Reviewerly/exHarmony huggingface dataset:
IMPLEMENTASI PROGRAM LITERASI DALAM PEMBELAJARAN BAHASA INDONESIA DI SMA NEGERI 1 KONAWE SELATAN PROVINSI SULAWESI TENGGARA

This study aims to explain the condition of the literacy program in Indonesian language learning at SMA Negeri 1 Konawe Selatan, Southeast Sulawesi Province. This research used descriptive qualitative research. The results showed that the literacy program was not running optimally. The problems of literacy programs in Indonesian language learning that occur at SMA Negeri 1 Konawe Selatan include irrelevant learning strategies, the availability of facilities and infrastructure that are less supportive and incomplete, and low reading interest in students as shown in the questionnaire results as much as 57% students do not agree to set aside their time for reading activities, 48% of students do not agree that reading activities are preferable to playing, 57% of students answered agree that reading activities are only done when they get assignments. This shows that the literacy program has not been running effectively to increase interest in reading and writing in students.
Research on Data Approximation Search Privacy Protection in Cloud Environment

In recent years, with the development of technology integration such as the Internet of Things, cloud computing, big data, etc., the volume and speed of data generated annually in the world have increased exponentially. The huge amount of data is hosted on the cloud platform, which aggregates and fuses various data mining algorithms from multiple sources to provide "wisdom" answers to the upper complex application requirements. There is currently no one-dimensional solution for large data search, such as "accuracy, timeliness, privacy granularity". This paper establishes a quantifiable measurement mechanism between the multidimensional indicators with intermediate evaluation criterion "(ϵ,δ)-Approximate" as a bridge, and implements a data retrieval scheme that coordinates the three dimensions of large data search. This mechanism solves the re-search problem caused by isomorphic search and data version update, and improves the efficiency of universal search by improving the Hadoop system architecture.
PELATIHAN SOFTWARE WINGEOM UNTUK MENINGKATKAN KOMPETENSI GURU DI KECAMATAN PANGALENGAN

Community service is conducted in the form of a training workshop on the use of wingeom software for elementary, junior and senior high school teachers in Pangalengan District. The purpose of this service is to improve teacher competence in using learning software in the classroom, especially wingeom software. The location of the service was held at SMAN 1 Pangalengan, with a total of 51 participants. Researchers conducted initial observations by distributing questionnaires on the google form. The results of preliminary observations indicate that teachers in schools are still lacking in the use of ICT, especially mathematical software in learning. The teachers do not have the skills to use the software in learning mathematics. The lack of use of ICT is due to the teachers' lack of understanding of ICT, so that teachers have difficulty in operating mathematical software. This has encouraged the implementation team to conduct wingeom software training to improve the competence of teachers in the ICT field in Pangalengan District. During the wingeom software training, the teachers were very enthusiastic in following their activities from the beginning to the end of the training. Through the questionnaire at the end of the training it was found that the teachers could master the wingeom software and be able to apply the software when learning especially learning about geometry. Wingeom software training can improve the competence of teachers in Pangalengan District. Through this mathematics software training, the teacher has skills n teaching mathematics that is interesting and fun for students.
Образы политических лидеров в условиях современности сквозь призму классических концепций

The article considers the possibilities of combining the classical approach to the typology of political leadership and post-Jungian archetypal typologies that arose in the late ’80s of the XX century and are still addressed to the issues of the practical effectiveness of building images in demand by society. The images chosen by politicians to communicate with audiences in today’s complex and contradictory media environment are viewed as an object of directed construction, on the one hand, and the other — as invariably meeting the current needs of society and responding to public demand. At the end of the article, the author makes a conclusion about which types of politicians will soon prevail.
Educational Mobile Apps to Enhance Language Learning in EFL Classroom

Technology has been widely used to enhance language learning all over the world. Likewise, in order to make the 21st century learners’ learning process more engaging and challenging, teachers should be able to use technology effectively. The use of educational mobile apps can take students outside of the structures of the classroom, and the students can take the outside world into the classroom which empowers students to enhance their learning experiences.Amongst the incredible number of apps, there is a great variety of apps intended for students of foreign languages. The areas of language the apps are designed to teach can range from teaching only vocabulary or pronunciation up to being well constructed language courses. This study explores how educational mobile apps available today would enhance language learning in EFL classroom at secondary level.The paper also highlights the benefits and future challenges of mobile learning in our educational environments in Indonesia. Moreover, this paper is also intended to examine both the qualities and limitations of some mobile apps available by assessing their features from the pedagogical, technical, and content point of view.
Implementasi Algoritma AES (Advanced Encryption Standard) Untuk Keamanan File Hasil Radiologi di RSU Imelda Medan

Data security is very important for all users of an information system, recently cryptography has become the method used in data. Cryptography is the study of mathematical techniques in an original information or message (plaintext) into a hidden text (Chipertext) and then converted into the original message again. Cryptography has three important elements, namely key generation, encryption and description. In cryptography, the block cipher algorithm is known, which includes AES (Advanced Encyption Standard) which is part of the Modern Symmetric Key Cipher, this algorithm uses the same key during the encryption and description processes so that the data we have will be difficult to cooperate with its meaning. The algorithmic technique is used to measure data in the form of certain codes, for the purpose of so that the stored information cannot be read by anyone except authorized people. Therefore, a data security system is needed in sending radiological results to patients because radiological results are confidential to patients. Keywords : Algorithm, AES, Encryption, Description, Cryptography
Designing and Planning with TYPO3

This chapter will give a good idea of how to design and plan TYPO3 websites and applications and will explain some fundamental components that make TYPO3 unique.
Practice and Exploration of Contemporary College Students’ Career Planning

With the implementation of China’s higher education enrollment expansion policy and the optimization and upgrading of the social industrial structure, the current employment situation faced by college students is becoming more severe. For many college students, graduation means unemployment. The education activities of college students’ career planning are essential to provide scientific guidance to college students’ employment activities, so that they can form a scientific concept of employment and seek new employment opportunities. This article mainly explores the career planning practice of contemporary college students, aiming to be able to discover the new employment situation of college students, propose new precautions and ideas, so as to improve the employment quality of college students in China.
Estimation Algorithm of CNN-based Relative Velocity Between Driving Vehicles

In this paper, we proposed an estimation algorithm of the relative velocity between two driving vehicles based on CNN(Convolutional Neural Network), as the perception of the surrounding environment around an autonomous car, such as distance and speed of other vehicles, is important. The proposed algorithm estimated the velocity of a target vehicle by using a stereo camera without any other sensors. A stereo camera is a sensor that acquires simultaneously RGB images and depth maps, and it is widely used for autonomous vehicles to obtain various information. The developed CNN-based semantic segmentation model with high speed and accuracy was used to recognize the target vehicle, detecting the shape of the target object and omitting background information around it. Due to this effect, the distance between the autonomous vehicle and target vehicle is more accurately estimated. The relative speed between each vehicle was estimated using the distance and time difference between frames. The performance of the proposed algorithm was compared with conventional methods and it was confirmed that the speed of the target vehicle was more accurately estimated using only the stereo camera.
Teleportation of the Bell States on IBM Q Computers Under Their Hardware Errors

We present and analyze our experimental results on teleportation of two-qubit maximally entangled Bell states on the NISQ (Noisy Intermediate-Scale Quantum) five-qubit processors IBM Q Burlington, Essex, London, Ourense, Rome, Santiago, Vigo and Yorktown. The main obstacle in practical implementation of quantum algorithms on the NISQ computers is caused by hardware errors which depend on the depth of the underlying circuit and its gates. We suggest several modifications of the original teleportation protocol to optimize the depths of its circuit and the connectivity of hardware qubits. In addition, we compare the dynamics of the output probabilities on the processor IBM Q Yorktown within one and a half years of our use of this processor. They clearly demonstrate the significant progress made in the hardware of quantum computers.
INNOVATIONS IN EDUCATION THROUGH THE SIGHT OF STUDENTS AND TEACHERS

This article analyzes and summarizes some of the results of a research conducted with a survey of teachers applying innovation in their pedagogical daily lives and students who have conducted their public practice in an online environment. The researched innovative solutions and activities, methods and techniques, the shared by leading teachers-innovators good practices („master classes“) with the future pedagogues are the basis of the indicated ideas and proposals for improving the pedagogical preparation of the pedagogue students from the Faculty of Pedagogy at Sofia University „St. Kliment Ohridski” by implementing the studied experience in the curriculum of academic disciplines aimed at providing not only theoretical but also practical knowledge and skills.
Efficient Low Power Region Enhanced Architectures For DWT And AES For Protected Coding Image

In this article presents an HDL template on the ASIC platform. For quicker and safer image data transmission stable encoding of pictures via image compression and AES through encryption, the DWT was facilitated. The DWT calculation algorithm based on a lifting scheme and a multi-level sub-bands on the ASIC platform are created. 2D-DWTwas built using it. The related sub-bands were chosen to minimize the compression time of the AES encryption, based on compression ratio and data recovery. To ensure high efficiency and latency, the DWT architecture was developedHDL model and AES algorithm for the area, timing and power performance of the ASIC platform have been developed and validated for the DWT architecture. Using 56 nm CMOS technology, the ASIC implementation was carried out.
Penerapan Algoritma Naïve Bayes Untuk Analisis Kepuasan Penggunaan Aplikasi Bank

The world of banking has been transformed by using mobile-based applications in services and providing convenience to consumers. Android-based applications such as mobile banking are not yet fully attractive to users because of their security value. In the field of text mining, there is a method of analyzing user satisfaction through content sentiment analysis. The approach used by the author in this study is to use the Naive Bayes Algorithm. This research was processed with the python programming language where there is a textblob module for the process of analyzing the effectiveness of using the Naive Bayes Algorithm. From the results of the processing of this research, the accuracy of using the Naive Bayes Algorithm is 0.8714 (87%)
Scalar-weighted FastIMM Based on Fading Memory Filter Model and Adaptive Markov Transition Matrix

In this study, a novel target tracking algorithm based on fading memory filter model and adaptive markov transition matrix is proposed to achieve a better tracking performance for the case where the measurement noise is high, target are distant and target maneuvers are intense. The proposed adp-FastSIMM-FM algorithm has been shown to have a better position estimation than the FastIMM-FM algorithm which has a better estimation than FastIMM and FastIMM-imp. Also, adp- FastSIMM-FM algorithm has a low computational cost.
Event correlation for deception detection in long video

Automated Deception Detection (ADD) is a challenging task and still under study as a visual analysis task. Based on the idea that human micro-expressions and body movements could be used as clues for ADD, many works have proposed some action recognition models for extracting face and body spatiotemporal features. However, these features are not sufficient evidence for deception; moreover, micro-expressions are difficult to detect and real-life deception samples are hard to collect, thus ADD still has many challenges. In this paper, we present a global two-stream network (GTSN), which not only extracts face and body features, but also utilizes the correlation between the deceptions. GTSN can improve the accuracy of deception detection by adding historical information based on the correlation between the deceptions. We build a dataset named Deception-Truthful (DT) for evaluating the performance of our proposed model. Experimental results demonstrate that our GTSN model outperforms other action recognition models used for ADD. Further, the proposed GTSN model also performs well on the real trial videos widely used in ADD.
Building and Extending TYPO3

In this chapter, we’ll look at the underlying architecture of TYPO3, what is built in as Core features, and how you can extend it with custom code.
Optimization of LDA parameters

The aim of topic modeling is to automatically discover topics in large collections of documents. Although it is used in many different fields, the questions of how to eliminate topic instability and how to optimize model parameters are not fully answered yet. In this study, optimization of parameters of Latent Dirichlet Allocation (LDA) model, which has been one of the most preferred topic modeling methods, is investigated. For this purpose, a parallel differential evolution algorithm with two cost functions (LDADE and Word2Vec) has been implemented and applied to two data sets with different properties. The results obtained from the application are discussed in detail.
Application of fractional bio-inspired filter for salient color detection

Computational modeling of visual attention has been a research field focused on emulating the behavior of biological visual systems in a given scenario, by using mechanisms developed for fixation prediction or salient region detection. In the literature, different approaches have been presented to emulate the interactions that occur in the early vision system of biological structures. However, mathematical modeling of these systems applying theories related to fractional operators could outperform the existing models. In this paper, we present a fractional bio-inspired filter for salient color detection in natural scenarios, based on the behavior and distribution of the cone photoreceptors cells in the retina. The filter was compared with two classic saliency algorithms over a natural color image dataset in terms of saliency prediction and processing time, using a Similarity (SIM) score and runtime performance, respectively. Our approach reach the second best result in therms of saliency prediction with a 48,9% of SIM with ground truth fixations maps and the fastest time response, with an average time of 0.12 s when processing a high resolution image, being 25% faster than Itti et al. algorithm, one of the most applied in robotic vision tasks.
Murder Mystery Game Setting Research Using Game Refinement Measurement

This paper explores the game sophistication of a party game is called Murder Mystery Game (MMG), which is very popular in teenagers, recently it was boom developed in China and Japan. For players, they have to promote game story process by performing the role which was assigned to them, finally, players need to find out who is the “murderer”, reversely murderer player has to try his best strategy to escape from the story. In this paper, our research focuses on the playing settings, MMG needs several players and cost a few hours, the game would become boring as the number of players becomes too large or too small, therefore we use the game refinement theory to analyze MMG setting to make the game process become more balanced and sophisticated. Computer natural and convergent simulations for a simple version of MMG are conducted to collect the data while game refinement measure is employed for the assessment. The results indicate several interesting observations, which can help game designers to create a better murder scenario.
Penggunaan media tali andha aksara jawa untuk meningkatkan keterampilan menulis aksara jawa

&lt;p&gt;&lt;em&gt;This research aims to improve Javanese script writing skills for four grade students of Ta’mirul Islam Surakarta Elementary School in 2018/2019 academic year by using Tali Andha Aksara Jawa media. This Classroom Action Research consisted of two cyles with two learning in each cycle. Subject in this research were students and teacher in IV E grade of Ta’mirul Islam Surakarta Elementary School. Research data collection by way of interviews, observations, test, and document analysis. Source triangulation and technical triangulation used for data validity. The data in this research used descriptive comparative analysis techniques and interactive analysis model by Miles and Huberman. Classical completeness of students in initial condition was 8%, in first cycle showed 56%. then in second cycle showed 92%.&lt;/em&gt;&lt;/p&gt;&lt;p class="Abstract"&gt;&lt;strong&gt;&lt;em&gt;Keywords&lt;/em&gt;&lt;/strong&gt;&lt;strong&gt;&lt;em&gt;: &lt;/em&gt;&lt;/strong&gt;&lt;em&gt;Writing skills&lt;/em&gt;&lt;em&gt;, Javanese script, Tali Andha Aksara Jawa, elementary school&lt;/em&gt;&lt;em&gt;&lt;/em&gt;&lt;/p&gt;
Introduction to High-Level Programming Languages

In the last chapter, we concluded Linux shell scripting. In this chapter, we will learn how to write programs with high-level programming languages like C, C++, and Python 3 with the RPi OS. The following is the list of topics we will learn in detail in this chapter:
A Fast Class Noise Detector with Multi-factor-based Learning

Noise detection algorithms commonly face the problems of over-cleansing, large computational complexity and long response time. Preserving the original structure of data is critical for any classifier, whereas over-cleansing will adversely affect the quality of data. Besides, the high time complexity remains one of the main defects for most noise detectors, especially those exhibiting an ensemble structure. Moreover, numerous studies reported that ensemble-based techniques outperform other techniques in the accuracy of noisy instances identification. In the present study, a fast class noise detector called FMF (fast class noise detector with multi-factor-based learning) was proposed. FMF, three existing ensemble-based noise detectors and the case with original data were compared on 10 classification tasks. C5.0 acted as the classifiers to access the efficiency of these algorithms. As revealed from the results, the FMF shortened the processing time at least twelve times by three baselines, and it achieved the highest accuracy in most cases.
Особливості формування музичного мислення майбутніх учителів у класі фортепіано

The relevance of this study is due to the intensive development of modern humanistic society. Pedagogical science is getting new contents. Therefore, cardinal direction in the development of creative qualities of the individual among which musical thinking is of particular importance. In this work musical thinking is defined as a special process in which emotional and rational elements are synthesized on the basis of sound phenomena, a new reality is created in the form of composers’ works, their interpretation, musical and theoretical understanding, and perception. Musical thinking has such a function: emotional, constructive- logical, controlling, developing. The author found the forming of musical thinking occurs in the course of specially organized work on interpretation of musical compositions and their performance. The article also defines the specificity of the performance activity of a musical teacher, which is in its subordination to the tasks of aesthetic education of the individual. Teaching effectively influence the development of music thinking, since this process has a universal character wide coverage of musical material, transformation elements and special kind of sound touch, relative technical availability. Some original methods of development musical thinking: emotional influx, the transformation of images-memories, associative sketches are defined. As a result of study, author identified the following features of the forming musical thinking of upcoming music teachers in piano training class: the emotional and creative nature of musical performance, the universal character of piano teaching, the synthesis of emotional and constructive- logical functions, the pedagogical orientation of the teachers performing activities, the obviousness of two type of interpretative concept- music and verbal, adaptation to extreme conditions of performance, using new educational technology.
The Effect of Self-Efication, Interest of Learning and Internet Use on Students Learning Motivation

This research was made to find out and analyze the effect of self-efficacy, interest in learning and internet use on student motivation. The sample used in this study were 220 respondents. The sampling technique used is the technique of purposive sampling and data collection techniques with a Likert scale. Analysis or test data using the application of SPSS 22 and Amos 23. The test is a test of test requirements, a classic assumption test and a hypothesis test. Researchers also conducted EFA, CFA and SEM tests.Based on the results of the study, two of the five hypotheses were accepted and three were rejected. H1 shows that the Self-Efficacy variable has a critical ratio (CR) value of 8.155> 1.96 and P of 0.000 0.05, then the hypothesis is rejected. H4 shows that the self-efficacy variable has a critical ratio (CR) value of 0.553 0.05, then the hypothesis is rejected. H5 shows that the self-efficacy variable has a critical ratio (CR) value of -1.735 0.05.