Reviewerly/exHarmony huggingface dataset:
Perbaikan Kualitas Citra Digital Menggunakan Metode Kervel Konvolusi

Image processing (digital image processing) is a discipline that studies image processing techniques. The image referred to in this study is a static image originating from the vision sensor (webcame). Mathematically, image is a continuous function with light intensity in a two-dimensional plane. So that it can be processed with a digital computer. An image must be represented numerically with discrete values. A digital image can be represented by a two-dimensional matrix f (x, y) consisting of M columns and N rows. In this study, the color model used is the HSV color model, namely the image (RGB) is converted into HSV to determine the comparison of the original image with the conversion results from RGB to HSV. In image color processing, there are various models, one of which is the hue, saturation, value (HSV) model. By using this model, an object with a certain color can be detected and reduce the influence of the light intensity from outside. The search for paint color codes serves to facilitate all the work of buyers and sellers in determining the color of paint to be taken so that sellers and buyers no longer have to use a catalog to determine paint color and paint code.Image processing (digital image processing) is a discipline that studies image processing techniques. The image referred to in this study is a static image originating from the vision sensor (webcame). Mathematically, image is a continuous function with light intensity in a two-dimensional plane. So that it can be processed with a digital computer. An image must be represented numerically with discrete values. A digital image can be represented by a two-dimensional matrix f (x, y) consisting of M columns and N rows. In this study, the color model used is the HSV color model, namely the image (RGB) is converted into HSV to determine the comparison of the original image with the conversion results from RGB to HSV. In image color processing, there are various models, one of which is the hue, saturation, value (HSV) model. By using this model, an object with a certain color can be detected and reduce the influence of the light intensity from outside. The search for paint color codes serves to facilitate all the work of buyers and sellers in determining the color of paint to be taken so that sellers and buyers no longer have to use a catalog to determine paint color and paint code.
Development of Sebaya Tutor Method Affiliated Learning Indonesian Language and Literature Students of Class XI SMA Negeri I Wonggeduku Konawe District

This study aims to identify and develop the interaction process of students towards the development of peer tutor methods with affiliation in learning Indonesian language and literature for class XI students of SMA Negeri 1 Wonggeduku, Konawe Regency. The approach in this research is a qualitative method. Methods of data collection through interview techniques (interview) and FGD (Forum Group Discussion). The data collection instruments used questionnaires and documentation. Data analysis used Miles and Huberman's analysis. The results showed that in the learning process there was an interaction between one student and another student in different classes in solving the problems given by the teacher so that the results of the assessment of attitudes changed significantly in the learning process of Indonesian Language and Literature by the coverage contained in the 2013 curriculum, namely: (a) spiritual attitudes related to the formation of students who have faith and piety; and (b) social attitudes related to the formation of attitude competencies, namely having a noble character, being independent, democratic, and responsible. In its presentation it is different from the flow found in the Tebaya Tutor, while the Affiliated Tebaya Tutor gets the flow of the implementation of learning in an updated way, students make the learning process easier and more enjoyable where students every week use verbal or text presentations in an affiliated way.
МЕСТО ГЛОБАЛЬНЫХ ИЗМЕНЕНИЙ ИНДУСТРИИ 4.0 В ПРЕПОДАВАНИИ ФИЗИКИ

The article discusses the effect of effect 4.0 on the efficiency of studying School Physics and on scientific physics in general. The Fourth Industrial Revolution is not just smart machines and systems, its spectrum is vast. The rapid separation of new technologies and universal innovations. It is important to apply these changes, such as awareness of changes in the fourth generation of the industrial revolution and mechanisms of governance, the development of society as a whole, in the development of education, in the implementation of a breakthrough in the era of globalization. The basis of these changes is physics. That is why effective teaching of physics in school will be one of the first steps in raising the demands of developmental time.
IoT Based Healthcare System

Looking at the current pandemic situation in the world, every human being's health has been a major concern. In this scenario, the best option for dealing with an epidemic is an IoT-based health monitoring system. The Internet of Things (IoT) is a recent internet trend that is becoming a popular research topic, especially in health care. The key goal of this project is to keep track of a patient's heart rate, temperature, and oxygen saturation (Spo2) in real-time. Aside from that, the device monitors the patient’s positions using tilt, temperature, humidity, and CO2 level in the room. Tilt is a core aspect of our project. The Arduino Nano is wired to all the sensors. The Arduino nano is a microcontroller that manages the system's functions. Arduino uses a Wi-Fi module to send data to an IoT platform through the ThingSpeak wireless network. In this system, Arduino uses a Wi-Fi module to send data to an IoT platform called ThingSpeak. ThingSpeak is used to store, retrieve and visualize our real-time data. So authorized individuals can access the patient's measured data from any location and take appropriate actions if it is required.
The Effectiveness Of Cooperative Learning On Reading Comprehension Skill

This study aims to know the effect of cooperative learning of typescript strategy on reading comprehension. In the existing knowledge and skill, students viewed as a subject, not an object, and students more important between teach. Despitefully, students, took a hand, attempt, and do with her that the learning, whereas in education refers to current knowledge and skill, the function teacher makes in invention a condition that it may students the developing optimal. This research forms the research of pre-experiment research. The population of this study was the seventh grade of MTs Al Ikhwan Kemudi Duduk Sampeyan Gresik. The method of data collection used is test and observation. The research started by giving pre-test and post-test. The data of the experiment were analyzed by using t-test formula to know the difference of the student’s individual in reading comprehension between cooperative learning in reading comprehension. The result of data analysis and the consideration result of research about the realization cooperative learning of typescript in reading comprehension skill in MTs Al Ikhwan Kemudi Duduk Sampeyan Gresik, be able to procurable that follow:The activity of the teacher, while apply of cooperative learning typescript that has implementable well, the teacher has effective in apply of cooperative typescript.See from the achievement of students in test pre-test and post-test reading comprehension skills; the cooperative learning typescript is very effective use as method learning in MTs Al Ikhwan.
KEMAMPUAN MENULIS BERITA MENGGUNAKAN TEKNIK TERBIMBING PADA SISWA KELAS XI SEMESTER GENAP SMA AL AZHAR 3 BANDAR LAMPUNG TAHUN PELAJARAN 2018/2019

The problems examined in this study include learning to use lecture learning strategies, question and answer, note taking, and copying the theory in the textbook. The teacher also has not provided guidance techniques to students about writing. The purpose of this study was to determine the XI grade students of SMA Al Azhar 3 Bandar Lampung in writing news. This study uses a qualitative method. Use this method to describe students' abilities in writing news using guided techniques. The results show that 30 students who were given the news writing test were included in the category of sufficient, because it is in the range between 56 - 75. So, it is recommended that Indonesian language teachers should look for new learning so as to improve students' writing ability in aspects of news elements and the use of spelling and punctuation.
Cyber Security Incentives and the Role of Cyber Insurance

This paper outlines the opportunities of and challenges in using cyber insurance to incentivise cyber security practices. Findings are basedon a review of existing industry reports and academic research.The paper forms part of an independent research project by RUSI and the University of Kent that provides actionable policy recommendations on how to incentivise cyber security through cyber insurance. They derive from a series of interviews and workshops with insurers, businesses, cyber security providers, government and other key stakeholders.The current evidence about the ability of cyber insurance to improve cyber security practices is limited. While cyber insurers may be ableto provide expertise to policyholders and increase their awareness of cyber risks, much of the existing evidence base is largely theoreticaland there is still considerable scepticism from customers about the benefits of cyber insurance.The uptake of cyber insurance, particularly by small to medium enterprises (SMEs), remains low. Existing research suggests that some of the overarching factors explaining this are: the high cost of policies and the difficulties insurers face in pricing premiums appropriately;confusion over what types of incidents insurance policies cover (and the issue of ‘silent cyber’); and a lack of understanding of risksstemming from cyber incidents.There is the potential for the cyber insurance market to learn from other insurance markets to increase uptake, although understanding the depth of these connections requires further enquiry.The paper concludes by identifying several policy questions raised by the existing literature. These questions serve to guide the next stage of the project and to prompt new conversations about how cyber insurance might better incentivise cyber security practices.
Attribution of Gradient Based Adversarial Attacks for Reverse Engineering of Deceptions

Machine Learning (ML) algorithms are susceptible to adversarial attacks and deception both during training and deployment. Automatic reverse engineering of the toolchains behind these adversarial machine learning attacks will aid in recovering the tools and processes used in these attacks. In this paper, we present two techniques that support automated identification and attribution of adversarial ML attack toolchains using Co-occurrence Pixel statistics and Laplacian Residuals. Our experiments show that the proposed techniques can identify parameters used to generate adversarial samples. To the best of our knowledge, this is the first approach to attribute gradient based adversarial attacks and estimate their parameters. Source code and data is available at: &lt;ext-link ext-link-type="url" xlink:href="https://github.com/michael-goebel/ei_red"&gt;https://github.com/michael-goebel/ei_red&lt;/ext-link&gt;.
Learning Action Correlation and Temporal Aggregation for Group Representation

In this work, we propose a deep graph model for collective activity recognition. Based on person’s visual embedding, we explore action correlation to construct the contextual information through GNN reasoning. Our proposed layer generates local evolution descriptor for each person, which contains action correlation and spatial information. Besides, we design temporal aggregation module to encode them into a meta-action space and then aggregate these descriptors to construct final group representation for collective activity recognition. We conduct experiments on two collective activity recognition datasets (collective activity dataset and volleyball dataset) and achieve 89.6% and 91.3% recognition accuracy respectively, which outperforms the compared state-of-the-art methods. Empirical results on collective recognition demonstrate that the effectiveness of learning action correlation and temporal aggregation for video-level group representation.
Multi Object Detection Using Deep Neural Network

This paper describes a neural network and the ability to infer common object tracking. The goal is not to re-examine the whole literature nor to attempt to evaluate all forms of neural nets suggested for the monitoring of objects. This analysis is based on the CNN, a strong basis to research the complexities of target detection. The CNN is a successful baseline. Such networks combine learning successfully, hence temporal communication and illustrate advanced success thus far. Throughout particular, divisions and levels of machine learning linking these divisions are underlined, as well as different training features, and thus incorporation of such systems into monitor. This article shows a modification of the deep neural network (DNN) model, which addresses a large number of all traces and false negatives. Quantitative conclusions from historical records are contrasted with the observations there are issues with catalytic activity, and thus standardization of tests, in the new evaluation approach. Throughout this post, we analyze object recognition tracking issues by using an simple Convolutionary Neural Network (CNN) to eradicate discrimination and identify subject from of the context concurrently.
Marriage in Honey Bees Optimization in Continuous Domains

This chapter discusses the marriage in honey bees optimization (MBO) is adapted to solve problems in continuous domains by using the adapted representation way and four proposed heuristics. Experiments are conducted on benchmark functions to evaluate the search ability of MBOs with each single heuristic and four incorporated heuristics. MBO is a swarm-based algorithm that was originally designed to the solve discrete problems by getting inspiration from the marriage process of honey bees. The bees optimization algorithm was MBO in 2001. MBO mimics the marriage process of bees, which evolve from a solitary colony to an eusocial colony. MBO was proposed to solve the propositional satisfiability problem. Its distinguishing feature from all other swarm optimization algorithms is that it works with partial solutions. The design of the adaptive parameters setting is a promising way to improve the performance of MBO.
Campus waterlogging simulation and model preference based on Kriging interpolation

In order to explore the main influence factors of the node water depth of rainwater pipe network located in a campus in Lanzhou city and to study the interpolation method suitable for the node water depth data, we analyze the data of the water depth of 246 nodes of the rainwater pipe network in the study area under the rainfall return periods of 7 years and 50 years (i.e., P=7 a and P=50 a, respectively). Using ArcGIS software, we make spatial difference analysis of node water depth data of rainfalls in the two return periods, and conduct a comparative study on the four Kriging interpolation models, i.e. stable model, spherical model, Gaussian model and index model, by means of cross-validation method. The results show that the Pearson correlations between the maximum depth of nodes and the depth of water accumulation for P=7 a and P=50 a are strong, and the correlation coefficients are 0.605 and 0.766, respectively. Through comparing the predicted values with the measured values of four Kriging semi-variation function models, it is found that the Kriged reduced mean error by Gaussian model is minimum (KRME=-0.87×10<sup>-4</sup> at P=7 a and KRME=0.87×10<sup>-3</sup> at P=50 a), and the Kriged reduced mean square error is the best (KRMSE=0.939 at P=7 a and KRMSE=0.947 at P=50 a). The Gaussian model is determined as the most suitable model for Kriging interpolation method of node water depth in the study area, which provides a more effective method to identify water logging in the study area by using limited waterlogging data, and provides a theoretical basis for the control and reduction measures of waterlogging.
ОРГАНИЗАЦИЯ УЧЕБНЫХ ИССЛЕДОВАНИЙ ПО МАТЕМАТИКЕ В УСЛОВИЯХ КРИТЕРИАЛЬНОГО ОЦЕНИВАНИЯ

Criteria-based assessment is an integral part of the process of updating the content of education. Its structure and features not only change the approach to evaluation, but also allow you to make new elements in the organization of the process of cognition. One of the tools of criteria-based assessment is the descriptor. The article discusses the features of educational research in mathematics, which is based on the activities of students to develop alternative descriptors for solving problems. The process of creating descriptors in the study of transformations of graphs of functions is described. The proposed approach makes it possible to increase the motivation of students, since the descriptors, which are the result of their research activities, will not only be used for self- assessment and mutual assessment, but also in the future they will the basis for summative assessment of educational achievements of students.
ОЦЕНИВАНИЕ УЧЕБНЫХ ДОСТИЖЕНИЙ УЧАЩИХСЯ В УСЛОВИЯХ ДИСТАНЦИОННОГО ОБУЧЕНИЯ МАТЕМАТИКЕ

Assessment is one of the important components of learning, which provides information about the progress of students in learning, aids to improve the learning process. The most urgent issue nowadays is the assessment in the framework of distance learning. This article analyses the literature on assessment, distance learning, and approaches to the development of assignments for assessment procedures. There are many different distance learning platforms for formative assessment, but these resources are not always relevant for summative assessment. Platforms, which allow you to use various types of tasks, determine the time for completing tasks, and automatically assign points are more suitable for conducting summative assessment in a process of distance learning. The example of the implementation of summative assessment tasks in Mathematics through the Microsoft Forms platform is given in the article.
Criminal Identification System using Deep Learning

In this paper, we have developed a system for detecting criminal faces, for this, we have used deep learning algorithms. Since deep learning is now the most famous technology, it is used in different applications. One such application is crime detection and prevention. This system identifies the criminal face, retrieves the information stored in the database for the identified criminal and a notification is sent to the police personnel with all the details and the location at which the criminal was under the surveillance of the camera.
Digital Singnature Pada File Dokumen Menerapkan Fungsi Hash Dengan Metode MD5

Documents that have a digital signature are intended to validate where the data comes from. Digital signature can be done through encryption. The algorithm that is usually used for a digital signature on a document file is the Message Digest (MD5) algorithm which is also a hash function. And it is necessary to do the security and authenticity of the Digital signature on the document file so that it is not easily manipulated by others. The method that suits this problem is to use an algorithm that is usually used to create digital signatures, namely the MD5 algorithm which is a hash algorithm of the MD5 type or direction to get the value. hash is 128 bits long. The MD5 algorithm can be used to check data integrity, create digital signatures on document files and others. A digital signature of the security and authenticity of the document file there is also a hash function in the journal entitled Implementing the MD5 algorithm for document security. By using a one-way hash function, it will generate a message Digest from the original message. Developed from the MD5 algorithm developed by Ron Rivest, accepting input messages of various lengths and generating a 128-bit hash code it has become one of the most widely used hash algorithms. This algorithm is basically made for the security and authenticity of digital signatures in document files, the hash function cannot answer all existing problems such as confidentiality issues.
Development of an Information Network for Affiliating Universities in Kerala: A Feasibility study

Library and information networks play a vital role in the sharing of information resources and building cooperation among libraries. Library cooperative initiatives like consortium and resource sharing services can seize the pricing of e-resources and ensure uniform availability of information resources. Regional level library networks can satisfy the information requirements of the user community in the micro-level. Kerala state is bestowed with sufficient infrastructure and human resources for the development of a network for library cooperation. This study enquires the possibility of the development of an information network for college libraries under four prominent affiliating universities in Kerala state to facilitate the avenues for cooperation and resource sharing.
The Use of Technology Techniques in the Formation of Critical Thinking in Schoolchildren as a Means of Personality Self-Development

The article discusses the role of using interactive methods, as well as the introduction of critical thinking development technology in the classroom
Using convolutional neural networks in solving problems of image analysis and recognition

Convolutional Neural Network (CNN) is a special type of Neural Networks, which has shown exemplary performance on several competitions related to Computer Vision and Image Processing. Some of the exciting application areas of CNN include Image Classification and Segmentation, Object Detection, Video Processing, Natural Language Processing, and Speech Recognition.Тhe purpose of the work, the results of which are presented in the article, was to research of modern architectures of convolutional neural networks for image recognition. The article discusses such architectures as AlexNet, ZFnet, VGGNet, GoogleNet, ResNet. Based on the results obtained, it was revealed that at the moment the network with the most accurate result is the ResNet convolutional network with an accuracy rate of 3.57%. The advantage of this research is that the given article gives a brief description of the convolutional neural network, and also gives an idea of the modern architectures of convolutional networks, their structure and quality indicators.
Perancangan Sistem Informasi Pencarian Alamat Rumah Sakit Di Kota Bekasi Berbasis WAP

Abstract - Current address retrieval information systems are only manually created through books or official documents such as drawing maps in the form of paper mounted on the wall or in official places in the Bekasi City neighborhood. Based on the description of the above problems, then made improvements in the field of information services. The manual address search information system will be developed into a digital (computerized) information system in the form of a Mobile Wireless Application Protocol (WAP) technology. This technology is created using srcipt html, xlm, and MySQL database. The purpose of this system planning is to provide convenience in the delivery of information searches the important addresses in the city of bekasi widely for the mobile phone users who can be accessed via the internet. Through the development of this system access to information can be done anytime and anywhere without having to deal directly with existing sources.
The EU Commission publishes an inception impact assessment about potential revisions to the research and development block exemption regulation and the specialisation block exemption regulation

In the course of the ongoing review of the application of the EU competition rules to horizontal cooperation agreements, the European Commission (“Commission”) published on 7 June 2021 an inception…