Reviewerly/exHarmony huggingface dataset:
Performance sensitivity of Operating System parameters in Microservice environments

Cloud services are undergoing a major shift from monolithic applications to graphs of hundreds of loosely-coupled microservices. Microservice architecture presents both opportunities and challenges while optimizing for system characterization and resource utilization. In this study, we characterize the performance sensitivity of Operating System parameters for two academic microservice benchmarks with respect to their thread scheduling, disk writes, and the TCP buffer. We demonstrate that through simple affinitization of kernel threads to cores of a Non-Uniform Memory Access processor and disk buffer configurations, there is a 26% and 19% decrease in Average Latency accompanied by a 27% decrease in 99% Tail latency for the benchmarks under consideration. While performance improvements can be gained, we also show that alternate nonoptimal configurations of the system parameters degrade the performance substantially.
Research and improvement of deep learning tool chain for electric power applications

With the promotion of artificial intelligence technology in various industries in China, deep learning technology driven by electric power data has begun to be applied on a large scale in the electric power industry, but in actual application we have also found some problems, for example, the current process and tools, seemingly clear and independent, but are actually interdependent and not flexible enough; for common requirements such as retrieval, functions are not flexible enough and often re-developed. Accumulated algorithm exploration will cause the same sample to appear repeatedly in multiple training sets, The waste of resources is serious. This article elaborated on the causes and solutions to solve these problems, redesigned the process and architecture, and developed software tools. First of all, this article believes that deep learning models have a life cycle, and proposes to reorganize the deep learning tool chain with the model warehouse as the center. Secondly, combined with the actual application of electric power AI, we decoupled the original data, labeled data, and sample definitions. Finally, we designed an expression of public functions such as retrieval, taking into account flexibility and versatility.
Fine-Grained Unbalanced Interaction Network for Visual Question Answering

Learning an effective interaction mechanism is important for Visual Question Answering (VQA). It requires an understanding of both the visual content of images and the textual content of questions. Existing approaches consider both the inter-modal and intra-modal interactions, while neglecting the irrelevant information in the interactions. In this paper, we propose a novel Fine-grained Unbalanced Interaction Network (FUIN) to adaptively capture the most useful information from interactions. It contains a parallel interaction module to model the two-way interactions and a fine-grained adaptive activation module to adaptively activate the interactions for each component according to their specific context. Experimental evaluation results on the benchmark VQA-v2 dataset demonstrate that FUIN achieves state-of-the-art VQA performance, we achieve an overall accuracy of 71.14% on the test-std set.
3D Shape Estimation With an Enhanced Sparse Representation Approach

In this paper, an enhanced sparse representation approach is proposed to estimate the 3D shapes of objects in 2D image sequences. In the proposed method, the unknown 3D shape is estimated via a two-stage scheme, namely the main 3D shape estimation stage and the compensatory 3D shape estimation stage. Moreover, a reweighted sparse representation model is constructed to extract the shape bases for each estimation stage. In the sparse model, a reweighted constraint is enforced to enhance the coefficient sparsity of the shape bases. Experimental results on the well-known CMU image sequences demonstrate the effectiveness and feasibility of the proposed approach.
UPAYA MENINGKATKAN KEMAMPUAN MEMBACA DENGAN MENYEBUTKAN HURUF AWAL MELALUI MEDIA KARTU GAMBAR

The research objective was to determine the increase in reading skills by mentioning the initial letters through the media of picture cards. The research subjects were 18 children of group B PAUD Ar-Rahma. This research was conducted in 2 cycles, namely, cycle I and cycle II, through stages, planning, implementing, observing, and reflecting. The data collection techniques used were observation and documentation. The data analysis method used was descriptive analysis with a qualitative approach. The Classroom Action Research was carried out collaboratively with a total of 4 people and 3 being a researcher at the same time acting as a teacher and friend and the other acting as an observer. The conclusion of the research result is the improvement of reading ability by using initial letters through picture card media in PAUD Ar-Rahma students.
Development of Multimedia Application Using TPACK Framework

Nowadays, there is a lot of information about women's health, and motivation for women is conveyed through books. Therefore, it cannot attract readers especially women and teenagers to learn and be concerned about this information. This is because learning from books can make people feel bored. Moreover, the way the books try to convey the information is very plain. Therefore, we planned to develop a multimedia application (apps) to attract users to learn about women's health. In this study, based on the book from the title PEACE for Women, we chose the problem statements module as the content in the multimedia apps. Furthermore, to prove the concept of an experiment based on the TPACK framework, we choose the basic design research method. There are four stages to go through in the development of well-functioning apps using TPACK which are planning, requirement analysis design defined, and testing phase. The usability and effectiveness of these multimedia apps were evaluated by two groups of respondents which is group A is conducted from a conventional approach and group B is from students who test using multimedia apps. The respondents were psychology students. Based on the results, the total score for group A was comparatively lower than group B. In conclusion, the multimedia apps that have been designed based on the TPACK framework can attract users to learn about women's health because it contains the technology and the elements of multimedia.
Research on the Development of Pedagogy in Applied under the Background of Internet Education

With the progress of society and the development of science and information technology, Internet education has become a hot topic. In the Internet era, the ways and methods of teacher education and teaching have also changed greatly. Under the background of this big era, the major educational institutions gradually rise through the Internet platform, and a hot tide of “Internet education” is coming. Nowadays, under the background of “Internet education”, major applied colleges and universities hope to use the Internet to help pedagogy develop in a new direction. This paper gives a brief overview of “Internet education”, analyzes the positive role of “Internet education”, and mainly studies the current situation of the development of applied university education and teaching. At the same time, the development path, challenges and analysis of applied university pedagogy under the background of Internet education are studied.
Information Security Governance in FinTech

This chapter introduces information security governance, various policies and standards used to profile information security governance, and available security governance models. It provides insight into the roles and responsibilities of individuals working at top-, middle-, and lower-level management. A security governance framework has two primary activities: directing and controlling. Directing is a top-down approach initiated by the board of directors and executives (top-level management) and followed by the middle- and lower-level management personnel. On the contrary, controlling is a bottom-up approach that includes daily operations performed by the lower-level management to work upon the directions provided by the top management. The chapter further presents an integrated framework for information security governance. Based on the integrated security governance framework, a general information security governance framework for FinTech is proposed that consists of important domains, components, individuals, their activities, and outcomes.
Formation of meta-subject components of ICT competence

The changes in education dictated by the 4th industrial revolution and the specifics of training future teachers in primary education associated with the multidimensionality of pedagogical activities give grounds for refining the structural and content model of ICT competence of future teachers in primary education. In the contemporary information society, establishing a holistic view of the unity of information processes is a prerequisite for educational process organization. The insufficient level of ICT competence in future teachers in primary education and the need to achieve meta-disciplinary results in education serve as a basis for the clarification and specification of the model of this concept. The authors propose an expansion of the invariant component composition of ICT competence with meta-subject components (the variable core of the competence): semiotic, technological, and integrative. Refining the structural and content model and identifying the methods and techniques that contribute to the formation of ICT competence in future teachers in primary education and allow reaching meta-subject results. One of the main instruments contributing to the formation of ICT competence is mathematical modeling based on the universal sign-symbol system and most suitable for designing computer models. The methodology based on the method of cross-curricular tasks allows achieving meta-subject results in the construction of the educational process of training future teachers in the field of primary education. Research demonstrates that enriching the educational process of future teachers in primary education with schematic, graphic, and geometric tools and the implementation of the method of cross-cutting tasks that serves as a leading means of teaching mathematics contribute to the emergence of a stable positive dynamic in the formation of information culture, particularly the meta-subject components of ICT competence of future teachers in the field of primary education.
Transformation of Digital Requirements: An Enabler for Successful Complex Projects

Abstract This paper discusses the lessons learned from transforming upstream operational requirements from a document environment into a requirements management tool (database). Operations requirements from upstream practices, procedures, specifications, and guides were migrated from a document centric environment into a requirements management system (data centric). Here, requirements were assigned attributes denoting the organization and accountable operational role that requirement. Many organizations, operating complex offshore procedures, especially where operations are highly regulated, are looking to move their operational requirements from a document centric environment to a data centric environment. This paper highlights some potential pitfalls and mitigation strategies for ensuring a successful migration.
Comparing geometric differences between landsat collection-2 to collection-1 level-1 products

In late 2020 the U.S. Geological Survey (USGS) began the distribution of Landsat products associated with their collection 2 reprocessing of the archive. Several changes were implemented within the Landsat Product Generation System (LPGS) and the calibration parameters applied to the Landsat imagery for the collection 2 processing. When comparing between collection 1 and collection 2 products, radiometric and geometric differences will be present. One of the most substantial changes between the two collections was an adjustment to the ground control which made the control more accurate from an absolute and relative perspective. Some of the other changes associated with collection 2 processing were to the Digital Elevation Model (DEM) used in terrain correction, the Thermal Infrared Sensor (TIRS) relative gains, TIRS absolute calibration, Operational Land Imagery (OLI) absolute gain model, OLI relative gain, and OLI bias calculation to name a few. Although these changes also have an effect on the differences between the product associated with these two collections, the change in the ground control, although typically less than one 30-meter multispectral pixel in magnitude, will have the largest effect on the differences between the products. This change in ground control is also a spatially dynamic change that although is low in spatial frequency, is nonlinear and is not a change that can be modeled on a global or even on a local Worldwide Reference System-2 (WRS-2) path and row scale. The effects of these ground control changes will be discussed and demonstrated within this paper along with examples showing their effect on specific datasets. This paper demonstrates some of these geometric differences associated with the ground control through both the registration statistics created during product generation and through an example comparison of a set of collection 1 and collection 2 products.
Designing innovative open spaces for learning

Today, innovative learning spaces represent much more than just removable furniture and open spaces for workers. The digital revolution in business and education fostered by the rapid development of Internet-based tools and solutions and Information and Communication Technologies (ICT) brought about profound changes to this sector. The aim of this research is to carry out large-scale, cross-site studies to measure the current impact of ICT on working practices. Our research develops and presents the new models of learning in open spaces as well as tests how ICT can be used to support innovation and work practices. In this paper, we also single our and describe the necessary prerequisites and skills that are associated with the specific ICT functionalities that are presently needed for the entire open innovation process. Our results can be of a special use for educators, innovators, entrepreneurs as well as relevant stakeholders operating in business or education (or, perhaps, both). This research outlines the most useful recommendations and described the patterns for innovations in learning in novel open spaces.
Analisis Motivasi Belajar Pada Pembelajaran Daring Siswa Kelas XI Mipa 6 SMA N 1 Petarukan Pemalang

This research using a questionnaire was carried out to determine the learning motivation faced by students in class XI MIPA 6 SMA N 1 PETARUKAN because knowing physics student motivation is very important in online learning. The purpose of this study was to determine: 1. How much motivation to learn physics students in online learning, 2. The role of the questionnaire in knowing the motivation to learn physics students in online learning. This research uses the type of research in the form of students filling out a link containing a learning motivation questionnaire where 35 students of class XI MIPA 6 SMA N 1 PETARUKAN are given a link in the form of a questionnaire about learning motivation in online learning. The resulting data regarding students' learning motivation was analyzed descriptively quantitatively. In this study, data showed that students' learning motivation in online learning was from each indicator, namely: 1. Knowing the desire to learn 2. Knowing the need to learn 3. Knowing the virtues of good grades 4. Knowing their own efforts in learning 5. Knowing the environment conducive learning. The average data yielded Strongly Agree 56.4% (Medium), Agree 81.4% (High), Disagree 27.4% (Low), Strongly Disagree 6% (Low). It can be concluded that the learning motivation of students in class XI MIPA 6 SMA N 1 PETARUKAN in online learning shows a moderate enthusiasm for learning.
Data Mining for Discovering Cognitive Models of Learning

A cognitive model is a descriptive account or computational representation of human thinking about a given concept, skill, or domain. A cognitive model of learning, includes both a way of organizing knowledge within a subject area and an account of how humans develop accurate and complete knowledge of that subject area. Learning designers engage in a variety of practices to unpack knowledge from subject matter experts and novices to develop cognitive models of learning and use those models to guide the design of instruction or instructional technologies. Traditional approaches to eliciting and organizing knowledge, such as conducting a cognitive task analysis (CTA) [14] with experts and novices, are labor-intensive and require specific expertise that many learning designers do not have. However, learning data generated from learners’ interaction with courses, can provide insight into how humans think and develop knowledge. As a continued effort, we extend the framework presented in our earlier work [17] to discover and refine cognitive models of learning with learning data. The framework includes 1. a Variational Autoencoder (VAE) and a Gaussian Mixture Model (GMM) that models and clusters cognitive learning patterns; 2. a multidimensional measure that quantifies validity and reliability of the discovered cognitive models of learning; 3. a topic-based solution that interprets the cognitive models from a linguistic perspective; and 4. a simulation-based analysis for both accuracy measures and course refinement insights. We demonstrate the end-to-end solution with two applications and four case studies that are deployed in an openly navigated learning system in a workforce learning environment. We also report the usefulness of the discovered cognitive models of learning with subject matter expert evaluation.
Analysis of Selfish Miner Behavior in the Bitcoin Network

Selfish mining is a recognized misbehaving attack in Bitcoin. Selfish miners intentionally delay the release of newly mined blocks with the goal of gaining more revenue. While several studies have been devoted to analyzing the selfish miner behavior, the impact of selfish behavior on Bitcoin network performance has received little to no attention at all. In this work, we focus on that impact using a Markov chain that models selfish behavior both from the aspect of mining and form the aspect of block distribution time. We find that blocks mined by honest miners undergo longer distribution time compared to blocks mined by selfish miners. This delay results in intentional forking and the resulting network inconsistency provides more opportunity for selfish miners to gain unfair revenue.
Variational actor-critic algorithms,

We introduce a class of variational actor-critic algorithms based on a variational formulation over both the value function and the policy. The objective function of the variational formulation consists of two parts: one for maximizing the value function and the other for minimizing the Bellman residual. Besides the vanilla gradient descent with both the value function and the policy updates, we propose two variants, the clipping method and the flipping method, in order to speed up the convergence. We also prove that, when the prefactor of the Bellman residual is sufficiently large, the fixed point of the algorithm is close to the optimal policy.
Development for a metrology system for the Arcus MIDEX mission

Arcus is an innovative MIDEX-class photon-counting X-ray spectroscopy mission. Due to the nature of the sources that Arcus will focus on, observations can be many tens of kiloseconds (ks) long. The resulting spectral images are reconstructed on the ground to remove measured pointing and instrument deflection effects that take place over that time, achieving a higher resolution than would be possible without removing these effects. Arcus’s 12 m focal length grazing incidence optics are separated from the detectors by a 10.8 m long by Ø1.85 m, onorbit deployable boom. This paper describes an implementation of an internal aspect sensor that uses flight tested commercial off the shelf (COTS) components to measure linear deflection from one end of that boom to the other to achieve a better than 22 micron resolution (3σ) correction for that motion, meeting the required performance that Arcus needs to maintain its achieve its imaging resolution.
Handling Overlaps When Lifting Gaussian Bayesian Networks

Gaussian Bayesian networks are widely used for modeling the behavior of continuous random variables. Lifting exploits symmetries when dealing with large numbers of isomorphic random variables. It provides a more compact representation for more efficient query answering by encoding the symmetries using logical variables. This paper improves on an existing lifted representation of the joint distribution represented by a Gaussian Bayesian network (lifted joint), allowing overlaps between the logical variables. Handling overlaps without grounding a model is critical for modelling real-world scenarios. Specifically, this paper contributes (i) a lifted joint that allows overlaps in logical variables and (ii) a lifted query answering algorithm using the lifted joint. Complexity analyses and experimental results show that - despite overlaps - constructing a lifted joint and answering queries on the lifted joint outperform their grounded counterparts significantly.
Optimization of Target Artifact Under Diffuse Reflection

As a common way of information acquisition, digital image acquisition has a wide range of applications. In daily life, due to the limitation of the scene, there will be diffuse reflection in the process of image acquisition, which leads to the presence of artifacts or highlights in the process of image acquisition and affects the quality of image acquisition. In order to suppress the above situation, the suppression effect of homomorphic filtering on artifacts is studied, and the filtering effects of ideal low-pass, Gaussian low-pass and Butterworth low-pass are compared. In Butterworth low-pass filtering, the cut-off frequency has an obvious effect on the suppression, and an adaptive cut-off frequency is designed. Through experimental comparison, the designed adaptive cutoff frequency has a good effect on the suppression of artifacts.
Process-oriented Creative Thinking Education Model: the Perspective of Six-thinking-hats Based on T-test

Creative thinking education is not valued in colleges and universities, which stems from the fact that the existing model of creative thinking education is essentially a result-oriented model, and there are some problems such as opaque creative thinking process, lack of practicality and passive creativity. We need to establish the process-oriented education model of creative thinking. This model can be established by the transparent thinking process of Six-thinking-hats” sequence of white-green-yellow-black-red-blue. The Preparation stage of creative thinking corresponds to White-thin king-hat, the Gestation stage and the Clarity stage correspond to Green, Yellow, Black and Red thinking-hats, and the Verification stage corresponds to Blue-thinking-hat. It is appropriate that every stage embeds different thinking tools. Six-thinking-hats make the creative thinking process transparent. The tools also make creative thinking education practical and cultivate the awareness and habits of active creativity. The T -test shows that the process-oriented creative thinking education model is more conductive than the result-oriented one.