Reviewerly/exHarmony huggingface dataset:
Tuition Fees as a Source of Funding and a Policy Instrument: International Experience

The article discusses conceptual grounds of tuition fee policies based on literature review and the study of country-specific cases of the USA, France and Russia in order to highlight general trends and identify practices which can be considered for implementation in Russia. The Authors believe that scholarly publications offer contradicting empirical results related to the impact of tuition fee policies on the performance of higher education institutes. Several theoretical frameworks such as human capital, demand and consumer choice theories as well as the concept of new managerialism are used to explain controversial empirical evidence. Moreover, the effects of tuition fee policies are proven to be contingent on multiple factors such as state governance system, dynamics of labor market, organizational design of higher education, maturity of financial assistance system, prestige and uniqueness of specific educational programs. It is concluded that, apart from PhD studies, overall trend is towards wider application and increase in tuition fees combined with high price for foreign students. Doctoral students in most cases do not pay tuition fees, but get salary for work in research projects conducted to develop new knowledge. Both in the USA and France the best education is provided by highly selective expensive private institutions (although in both countries there are high quality public education). In Russia the most attractive, though expensive for those who pay tuition fees, are public universities because they provide high quality education. Potential change in tuition fee policy in Russia should acknowledge that, in general, higher tuition fees are justified for studies providing higher future earnings. Increase in tuition fees should be coupled with more developed financial aid system.
Artificially Evolved Chunks for Morphosyntactic Analysis

We introduce a language-agnostic evolutionary technique for automatically extracting chunks from dependency treebanks.We evaluate these chunks on a number of morphosyntactic tasks, namely POS 1 tagging, morphological feature tagging, and dependency parsing.We test the utility of these chunks in a host of different ways.We first learn chunking as one task in a shared multitask framework together with POS and morphological feature tagging.The predictions from this network are then used as input to augment sequence-labelling dependency parsing.Finally, we investigate the impact chunks have on dependency parsing in a multi-task framework.Our results from these analyses show that these chunks improve performance at different levels of syntactic abstraction on English UD treebanks and a small, diverse subset of non-English UD treebanks.
Teacher Monitoring Application in Teaching Based on CodeIgniter Framework in High Schools

This is Teacher monitoring in teaching at one Karawang Middle School, is needed to monitor teachers in teaching in class so it can be seen whether the teacher often does teaching and learning activities or not, teachers do not always attend school then carry out teaching and learning activities and also not teachers are not in attendance does not give assignments as a substitute for learning. This monitoring application can support the teacher monitoring process in teaching in the classroom. The system development method used is a waterfall and uses PHP and MySQL. This application is a consideration of how often the teacher teaches in class.
Risk Reduction Tools For Education Internationalization

The internationalization of education is attended with numerous risks.The paper aims to identify, analyze and evaluate tools of de-risking for education internationalization.Our study is based on the analysis of the activities of multicultural educational platforms.The research being done involved the study of the level of tolerance of students and teachers of Kazan Federal University (Russia), as well as an expert survey on the possibility of using multicultural educational platforms.The experience of using multicultural educational platforms by universities as a tool to reduce the risks of internationalization allows to extend our geographical scope through their activities in a rapidly changing environment and to raise graduates' competitiveness.
PEMODELAN NILAI KURS TERHADAP HARGA SAHAM PADA DATA LONGITUDINAL MENGGUNAKAN REGRESI NONPARAMETRIK SPLINE

The purpose of this study was to obtain the models between currency value and stocks in longitudinal data. The models were obtained by using nonparametric truncated spline regression. The data consisted of stocks from three companies namely PT. Mandom Indonesia, PT. Unilever Indonesia and PT. Akasha Wira Internasional and currency value of AUD to IDR. The data were splitted into two sub samples which were “in sample” data from January 2013-December 2017 that were used to generate the models and “out sample” data from January 2016-December 2018 to validate the models, MAPE was used as measurement in validation. This resulted in three distinctive models which were model with order and 3 knots for PT. Mandom Indonesia and PT. Unilever Indonesia, model with order and 4 knots for PT. Akasha Wira Internasional stock, all with there own respective knot points and MAPE value of 9.62%, 15.61% and 48.8% sub sequently.
A New Hybrid Descriptor Based on Spatiogram and Region Covariance Descriptor

Image descriptors play an important role in any computer vision system e.g.object recognition and tracking.Effective representation of an image is challenging due to significant appearance changes, viewpoint shifts, lighting variations and varied object poses.These challenges have led to the development of several features and their representations.Spatiogram and region covariance are two excellent image descriptors which are widely used in the field of computer vision.Spatiogram is a generalization of the histogram and contains some moments upon the coordinates of the pixels corresponding to each bin.Spatiogram captures richer appearance information as it computes not only information about the range of the function like histograms, also information about the (spatial) domain.However, there is a drawback that multi modal spatial patterns cannot be well modelled.Region covariance descriptor provides a compact and natural way of fusing different visual features inside a region of interest.However, it is based on a global distribution of pixel features inside a region and loses the local structure.In this paper, we aim toovercome the existing drawbacks of these descriptors.To this, we propose rspatiogram and then a new hybrid descriptor is presented which is combination of rspatiogram and traditional region covariance descriptors.The results show that our descriptors have the discriminative capability improved in comparison with other descriptors.
A Comparative Study of Software Architectures in Mobile Applications

The mobile market grows larger year by year and at the core of those devices, we have the mobile applications that push the technological advancement forward continuously. Due to the increased hardware performance and the popularity of those devices as well as advancements in their operating systems, mobile applications have grown to be complex projects with many dependencies and large teams working on them. As the application becomes bigger and more complex, the problem of choosing the right software architecture arises. This study focuses on an analysis of the most commonly used architectural patterns on mobile applications highlighting their features and flaws. Moreover, it also presents a comparison between them when implementing a medium-sized application. The usage of the appropriate architecture can simplify the work of developers and enable the creation of sustainable applications and the improvement of the software?s capacity to endure and evolve over time.
Correction: Rapid visual categorization is not guided by early salience-based selection

[This corrects the article DOI: 10.1371/journal.pone.0224306.].
Cross-enhancement transform two-stream 3D ConvNets for action recognition

Action recognition is an important research topic in computer vision. It is the basic work for visual understanding and has been applied in many fields. Since human actions can vary in different environments, it is difficult to infer actions in completely different states with a same structural model. For this case, we propose a Cross-Enhancement Transform Two-Stream 3D ConvNets algorithm, which considers the action distribution characteristics on the specific dataset. As a teaching model, stream with better performance in both streams is expected to assist in training another stream. In this way, the enhanced-trained stream and teacher stream are combined to infer actions. We implement experiments on the video datasets UCF-101, HMDB-51, and Kinetics-400, and the results confirm the effectiveness of our algorithm.
The Development of Research Recommendation System for Southern Thailand Development

The research was to identify needs on design and development of a research recommendation system for 14 southern province Thailand development.The system employs semantic search function, research system structure and scope of knowledge during January 2008 to December 2017.3,873 entries had been gathered from Thai Library Integrated System (ThaiLIS), Thai National Research Repository (TNRR), and Southern universities research database by employing textual analysis and knowledge organization focusing on Classification Approach and categorization which main topics are sorted and categorized.To develop ontology, it applies knowledge engineering concept and using Protégé Ontology Editor version 3.5 beta and version 5.5 beta to process the data for the accurate system development according to user-centered design concept.The study findings were the developed system is able to support information exchange, information retrieval, and research search and to decrease research redundancy and unnecessary budgeting.Moreover, the system could possible enhance conducting more innovations, confirming experts in the area, showing research trends, and showing research results on related fields, strategies, and problems which leads to the Southern developments extensively.After the implementation, the users' overall opinions and satisfaction was at a high level ( = 4.14, S.D = 0.14) and information retrieval efficiency of system was at a good level (overall = 0.70-0.88)with 0.70 accuracy, 0.78 recall, 0.88 precision, and 0.82 F-measure.
Why we still don't need/want variables: Two SALTy case studies

This paper defends the claim that variables and assignment functions are not needed as part of the semantic machinery against two apparent challenges. The relevant domains at first glance appear to show the need for variable names - but only if the variable-ful theory is supplemented with a stipulation preventing 'meaningless coindexation'. I argue that not only are both domains amenable to variable free analyses, but that indeed the variable free analyses have advnatages over the analyses using variables.
The Role of Leadership and Strategic Decision on Regional Development in Developing Countries

Purpose: This research paper is focusing on the role of leadership and strategic approach for the best institutional model toward balanced regional economic development (RED) in developing countries.The research paper examines the cohesion among leadership models and decision making structures toward strategic model for regional economic development in Kosovo.Final purpose is setting up the suitable decision making structure across all regions in the country that through proactive and authentic leadership, as well effective institutional structures creates capacity in each region for better utilization of the resources.Design/Methodology/Approach: The paper methodology used a mixed-methodological approach including both qualitative and quantitative data collection and appraisal, which included desk review covering existing literature at national and international level, semistructured interviews with key stakeholders, relevant reports and other related documents.Findings: The research paper has finded that there are significant relationships among leadership role, organizational structures and regional development.Acording to the paper a suitable leadership model followed by responsible institutional framework and decision making structures is usualy the most important factor influencing growth at the regions.Actually in Kosovo regions and municipalities lack the capacities to create an effective environment for private sector development and job creation for all communities.The paper analysis shows that both-leaderhsip and decision making structure amplifies the institutional structure and institutional resources' effect on the better performance of regions.Practical Implications: The practical implications deriving from this research concludes that future approach to RED should be based on balanced distribution of responsibilities between different governmental levels with clear vision and leadership, as well as with much more advanced institutional structures and detailed work design.This means that creative leadership will ensure not only better performance in economical development aspects but meanwhile will adjust better to external changes and work more efficiently.Originality/Value: The research paper shows its originality in a specific case study and the value of this is finalized with the regional economic development model that will serve as one stop shop at different regions supporting the economic and overall development.
The development of chemistry practicum e-module based on simple-practice

Practicum is an important element in chemistry. In chemistry learning with practical methods students are given the opportunity to be creative, find, or prove a phenomenon that he experienced and the concepts his learned. Therefore, it is important to develop the learning method using practicum to accommodate the progress and needs of the times so that learning is close to students so that learning becomes meaningful. In this research, the development of digital integrated chemistry practicum modules based on simple practice is carried out. The research sample consisted of 248 students and 26 chemistry teachers, and was validated by 3 expert judges. In the initial stage, the module developed is validated by expert judges. The validation results show that the module is categorized as valid in terms of content eligibility, language feasibility, and presentment eligibility with an average score of 3.81 (scale 4). In the final stage, a module testing is conducted for chemistry students and teachers in the form of collecting responses. Chemistry teacher response results indicate that the module is feasible to be used as a source of student learning on chemistry practicum class XI high school even semester with an average score of 3.78 (scale 4). The results of the students' responses showed that the module was appropriate for them to use as a source of learning on chemistry practicum with an average score of 3.79 (scale 4). The results of student responses on the presentment eligibility aspect showed the highest value of 3.98 (scale 4), the module developed was presented digitally integrated which can be accessed online. Keywords: Chemistry; e-module; practicum; simple-practice
Multiple Reconstruction Compression Framework based on PNG Image

It is shown that neural networks (NNs) achieve excellent performances in image compression and reconstruction.However, there are still many shortcomings in the practical application, which eventually lead to the loss of neural network image processing ability.Based on this, a joint framework based on neural network and scale compression is proposed in this paper.The framework first encodes the incoming PNG image information, and then the image is converted into binary input decoder to reconstruct the intermediate state image, next, we import the intermediate state image into the zooming compressor and repressurize it, and reconstruct the final image.From the experimental results, this method can better process the digital image and suppress the reverse expansion problem, and the compression effect can be improved by 4 to 10 times as much as that of using RNN alone, showing better ability in the application.In this paper, the method is transmitted over a digital image, the effect is far better than the existing compression method alone, the Human visual system cannot feel the change of the effect.
Application of E-Learning and Artificial Intelligence in Education Systems in Indonesia

Technology movement creates progressive impacts towards the development of communication network, computer, and the Internet.An innovation that is known as Artificial Intelligence (AI,) is one of many products.The usage of AI technology is predicted to expand globally, including in Indonesia.The influence of AI technology on improving the effectiveness of e-Learning concepts enables integration into the advancement of the education system in Indonesia.This study aims to explore the potential and impact of applying AI technology in e-Learning, and the readiness of various factors that influence the education system and Information and Communication Technology (ICT) in Indonesia.The discussion is based on secondary data and comprehensive observations of the prevailing learning structure.
Generating Paraphrases with Lean Vocabulary

In this work, we examine whether it is possible to achieve the state of the art performance in paraphrase generation with reduced vocabulary.Our approach consists of building a convolution to sequence model (Conv2Seq) partially guided by the reinforcement learning, and training it on the subword representation of the input.The experiment on the Quora dataset, which contains over 140,000 pairs of sentences and corresponding paraphrases, found that with less than 1,000 token types, we were able to achieve performance that exceeded that of the current state of the art.
Analysis of Eye Tracking of Physiotherapist during Walk Rehabilitation

The measurement of walking is important for evaluating the health of elderly people. This evaluation is performed by experts in gait assessment (such as doctors or physiotherapists), who vary in terms of skill. To guarantee evaluative quality, engineering of gait-measurement solutions is desired. This paper describes a method of quantifying tacit physiotherapist knowledge of walk rehabilitation by tracking and analysing their eyes. We constructed the eye-tracking system to extract the points of gaze of multiple physiotherapists. The result shows that proficient physiotherapists exhibit special eye movements, which we defined as `rhythmical'. We evaluated the proficiencies of all subjects based on their rhythmical-eye movement. It is clear that proficiency does not increase linearly with rhythmical-eye movement, but instead exhibits a staircase-like behaviour. Consequently, we elucidated that the `rhythmical-eye movement' is one part of tacit knowledge of the proficient physiotherapists. And it is useful to establish the walking measurement closer to the proficient physiotherapists.
SUF: Smart and User Friendly Office Setup in Pervasive Computing Environment

It aims at providing security not only to the transmission or the data input–output but also to the defense system from the source which is target node attached to the network, particularly in the wireless network environment. To fulfill the requisites of the pervasive computing model, distributed trust can also be added to the security infrastructure instead of the traditional meaning of appraising trust, so trust management can establish a trust relationship. This adapted approach works on utter strategies for authenticating visitor(s) and access control, providing the individual securitycredentials, by providing the permission to the entity to change the access rights of other entity or provide them the access to deferring the third parties when required. Services are accessible by the authorized users only if they have rights to access or if the user has assigned that access right to them because of all the rights for which they possess the permission they can assign. The rights can be taken back or annulled. The rights for specific service or the particular service also possess the right to make use of the other service is associated with the user, devices and the agents only.
EFFECT OF CROSSWORD PUZZLE TEACHING STRATEGY TOWARDS STUDENTS’ VOCABULARY MASTERY

This research is to find out that crossword puzzle teaching strategy gives a significant effect towards students’ vocabulary mastery at SMA Amir Hamzah Medan. The crossword puzzle is a kind of word game which can improve the learners to enrich their vocabulary knowledge. The research design used is pre-experimental design formed as one group pretest- posttest design using quantitative approach. The data collecting method is test. The research data are analyzed by applying paired samples t-test formula through SPSS 23 and the result of the research shows that the value of the t-count is 51,700, while the t-table with the significance level of 5% and Df of 12 is 2,179. The t-count is higher than the t-table (51,700&gt;2,179). This means that the null hypothesis (H0) is rejected while the alternative hypothesis (Ha) is accepted. In conclusion, there is a significant effect towards students’ vocabulary mastery before and after having taught by the utilization of crossword puzzle teaching strategy at SMA Amir Hamzah Medan.
Improved C-COT based on feature channels confidence for visual tracking

In the field of visual tracking, the methods of Discriminative Correlation Filters (DCF) have showed excellent performance, which rely heavily on the choice of feature descriptors. The Continuous Convolution Operator Tracker (C-COT) is a novel correlation filter to track the target position in the continuous domain, which achieved significant effects. However, as for various visual scenes, different feature descriptors are suitable to different environments. If each feature channel is given the same confidence during the tracking phase, it would limit the performance of some good features. To address this problem, this paper proposes an improved C-COT algorithm that can adaptively perform feature channel weighting. The Average Peak Correlation Energy (APCE) is used to evaluate the corresponding response map of each feature channel, guiding the target appearance model to give different weights to different features. Then, we can obtain the final weighted feature response map whose peak value is applied to locate the target. In addition, the C-COT updates the appearance model rigorously in every frame, which may lead to over-fitting and increase computional complexity. Therefore, in order to reduce the redundancy of the online training sample and avoid similar background interference, we adopts the method of Peak Side Lobe Ratio (PSLR) to update the model. We perform comprehensive experiments on OTB50 and OTB100. The results show that the improved tracker achieves better accuracy, especially in some specific video scenes. In addition, speed has also improved.