Reviewerly/exHarmony huggingface dataset:
Topical issue scientific machine learning (2/2)

GAMM-MitteilungenVolume 44, Issue 2 e202100010 PREFACE Topical issue scientific machine learning (2/2) Peter Benner, Corresponding Author Peter Benner benner@mpi-magdeburg.mpg.de Computational Methods in Systems and Control Theory, Max Planck institute for Dynamics of Complex Technical Systems, Magdeburg, Germany Fakultät für Mathematik, Otto-von-Guericke Universität Magdeburg, Magdeburg, Germany Correspondence Peter Benner Email: benner@mpi-magdeburg.mpg.deSearch for more papers by this authorAxel Klawonn, Corresponding Author Axel Klawonn axel.klawonn@uni-koeln.de Department of Mathematics and Computer Science, University of Cologne, Köln, Germany Center for Data and Simulation Science, University of Cologne, Köln, Germany Correspondence Peter Benner Email: benner@mpi-magdeburg.mpg.deSearch for more papers by this authorMartin Stoll, Corresponding Author Martin Stoll martin.stoll@mathematik.tu-chemnitz.de Chair of Scientific Computing, Department of Mathematics, TU Chemnitz, Chemnitz, Germany Correspondence Peter Benner Email: benner@mpi-magdeburg.mpg.deSearch for more papers by this author Peter Benner, Corresponding Author Peter Benner benner@mpi-magdeburg.mpg.de Computational Methods in Systems and Control Theory, Max Planck institute for Dynamics of Complex Technical Systems, Magdeburg, Germany Fakultät für Mathematik, Otto-von-Guericke Universität Magdeburg, Magdeburg, Germany Correspondence Peter Benner Email: benner@mpi-magdeburg.mpg.deSearch for more papers by this authorAxel Klawonn, Corresponding Author Axel Klawonn axel.klawonn@uni-koeln.de Department of Mathematics and Computer Science, University of Cologne, Köln, Germany Center for Data and Simulation Science, University of Cologne, Köln, Germany Correspondence Peter Benner Email: benner@mpi-magdeburg.mpg.deSearch for more papers by this authorMartin Stoll, Corresponding Author Martin Stoll martin.stoll@mathematik.tu-chemnitz.de Chair of Scientific Computing, Department of Mathematics, TU Chemnitz, Chemnitz, Germany Correspondence Peter Benner Email: benner@mpi-magdeburg.mpg.deSearch for more papers by this author First published: 07 June 2021 https://doi.org/10.1002/gamm.202100010Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume44, Issue2Special Issue: Scientific Machine Learning ‐ Part IIJune 2021e202100010 RelatedInformation
Memorization and Generalization in Neural Code Intelligence Models

Deep Neural Networks (DNN) are increasingly commonly used in software engineering and code intelligence tasks. These are powerful tools that are capable of learning highly generalizable patterns from large datasets through millions of parameters. At the same time, training DNNs means walking a knife's edges, because their large capacity also renders them prone to memorizing data points. While traditionally thought of as an aspect of over-training, recent work suggests that the memorization risk manifests especially strongly when the training datasets are noisy and memorization is the only recourse. Unfortunately, most code intelligence tasks rely on rather noise-prone and repetitive data sources, such as GitHub, which, due to their sheer size, cannot be manually inspected and evaluated. We evaluate the memorization and generalization tendencies in neural code intelligence models through a case study across several benchmarks and model families by leveraging established approaches from other fields that use DNNs, such as introducing targeted noise into the training dataset. In addition to reinforcing prior general findings about the extent of memorization in DNNs, our results shed light on the impact of noisy dataset in training.
Imitation by Predicting Observations

Imitation learning enables agents to reuse and adapt the hard-won expertise of others, offering a solution to several key challenges in learning behavior. Although it is easy to observe behavior in the real-world, the underlying actions may not be accessible. We present a new method for imitation solely from observations that achieves comparable performance to experts on challenging continuous control tasks while also exhibiting robustness in the presence of observations unrelated to the task. Our method, which we call FORM (for Future Observation Reward Model) is derived from an inverse RL objective and imitates using a model of expert behavior learned by generative modelling of the expert's observations, without needing ground truth actions. We show that FORM performs comparably to a strong baseline IRL method (GAIL) on the DeepMind Control Suite benchmark, while outperforming GAIL in the presence of task-irrelevant features.
The substantiation of the essence of a future teacher’s professional culture as a personal phenomenon from the standpoint of the culturological approach

The article covers various definitions of the concept of “culture”, which expand and fill the concept of “a teacher’s professional culture” with a new meaning and content. The specified personal phenomenon is viewed on the basis of the culturological approach and it manifests itself in the permanent process of professional and personal development and self-development, identifying humanistic orientation, self-actualization, and, in this regard, the ability to carry out purposeful activities, find the new meanings of the professional life, professional “self”, professional functions, find the ways of one’s “essential forces” realization. The definition of the problem field allowed us to identify the tasks of the possible directions of the formative process in relation to a future teacher’s professional culture. The task should be focused around future teachers’ culturological and worldview preparation.
Development of innovations in the educational environment: inclusive education and digital technologies

The introduction of digital technologies in the educational process makes it possible to personify the presentation of numerical and graphical information, individually select the pace of learning, make the process of assessing competencies objective and increase the level of methodological support of the educational process. The use of the latest digital technologies in the planning of studentcentered inclusive education allows releasing the time reserves of teachers and ensuring the comfort of the implementation of routine processes. The purpose of this work is to analyze the characteristics of student-centered learning relative to the needs of students studying inclusively.
&lt;p&gt;Effects of Mobile Phones on Students’ Academic Performance in Religious Education&lt;/p&gt;

This study examined the effects of the mobile phones on high school students’ academic performance in Religious Education. The aim of the study was to test the efficiency using of mobile phones against the lecture method. Seventy-two participants (31 females and 41 males), in the Kingdom of Eswatini, participated in this quasi-experimental study. Purposive sampling was used to select participants who were randomly assigned to two groups (control and experimental). The control group was taught the topics, “The birth of the church and its spread” using a lecture method, whereas the experimental group was taught the same topic using mobile phones. The independent t-test and the dependent t-test were used to analyse data. The independent variable used was “teaching method,” with two levels: lecture versus mobile phones. The dependent variable was the participants’ scores derived from the pre-test and post-test. The independent t-test and the dependent t-test were used to analyze data. The results revealed that there was a significant difference in favor of the experimental group. The study concluded that the use of mobile phones improved students’ academic performance in Religious Education, and thus the integration use of mobile phones in the teaching of Religious Education is recommended in order to improve performance.
The Evaluation of Effectiveness for the Collaborative Combat of an Unmanned Aerial Vehicle Based on Grey Minimum Entropy

The main points to the evaluation of effectiveness for the collaborative combat of the unmanned aerial vehicle (UAV) lie within the construction of a reasonable indicator system and an accurate contribution model. As for point one, this article introduces a new method combining the Delphi consulting method and the principal component analysis method to avoid the underlying subjective and time-consuming defects of the existing methods. As for another point, a weighting method is adopted combining the subjective and objective parameters to minimize the errors caused by a single entity. Firstly, the modified grey relational degree analysis method is used to obtain the subjective weight, which can reduce the influence of the extreme values and outliers by enhancing the selection process of the reference sequence. Secondly, this paper adopts the weight of minimum entropy weight method to obtain the objective weight; it can avoid the information loss caused by the original method, which only determines the weight based on the frequency of each element present in the effective combination. At last, the principle of minimum relative entropy is adopted to obtain a more reasonable weight distribution coefficient. The simulation experiments established the rationality and effectiveness of the proposed method.
Studying the Changes in Solar Radiation and Their Influence on Temperature Trend in Iraq for a Whole Century

Most studies indicated that the values ​​of atmospheric variables have changed from their general rates due to pollution or global warming etc. Hence, the research indicates the changes of direct solar radiation values ​​over a whole century i.e. from 1900 to 2000 depending on registered data for four cities, namely (Mosul - Baghdad - Rutba - Basra. Moreover, attemptsto correlate the direct solar radiation with the temperature values have been ​​recorded over that period. The results showed that there is a decreasing pattern of radiation quantities over time throughout the study period, where the value of direct radiation over the city of Baghdad 5550 w/m2 was recorded in the year 1900, but this ratio decreased clearly to approximately 5400 w/m2 in the year 2000, which is perhaps due to the increase of general pollution rates in the atmosphere. The results also showed that the city of Rutba recorded the highest annual rate of radiation quantities, and Baghdad with Mosul recorded the lowest radiation ratios compared to the rest of the cities, in addition to that there was a large convergence of radiation ratios between them to some extent. The results showed that there is a sharp drop in radiation ratios, specifically in the years1980and 1990. As for the extent of the relationship for solar radiation with temperature levels throughout the study period, it was found that there is an inverse relationship between them, and this confirms that the cause of high temperatures is not because of increased solar radiation, but it may rather due to other reasons such as increased greenhouse gases.
Evolution of Mobile Phones

The topic contains the steps and turning points of how Mobile Phones turned into Smart Phones. It not only contains the past journey of mobile phones but also the future prediction of smart phones, it will contain the projection of how smart phones will evolve after a decade. The projection will show the new resources that will be integrated in the smartphone and also how the existing system will be modified and updated. The current smart phone contains an average of 4 sensors, which will be appended in the future. This journey of adding various new sensors will be projected in the topic. The topic will also involve the evolution of the Smart Phone’s operating system, it will exhibit the ways in which the current operating system can be improved. It will also contain the circumstances or the turning points in the development of operating system in the future. In the evolution of Mobile Phones the major component is the Hardware, the topic will contain how the hardware components were evolved. Also the topic will showcase some of the sensors and other hardware components that will be developed in the future.
Comparative Evaluation of Lung Cancer CT Image Synthesis with Generative Adversarial Networks

Generative adversarial networks have already found widespread use for the formation of artificial, but realistic images of a wide variety of content, including medical imaging. Mostly they are considered to be used for expanding and augmenting datasets in order to improve accuracy of neural networks classification. In this paper we discuss the problem of evaluating the quality of computer tomography images of lung cancer, which is characterized by small size of nodules, synthesized using two different generative adversarial network, architectures – for 2D and 3D dimensions. We select the set of metrics for estimating the quality of the generated images, including Visual Turing Test, FID and MRR metrics; then we carry out a problem-oriented modification of the Turing test in order to adapt it both to the actually obtained images and to resource constraints. We compare the constructed GANs using the selected metrics; and we show that such a parameter as the size of the generated image is very important in the development of the GAN architecture. We consider that with this work we have for the first time shown that for small neo-plasms, direct scaling of the corresponding solutions used to generate large neo-plasms (for example, gliomas) is ineffective. Developed assessment methods have shown that additional techniques like MIP and special combinations of metrics are required to generate small neoplasms. In addition, an important conclusion can be considered that it is very important to use GAN networks not only, as is usually the case, for augmentation and expansion of the datasets, but for direct use in clinical practice by radiologists.
PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration

Model-based Reinforcement Learning (RL) is a popular learning paradigm due to its potential sample efficiency compared to model-free RL. However, existing empirical model-based RL approaches lack the ability to explore. This work studies a computationally and statistically efficient model-based algorithm for both Kernelized Nonlinear Regulators (KNR) and linear Markov Decision Processes (MDPs). For both models, our algorithm guarantees polynomial sample complexity and only uses access to a planning oracle. Experimentally, we first demonstrate the flexibility and efficacy of our algorithm on a set of exploration challenging control tasks where existing empirical model-based RL approaches completely fail. We then show that our approach retains excellent performance even in common dense reward control benchmarks that do not require heavy exploration. Finally, we demonstrate that our method can also perform reward-free exploration efficiently. Our code can be found at this https URL.
Pembangunan Aplikasi Permintaan Cuti Berbasis Web Menggunakan Framework Hibernate dan Spring MVC

PT XYZ is a subsidiary of one of the largest IT companies in Indonesia which is engaged in Information and Communication Technology (ICT). The company's business unit consists of many aspects, for example in the IT distribution business, providing retail for ICT products, outsourcing IT personnel, designing, installing and maintaining all things related to information technology. In order to run all of its businesses, this XYZ company requires a lot of high quality and high quality human resources, but with the outbreak of the Covid19 pandemic, the work process for PT. XYZ is disturbed because it is done in their respective homes. This results in difficulties for employees in processing administrative matters with the office. One of them is in the matter of taking care of leave permits because the previous leave licensing process was still done manually. The management decided to build an application that can be used by all employees in all subsidiaries. Therefore, the aim of this research is to make an application that can support the administrative needs of employees in the field of leave licensing called "LeaveRequest". This application is designed using the Java programming language with the Spring Boot framework and using the Waterfall software development method. This study found the results that the majority of respondents strongly agree with the design and usability of this application, so it can be concluded that the LeaveRequest application has succeeded in fulfilling the needs in serving the utility of PT. XYZ in work from home condition.
Optimization of K-means Algorithm Base on MapReduce

Abstract In the context of big data, the K-means clustering algorithm is sensitive to the initial clustering center, the detection and removal of outliers are difficult, and the data is tilted. The KMEANS-BRMS (K-means algorithm based on range mean and sampling) algorithm based on range mean and sampling is proposed. First, for the initial data set, the “range mean value method”(Mean Range method, MRM) is proposed to obtain the initial cluster centers. In order to eliminate the influence of outliers, a range threshold is set above and below the range mean, and all points under this threshold constitute an initial center. The set of points to be selected, in which the maximum and minimum distance criteria are adopted to select the initial clustering center, which effectively avoids the problem of the sensitivity of the initial center point and the influence of outliers caused by the random selection of the initial clustering center. Next, the BSA(Based on pond sampling and first adaptation algorithm) strategy of adapting algorithm for the first time to deal with the data skew problem in the MapReduce stage, and improve the clustering efficiency. Finally, combined with the MapReduce framework model, the data cluster center is mining in parallel to generate the final clustering result. Experiments show that the clustering results of the KMEANS-BRMS algorithm are more stable and effective, and at the same time it can more effectively improve the efficiency of parallel computing in the big data environment.
On the issue of improving the quality of the school textbook

The article discusses the issues of assessing the quality of a school textbook, reveals the essence of the new system of criteria for determining the quality of domestic textbooks, according to which the textbooks are examined through the assessment of the didactic apparatus of the textbook and the implementation of its functions. The assessment of the quality of the didactic apparatus is determined on the basis of an assessment of the quality of the textbook structure, the content of the textbook, the learning organization apparatus, the perception apparatus, the orientation apparatus, illustrative material, the electronic textbook application, and the compliance of the textbook design with ergonomic and esthetic requirements. The quality assessment of the functions performed by the textbook is determined on the basis of the assessment of the coordinating, systematizing, informative, motivational, developing, transformational, value-orientation and educational functions, self-education and navigation functions, integrating, controlling and correcting functions of the textbook
Smart Contracts in the Context of Procure-to-Pay

Smart contract technology is beginning to alter the way supply chain processes are designed and executed. Blockchains enable peer-to-peer networks where contractual terms are automatically executed without the need for unbiased intermediaries. Due to the immutability of blockchains, smart contracts reduce risks and provide traceable audit trails of all transactions. Moreover, smart contracts can be automatically triggered, resulting in decreasing administration and service costs while improving process efficiencies. These attributes make smart contract technology a promising invention for the poorly automated procure-to-pay process. That is, if the existing technological limitation, like poor scalability, high energy consumption, and limited transaction throughput, can be solved. The primary purpose of this chapter is to investigate how smart contracts can be implemented into existing procure-to-pay processes, what advantages can be gained from the application, and which technological restrictions are yet to overcome. To this end, a systematic literature review was conducted. Academic and practitioner literature were analyzed based on a qualitative and deductive methodology. Additionally, this chapter presents a use case for smart contracts in procure-to-pay in the context of international trade. That way, it lays a foundation for future research, provides valuable insight for procurement managers, and offers approaches to overcome the most pressing challenges.
Using Mobile-Assisted Language to Encourage EFL Learning among Indonesian Learners of English

Digital Literacy (DL) is defined as the ability to use information and communication technology to communicate with cognitive and technical skills. One of the Digital Lit- eracy is Mobile-Assisted Language Learning (MALL) or mobile phones-based lan- guage learning. Merits of this study are worthy of helping learners easier understand the language learning materials presented by either guided face to face in the classroom or self-learning out of the school. The study used experimental and control classes to compare the results that the significance of Mobile-Assisted Language Learning in learning language could be prescribed. Refer to the initial students’ ability, this study designed pre and post-test for the experiment. Furthermore, participants were 40 stu- dents of second-year students at the English Education Department. Same topics were taught for experiment and control class in alter methods. The results claimed that the using post-test of MALL had merits on improving experimental group more than con- trol group performance. The results declared that using MALL would encourage stu- dents’ learning activities such as self-language learning, enriching vocabulary, promot- ing teacher’s pedagogic, student’s cognitive, writing skill, reading comprehension, speaking, grammar and listening skill. Lastly, this paper implied MALL as a reference for future curriculum and material development.
Unfolding Laypersons Creativity Through Social VR - A case study

Involving laypersons in collaborative design projects faces the challenge of having an adapted representational ecosystem. There is a lack of adequate representational tools for multidisciplinary actors to graphically and physically vizualize and externalize their ideas. Using VR is a promising way of renewing participatory design, but settings with VR raise the difficulty to express ideas on the model, and to support collaboration since using VR headsets eventually hinder design communication between participants wearing them. In this paper we present the a case study of one workshop involving non-designers as participants, based on collective 3D sketches using a Social VR system (without headsets), in which several users simultaneously and immersively sketch using handheld tablets, operating a 3D model as contextual background. The workshop was supported by a representational ecosystem containing: (1) Traditional freehand sketching on paper and working with pre-cut physical components used as boundary objects to represent a scaled model; and (2) immersive 3D model allowing collective life-sized visualization, 3D sketching and interaction. The paper describers the case study and provide insights about layperson's collaborative design.