nils-herrmann/clean_scirepeval huggingface dataset:
Computer Age Statistical Inference: Algorithms, Evidence, and Data Science

The twenty first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data' 'data science' and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories Bayesian, frequentist, Fisherian individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
PointNet: A 3D Convolutional Neural Network for real time object class recognition
Venue: 2016 International Joint Conference on Neural Networks (IJCNN)

During the last few years, Convolutional Neural Networks are slowly but surely becoming the default method solve many computer vision related problems. This is mainly due to the continuous success that they have achieved when applied to certain tasks such as image, speech, or object recognition. Despite all the efforts, object class recognition methods based on deep learning techniques still have room for improvement. Most of the current approaches do not fully exploit 3D information, which has been proven to effectively improve the performance of other traditional object recognition methods. In this work, we propose PointNet, a new approach inspired by VoxNet and 3D ShapeNets, as an improvement over the existing methods by using density occupancy grids representations for the input data, and integrating them into a supervised Convolutional Neural Network architecture. An extensive experimentation was carried out, using ModelNet a large scale 3D CAD models dataset to train and test the system, to prove that our approach is on par with state of the art methods in terms of accuracy while being able to perform recognition under real time constraints.
Niche tourism in Cyprus: conceptualising the importance of social entrepreneurship for the sustainable development of islands

The idiomorphic character of islands makes them important destinations worldwide. However, in an effort for islands to be competitive in the global economic sphere, their resources are often overutilised for the sake of tourism and the unregulated pressures of human development. Cyprus is an example of an island that, despite its long past in regard to tourism, faces problems of saturation, decreased competitiveness, and unbalanced development. As such, sustainability concerns regarding islands' future are raised and more emphasis towards their sustainable development is needed. Nonetheless, social entrepreneurship focusing on the creation of innovative products and procedures that would benefit the entire local community could become an important vehicle for sustainable development of sensitive destinations, such as islands. The aim of this conceptual paper is to explore the notion of social entrepreneurship in an island context focusing on the island of Cyprus. In this regard, the paper explores how islands' distinctive elements as small destinations can address the concept of social entrepreneurship in a sustainable manner. The paper proposes that niche tourism products and more specifically, volunteer, cultural heritage and eco tourism, under the prism of social entrepreneurship, can become the means towards islands' product diversification and long term environmental, social, and economic sustainability.
Surface morphology control of In2S3 buffer layer by Sn incorporation and its application to cadmium free Cu(In,Ga)Se2 thin film solar cells

Sn atoms were incorporated into In 2 S 3 thin film to modify the morphology of the In 2 S 3 buffer layer for Cd free Cu(In,Ga)Se 2 (CIGS) thin film solar cells. The incorporation of Sn atoms into the In 2 S 3 films was carried out by adding a SnCl 2 dissolved solution to an InCl 3 and CH 3 CSNH 2 dissolved solution during chemical bath deposition process. With Sn incorporation into In 2 S 3 film, the surface morphology of In 2 S 3 film was significantly changed showing more uniform and smooth film. Raman spectroscopic analysis shows that the backbone of In 2 S 3 lattice disappear completely with 10% Sn incorporation in the film. In addition to effect of Sn content on the surface morphology of In 2 S 3 film, we found that the morphology of Sn incorporated In 2 S 3 film strongly depends on the pH value in the reaction solution. At the pH value of 2.53, the film became very dense without pores and secondary phases. The film was completely covered the surface of CIGS substrate. Photoluminescence analysis indicates that the shallow acceptor levels at the CIGS surface might be passivated by Sn doping during chemical bath deposition process. As a result, the efficiency of CIGS solar cell with 4.9% Sn doped In 2 S 3 buffer was improved from 9.98 to 12.7%
John Dewey and the Role of the Teacher in a Globalized World: Imagination, empathy, and 'third voice'

Reforms surrounding the teacher's role in fostering students' social competences, especially those associated with empathy, have moved to the forefront of global higher education policy discourse. In this context, reform in higher education teaching has been focused on shifting teachers' practices away from traditional lecture style teaching historically associated with higher education teaching towards student centred pedagogical approaches, largely because of how the latter facilitate students' social learning, including the development of students' abilities connected to empathy, such as intercultural understanding. These developments towards learner oriented higher education teaching may offer promising opportunities; however, a central problem within these current policy recommendations is that the connection between cultivating empathy and cultivating imagination is not explicitly foregrounded. Against this background, I turn to Dewey's notion of imagination to show how imagination is indispensable to all learning, and therefore has a role to play in teaching. In this article, I show how imagination is not only deeply connected to empathy, but also critical for gaining intercultural understanding and is a condition for the possibility that, as human beings, we can learn with and from others. On this basis, I argue that Dewey's notion of imagination provides significant insight on how to rethink what is needed to create inclusive classrooms in higher education, especially under conditions of cultural, linguistic and religious diversity. First, I consider Dewey's concept of learning and the indispensable role of imagination in learning. Second, drawing on the work of Martha Nussbaum, I examine how teaching through the narrative arts in higher education cultivates the imagination and helps us engage the lives of others. I use an example from my own teaching to illustrate how the narrative arts can foster dialogue across difference through the development of what I call 'third voice' a different or other 'position' that productively mediates reflective interaction between participants, including teacher and learners. In closing, I consider the implications of my discussion for present and future higher education policy on the evaluation of 'quality teaching'
Practice makes pedagogy John Dewey and skills based sustainability education

The purpose of this paper is to ground contemporary sustainability education in John Dewey's democratic pedagogy. Specifically, the authors argue that Dewey's thought anticipates, and theoretically informs, the sustainability skill set required of contemporary citizens in a complex and changing world.  For illustrative purposes, the authors consider how these skills are at work in current approaches to the adaptive co management of ecosystems, and they argue that these same skills are at work across professional and cultural contexts, toward the achievement of sustainable societies. In turn, the authors situate Dewey's relevance to contemporary sustainability education in his writing on interdependence, fallibilism and experimentalism.  Dewey's writings provide both a historical antecedent and still valid moral and practical justification for sustainability education's emphasis on integrated and adaptive learning.  Grounding sustaina.
Beyond 'either or' thinking: John Dewey and Confucius on subject matter and the learner

This article compares the educational thought of John Dewey and Confucius on the nature of and relationship between subject matter and the learner. There is a common perception in the existing literature and discourse that Dewey advocates child or learner centred education whereas Confucius privileges subject matter via textual transmission. Challenging such a view, this article argues that both Dewey and Confucius reject an 'either subject matter or learner' thinking that recognises no intermediate possibilities in between. Instead, both thinkers emphasise the importance of both subject matter and the learner, and maintain that educators need to direct learning by integrating appropriate content into the learner's total experience. The article concludes by highlighting the contemporary relevance and educational implications of the views of Dewey and Confucius for the current trend to promote 'student centred education'
Why Should Scholars Keep Coming Back to John Dewey?

This essay attempts to explain why philosophers, philosophers of education, and scholars of democracy should keep coming back to John Dewey for insights and inspiration on issues related to democracy and education. Mordechai Gordon argues that there are four major reasons that contribute to scholars' need to keep returning to Dewey for inspiration and guidance. First, is Dewey's pragmatic educational approach that seeks to maintain quality and stability in schools while rejecting the tendency to implement extreme changes in education based on the shifting winds of time. Second, Dewey's works contain both modern and postmodern elements and as such, it is difficult to label him as a member of one particular school of thought. Third, is the fact that Dewey's body of research represents a wide range of topics and interests from art to politics and from philosophy to the nature and purpose of education. Indeed, many of Dewey's essays and books can be viewed as a dialog between modern and postmodern ideas. Finally, and perhaps most important, Dewey's vision of democracy challenges us to recreate our global communities and our systems of education to meet the changing circumstances of history in such a way that all citizens (not just the wealthy or the powerful) can benefit.
Role of Management Accounting Practices in Creating Values A Case Study of Asia Highway.

Management accounting plays crucial role in a company because management accounting information helps managers to make decision. One of the areas that need critical analysis to make decision is marketing area where customers' satisfaction is essential. In order to sustain customer satisfaction, various efforts need to be done by a company so that values to customer can be delivered. This study examined the role played by management accounting practices in the biggest highway concessionaires in the country in delivering values to customers. Furthermore, continuous improvement and innovation initiatives implemented by the company in delivering the customer values are carefully examined to see the how management accounting practices being applied in those initiatives. The impact of the efforts conducted, financially and non financially were examined too.
A Mobile Knowledge as a service (mKaaS) model of knowledge management system in facilitating knowledge sharing of cloud education community environment
Venue: 2016 Third International Conference on Information Retrieval and Knowledge Management (CAMP)

A Mobile Knowledge as service (mKaaS) can be defined as an arising concept that binds among three sides of knowledge: management (KM) markets, and organization. mKaaS is programs as a system which afford the essential bases (data, information, knowledge) as organizational outputs (e.g. advice, answers, facilitation) for the sake of meeting the person's or user requirements. mKaaS is delivered through knowledge markets as a cloud computing (CC) environment. There is a desire need of knowledge management system (KMS) that insure the delivery of services to the right person in the right time, so that by using the KM processes, the mKaaS can be well manage in a proper form. The KM has four main processes regarding to the acquisition, storage, dissemination and application of the knowledge. This paper presents the concept and its model for facilitating the knowledge of services in mobile computing environment known as mKaaS in a system so that person can make used of in terms of knowledge organization as organizational output for referencing in the current of best practice and lesson learnt especially related to the CC environment. By using this mKaaS Model of KMS, the persons who are engaged or connected to the CC can be easily get the mKaaS as they are wanted or to be considered for the potential purposes in achieving their goal or mission statement.
Exploring Staff Clinical Knowledge and Practice with LGBT Residents in Long Term Care: A Grounded Theory of Cultural Competency and Training Needs
Venue: Clinical gerontologist

Existing literature shows that LGBT residents are likely to face suboptimal care in LTC facilities due to prejudice and discriminatory policies. The aim of this project was to assess the LGBT cultural competency of staff working in LTC facilities, identify their current training needs, and develop a framework for understanding LGBT cultural competency among LTC staff and providers.  This grounded theory study comprised data from focus groups of interdisciplinary staff from three LTC facilities.  Results suggested that LTC staff struggle with how to be sensitive to LGBT residents' needs. Tension appeared to exist between wanting to provide an equal standard of care to all LTC residents and fearing they would show "favoritism" or "special treatment," which might be viewed as unprofessional. Participants indicated training could help to address the ambivalence they experience about providing sensitive care to subpopulations of residents who face stigma and oppression.  LTC staff stand to benefit from cultural competency training focused on LGBT residents. Training should be not only informational in nature, but also facilitate greater self awareness and self efficacy with respect to providing care to LGBT people.
Deconstructing Multiple Oppressions Among LGBT Older Adults

The purpose of this chapter is to interrogate oppression through an analysis of discourses related to lesbian, gay, bisexual, and transgender (LGBT) older adults. As part of our reflexive posture, we attend to the social constructions of meaning about age, ability, gender, race, and sex and their colossal impacts on LGBT older adults. We are mindful of the weight of oppression for LGBT older adults in general but in particular overlooked subgroups of this diverse population (e.g. people who are with low income, people of color, and people who are transgender and do not fit into the binary of woman or man, gay or straight) We confront multiple layers of discrimination by deconstructing cultural assumptions of normalcy (e.g. heteronormativity within the LGBT community) presented in visual form, verbal text, and within discourses.
Stability analysis and autonomous stabilization control of a bicycle based on a three dimensional detailed physical model
Venue: IECON 2016 42nd Annual Conference of the IEEE Industrial Electronics Society

The purpose of this study is analysis and control of a bicycle based on the proposed thee dimensional physical model. There are errors between models and actual equipment because conventional models have not captured the three dimensional dynamics accurately in previous studies on a bicycle. For the problem, we have derived three dimensional physics model, analyzed structure of, and designed controller for self stabilization of a bicycle. In conclusion, parameters of a bicycle enhancing stability are calculated. Furthermore, the controller based on the proposed model is effective for attitude stabilization of a bicycle during low speed riding.
Design and Implementation of Ship Motion Model Based on the Semi physical Simulation System
Venue: 2016 3rd International Conference on Information Science and Control Engineering (ICISCE)

To avoid the problems caused by complex sea conditions, like high costs, ships passive movement could not be controlled that brought by the ship experiment, in this paper, a simulated ship motion model system is developed to resolve this problem, which improved the reusability and reduced the actual cost. Six degrees of freedom movement mathematical model and sea state interference model are established based on existing research of ship space motion model. Add the real device error to the raw data of the inertial devices which is obtained by the proposed model, then calculate it and take it as the benchmark information to evaluate attitude precision of the inertial navigation system that moved with the three axes turntable. Considering with real work situation of inertial devices, detailed design and realization method are provided by the proposed model, which has functions like data dynamic real time display, output, storage, and evaluate precision of inertial navigation system. So it has engineering and practical application significance.
Electroencephalographic Motor Imagery Brain Connectivity Analysis for BCI: A Review
Venue: Neural Computation

Recent research has reached a consensus on the feasibility of motor imagery brain computer interface (MI BCI) for different applications, especially in stroke rehabilitation. Most MI BCI systems rely on temporal, spectral, and spatial features of single channels to distinguish different MI patterns. However, no successful communication has been established for a completely locked in subject. To provide more useful and informative features, it has been recommended to take into account the relationships among electroencephalographic (EEG) sensor/source signals in the form of brain connectivity as an efficient tool of neuroscience. In this review, we briefly report the challenges and limitations of conventional MI BCIs. Brain connectivity analysis, particularly functional and effective, has been described as one of the most promising approaches for improving MI BCI performance. An extensive literature on EEG based MI brain connectivity analysis of healthy subjects is reviewed. We subsequently discuss the brain connectomes during left and right hand, feet, and tongue MI movements. Moreover, key components involved in brain connectivity analysis that considerably affect the results are explained. Finally, possible technical shortcomings that may have influenced the results in previous research are addressed and suggestions are provided.
Sampling based distributed Kernel mean matching using spark
Venue: 2016 IEEE International Conference on Big Data (Big Data)

Limited access to supervised information may forge scenarios in real world data mining applications, where training and test data are interconnected by a covariate shift, i.e. having equal class conditional distribution with unequal covariate distribution. Traditional data mining techniques assume that both training and test data represent an identical distribution, therefore suffer in presence of a covariate shift. Kernel Mean Matching (KMM) is a well known approach that addresses covariate shift by weighing training instances appropriately. However, it has time complexity cubic in the size of training data, which is computationally impractical for large or streaming datasets due to limited scalability. In this paper, we present a sampling based algorithm to address the limited scalability problem of KMM. Moreover, we show that the approach is highly parallelizable, and therefore propose a distributed algorithm for estimating training instance weights efficiently using Spark. Experiment results on benchmark datasets show that the proposed approach achieves competitive estimation accuracy within much lower execution time compared to the KMM algorithm. Moreover, it indicates that larger size of training data results into a higher accuracy with minimal effect on execution time of the proposed approach.
Efficient Sampling Based Kernel Mean Matching
Venue: 2016 IEEE 16th International Conference on Data Mining (ICDM)

Many real world applications exhibit scenarios where distributions represented by training and test data are not similar, but related by a covariate shift, i.e. having equal class conditional distribution with unequal covariate distribution. Traditional data mining techniques suffer to learn a good predictive model in the presence of covariate shift. Recent studies have proposed approaches to address this challenge by weighing training instances based on density ratio between test and training data distributions.  Mean Matching (KMM) is a well known method for estimating density ratio, but has time complexity cubic in the size of training data. Therefore, KMM is not suitable in real world applications, especially in cases where the predictive model needs to be updated periodically with large training data. We address this challenge by taking fixed size samples from training and test data, performing independent computations on these samples, and combining the results to obtain overall density ratio estimates. Our empirical evaluation demonstrates a large gain in execution time, while also achieving competitive accuracy on numerous benchmark datasets.
Efectos de un programa de ejercicio de fuerza resistencia muscular en la capacidad funcional, fuerza y calidad de vida de adultos con enfermedad renal cronica en hemodialisis

Exercise may be a therapeutic tool for improving the functional capacity in patients with chronic kidney disease (CKD) who are on hemodialysis (HD)  To determine the effects on muscle strength (MS) functional capacity (FC) and quality of life related to health (QOLRH) of a resistance training program in patients with CKD on HD.  Thirteen CKD patients aged 38.8 3 years, (7 men) on HD for more than one year participated in an exercise program twice a week during 8 weeks. At the beginning and at the end of the program, MS using a knee extension isometric strength test, FC using the six minutes walking test (6MWT) and QOLRH using the KDQOL CV 36 questionnaire were evaluated. Heart and respiratory rates, blood pressure, oxygen saturation and modified Borg scale were measured as control variables  After training, there were significant improvements in MS in both legs; in the distance travelled during 6MWT and in the physical component summary score of the KDQOL 36. Furthermore, a significant decline in diastolic blood pressure was observed. All other control variables did not change significantly.  Exercise training during eight weeks in CKD patients in HD resulted in significant improvements in muscle strength, walking capacity and in the physical component of a quality of life score for patients with CKD.