Reviewerly/exHarmony huggingface dataset:
Media Belajar Interaktik Komunikatif Pada Anak Usia Dini Dengan Kartu Bergambar Kegiatan Sehari-hari Di Taman Kanak-Kanak

Early childhood education is very important and as a basis for subsequent developments. Communication is formed from simple words to complex sentences. Developing vocabulary skills in pre-school children is one of the crucial aspects of development for early childhood. This study aims to optimize communication skills in early childhood through communicative interactive learning media in early childhood with picture cards of daily activities in kindergarten. The study was conducted in 20 kindergartens in Central Semarang. The research method used is the quasi experimental method. Data collection techniques using pretest, posttest, observation, interviews with teachers and parents, and documentation. The results of this study are an increase in the interactive communication skills of TK A children through the media of picture cards in developing their language skills.
Ortogramia, I create my own orthography. An experience from a primary school

This paper proposes a learning path leading towards the acquisition of the main orthographic rules of Italian, implemented in the first years of the primary school, developed on the basis of a teacher’s experience. It describes the characteristics of the learning materials created for and used with different children, by respecting their individual learning styles.
FEATURES OF THE ELECTIVE COURSE “FOUNDATIONS OF INFORMATION CULTURE” IN BACHELORS’ EDUCATIONAL AND PROFESSIONAL TRAINING PROGRAM “SECONDARY EDUCATION (THE ENGLISH LANGUAGE AND LITERATURE)”

In the context of integration of the Ukrainian education into the European educational space future teachers’ information culture as a phenomenon, as well as the search and testing of the effective ways of its formation, remain to be topical issues for pedagogical theory and practice. The content, forms and methods of realization of the author’s technology of information culture formation are reflected in the course “Foundations of information culture”. The elective is a component of bachelors’ educational and professional training program “Secondary Education (The English Language and Literature)” at TNPU. Along with other components, the course promotes the formation of integral competency, a number of general and professional competencies, and also reaching certain program learning outcomes of professional training. The purpose of the article is to analyze and disseminate the experience of teaching an elective course, which aims to form the basis of information culture of future teachers of foreign languages, and outline the prospects for its use in corresponding future educational and professional training programs. The article discusses “the past” of the course, analyzes the first curriculum, thematic content, changes in study programs which have been made up to present. The paper also discusses “the present” of the elective, and outlines prospects as for teaching it in the future.
Research on the Cultivation of College Students' Autonomous Learning Ability -and Construction of Evaluation Mechanism in the Network Environment

The purpose of college education is to cultivate more high-quality applied talents. In the current network environment, to deliver more outstanding higher education talents to the talent market, it is necessary to change educational concepts and continuously improve students' autonomous learning ability. Under the current Internet background, self-learning ability training is the need of students' continuous growth, development and improvement. To promote the self-learning ability training of college students, it is also very important to improve the construction of the corresponding evaluation mechanism. This article introduces the important basis for the cultivation of students' autonomous learning ability, and analyzes the strategies for the cultivation of college students' autonomous learning ability and the construction of evaluation mechanism.
Segmentation of Mammogram masses for Smart Cities Health Systems

One of the fundamental aspects of smart cities is an improvement in the health sector, by providing its citizens with better care and prevention and detection of diseases. Breast cancer is one of the most common diseases and the one with the highest incidence in women worldwide. In smart cities, to improve the quality of life of its citizens, especially for women, is to diagnose breast tumors in shorter periods with simpler and automated methods. In this chapter, a new deep learning architecture is proposed to segment breast cancer tumors.
Morphological based Medical Image Processing on Cervical Cytology Cancer Images using Connected Component Techniques

Cervical cancer is the fourth most common cancer in women. In 2018, it was estimated 570000 women were diagnosed with cervical cancer worldwide and about 311000 women died from the disease. An efficient technique is essential for solving the complication in the diagnosis of cervical cancer images.In this research, a new method is developed for cervical cancer image segmentation. First, the RGB image is converted into an HSI color model. The thresholding is applied to the saturation and intensity components to get binary images. These binary images are combined to get a new mask. Using the connected component concept nucleus and cytoplasm are segmented accurately.For the performance evaluation, peak signal-to-noise ratio (PSNR), mean square error (MSE), structural similarity index (SSIM), image quality index (IQI), structural content (SC), normalized cross-correlation (NK), precision (PR), recall (RC), the Average Difference (AD) and image fidelity (IF) are taken. The proposed techniques' highest PSNR values are 44.2341, 46.7953, 60.5925, and 61.4862, respectively. The proposed segmentation technique can attain a high PSNR (>40db) value at a threshold value equal to 0.1. Also proposed approach attains good precision, recall, and SSIM values.The lowest MSE values using proposed segmentation techniques are 0.0454, 0.0351, 0.0924, and 0.0271 individually. The AD, NK, SC, NAE, and LMSE values for the implemented approach are low, showing the segmented image's quality is very good. Thus, the proposed model performed better compared to other methods.
Alcuni recenti strumenti INVALSI per l’insegnamento dell’italiano

In a difficult moment for the education system, INVALSI proposed three new resources for schools: formative testing, videos and webinars. The article presents some characteristics, aims, results and prospects of these projects.
The Price of Bitcoin: GARCH Evidence from High-frequency Data

This is the first paper that estimates the price determinants of Bitcoin in a generalized autoregressive conditional heteroscedasticity (GARCH) framework using high-frequency data. Derived from a theoretical model, we structurally estimate Bitcoin transaction demand and speculative demand models using hourly data for 2013–21. In line with the theoretical hypothesis, our empirical results confirm that both the Bitcoin transaction demand and speculative demand have a statistically significant impact on the Bitcoin price formation. The Bitcoin price responds negatively to the Bitcoin velocity, whereas positive shocks to the aggregate Bitcoin stock, interest rate and size of the Bitcoin economy exercise an upward pressure on the Bitcoin price.
Mengajarkan Bahasa Pemrograman Python Di Tingkat SMA Untuk Meningkatkan Manajemen Sumber D aya Manusia

Technology rather than becoming producers, both hardware and software. Indonesia also has ashort age of programmers, thus many programmers from India and the Philippines work inIndonesia. Interms of hardware, Indonesia seems difficult to competein the short and medium termwith countries that have an established electronics industry culture. Butin the field of softwareIndonesia has agre at opportunity, if Indonesia can educateas many human resources as possible toenable them to write programming code. Allthistime, most Indonesians have tended to only learn touse applied software (applications) that are on the outer layer, it is far from the core of computerscience, so they are unable to control computers outside of the frame work created by theapplication maker. The increasingly close combination of information and communicationtechnology allows large companies to control computer networks from outside the traditionaljurisdiction of a country. As a result, computer users in Indonesia are unable to control the use ofcomputer networks for national interests and are at risk of being trapped in applied programscreated by foreign companies.Keywords ; programm, hardware, python, human resource
The Development of the Flood Inundation Area Model in the Way Sekampung Sub-Watershed in Lampung

Flood disasters often occur in most areas in Indonesia. Floods are the most common disasters that cause losses and casualties. Flood disaster mitigation needs to be done to overcome and reduce the impact of losses. Mitigation of flood disasters will be helpful if you can predict in advance the potential for inundation caused by flooding, namely by modeling flood inundation. So far, research on modeling the area of flood inundation in Indonesia can be categorized as relatively rare. It is due to the many obstacles that surround it. The problem faced is the unavailability of complete data caused by limited funds and the complexity of most of the watersheds in Indonesia. The study aims to develop a flood inundation area model based on land use conditions and rain variables. It is done by maximizing minimal data and integrating empirical and 2D hydrodynamic modeling formulated with statistical models. The method used is to collect secondary data in the form of rain and land use data and primary data by conducting field surveys of flood inundations that have occurred. Then, it is followed by hydrological modeling to obtain flood hydrographs by integrating HEC-RAS, HEC-GEO RAS, and Arc GIS to generate variables to be modeled statistically using the Multiple Linear Regression approach. The modeling uses samples in some Way Sekampung sub-watersheds in Lampung Province, each with two rain time series data. The independent and dependent variables are the variables to be modeled where the independent variables are Watershed Area (X1), % Forest Area (X2), % Residental Area (X3), % Agricultural / Rice Field Area (X4), % Mixed Plantation Area (X5), % Other Area (X6), River Slope (X7), River Length (X8), Rainfall (X9), Flood Peak Time (X10), Flood Discharge (X11) and one dependent variable, namely Flood Inundation Area (Y)Four independent variables do not affect statistical modeling, namely X4, X6, X7, and X9. The model obtained is Y = 150,442 -0,242 X1 -0,412X2-0,515X3-0,241X5+ 2,050 X8 -0,704 X10+ 0,020 X11 4. MAPE test results (Mean Absolute Percentage Error) The model equation shows a value of 4.672% of the data. Thus, the model is in the Class 1 category that is Very Accurate.
A Hybrid Approach Using ACO-GA for Task Scheduling in Cloud

Cloud computing is a fast-growing technology in today's world that offers a wide variety of services based on the need of its users. Cloud provides services like computing, storage, and networking which are accessible through the Internet. In the computing cloud, task scheduling plays a vital role in optimizing resource utilization and providing quality of service (QoS) to the customer. Efficient task scheduling is needed to fulfill the user requirement and system performance. Traditional task scheduling algorithms in a cloud platform like max–min, shortest job first, and round-robin are not so effective in reducing makespan and cost. The main motive behind this research is to apply a combination of the genetic algorithm for task scheduling in a cloud environment and analyzes its effect, as the genetic algorithm can efficiently solve NP-hard problems. This paper proposes a hybrid approach task that combines the advantages of the two most widely used evolutionary algorithms: genetic algorithm (GA) and ant colony optimization (ACO) for improving the scheduling in the cloud using hybrid approach to overcome the limitation of unnecessary diversity. The experimental result conclusively proved that there is an 18% to 20% reduction in cost and makespan by ACO-GA-based task scheduling in the cloud as compared to simple GA and ACO.
LibGuides: Media Literacy: The SIFT Method

Media literacy encompasses the practices that allow people to access, critically evaluate, and create or manipulate media.
Estrategias didácticas para el proceso de enseñanza – aprendizaje en tiempos de pandemia Covid -19

En tiempos en que la pandemia ha obligado a implementar clases on line o virtuales es importante dedicar el tiempo y recursos en mucha mayor proporcion a los estudiantes. En este trabajo se presentan un conjunto de estrategias didacticas que contribuyan al mejoramiento del proceso de ensenanza – aprendizaje en las Unidades Educativas; para lo cual se empleo la ruta cuantitativa – cualitativa de la investigacion, con un alcance descriptivo. En el estudio se determino que la mayoria de los estudiantes consideran a un nivel medio es efectiva la educacion online en el proceso de aprendizaje y para lo cual, se proponen estrategias, tales como: innovacion educativa, investigacion, guias didacticas y un modelo de evaluacion para emprender la transformacion de la educacion.Palabras clave: Ensenanza, aprendizaje, estrategias, pandemia, COVID-19. ABSTRACTThe pandemic time has forced to implemented online or virtual classes, it is important to dedicate more time and resources for students. This work presents a set of teaching strategies that contribute to the improvement of the teaching-learning process in the Educational Units, which the quantitative - qualitative path of research was used, with a descriptive scope. The study found that most of students consider online education in the learning process to be effective at an average level, proposing strategies such as: educational innovation, investigation, teaching guides, and an evaluation model to undertake the transformation of education.Keywords: Teaching, learning, strategies, pandemic, COVID-19.
Rancang Bangun System Pintu Otomatis Menggunakan Keypad dan RFID Berbasis Arduino Mega 2560

he door is a very important tool in a house, office and room. Because the door is the first layer to protect the contents of the room, because it must have a door security system. Doors have a variety of models in the key types as we know in ancient times the key shape of the keyhole is quite large and also supported by the key that is quite large, it also does not escape from criminal acts such as key suppositions that occur frequently. In the modern world digital technology is developing very rapidly, a lot of automation has been developed, doors that are usually opened and closed manually can be made possible to automate so that it can facilitate various human activities and also be equipped with a security system protected by passwords, if we want to enter the door we must know the password first or by using the ID tag tap. With increasingly  developing technology the author tries to apply the technology in automating a door. One of them is the System to Open the Automatic Gate Door Cover Using a Keypad and RFID with the Arduino Mega 2560 Module
A Framework for Efficient Multilevel Polarity-Based Sentiment Analysis Using Fuzzy Logic

The evaluation of any product or event on social media with the opinion or emotion of peoples is known as sentiment analysis (SA). A great deal of attention has been attracted in recent years, toward both science and industry fields for a variety of uses. Machine learning and the text mining uses this most widely known application area of sentiment analysis. This paper presents a framework for efficient multilevel sentiment analysis using fuzzy logic for the classification of online test reviews polarity as strong positive, positive, negative and strong negative. This proposed model can use the fuzzy logic classifier to enhance the degree of sentiment polarity of reviews. Here, fuzzy logic classifier is used for finding the sentiment classes. This also utilizes the mechanism of imputation of missing sentiment for integrating non-opinionated sentences in generating precise results. Results show that the proposed method has a capability of extracting opinions and classify them in an effective way. The proposed method has a capability to predict the degree of sentiment polarity for the reviews on a social media. The better precision and F1-scores are obtained for an objective/subjective classification and polarity (positive/negative) classification on twitter dataset.
Efficient Cryptographic Constructions with Strong Security Guarantees

Digital devices, systems, and networks effect more and more parts of everyday life. However, due to the complexity of modern digital technology a variety of techniques and mechanisms are required in order to secure communication and to protect sensitive data. The science dealing with secure communication and data protection is called cryptography. This thesis bridges the gap between cryptographic constructions with strong security guarantees and efficient execution. Here, strong security mainly refers to security against adaptive adversaries. For instance, this may refer to several kinds of queries which depend on the respond to previous queries as well as corrupting machines depending on prior corruptions. Efficiency refers to improvements in speed and savings in space. Those are achieved by lower computational costs, fewer communication rounds or smaller elements like keys, ciphertexts, and digital signatures.
A Novel Feature Matching Rank Search Mechanism over Encrypted Cloud Data

A Secure and Dynamic Multi-keyword Ranked Search Scheme over Encrypted Cloud Data Due to the increasing popularity of cloud computing, more and more data owners are motivated to outsource their data to cloud servers for great convenience and reduced cost in data management. However, sensitive data should be encrypted before outsourcing for privacy requirements, which obsoletes data utilization like keyword-based document retrieval. In this paper, we present a secure multi-keyword ranked search scheme over encrypted cloud data, which simultaneously supports dynamic update operations like deletion and insertion of documents. Specifically, the vector space model and the widely-used TFIDF model are combined in the index construction and query generation. We construct a special tree-based index structure and propose a “Greedy Depth-first Search” algorithm to provide efficient multi-keyword ranked search. The secure kNN algorithm is utilized to encrypt the index and query vectors, and meanwhile ensure accurate relevance score calculation between encrypted index and query vectors. In order to resist statistical attacks, phantom terms are added to the index vector for blinding search results. Due to the use of our special tree-based index structure, the proposed scheme can achieve sub-linear search time and deal with the deletion and insertion of documents flexibly. Extensive experiments are conducted to demonstrate the efficiency of the proposed scheme.
CBIR System Development Using the Concepts of Image Feature Synthesis with Matching Parameters-A Survey

In this survey/review article, a brief review or survey about the CBIR system development using the concepts of image feature synthesis with matching parameters is presented w.r.t. the work done by various researchers across the world who has researched similar topics as such this paper finds a base paper or as a ready reckoner for those who want to pursue research in this field of CBIR.
Kohesi Dan Koherensi Pada Teks Lagu Anak-Anak Serta Penanaman Karakter Pada Pendidikan Prasekolah

Inculcating character education through children's songs is an important step in efforts to build national character in education in schools or madrasas. This study aims to (1) describe the forms of cohesion contained in children's song lyrics, (2) describe the forms of coherence contained in children's song lyrics, and (3) describe the contents of the character content in children's songs. child necessary for the development of a child's personality. This type of research is descriptive qualitative with data in the form of a piece of children's song text that contains the value of character education which is analyzed from the point of view of cohesion and coherence. Data collection techniques using observation techniques and note-taking techniques. The research data analysis technique used a separate method with the basic technique used, namely the BUL (For Direct Elements) technique, the validity of the data was through the theory triangulation technique. The results of this study indicate that the grammatical cohesion contained in children's songs is in the form of references and ellipsis. Lexical cohesion in the form of repetition and anatomy. The coherence found is a marker of a timing relationship and a marker of a causal relationship. Children's songs pay less attention to the integration of linguistic aspects and only prioritize repetition of words, phrases, clauses and 10 children's songs that have been analyzed already contain the character values needed by children so that they are suitable for use as teaching materials in pre-school education to build national character.
The Impact of Governance Quality on Improving Innovative Activities in Selected MENA Countries

Moving towards a knowledge-based economy is an important factor for developing countries. Achieving this goal requires improving different pillars such as innovation. Governance quality is a key factor to create innovation pillars and improve innovative activities. In this paper, we describe the impact of governance quality on improving innovation in selected MENA countries during 2009-2018. We used an empirical model and panel data method to describe the relationship between governance quality and innovative activities by considering control variables such as inflation, domestic credit provided by the financial sector (%GDP), the net inflow of foreign direct investment (FDI), and trade (%GDP). Empirical results indicate that the governance quality has a positive and significant effect on the performance of innovation in MENA countries. The positive effect of the governance quality sub-indices indicates that an improving institutional environment is necessary to stimulate innovation activities. The results also show that trade in MENA a country not only harms but also discourages innovative activities. According to empirical results, we propose that improving governance quality concentrated on government effectiveness and control of corruption is essential for innovative activities in MENA countries.
DIGITAL SIGNATURE ALGORITHM TO MAINTAIN PERFECT FORWARD SECRECY (PFS) USING HYPERELLIPTIC CURVE CRYPTOSYSTEM

Key management plays a major role in public key cryptosystem, especially using session keys changing the session key from time to time enhances the robustness of the cipher at every stage of its transmission from one end to the other. The mission of protecting the session keys against the adversary can be achieved by perfect forward secrecy (PFS). The present paper explains the digital signature algorithm with perfect forward secrecy (PFS) basing on Hyper Elliptic Curve Cryptosystem. Hyper Elliptic Curve Cryptosystem (HECC) provides equal security level as other conventional public key cryptosystems with shorter key length. The proposed digital signature algorithm strengthens the cipher in all directions of confidentiality authentication and integrity.