Reviewerly/exHarmony huggingface dataset:
A Benchmark for Bivariate Causal Discovery Methods

&amp;lt;p&amp;gt;The Earth&amp;amp;#8217;s climate is a highly complex and dynamical system. To better understand and robustly predict it, knowledge about its underlying dynamics and causal dependency structure is required. Since controlled experiments are infeasible in the climate system, observational data-driven approaches are needed. Observational causal inference is a very active research topic and a plethora of methods have been proposed. Each of these approaches comes with inherent strengths, weaknesses, and assumptions about the data generating process as well as further constraints.&amp;lt;br&amp;gt;In this work, we focus on the fundamental case of bivariate causal discovery, i.e., given two data samples X and Y the task is to detect whether X causes Y or Y causes X. We present a large-scale benchmark that represents combinations of various characteristics of data-generating processes and sample sizes. By comparing most of the current state-of-the-art methods, we aim to shed light onto the real-world performance of evaluated methods. Since we employ synthetic data, we are able to precisely control the data characteristics and can unveil the behavior of methods when their underlying assumptions are met or violated. Further, we give a comparison on a set of real-world data with known causal relations to complete our evaluation.&amp;lt;/p&amp;gt;
An Improved LC Visual Attention Detection Algorithm

Image visual attention detection is a hot research topic in recent years and an important research direction in the field of computer vision. An excellent image visual attention detection algorithm will greatly improve the accuracy of subsequent image segmentation, target recognition, and image retrieval so that we can have a more comprehensive and accurate understanding of the target contained in the image. This paper in view of LC image attention detection algorithm without considering the spatial information of image pixels places saliency map, this paper proposes an improved LC image attention detection algorithm, the method fully considers the pixel grayscale contrast and the spatial distance of saliency map, and the influence of the mathematical model is established for each pixel point distribution of the significance of exclusive value. Finally, we used MATLAB to program the algorithm and tested the algorithm on MSRA 10K, the test set of public image data. The experimental results showed better performance than LC algorithm, which proved that our idea was effective.
DESIGN OF INTELLIGENT SERVICE SYSTEM FOR MIDDLE SCHOOL STUDENTS'GROWTH BASED ON CROSS DOMAIN BIG DATA FUSION

The state attaches great importance to the development of the comprehensive quality of primary and secondary school students, and the application of intelligent technology to serve education has been favored. The current smart campus service technology can no longer meet the requirements of data collection, governance and decision-making assistance. This paper proposes a method to create a multi-dimensional campus intelligent perception platform to collect huge multi-domain, multi-dimensional, and heterogeneous student data, and to use cross-domain big data fusion technology to establish a student growth smart service platform. This method designs a smart service system for the growth of middle school students. The system has the functions of integrating information resources, pushing targeted and customized talent development suggestions, as well as warning and intervention for related problems. These results can be more objective, comprehensive and efficient evaluation of students' comprehensive quality, push personalized education, and promote the healthy growth of middle school students.
Using the numerical solution for partial fractional differential equation by ADI numerical method to cryptography in Hill matrix system

Calculus is the subject of evaluating derivatives and integrals of non-integer orders of a given function, fractional differential equations is the subject of studying the solution of differential equations of fractional order is considered in this paper, which contain initial conditions. The general form of a fractional differentia equation is supported by:y(s) = k(c, u), y(stk) (c0) = u.Where k = 1, 2, … , n + 1, n < q < n + 1, and n is an integer number. The solution of fractional differential equations has so many difficulties in their analytic solution, therefore numerical methods may be in most cases be the suitable method of solution.This paper introduces and study a numerical solution by ADI methods for solving fractional differential equations.We used the matrix obtained from this solution as a key matrix for cryptography the plain text and transform it to cipher text by using the method of Hill matrix system the quantity demand and investment in research and development, while the other model focuses on a more realistic relationship between the quantity demand and the price.
Multiplying Matrices Without Multiplying

Multiplying matrices is among the most fundamental and compute-intensive operations in machine learning. Consequently, there has been significant work on efficiently approximating matrix multiplies. We introduce a learning-based algorithm for this task that greatly outperforms existing methods. Experiments using hundreds of matrices from diverse domains show that it often runs $100\times$ faster than exact matrix products and $10\times$ faster than current approximate methods. In the common case that one matrix is known ahead of time, our method also has the interesting property that it requires zero multiply-adds. These results suggest that a mixture of hashing, averaging, and byte shuffling$-$the core operations of our method$-$could be a more promising building block for machine learning than the sparsified, factorized, and/or scalar quantized matrix products that have recently been the focus of substantial research and hardware investment.
Design of Educational Modules in the Development of Economic Competency in Professional Development

This article describes the experience of designing a professional education system based on the integration stages and the Four Stages of Competence stages of training modules that are similar in content to the development of the economic competence of managerial personnel during professional development
Book Review of 'Law for Computer Scientists and Other Folks' (Mireille Hildebrandt, Oxford University Press, 2020)

Book Review of the Book by Mireille Hildebrant: 'Law for Computer Scientists and Other Folks' published by Oxford University Press in 2020 both in online open access and in hardcopy.
Quantum Watermarking Scheme based on Spatial Domain and Frequency Domain

Quantum watermarking technology, which is used in anti-counterfeiting and copyright protection, play an important role in the future quantum computer era. To embed more data and reduce image distortion, a novel quantum watermarking method of combining spatial domain and frequency domain is proposed. To this end, the carrier and watermark image are prepared by the novel quantum model of color digital images.  The proposed quantum watermarking method is divided into two parts according to the needs of the owner and the importance of the watermarks. These two parts of watermark are embedded into the cover using the spatial and frequency domain. Analysis indicates that the complexity of the watermark separation process increases the difficulty for the attacker to reconstruct the quantum watermarking. Numerical simulation results using MATLAB software shows that this algorithm has better embedding capacity. Not only that, it also has good invisibility and can ensure the security.
ESTRATEGIAS DIDÁCTICAS B-LEARNING PARA EL APRENDIZAJE DE QUÍMICA EN TERCER AÑO DE EDUCACIÓN MEDIA TÉCNICA

The present article deals with the achievements in the learning of the chemical nomenclature obtained with the application of b-learning didactic strategies in Venezuelan students of third year of Secondary Technical Education. Based on a projective research, with field design, the methodology was planned in four stages: diagnosis, planning, execution, and evaluation. The techniques of observation, survey and in-depth interview were applied, using the field diary and questionnaires as instruments. The importance of the work is reflected in the proposal of strategies that allowed the development of cooperation skills, critical thinking, meaningful learning, motivation, and active participation of students in activities, both in a classroom setting and through a virtual learning environment (VLA), allowing them to strengthen their competencies in an integral way, thus promoting other ways of teaching and learning chemistry or another area of knowledge.
Use of Automatic Scoring Type Materials in Practical Class of Real-time Operating System

Authors proposed the teaching material system of education-oriented μITRON4.0 specification operating system on 8-bit PIC microcontrollers, and reported its class practice in the Polytechnic University of Japan1). This paper proposes a set of automatic scoring type materials for the same real-time OS class as additional teaching materials. This paper also shows the effectiveness of the proposed materials in terms of educational effect and intrinsic motivation for students by its class practice.
UTAUT2를 응용한 4차 산업 기술수용에 관한 연구 : 증강현실(AR)과 드론 서비스를 중심으로

This study analyzed the factors influencing the technology acceptance of the general public in the drones and ARs, one of the key technologies of the industry 4.0. The theoretical basis was the extended unified theory of acceptance and use of technology model(UTAUT2), which uses performance expectancy, effort expectancy, social influence, facilitating conditions, and hedonic motivation as factors common to both services. The price value factor was excluded considering that most ARs were free, and the perceived risk factors, including privacy, which were not in UTAUT2, were included because they are important factors for ICT technology acceptance. The hypothesis was tested by structure equation model. Social influence and hedonic motivation had a positive(+) effect on intention to use technology. On the other hand, in the case of effort expectancy, neither the AR nor the drone had a significant influence on intention to use technology. Furthermore, performance expectancy had a positive(+) effect on intention to use in AR, but no significant influence was found out in drones. On the contrary, in the case of the facilitating conditions, the influence of the drones was positive (+), but the relation of AR was not investigated. The perceived risk was tested for the negative (-) influence of use intention of AR, but no significant relationship was found out for the drones. Among the significant influencing factors, hedonic motivation was the most powerful factor in AR and drones. Theoretical and practical implications are presented based on these results.
Virtual Reality Chinese Teaching System Based on Deep Learning Algorithm

One belt, one road initiative, China has been gradually strengthening its exchanges and cooperation with other countries along the way. Language communication is a prerequisite for the smooth progress of bilateral relations. Chinese has become an important language for international communication. Multi-objective genetic algorithm has the ability to deal with large problem space. In a step of evolution, multiple feasible solutions can be obtained, and there is no requirement for prior knowledge in the problem domain. It is insensitive to the convexity of function definition domain. This paper studies one belt, one road, and the basic theory and method of genetic algorithm and its multi-objective optimization problem. It studies the problems of language learning, teaching process, selection of teaching materials and teaching management. In order to improve the quality of Chinese teaching, we should consider and explore the reform of Chinese teaching from the aspects of standardizing student management.
Sustaining Cultural Tourism Through Higher Female Participation in Nigeria: The Role of Corporate Social Responsibility in Oil Host Communities

This paper adds to the gender discourse in sustainable African tourism development from the corporate social responsibility (CSR) perspective. Specifically, we examine the impact of CSR on the development of rural women in cultural tourism. A total of 600 rural women were sampled across the Niger Delta. Results from the use of a logit model indicate a significant relationship between CSR and cultural tourism development in oil host communities in Nigeria. This implies that CSR of a multinational oil company (MOC) is a critical factor for sustaining cultural tourism. The findings suggest increased female participation in General Memorandum of Understanding (GMoU) interventions of MOC and the need to pay close attention to which extent the participation of rural women in the GMoU projects may be limited by cultural and traditional obstacles.
Macro-Fiscal Gains from Anti-Corruption Reforms in the Republic of Congo

This paper argues that oil revenue management and public investment in Congo are vulnerable to corruption as a result of limited transparency and accountability. Corruption has potentially contributed to poor macro-fiscal outcomes. The paper acknowledges the authorities' anti-corruption efforts made so far and proposes further critical reforms to reduce remaining vulnerabilities. Using a dynamic stochastic general equilibrium model results show that, depending on the reforms adopted, the potential additional growth can range between 0.8 to 1.8 percent per year over the next 10 years, and debt can decline by 2.25 to 3 percent of GDP per year over the same period. These results suggest that macro fiscal gains from anti-corruption reforms could be substantial even under conservative reform scenarios.
BI-DIRECTIONAL MONTE CARLO TREE SEARCH

This paper describes a new algorithm called Bi-Directional Monte Carlo Tree Search. The essential idea of Bi-directional Monte Carlo Tree Search is to run an MCTS forwards from the start state, and simultaneously run an MCTS backwards from the goal state, and stop when the two searches meet. Bi-Directional MCTS is tested on 8-Puzzle and Pancakes Problem, two single-agent search problems, which allow control over the optimal solution length d and average branching factor b respectively. Preliminary results indicate that enhancing Monte Carlo Tree Search by making it Bi-Directional speeds up the search. The speedup of Bi-directional MCTS grows with increasing the problem size, in terms of both optimal solution length d and also branching factor b. Furthermore, Bi-Directional Search has been applied to a Reinforcement Learning algorithm. It is hoped that the speed enhancement of Bi-directional Monte Carlo Tree Search will also apply to other planning problems.
Placing the Courses in Question Booklets with A* Algorithm in Central Exams

With the Covid-19 epidemic that turned into a global epidemic, interest in online journalism has increased as much. The quarantine process spent at home has meant the beginning of the golden age of new internet-based communication technologies. Now, there is the “phygital” process, which is the period in which the physical and the digital are combined. Many scientific data and opinions have brought into question the permanence of this period, which is called the “new normal”. This study focuses on the question of whether it’s possible to reproduce the news in the context of the concepts of “new normal” and “phygital” in the news about pandemic in the online journalism environment. This situation shows that it is important to review many headlines of the news from news value to content. For that reason, it’s seen that in the news in which daily cases are dealt with during the pandemic process, nothing other than the numbers flying in the air over time. This shows that over time information becomes meaningless, intricacy and the purpose of the news is lost. The fact that a news is embedded in patterns where only the daily number of cases are given rather than justified information causes the interest in the news to decrease over time. With this study, how the news about the pandemic is given on the daily most clicked news sites is evaluated through the macro structure in Van Dijk's discourse analysis model.
Pengaruh Metode Chain Writing terhadap Keterampilan Menulis Siswa Kelas V Sekolah Dasar

This study aimed to find out the effect of the implementation of the Chain Writing method on writing skills of grade V SDN Cisasah in learning to developing main ideas. This was a quantitative research with quasi experimental design. The basic consideration for using this design was that learning takes place naturally and the results obtained could be used to measure the effect of a treatment in the characteristics of the subject. The subject of this study were students grade V who came from two groups of students, namely the experimental group (implementing the Chain Writing method) and the control group. The data were collected through test technique divided two part, namely pretest and. The analysis technique this study was t-test. Based on this research showed that: (1) there are differences in the ability to writing skills to develop main ideas between students from experimental group with control group as evidence by the Sig. (2 tailed) is 0.00&lt;0.05; and (2) there is an effect of implementing Chain Writing method for improving writing skills to developing the main ideas. Based on the mean value of the posttest results showed the experimental group is greater than the control group (83.70&gt;57.90)
Numerical investigation of effects of lip stiffness on reed oscillation in a single-reed instrument

The sound of a single-reed instrument is produced by the interactions among flow, reed oscillation, and acoustic resonance in the resonator. To investigate the effects of lip stiffness on the reed oscillation and acoustic propagation in the single-reed instrument, we conduct a flow simulation coupled with a dynamic beam analysis. The flow and acoustic fields are simulated by solving the three-dimensionalNavier–Stokes equations, while the geometry of the instrument is expressed by the volume penalization method in the computational grids. The lip force on the reed is modeled as a function proportional to the distance between the lip position and reed surface, and the coefficient of lip stiffness was changed in the simulation. The mouthpiece of the instrument was set in the pressure chamber. The results showed that the self-sustained oscillation of reed started by adjusting the initial pressure condition of the chamber without the lip force, and amplitudes of the reed displacement decreased until a stable condition by adding the lip force. The lip stiffness was found to affect the amplitude of reed displacement, indicating the necessity of controlling the lip force to obtain stable oscillation.
Big Data Processing Using Serverless Computing

Big data is a term that refers to a significant amount of structured, semi-structured, or unstructured data. In today's business world, data is critical to the success of a company. Big Data projects and technologies are being utilised to examine this huge amount of data in order to gain insights that can aid in strategic decision-making. That is why managing such a big amount of data will be difficult and complex. In practise, there are several challenges to processing and calculating this data, including server administration, storage, clustering, algorithm deployment, and so on. Because everything is done manually in the Cloud, it's impossible to design the correct architecture for data analysis. Serverless computing is a method of providing clients with pay-per-use backend services. Serverless computing is a method of providing clients with pay-per-use backend services. Users can write and deploy programmes without having to worry about running and managing servers with a serverless service. This paper illustrates how to implement, operate, and control a serverless big data application on AWS, as well as how to provide a serverless architecture for big data processing (Amazon Web Service). In addition, in a serverless system, we will show the distinction between standard data analytics and big data analytics.
To Physics Journal

The journal is keen to publish the scientific results of the original research in the form of full papers and short notes. Review Articles from various branches of Physics are also invited for publication. The Journal emphasizes both fundamental andÂ applied research work in Physics.Â  The journal publishes refereed papers covering current research in Physics in the following category: Astrophysics, Atmospheric and Space Physics; Atomic & Molecular Physics; Biophysics; Condensed Matter Physics; General & Interdisciplinary Physics; Nonlinear dynamics & Complex Systems; Nuclear Physics; Optics and Spectroscopy; Particle Physics; Plasma Physics; Relativity & Cosmology; Soft condensed matter Physics; Statistical Physics; Materials Physics.
PERBEDAAN STRATEGI READING ALOUD DENGAN TWO STAY TWO STRAY TERHADAP HASIL BELAJAR SISWA PADA MATA PELAJARAN IPS EKONOMI KELAS 8 SMP NEGERI 12 PAREPARE

Research Objectives is the purpose to find out 1) Students' learning outcomes on subjects IPS Economics with the application of Reading Alound Strategy on 8th grade students of SMP Negeri 12 Parepare; 2) Student learning outcomes in Economic IPS subjects with the application of Two Stay Two Stray Strategy on 8th grade students of SMP Negeri 12 Parepare and 3) Differences in students' IPS learning outcomes between the application of Reading Alound Strategy and Two Stay Two Stray in Grade 8 students of SMP Negeri 12 Parepare. This research is a quasi experimental research (quasi experiment) with pretest posttest equivalent group design (pretest post group design). The subjects of this study were the eighth grade students of the even semester of the 2017/2018 lesson year that the division; class 8.1 amounted to 22 people and class 8.2 amounted to 23. This study was conducted in 3 meetings. Data collection techniques in this study using observation sheets, tests and documentation. Instrument validity test is performed by expert judgment and for test questions using item analysis by calculating the level of difficulty and different power. Furthermore, the reliability test is calculated using the formula KR-21. For prerequisite analysis test, normality test using Kolmogorov-Smirnov test and for homogeneity test using Levene test. Data analysis techniques for hypothesis testing using the formula-t test polled variance two independent samples. The results showed that: 1) Learning outcomes with Reading Alound Strategy at the time of pretest known the average value of the result is still that is 66.74 while at the posttest of 70.65. 2) Learning outcomes with Two Stay Two Stray Strategy at the time of pretest is 72,39. At postest it is known that the average yield value is 82.83. 3) There is difference of learning result value with Reading Alound Strategy with Two Stay Two Stray Strategy at Grade 8 students of SMP Negeri 12 Parepare. This can be seen from the results of hypothesis testing using the test-t polled variance at the student's posttest value menunjuukan that thitung is equal to 2.097 larger than the ttabel whose magnitude is 1.994.