Reviewerly/exHarmony huggingface dataset:
ANALISIS KESULITAN BELAJAR MAHASISWA DALAM PEMBELAJARAN DARING PADA MATA KULIAH STATISTIKA

The research was carried out with the aim of analyzing difficulties in the student learning process in online learning in Statistics courses. This research was conducted using a descriptive qualitative method. Descriptive qualitative research has several stages as follows: data collection, data reduction and drawing conclusions on research data. The research was conducted at the Indonesian Technocrat University. The research subjects were Students of the Mathematics Education Study Program 2021 Class A who were taking an online Statistics course. Based on the description of the research results, it can be concluded that the difficulties in the student learning process in Statistics courses which are carried out online are influenced by internal factors and external factors. Learning difficulties from internal factors include: difficulties in motivation and interest in learning and difficulties in understanding the material. Learning difficulties influenced by external factors, namely: difficulties in understanding lecturer explanations, signal difficulties and data quotas owned by students, difficulties in using learning applications, limited gadgets owned and difficulties in obtaining support for the learning environment.
Image Mosaicing

Image mosaicing is a technique for combining many images of the same scene to generate a larger, seamless panoramic image. Image mosaicing can be traced back to the days of manually piecing images. Image-mosaicing techniques have been created to automate the process since the introduction of computer technology. The method consists of five phases, including feature matching and estimation of the homography matrix. Image mosaicing is commonly used in virtual tourism, video games, and photo editing. Despite the fact that the image panoramic feature is accessible in digital cameras, there is still potential for improvement, and more research in this sector is required.
An Optimality-Theoretic Analysis of Word-stress Learnability: Evidence from Moroccan-English Interlanguage

This study adopts a theoretical analysis of the learnability of English word-stress. It intends to provide an Optimality-theoretic analysis of word-stress learnability among Moroccan learners of English. Language acquisition, from an Optimality Theory perspective, is a process of reordering the constraints from an initial state of the grammar to the language-specific ranking of the target grammar. To account for stress development, this paper makes use of the Constraint Demotion Algorithm (Tesar &amp; Smolensky, 1996; 2000), which learners adopt to infer the correct hierarchy of constraints. Starting with a default hierarchy supplied by Universal Grammar, learners proceed with the recursive demotion of higher-ranked constraints until the correct ranking is reached. The algorithm, starting by initializing the hierarchy, assumes that constraints are unranked and thus hosted in the same stratum. Sixty Moroccan learners participated in the study. The informants are third-year students at Ibn Tofail University. They were administered an oral multiple-choice test that elicited their intuition about English stress patterns. The overall findings of the study reveal that learners’ prior (L1) ranking influences their learnability of English stress. That is, Moroccan learners misplace stress in English words due to the initial state of their grammar. From the findings, OT is evidenced to successfully predict learning stages using CDA, wherein each demotion signals a learning stage.
Incremental Question Paper Generator

Exams are getting digitized all over the world. Basically, meaning that the traditional paper-based tests are being replaced by the certain computer-based tests which have proven to be both more consistent in allocating marks and faster than teacher correcting papers. The traditional exams usually consisted of subjective answers which were not the best way of grading the student’s perception of the subject. Hence, we are developing a computer-based system that will generate MCQ based question that will be better suited to grade students academically. So, Incremental Question Paper Generator (IQPG) is an attempt at developing a software which can implement adaptive evaluation along with generation of questions on its own. The software aims to generate an increasingly difficult or easy in simpler words, it aims to generate a question paper which dynamically changes the difficulty of its questions. Along the same the software generates these questions by learning from a pre-made dataset of questions.
Research on STM32-Based Signal Conditioning System Measurement System

The measurement of the signal modulation system is a vital part of channel transmission signal technology, which has a very important position in the signal communication quality assurance system. With the development of radio communications in modern radio technology, the research of AM and FM signal modulation measurement methods has become an important element in this field of research. This research is a signal modulation system using an STM32F407 microcontroller as the control core. The hardware of the system is mainly composed of a coherent demodulation circuit system and a comparator judgment circuit system, and the coherent demodulation circuit system is divided into AM demodulation circuit system and an FM demodulation circuit system. The frequency of the input signal was measured by a comparator, and the frequency change was used to initially determine the signal type. In which the modulating signal of AM signal was obtained by DDS generating separate orthogonal sine and cosine signals with the input signal through a series of operations, while the FM signal was operated with the sine signal. Finally, the amplitude and frequency information of the FM signal was obtained through the comparator, and finally reduced to the modulating signal of the FM signal. Output demodulated signal, its signal waveform without obvious distortion apparent phenomenon. Promotes the prospect of using the calibration of AM and FM signal generators in the field of communication.
Physics-informed hierarchical echo state network for predicting the dynamics of chaotic systems

Echo state network (ESN), a type of special recurrent neural network, has gained attention for its simplicity and low computational cost, making it commonly used for data-driven prediction of complex dynamical systems. However, in cases of insufficient or poor-quality data, data-driven approaches can suffer from low prediction accuracy caused by overfitting. To address this problem, a physics-informed hierarchical echo state network (Pi-HESN) is proposed for predicting the dynamics of chaotic systems. Firstly, the Pi-HESN can capture the latent evolutionary patterns hidden in the dynamical systems by processing data layer by layer in stacked reservoirs. Secondly, the Pi-HESN integrates data and physical laws in a unified way, incorporating prior physical knowledge into the objective function to ensure basic physical principles are respected. The combination of data-based and knowledge-based approaches in Pi-HESN improves model generalization, alleviates the shortage of training data, and ensures physical consistency of results. Experiments on four classical chaotic systems illustrate that the proposed Pi-HESN outperforms the original ESN and existing hierarchical ESN-based models in accuracy and predictability horizon.
Pedagogical Co-Creation as a Condition for Training Future Music Teachers to Lead Folklore Groups

The article examines the phenomenon of co-creation as a condition for the professional growth of future music teachers. The content of creative interaction of future teachers-musicians both during classroom work and in the process of production practice is highlighted. The author of the article draws attention to the fact that the process of co-creation has a positive effect not only on student learning, but also on the development of the teacher himself, improves his creative abilities, deepens knowledge and creative skills. Such interaction is the best possible means of establishing a working atmosphere in the artistic team, and also has a developmental impact on the practical activities of future music teachers in direct work with students. Based on the works of modern researchers of this issue, the author comes to a conclusion about the use of special forms and methods of professional training for ensemble management, the development of a number of personal qualities for creative communication. The work provides examples of interaction and useful co-creation of teachers and students. The author offers ways to overcome problems and misunderstandings on the way to productive interaction between members of the artistic team.
Mathematical Models as a Key to Effective Teaching of Set Theory at Undergraduate Level

The paper is dedicated to the problem of optimization of teaching set theory at undergraduate level (as a part of Mathematical Logics course). The authors’ original method of using mathematical models for teaching set theory is presented. Concrete recommendations for increasing effectiveness of teaching set theory are given. The paper contains original mathematical models which were proved to promote deep understanding of the key concepts of set theory in students, as well as their ability to apply those concepts to solving real-life problems. All conclusions and recommendations are based on the results of modern research in education and on the authors’ teaching experience. The effectiveness of presented technique was proven in practical teaching at Voorhees University, South Carolina, USA and at Denmark Technical College, South Carolina, USA.
Features of the Formation of Artistic and Figurative Thinking of Students by Means of Sculpture as a Form of Fine Art

Based on the analysis of scientific literary sources and based on the author's own experience, the author in the article pays attention to the development of sculpture in the modernity, its features, differences from other types of fine art forms. The relevance of the topic is due to the need to train of highly qualified art teachers who have effective teaching methods. One of the stages of such training is the development of spatial thinking among students of pedagogical universities in sculpture classes. This kind of art allows students to go beyond the plane of the page into three-dimensional space. Sculpture classes allow you to see the relationship of different objects with the landscape, air, and each other. The main types of sculpture are characterized, the historical path is described, the essence and specific means inherent in the art of sculpture are revealed and characterized inherent in the art of sculpture. The role of sculpture in the formation of the aesthetics of the environment. The ways of solving creative tasks by means of sculpture, the importance of sculpture in the educational process is highlighted, because students should be guided by the works of high art of both old classical masters and contemporary artists. Familiarization with the world's best works of painting and sculpture contributes to development of artistic and imaginative thinking, formation of students ‘sense of beauty, the ability to understand the beauty of not only art, but also the surrounding world and the surrounding world, the formation of imaginative and spatial thinking. The art of sculpture is characterized as an artistic and figurative reflection of life. It is substantiated how important this important branch of art is in the formation of creatively thinking specialists - artists, future teachers, and teachers of fine arts. It is also shown how sculpture is connected with other art forms, that are important for students who acquire knowledge in the field of fine arts, art, as well as with such disciplines as descriptive geometry drawing, and plastanatomy. It is highlighted how artworks, while decorating our lives, also contribute to the preservation of historical memory contribute to the preservation of the historical memory of peoples, being a kind of a constant in the time line. The work is addressed to scholars, employees of the system of higher artistic and pedagogical education, students.
The Implementation of the Paikem Approach by Using the Graphic Media to Increase Students’ Activeness and Learning Outcomes in the Language Subject

Student engagement is not optimal and has an impact on learning outcomes, so the PAIKEM approach, aided by graphic media, must be used. The study's goal was to examine the increase in activeness and learning outcomes of Indonesian fourth grade students after using the PAIKEM approach with graphic media. This is a two-cycle classroom action research project. In this study, data was collected through observation and testing methods. The study's findings were analyzed using both descriptive statistical and quantitative descriptive methods. According to the findings of the first cycle of research, the average value of student learning activity was 71 and 71% of classical completeness was obtained. In cycle II, the average value of student learning activity was 86.41, with a classical completeness of 86.41%. The average activeness of 15.41 and 15.41% of classical completeness appears to have increased. The second research cycle yielded an average of 66 student learning outcomes and 66% classical completeness. In cycle II, the average value of student learning outcomes is 85.5, with a classical completeness of 85.5%. There appears to be a 19.5 and 19.5% increase in learning outcomes, respectively. It was concluded that using the PAIKEM approach in conjunction with graphic media could improve the learning outcomes of Indonesian students in elementary school class IV.
Comparative Study Between Archaic and Advance Technique to Evaluate the Impact of Mining Activities on Neighboring Environment

Abstract: Geo-material plays significant role in the expansion of social progress, industrial growth and treasure of all nations. Rocks are one of the most accessible natural resource and one of the most important building material for urban development. It has been used from the initial spells of our progress for a multiple uses that have increased in quantity and complexity with time. Stone is a major basic raw material applied in crushed form for construction. Minerals are non-renewable in nature and also limited as well and Rocks are the assemblage of minerals. A mineral formerly extracted from the earth were leftover forever so the suitable arrangement of use for minerals including exploration and exploitation should be implemented. Compared to traditional methods, new advanced methodologies are widely used for surveying, mapping and monitoring of these natural resources. Remote Sensing and GIS/ GPS technology including drone technology has been capable as native/ global survey using aerial photo and satellite imagery for temporal study. The multi-temporal nature of satellite imagery helps to monitor present and past situation of the earth features. Thus, provides a useful information to identify land use/ land cover changes and calculate the amount of change. Satellite images are a valuable source of data for surveying, mapping, and monitoring of terrestrial resources as compared to older approaches such as topography and aerial photography. The multi-date character of space technology integrated with drone technology allows to manage/ monitor the mining activities.
Website Traffic Forecasting Using Deep Learning

Abstract: Nowadays, there is an increasing emphasis on how to predict traffic on web pages, and there is a need to explore different methods for effectively predicting future values of multiple time series. Evaluating website traffic on a web server is crucial for web service providers because, without proper demand forecasting, customers might face long waiting times and abandon the website. However, this is a difficult task because it requires reliable predictions based on the arbitrariness of human behavior. The most effective way of transmitting information would be to predict network traffic and display it visually. Nowadays we depend too much on Google's servers, but if we wanted to host a server for many people, we might have predicted in advance the number of users to prevent server failure. Time series prediction is important in many different areas. Although there are already many systems and models for predicting Internet traffic flow, most of them use shallow traffic models and are still somewhat unsatisfactory. Therefore, we will use deep learning techniques based on current and past data to predict future traffic.
Suspicious Activity Detection Using Different Models

Abstract: In today's insecure world, video surveillance systems play a significant role in keeping both indoors and outdoors secure. Real-time applications can utilize video surveillance components, such as behavior recognition, understanding and classifying activities as normal or suspicious. People are at risk from suspicious activities when it comes to the potential danger they pose. Detecting criminal activities in urban and suburban areas is necessary to minimize such incidents as criminal activity increases. The early days of surveillance were carried out manually by humans and involved a lot of fatigue, since suspicious activities were rare compared to everyday activities. Various surveillance approaches were introduced with the advent of intelligent surveillance systems. This paper analyzes two cases that could pose a threat to human lives if ignored, namely the detection of gun-related crimes, the detection of abandoned luggage, the detection of human violence, the detection of lock hammering, the theft of wallets, and the tempering of ATMs on surveillance video frames. In these papers they have used a neural network model that is Faster R-CNN and YOLOv3 technique to detect these activities.
Early Detection of Eye Disease Using CNN

Abstract: The eyes perform an essential part of life. The eye is one of the organs that assist humans learn about their natural environments and collect information from them. Almost everywhere in the world, the frequency of eye disease has increased, needing a serious response. Immediate eye detection will be invaluable assistance in offering further treatment to prevent blindness. In this study, a Convolution Neural Network model is used for identifying eye diseases. This research aims to categorize human eyes into four categories: trachoma, conjunctivitis, cataract, and healthy. The investigation got an accuracy of 88.36%, while the CNN model evaluation provided Precision of 89.25%, Recall of 88.75%, and F1 Score of 88.5%. Based on the accuracy and evaluation results, this system can be used for the early detection of multiple eye diseases. Several random samples were also used for testing in this investigation. The test results indicate that this system is functional.
Stochastic Zeroth-order Riemannian Derivative Estimation and Optimization

We consider stochastic zeroth-order optimization over Riemannian submanifolds embedded in Euclidean space, where the task is to solve Riemannian optimization problem with only noisy objective function evaluations. Towards this, our main contribution is to propose estimators of the Riemannian gradient and Hessian from noisy objective function evaluations, based on a Riemannian version of the Gaussian smoothing technique. The proposed estimators overcome the difficulty of the non-linearity of the manifold constraint and the issues that arise in using Euclidean Gaussian smoothing techniques when the function is defined only over the manifold. We use the proposed estimators to solve Riemannian optimization problems in the following settings for the objective function: (i) stochastic and gradient-Lipschitz (in both nonconvex and geodesic convex settings), (ii) sum of gradient-Lipschitz and non-smooth functions, and (iii) Hessian-Lipschitz. For these settings, we analyze the oracle complexity of our algorithms to obtain appropriately defined notions of $\epsilon$-stationary point or $\epsilon$-approximate local minimizer. Notably, our complexities are independent of the dimension of the ambient Euclidean space and depend only on the intrinsic dimension of the manifold under consideration. We demonstrate the applicability of our algorithms by simulation results and real-world applications on black-box stiffness control for robotics and black-box attacks to neural networks.
Penerapan Literasi Digital Dalam Meningkatkan Motivasi Dan Prestasi Belajar Siswa Pada Mata Pelajaran Produk Cake Dan Kue Indonesia

The purpose of this study is to know the motivation improvement and students learning achievement through the implementation of digital literacy at XI grade TB 1 SMK Negeri 5, Denpasar on the subject of product Cake and Indonesian Kue. The kind of this study is experiment with quantitave analysis techniques by using method of pre-experimental design type one group pre-test &amp; post-test and purposive sampling techniques. The subject of this study is students at grade XI Tata Boga 1 SMK Negeri 5 Denpasar. On pre-test average value of learning motivation the result showed 112.05, with the highest value is 128.00 and the lowest is 97.00. On learning achievement average value the result showed 68.09, the highest value is 80.00 and the lowest is 56.67. When digital literacy implemented on learning process, on post-test all values improved, namely on learning motivation obtained average value 116.72, the highest value is 130.00 and the lowest is 101.00. On learning achievement showed average value is 80.97, the highest value is 86.33 and the lowest is 78.00. So, it can be concluded that by the implementation of digital literacy maximally on learning process was able to improve students motivation and their learning achievement.
Doctoral training in Bulgaria in the light of the Bologna process and the European Education Area

Abstract: Doctoral training is a key prerequisite for building the European Education Area. The article aims to provide an overview and an analysis of doctoral training in Bulgaria in the context of the Bologna Process and the European Education Area. The mains tasks are to outline the perspectives and challenges facing doctoral education, while at the same time attempting to derive recommendations for optimizing the educational and research process within doctoral education in Bulgaria. To achieve these aims, desk research and secondary data analysis were used, as well as content analysis of administrative and legal documents. The working hypothesis is that although the national-level regulatory framework is largely in line with European standards and guidelines, there are gaps in the implementation of the Bologna Process tools. Key words: doctoral training; Bologna Process; European Education Area; europeanization of education; European university alliances.
Literary Works Including Children with Special Needs

Owing to their inclusion in the education system, teachers often encounter students with special needs during their work. When working with these students, the teacher’s level of empathy is extremely important, however it is difficult to achieve if they are not familiar with how these students think and feel. One way of becoming acquainted with individuals with special needs is by becoming familiar with their thinking patterns, especially their emotional responses. The paper presents literary sources related to the topic, wherein the sources are evaluated, and the selected works are analysed. Besides the method of analysis (protagonists, supporting characters, literary space, literary time, subject, theme, motifs, narrator, structure, and plot), the descriptive method for presenting theoretical starting points and the method of synthesis in the conclusion are also used.