Reviewerly/exHarmony huggingface dataset:
Research on the strategy of improving sports skills in colleges and universities from the perspective of virtual reality

With the rapid development of virtual reality technology, the field of physical education in colleges and universities has gradually focused on the development of the organic integration of virtual reality technology and sports skills. Aiming at the limitations of this field and the practical needs of college sports technology difficulty, this paper investigates the basic situation of the application of virtual reality technology in sports skills teaching in 7 colleges and universities in Shaanxi, China by means of questionnaire survey and statistical analysis. The actual demand of virtual reality technology in college sports skills, college sports students’ motivation to participate in virtual reality technology, use experience and demand sports items are statistically analyzed. Finally, in view of the challenges of using virtual reality technology in college sports skills, reasonable strategies are put forward, aiming to provide more effective and interesting auxiliary teaching methods for college sports technology teaching.
Mathematical modelling of some simplest fuzzy two-term (PI/PD) controllers

From the literature, it appears that the combination of Mamdani Minimum (MM) inference and Centre of Area (CoA) defuzzification was rarely used for the modelling of the Simplest Fuzzy (SF) two-term (PI/PD) controllers. In this work, to reduce this gap, mathematical models of three SF two-term controllers are unveiled via MM inference and CoA defuzzification. Apart from modelling, properties of the newly derived controllers are analysed. Finally, to illustrate the applicability of the controllers developed in this article, a simulation example and a real-time study are provided.
Monitoring system for electrical variables implementing blockchain and python

Objective: This article presents one of the Blockchain applications in power systems employing the electrical variables monitoring delivered by a simulated relay.&#x0D; Methodology: The electrical variables are verified, compared, and uploaded to a blockchain network created by a network of servers; these are responsible for uploading, validating, and exporting information to the system. This study is carried out through the Python programming language.&#x0D; Results: An algorithm capable of integrating these variables from a simulated relay is created, 4 servers are created that are in charge of taking the relay signals every minute, validating that they are unique in the blockchain and uploading them, the first node that completes this task uploads its identification and the information of the relay, the processing times of the information once obtained are approximately 10 seconds&#x0D; Conclusions: It is concluded that the algorithm is capable of decentralizing the information collected by the servers in times equal to or greater than one minute, which can be very useful when saving information, in applications such as control by the network operator it falls short by having times greater than or equal to one minute, it should be taken into account that, for the development of a blockchain with a greater number of equipment, it is advisable to use machines with high levels of processing, much higher RAM memories, these characteristics allow the algorithm to run smoothly and in the shortest possible time.&#x0D; Financing: Universidad Distrital Francisco José de Caldas
Markowitz Meets Technical Analysis: Building Optimal Portfolios by Exploiting Information in Trend-Following Signals

Technical indicators are widely used by market participants to identify trends in asset prices and in trading volumes. However, it is unclear how to reconcile this approach with a portfolio selection policy that guide investment decisions in many assets at the same time. We bridge the gap between Markowitz approach to mean-variance portfolios and technical analysis by devising a portfolio strategy in which optimal weights are directly parameterized as a function of multiple trend-following signals. We present an empirical application in which four commonly used technical indicators are employed to obtain portfolios of all constituents of the S&P500 index.
Antecedents to Continuance of Use Intention of Adopting Learning Management System (LMS) in E-commerce Learning: Implementation of IS Success Model

This research aimed to analyze the continuance of use intention of adopting Learning Management System (LMS)using IS success model.This research used four independent variables to evaluate the continuance of use intention of adopting LMS: LMS quality, knowledge quality, perceived of use, LMS satisfaction, and continuance to use intention.The population of this research was the younger generation using the LMS from Kampus Komerce for ecommerce online training in Indonesia.The sample size of this research was 150 chosen randomly chosen respondents.The analysis tool used was Structural Equational Modeling with Partial Least Square.The research result proves that LMS quality has a positive impact on the perceived of use and LMS satisfaction, knowledge quality has a positive impact on perceived of use and LMS Satisfaction, perceived of use has a positive impact on LMS satisfaction, perceived of use, and LMS Satisfaction has a positive impact on the continuance to use intention.Therefore, this outcome supports the IS success model within the LMS context.
Topic Outlines, a tool to focus report writing

TAs reported that development of the activity allowed them to 1) practice integrating multiple perspectives to find the fundamental themes that they agreed were the most important to set students up for success; and 2) changed their approach to teaching by ensuring that they know what skill is being worked on in each activity and they now look for alignment between the learning outcome and the student activity instructions.
Least Privilege Learning for Attribute Obfuscation

As machine learning systems become ever more prevalent in everyday life, the need to secure such systems is becoming a critically important area in cybersecurity research. In this work, we address the “feature misuse” attack vector, where the features output by a model are abused to perform a function that they were not originally designed for, such as determining a person’s gender in a facial verification system. To mitigate this, we take the security concept of “least privilege”, where a system can only access resources it explicitly needs to complete its task, and apply it to training deep neural networks. This “least privilege learning” ensures features do not contain information regarding protected attributes that are superfluous to the primary task, reducing the potential attack surface for feature misuse and reducing undesired information leakage. In this paper, we present two main contributions. Firstly, a novel training paradigm that enables least privilege learning by obfuscating protected attributes in verification and re-identification scenarios. Secondly, a comprehensive evaluation framework for models trained with least privilege learning, encompassing multiple datasets and three application settings: verification, re-identification, and attribute prediction.
MEMORANDUM ON THE RESULTS OF THE AUDIT IN ULYANOVSK PEDAGOGICAL INSTITUTE FOR 1932-1933 ACADEMIC YEAR (TO THE 90TH ANNIVERSARY OF THE ULYANOVSK STATE PEDAGOGICAL UNIVERSITY NAMED AFTER I. N. ULYANOV)

A memorandum is published on the results of a survey of the Ulyanovsk Pedagogical Institute activity after the first academic year (1932-1933). The original document is stored in the State Archive of the Recent History of the Ulyanovsk Region. The published material reflects the institute's success in the educational process management and recruiting students. It also notes the difficulties and problems that educational institutions of this level faced in general at their first stage of development.
Distribution of Horseshoe Crabs Satellites Analyzed by Logistic Regression

Pairs of horseshoe crabs arrive at the beach and spawn during spring.Single males go to the beach as well, and they make competition against males with partners for fertilization.The group size of satellite males is so large that there is a nonrandom distribution in which habitat selection and local environmental conditions are not responsible.The experimental manipulations show that satellites cannot only copy other male satellites' behaviors.According to the evidence revealed by experiments and observations, the possible explanation about the nonrandom distribution of satellite males located among nesting pairs is that it is more likely for unattached satellite males to attract females than others.To analyze the data from this study, R was used to generate the confusion matrix, which checks if the predictable value is close to the actual value, logistic regression, which checked if the model should be modified, and logit function to evaluate the model.As a result, logistic regression showed that the model should be modified because it was not proper.Width and weight were selected as variables.In conclusion, the logistic regression showed that a male horseshoe crab with larger width and weight was more likely to own satellites.Also, the color of a horseshoe crab was related to the satellite.
Elastic Resource Allocation Based on Dynamic Perception of Operator Influence Domain in Distributed Stream Processing

With the development of distributed stream processing systems, elastic resource allocation has become a powerful means to deal with the fluctuating data stream. The existing methods either focus on a single operator or only consider the static correlation between operators to perform elastic scaling. However, they ignore the dynamic correlation between operators in data stream processing applications, which leads to lagging and inaccuracy resource allocation, increasing processing latency. To address these issues, we propose an elastic resource allocation method, which is based on the dynamic perception of operator influence domain, to perform resource allocation dynamically and in advance. The experimental results show that compared with the existing methods, our method not only guarantees that the end-to-end latency meets QoS requirements but also reduces resource utilization.
Bayesian Detection of a Sinusoidal Signal With Randomly Varying Frequency

The problem of detecting a sinusoidal signal with randomly varying frequency has a long history. It is one of the core problems in signal processing, arising in many applications including, for example, underwater acoustic frequency line tracking, demodulation of FM radio communications, laser phase drift in optical communications and, recently, continuous gravitational wave astronomy. In this paper we describe a Markov Chain Monte Carlo based procedure to compute a specific detection posterior density. We demonstrate via simulation that our approach results in an up to 25 percent higher detection rate than Hidden Markov Model based solutions, which are generally considered to be the leading techniques for these problems.
Incorporating Contextual Information in Prediction Based Word Embedding Models

A clustering-based language model is proposed for analyzing the performance of context sensitive word embedding models that uses contextual information. The construction of text readability and prediction models faces several shortcomings due to the complex nature and structure of language. The language structure is complicated all the more by words having vastly different meanings and interpretation based on the context in which it is used. This paper aims to resolve this issue by first clustering the sentences based on similarity and then performing word embedding separately on each of these clusters to obtain an enhanced outcome. This would serve to embed the same word separately in varying context as an improvement over the standard existing word embedding models provided by various prediction based models. Comparing the two approaches, our results have showed that clustering improves the performance of the model and discriminate the contextual information based on sense which leads to more accurate representation in vector form.
The Impact of the k-Nearest Neighbor Parameters in Collaborative Filtering Recommender Systems

Recommender Systems (RS) have become very important recently, they are a main component of many applications in different fields. They aim to give beneficial information according to the profile of each user among the huge existing online information. RS are based on several approaches to provide the best results and give satisfaction to the active user. Collaborative filtering is one of these approaches. It helps to choose a product according to the consumer’s preference from many and various choices. It uses the k-Nearest Neighbor (kNN) technique for the extraction of similar users from the group of users. In this paper, we will study the effect of the parameters of the kNN algorithm on the obtained results. For that, we have varied the value of k, then we have measured for each value the prediction accuracy, using the Root Mean Square Error (RMSE), and the Mean Absolute Error (MAE) metrics. The experiments are carried out also to find the value of k which gives good results in both metrics. Then we have calculated also the RMSE and MAE metrics for different similarities in order to find the similarity which gives good results compared to others.
Extrinsic Parameters Self-calibration Algorithm for Surveillance Camera Integrating Ground-Pedestrian Constraints

To solve the problem that the extrinsic parameters calibration of surveillance camera needs manual operation and complex process, an extrinsic parameters self-calibration algorithm is proposed. Firstly, the monocular depth estimation network is used to estimate the depth information of the scene from the images. In addition, the plane areas are detected by the instance segmentation network. Then RANSAC is applied to overcome the influence of noise points on the ground point cloud and regress the ground parameters. Meanwhile, the pedestrian geometric model is used to estimate the ground parameters from the pedestrian head and foot position sequence. Finally, considering the redundancy of the two estimates, a BP neural network is established to fuse the two estimations for higher precision camera extrinsic parameters. Experiments show that the algorithm can effectively take the advantages of depth estimation and pedestrian geometric model, and has higher automation level and estimation accuracy than the traditional camera self-calibration algorithm which is based on pedestrian geometric model.
PENGEMBANGAN E-MODUL DENGAN APLIKASI 3D PAGEFLIP PROFESSIONAL UNTUK MENINGKATKAN HASIL BELAJAR PADA PEMBELAJARAN IPA KELAS 5 SEKOLAH DASAR

This study aims to: Determine the improvement of E-Module with the 3D PageFlip Professional application to improve learning outcomes in science learning in grade 5 elementary schools. This type of research is a Research and Development with a non-randomized subject experimental method pre-test post-test control group design. With respondents, the number of students of SDN Gugus Sunan Muria, Demak District was 280 students. This study uses a quantitative approach. The results of this study indicate the highest value obtained in the control group is 84 and the lowest value is 55 with an average of 67.The highest score obtained in the experimental group is 93 and the lowest score is 67 with an average value of 80 indicating that the average value of the experimental group is greater than the control group experienced a significant difference. The data from the t test shows that t count t table, namely 26.041 1.6503 and the N-Gain value is in the high category and the interpretation is very effective. Based on this research it is requested that to improve student learning outcomes using e-modules by using the 3D Pageflip professional application.
Pemberdayaan Guru SD/MI Melalui Peningkatan Kualitas Pembelajaran Matematika

This activity aims to provide basic knowledge about learning mathematics how to use media and several learning models, one of which is RME, as well as knowledge about the 2013 curriculum. math. To increase the basic knowledge of mathematics learning, the trainees were given basic knowledge and skills on: 1) Mathematics Learning Problems at SD/MI Level, 2) Elementary Mathematics Textbooks according to the 2013 Curriculum, 3) RME, 4) Fun Mathematics Learning Methods. The service was held at SDI Makarimul Akhlak Building with ±30 participants on Saturday, May 14-19 2016. The methods used were lecture, practice, question and answer, discussion and practice methods. Based on the results of the evaluation, it turned out that in general there was an increase in the knowledge of the training participants for the empowerment of SD/MI teachers in improving mathematics learning, this was evidenced by the tasks given to the participants. In the future, the hope of this activity is that participants can practice in class during math lessons and can transfer the knowledge that has been obtained to other SD/MI teachers.&#x0D; Keywords: Mathematics, RME, Curriculum 2013
Payroll Accounting System of Lecturers At Politeknik Harapan Bersama

Abstact:In carrying out its company operations, companies need to develop an adequate system and procedure so that all company activities can run smoothly.In providing salaries or wages, companies may not give salaries or wages arbitrarily, because salaries or wages are a form of company appreciation for all employee contributions to the company for the work that has been done, the amount of income received by the employee, the minimum must follow the laws and government regulations that regulate wages that are adjusted in each region in the form of the Minimum Wage.This study aims to determine the salary information system for lecturers at Politeknik Harapan Bersama.This study uses primary data in the form of interviews with the Head of Finance and Head of Personnel at Politeknik Harapan Bersama and uses secondary data in the form of organizational structure and payroll system flowcharts.The analytical technique used in this study is qualitative analysis which underlies theory of Mulyadi (2001).The results of this study can be said that the payroll information system at the Harapan Bersama Polytechnic is in accordance with the theory of Mulyadi (2001) with the compatibility between the functions involved in the system, the documents used, internal controls, accounting records, and flowcharts on the payroll system for the lecturers of Politeknik Harapan Bersama.The Accounting Section which controls the lecturers' payroll process is still in the Finance Department, therefore it is recommended that the Accounting Section become an independent section in order to have better policies in the process of controlling the payroll system for Politeknik Harapan Bersama lecturers.
A Study of Early Childhood Education and its Impact on Student Learning Skills: An Evidence from Tehsil Shorkot, Pakistan

Early childhood education covers the period from birth to six years. The area of the study was limited to primary school teaching classes. The study was conducted in Tehsil Shorkot. All primary school Teachers of Tehsil Shorkot were this study's population. The sample of the study was 20 schools which were selected by using the purposive sampling technique. The teachers were the study's respondents, six teachers from each school were taken as a sample, and 120 teachers were selected in this way. A well-structured questionnaire was used to collect the data, and the data were analyzed using SPSS. The study concluded that in early childhood education, students follow the discipline, and it plays an essential role in life coming after it. Students showed enthusiasm while reading and writing. Effect of early childhood education on students, which things in their surroundings are introduced to them. Students work with their friends and try to help them. Board was used to make different shapes. Data also revealed that weather charts used to memorize seasons name, a poster on health and hygienic food used to develop healthy clean habits, shape kit used to recognize different shapes like circle triangles, etc.; flashcards used to show various concepts of daily science. Helping visualizing ideas via AV aids and multimedia was a great strategy to make students' concepts very clear. About three-fourths of respondents said that colored pencils papers used for different activities. ECE rooms develop listening skills via other storybooks and playground equipment like skipping rope and climbing structures are used for exercise.
Implementasi Pengelolaan Education Management Information System (EMIS) di Madrasah Diniyah Takmiliyah Al Hidayah Mojokerto

Implementation Of Education Management Information System (EMIS) Management in Madrasah Diniyah Takmiliyah Al Hidayah Mojokerto. The Education Management Information System (EMIS) at Madrasah Diniyah Takmiliyah Al Hidayah is an information system that collects madrasa data online with one door. However, in reality, there are still obstacles and problems, such as the EMIS network, which is often problematic, and the information for updating EMIS data often seems sudden. This hinders the management of EMIS data at Madrasah Diniyah Takmiliyah Al Hidayah.This study aims to determine the effectiveness of EMIS in Madrasah Diniyah Takmiliyah Al Hidayah and its influence in the decision-making of the Mojokerto district government to determine Regional Operational Assistance for Madrasa Diniyah Takmiliyah Al Hidayah. This research has the benefit of letting the public know that at Madrasah Diniyah Takmiliyah Al Hidayah Mojokerto, in managing madrasa data, they have used an online system, namely EMIS, so that the data in EMIS Madrasah Diniyah Takmiliyah Al Hidayah can be reached anywhere and anytime. This study uses a qualitative descriptive method, while for data collection using interview, documentation, and observation techniques
Meningkatkan Keterampilan Berbicara Menggunakan Metode Teams Games Tournaments (TGT)

Improving Speaking Skills Using the Teams Games Tournaments (TGT) Method. This classroom action research aimed at describing the speaking skill learning process using the Teams Games Tournaments (TGT) method for the first-year students of Indonesia Language and Literature Education, Muhammadiyah University of Kupang 2019/2020 academic year. The research was conducted in two cycles. The data were collected through observation, tests, and documentation. The data were analyzed quantitatively and qualitatively. The study showed that there was an improvement in the learning process and the studentâ€™s score after applying the Teams Games Tournaments method. Students were motivated and enthusiastic in learning activities. There was an active interaction between students and lecturers during the learning process. In addition, there was also an improvement in the studentsâ€™ speaking skill scores. In the first cycle, the whole average of studentsâ€™ score was 66.13 became 75,33 in the second cycle