision-making process of investors, which led to the acceptance of all assumptions regarding the level of influence of behavioral factors in decision making for individual investors.