Reviewerly/exHarmony huggingface dataset:
Pengembangan Media Animasi Fisika Menggunakan Software Adobe Flash Cs6 Pada Materi Momen Gaya

In this study aims to find out the feasibility of physical animation media using adobe flash software Cs6 on material moment style. This research uses 4D research design consisting of 4 stages, namely Define, Design, Develop, and Disseminate. This research can only be completed in the development stage, this is due to the Covid 19 pandemic globally so researchers can not do the next research step. In this study using the instrument of initial needs observation sheet research and expert validation test questionnaire consisting of media experts and material experts. Based on the data of the results of research and discussion that has been described, it can be concluded that the Development of Animation Media Using Adobe Flash CS6 In the material of the style moment using the 4D model as the research is very feasible to use proven with the results of design validation conducted by means of validation tests media experts and material experts get results of 85 % and 80 % with very decent results and worth to use.
DIRECTIONS OF DEVELOPMENT OF LEARNING MANAGEMENT SYSTEMS

The article considers the concept of a learning management system; examines the principles of a learning management system; highlights the features of Learning Management Systems; provides an analytical review of the most common learning management platforms. The article reveals a comparative analysis of both commercial and free integrated electronic management systems of the educational process with electronic management systems of their own development of higher educational institutions, as well as their functional capabilities in management educational process and their characteristics. Known educational management systems the process is focused on supporting the main functions of training. When analyzing the scientific literature on the development of control systems, we found that many scientists have dealt with this problem. The article discusses in detail the most popular learning management systems. We found that most users had such management systems as: Moodle, Claronline, ATutor, Mindflash, SkyPrep , Sakai, OpenACS. We analyzed each management system and found out how they differ, what software is needed to install the platform. For a visual example, we have inserted an image of each learning management system so that when describing it, we can see a real picture of the software. Visualization helps inform readers about the program. This made it possible to identify the advantages and disadvantages of modern learning management systems, develop a number of recommendations for improving the use of learning management systems. In our scientific work, we have systematized all learning management programs in a table. This allowed us to show them, compare them, and determine which one is the most effective. In general, it can be noted that the development and implementation of modern learning management systems is certainly one of the important issues of education, since they are a modern and effective means of ensuring the integrity and accessibility of training. This is especially true in recent years, when distance learning has become widespread. The transition to online learning is due to the spread of coronavirus infection. This situation was the impetus for the development of online learning platforms.
Research on Active Monitoring System of Power Supply Service Demand Based on Computer Big Data

With the improvement of the overall service level of society, people&#x0027;s requirements for power supply services are getting higher and higher. In order to improve the quality of power supply service, reduce the risks in power supply business activities, improve the business efficiency and management level of enterprises, build a unified audio and video monitoring system, and achieve a three-level management model of centralized supervision at the provincial level and local monitoring at the city and county levels. The main requirements function of the customer appeal information management system of the electric power company include the acceptance and review of appeal information, the appeal return visit and response information management function, the responsibility determination function, the monitoring and reminding function, the work order query function, the case information maintenance management function and the software system Operation and maintenance management functions. The thesis outlines the overall software design and database logic scheme of the information system on the basis of demand analysis, and further discusses the relational data model of database tables and the design of main business processes. On the basis of the system design, the program implementation and testing of the main modules of the system are completed.
THE IMPLEMENTATION OF PRONUNCIATION PRACTICE COURSE USING THE MINIMUM PAIR STRATEGY METHOD IN ENGLISH TEACHING

The learning of English has its level of difficulty. One of its difficulties is pronunciation practice which is influenced by several factors. This study purposes to determine the factors that influence the difficulty in pronunciation practice. This study aims to implement a minimal pair strategy to facilitate learning pronunciation for students in one of the elementary schools in Temanggung as the object of this study. This study uses an experimental method by dividing a class of third-grade into two groups, namely the experimental group and the control group. By using this method, two different data will be generated to compare how effective the implementation of the minimum pair strategy is for elementary school students, especially for learning pronunciation.
Storage of Text Messages on e-Book Files using Least Significant Bit and Haar Wavelet Method

This study uses the technique of incognito data and information into a container in the form of images combined with the addition of the password by using the method of Least Significant Bit (LSB) and the method of Haar Wavelet. Testing the system by sending a message in the form of a text file and an image file with the process of the original image are transformed to wear haar wavelet divided into four zones of frequency, namely LL, LH, HL and HH. Where Bit-bit Readings are planted in a zone LL and attempted insertion of the bit of the file reading into the last bit in each byte of the image file as well as can show you back the results of the message. The results of the research, i.e. images that have been processed by the method of LSB and Haar Wavelet does not change the file size, resolution, dpi and physical form image. The advantage of this method is very simple computing, oriented computers, which need less space to store and time efficient.
Setting Up Your Project for VR Development

The goal of this chapter is to set up a Unity3D project for virtual reality development. I will discuss the VR hardware requirements and the version of Windows and Unity that you will be using. I will walk you through setting up the required SDKs, Unity’s XR Plugin Management, choosing the various Player settings within Unity, and finally, switching your platform for Android development. You will also import your first Unity package, which will serve as the environment in which you will build your VR framework.
PERANCANGAN BILAH INVERSE TAPER BERBAHAN STYROFOAM DENGAN AIRFOIL NACA 4412

In the manufacture of wind turbines, there are several parameters that are taken into account, namely the wind speed in the area to be installed. The wind speed in Indonesia ranges from 3m/s – 11m/s, so it is quite difficult to implement a macro-scale wind turbine and the facilities are still inadequate. So this design is a design to make a micro-scale wind turbine that adapts to the characteristics of wind speed in Indonesia. In this design, a blade with the Inverse Tapper type is made which is a blade type with an enlarged shape to the end to get a large sweep at the end of the blade and produce a lift force that is greater than the drag force on the blade so that it can rotate the blade. In the design of this blade, material changes are also made, generally the material used in the blade is made of wood, fiber, and aluminum. In this design, a material made of styrofoam is used, this is to make the mass of the blade lighter and make the blade able to rotate at the smallest wind speed. In this design, the maximum power obtained is 553 watts at 668 rounds of blade rotations&#x0D; . Keywords : Airfoil, Inverse Blade, Cl/Cd, Styrofoam.
INDeeD: Identical and disparate feature decomposition from multi-label data

Deep learning technology has made a significant improvement in image recognition performance.Unlike single-labeled training and inference, multi-labeled classification tasks hardly characterize individual label in the training of deep neural networks due to co-occurrence of the labels.Training data contains few samples of separated single label and the networks learn diverse compositions of labels from the data.Contextual bias caused by the co-occurrence of labels disturbs multi-label classification.We propose Identical and Disparate Feature Decomposition (INDeeD) from multi-label data that explicitly learn the characteristics of individual label.By training a backbone network combined with Identical and Disparate blocks on the instance pairs of partially common and contrastable labels, the network is generalized to decompose and learn individual label features.Proposed INDeeD scheme can be simply incorporated in any type of networks.We use ML-MNIST, ML-CIFAR-10, VOC-2007, and MS-COCO datasets to evaluate the performance of IN-DeeD showing improved mAP over baseline.
Email

Email notification is an integral part of today’s enterprise systems. Java enables email notification by offering JavaMail API. Using this API, you can send email communications in response to an event (e.g., a completed form or a finalized script). You can also use the JavaMail API to check an IMAP or POP3 mailbox.
Spread-based elite opposite swarm optimizer for large scale optimization

To prevent the traditional particle swarm optimizer (PSO) from inefficient search in complex problem spaces, this paper presents a novel spread-based elite opposite swarm optimizer (SEOSO) for large scale optimization. Inspired by the dandelion seeds in nature, the seeds can randomly spread by wind and grow better for the next generation. To achieve this, the spread learning and elite opposite learning are introduced in SEOSO. In spread learning, the particles are divided into some subswarms and these subswarms can exchange the particles to get more useful information that improves the diversity of the swarm. In elite opposite learning, the opposite position of the particle is used to exclude the worse direction. The experiments are conducted on 35 benchmark functions to evaluate the performance of SEOSO in comparison with several state-of-the-art algorithms. The comparative results show the effectiveness of SEOSO in solving large scale optimization problems.
Unifying Classification and Bounding Box Regression Head For Object Detection

Abstract Object detection usually includes two parts: objection classification and location. At present, the popular object detectors usually use two detection heads: one head is used to predict classification score, and the other one is used to predict the bounding box (bbox), respectively. In this paper, we first stack classification head after feature extract convolutional neural networks of bbox regression head. Then, we establish the classification networks by using a bounding box feature. The bounding box feature is very useful when the classification head uses soft Intersection over Union (IoU) labels. In experiment parts, only using PASCAL VOC 2007 datasets, soft Centerness labels, and soft IoU labels get 50.06 mAP and 52.08 mAP on VOC 2007 test. Compared with FCOS, they have 1.08% and 1.12% improvements. Using PASCAL VOC 2007 and 2012 datasets, our Union A*B head gets 78.71mAP after 12 epochs training with ResNet-101 as backbone and FPN as the neck. Extensive experimental results show that the proposed algorithm is superior to other detection methods.
An Improved Stereo Matching Algorithm Based on AnyNet

In many applications of depth estimation, accurate disparity map needs to be generated quickly. In order to obtain accurate disparity map, the current mainstream algorithm mostly adopts deep complex network architecture, which requires a large amount of computation and is difficult to be applied in real-time scenes. However, some real-time networks have low disparity accuracy, which also limits their application scenarios. Based on the above shortcomings, this paper improves AnyNet stereo matching algorithm and proposes a stereo matching algorithm with high real-time performance and high accuracy. First, a multi-scale feature extraction module is designed to capture and fuse contextual feature information, and then an attention module is constructed to reduce the mismatch problem of ill-posed regions (repetitive, no/weak texture regions). The algorithm proposed in this paper can predict the disparity map in multiple stages during reasoning, weigh the amount of calculation and accuracy according to actual needs, and select the corresponding stage adaptively. Evaluated on the KITTI 2015 dataset, compared with the reference algorithm AnyNet, the final predicted disparity map error rate is reduced by 2.43%, and the running speed is only 1.24% slower.
GraDex—Graph-Based Data Analytics for Extractive Text Summarization

This paper aims to brief the reader about different Automatic Text Summarization methods and their efficiency when it comes to providing meaningful summaries. In this paper, we have conducted comparative research between the BERT model for text embeddings along with K-Means clustering to identify sentences closest to the centroid for summary selection, and a Word Frequency algorithm that computes the frequency of appearing word, assigns appropriate weights and selects sentences based on a threshold score. The purpose of this is to compare the two different approaches, for Reviews and Feedback Analysis of different texts and their summaries. Through our research, we were able to find that BERT outperforms the Word Frequency model according to all the evaluation metrics and this is clearly demonstrated in the following sections of the paper.
L

This Encyclopedia brings together jurists, computer scientists, and data analysts to map the emerging field of data science and law for the first time, uncovering the challenges, opportunities, and fault lines that arise as these groups are increasingly thrown together by expanding attempts to regulate and adapt to a data-driven world. It explains the concepts and tools at the crossroads of the many disciplines involved in data science and law, bridging scientific and applied domains. Entries span algorithmic fairness, consent, data protection, ethics, healthcare, machine learning, patents, surveillance, transparency and vulnerability.
Experience Builder

For those who have decided to leverage a Lightning-based template as a starting point for a new Experience Cloud site, a major bonus awaits. That bonus is the opportunity to leverage Experience Builder, the primary tool with which all Lightning-based sites are constructed. Experience Builder, as shown in Figure 5-1, is found as a unique section within the site workspaces and provides the paintbrush, paint, and canvas for those creating a site from Customer Service or any other Lightning-based template. This tool has significantly changed the site creation process and has enabled and empowered many “declarative developers” in the Salesforce ecosystem to develop functional, effective, and vibrant sites.
Conference Tutorial: Can federated learning solve our data privacy problems? State of the art and open challenges

Data privacy and regulations prevent the free transmission and sharing of information to a central place. While these regulations aim to ensure data owners can maintain clear control of their data, they also inhibit the training of machine learning (ML) algorithms and the analysis of processes that would benefit multiple stakeholders. Federated learning (FL) has provided an alternative to ensure multiple data owners collaboratively train ML models without sharing their data with each other. Sharing knowledge, rather than data, has allowed the mitigation of some of data privacy exposure risks. However, there are multiple open challenges that need to be addressed. In this talk, I will provide an overview of the state of the art and open challenges. Some of the topics I will discuss include the impact of FL on inference of private data, fairness, and transparency.
Mobile Learning Application Integrated with Learning Management System

Since mobile learning has broken through the limitation of time and space, and also provided a new form for education. This paper analyzes the deficiencies of the learning management system in supporting mobile teaching, and proposes the technical solutions. Taking Shanghai Jiao Tong University as an example, the enhanced application of learning management system which adapted in mobile terminal has integrated with the live class and VOD system with functional modules such as roll call and poll through LTI, thus promoting students to achieve learning experiences.
Crime by Crowd is Not Crime any More: A Predictive Analysis of Riot and Radicalization Oriented Text of Social Media

The paper focuses on the study of new algorithmic approaches to detect possible riots that may occur. In this paper, we have come up with a new approach that can be implemented successfully to mitigate the problem addressed. Dataset has been prepared by collecting data from various social media and microblogging sites using the Apriori algorithm, Association Rule Learning algorithm, and Data Mining Algorithm. The dataset is then preprocessed and is used for Model Training. Classification Algorithms are executed on the preprocessed dataset aiding in the training process of the model. The trained model now attempts to detect the probability of possible riots.
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This Encyclopedia brings together jurists, computer scientists, and data analysts to map the emerging field of data science and law for the first time, uncovering the challenges, opportunities, and fault lines that arise as these groups are increasingly thrown together by expanding attempts to regulate and adapt to a data-driven world. It explains the concepts and tools at the crossroads of the many disciplines involved in data science and law, bridging scientific and applied domains. Entries span algorithmic fairness, consent, data protection, ethics, healthcare, machine learning, patents, surveillance, transparency and vulnerability.
METHODOLOGICAL APPROACHES TO THE DEVELOPMENT OF FUTURE TEACHERS’ SKILLS OF INFORMATION LEARNING ADMINISTRATION

The article is devoted to solving the problem of integrating graduates of a pedagogical university into the information and educational space of the modern school. The necessity of conversance of future teachers with the basic concepts and principles of information management is shown. The expediency of developing the senior students’ skills of learning administration in the conditions of informatization of the educational environment is substantiated. The role and place of innovative educational technologies in the system of training and professional and pedagogical support of future teachers are determined.
Productive University Education in the Context of Human Capital Development

The article discusses the problem of productive education at a university, identifying its general didactic structure.In the context of the development of human capital in the knowledge economy, an overview of the most significant areas of transformation of higher education is given.The urgency of the idea of productive education as a promising educational format, implying two lines of productivity, has been substantiated.The first line is associated with obtaining an external observable product of educational activity (for example, a solution to a case or a created project).The second line of productivity is internal personal increments that arise in the process of carrying out this activity.The fundamental position of the authors regarding the systematic approach when considering productive education.On the basis of theoretical analysis, the authors identified a general didactic structure of productive education, independent of the level of higher education.This is a system that includes goal-setting based on the principles of practice-oriented education and quasi-professionalism; content in the form of systemic generalized knowledge; problem, project or case study technologies; reliance on the existing stock of specific knowledge; evaluation of the external product (as an alienated result) and the internal product (personal increments), interdependent among themselves.Particular attention is paid to the harmonization of the content and procedural aspects of productive education in the article.The article provides examples of courses / modules implemented in the logic of productive education in bachelor, master, and postgraduate studies.The analysis of the didactics of the courses allowed the authors to assert about their general structure, independent of subject specificity.The feedback results obtained by various qualitative methods demonstrate the productivity of these courses for students, which is expressed in the experience gained and the independent acquisition of new knowledge, in the practical testing of knowledge and in the quasi-professional context of learning, subjective involvement in educational activities and awareness of external and internal results.
On some codes from rank 3 primitive actions of the simple Chevalley group $ G_2(q) $

Let $ G_2(q) $ be a Chevalley group of type $ G_2 $ over a finite field $ \mathbb{F}_q $. Considering the $ G_2(q) $-primitive action of rank $ 3 $ on the set of $ \frac{q^3(q^3-1)}{2} $ hyperplanes of type $ O_{6}^{-}(q) $ in the $ 7 $-dimensional orthogonal space $ {{\rm{PG}}}(7, q) $, we study the designs, codes, and some related geometric structures. We obtained the main parameters of the codes, the full automorphism groups of these structures, and geometric descriptions of the classes of minimum weight codewords.
Phase-Amplitude Relations for a Particle with a Superposition of Two Energy Levels in a Double Potential Well

We study the connection between the phase and the amplitude of the wave function and the conditions under which this relationship exists. For this we use the model of particle in a box. We have shown that the amplitude can be calculated from the phase and vice versa if the log analytical uncertainty relations are satisfied.