Reviewerly/exHarmony huggingface dataset:
Machine-Learning Algorithms on Cognitive Multisensor Image Application

Real-time satellite images play a vital role in remote sensing applications such as regular land surface monitoring and atmospheric application without any physical contact. The satellite images have more of bands, and the machine-learning algorithm is implemented to remove the redundant information between bands, which gives more sophisticated results compared with other standard image processing techniques. The spectral values are shown to have a more prior role for object classification. Preservation of these components and maintaining the tradeoff level between the images are mandatory for efficient classification of the satellite images. The proposed values are measured with statistical parameters such as PSNR, ERGAS, RASE, and entropy.
WHAT IS IN A TWEET? DESIGNING A SEMANTIC LEXICON BASED ON EaD STUDENTS' OPINIONS

Among the various challenges regarding distance education is the necessity of reducing the student dropout rate. In this sense, the present research aimed to contribute to the design of a lexical database focused on emotions and opinions that can be incorporated into a predictive evasion software. For the database design, we used the Scup tool to collect 150 tweets containing distance education students’ opinions and analyzed them in the light of Martin and White’s Appraisal Framework, along with five resources related to the sentiment Analysis field, which were taken from Liu’s work. In addition, we used the Aulete dictionary to describe the lexical units found in our corpus to better fit them into the analysis categories. Results showed 220 opinion tokens, which were identified and labeled according to their polarity. Moreover, these tokens were included in the domains attitude (judgment and appreciation) and graduation (sharp and strong) from the linguistic framework used. The results also indicated the necessity of another resource to help identify the use of figurative language, slangs, and extralinguistic elements, such as GIFS and emojis.
FORMATION OF PERFORMANCE RELIABILITY OF THE FUTURE TEACHER OF MUSIC ART

The purpose of this study is to highlight the theoretical foundations of the formation of performing reliability of the future music teacher in the process of professional instrumental and performance training. The leading provisions of personality-activity, acmeological, and axiological approaches were chosen as the methodological basis of the study. Based on the study and analysis of scientific and methodological sources, we consider the concept of "performing reliability" as a necessary component of the performing skills of a music teacher, as a relatively stable personal development, established through theacquisition of musical-theoretical knowledge, mastery of musical-performing, interpretive, and stage artistic skills. The results indicate that students who are giving priority to higher motives of musical activity, awareness of the importance of such a personal development as performance reliability, which is a necessary component of professional competence of the future music teacher, stimulate students to expand their own instrumental and performancecapabilities, to self-improvement of personal will and professional qualities. The scientific relevance of this study lies in substantiating of the basics of formation of the musical activity motivation, the conditions which, according to the author, will promote success of this process in the course of instrumental and performing educational activity are outlined. The author offers a general way of forming performing reliability, which consists in the optimal pedagogical interaction in directing the individual to the internal awareness of the purpose of the activity as personally significant ones. This leads to the predominance ofhigher meaning-making motives, such as self-improvement and self-actualization in the modern society.
Towards Real-Life Adoption of Conversational Interfaces: Exploring the Challenges in Designing Chatbots That Live up to User Expectations

Chatbots are increasingly popular, but state-of-the-art chatbots still struggle to meet user expectations, limiting their application in many domains.The factors affecting use have been studied extensively in laboratory contexts, resulting in context-independent requirements.However, user expectations and experiences of chat interfaces are affected by the context of use.Research efforts measuring experiences with chat interfaces need to shift from studies in controlled laboratory settings to studies in real-life settings in various domains.This paper explores this field of study by reporting on a small-scale real-life case study on the gap between expectations and experiences with an educational chatbot.More case studies in the wild, such as this one, could contribute to a deeper understanding of factors affecting acceptance and real use.We propose the use of the CIMO logic across these studies to build upon previous results.
Activation Maximization with a Prior in Speech Data

Recently, more and more studies regarding neural networks have been done.However, the learning process of neural networks is often elusive to human beings, which leads to the advent of feature visualization techniques.Activation Maximization (AM) is one of the feature visualization techniques, originally designed for image data.In AM, the input data is optimized to find the data that activates the selected neuron.In this paper, the emotion recognizer's output is selected as the neuron, and the latent code of a generator (of Generative Adversarial Networks) is optimized instead of the input raw data.The aim of this study is to apply AM to different representations of audio data (waveform-based data and mel-spectrogram-based data) and different model structures (CNN, WaveNet, LSTM), and to find out the most suitable condition for AM in audio domain data.Additionally, we have also tried to visualize the essential features of being a certain class for emotion classification in speech data, using 2 datasets: the Toronto emotional speech set (TESS) and the Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS).The mel-spectrogram-based models were found to be superior to the others, showing the distinctive features of selected emotions.More specifically, the CNN-mel-spectrogram-based model was the best in both qualitative and quantitative (FID score) results.Moreover, as demonstrated in this study, AM can also be employed as an output enhancer for generative models.
Deep Learning Technology-based Model to Identify Benign and Pro-B Acute Lymphoblastic Leukemia (ALL): Xception + LIME

Leukemia is a type of cancer that occurs when abnormal blood cells take place in the bone marrow.Leukemia can either be acute (fastly growing) or chronic (slowly growing) and it is considered as one of the most commonly diagnosed cancers for children younger than the age of 15 or adults older than the age of 55.Leukemia can be diagnosed through various types of tests and depending on the aggressiveness of the disease, the treatment may differ.To provide a low-cost, timeefficient solution, this study employs the deep learning technique to train the Xception, VGG16, VGG19, and MobileNet models to optimize the accuracy of medical image detection.Through medical imaging, the trained model is able to detect anomalies in the dataset and identify whether the given data is a benign acute lymphoblastic leukemia (ALL) or a Pro-B ALL.Overall, this VGG16 showed the most optimal performance in terms of accuracy and precision, producing a 98.5% accuracy in detecting abnormal regions from the dataset.This study also further used XAI technique and a deep convolutional neural network to visualize the results of anomalies.As a result, this paper concluded that both deep learning and machine learning techniques are yet to replace human resources and intelligence as the heatmap and the LIME portrayal identified different regions as abnormal parts, therefore proving the inconsistency of deep learning technology.
An approach to the genesis of Mahoor copper deposit, southwest of Nehbandan, based on mineralogy, fluid inclusions and sulfur isotopes studies

An approach to the genesis of Mahoor copper deposit, southwest of Nehbandan, based on mineralogy, fluid inclusions and sulfur isotopes studies
A Decentralized, Secure, Peer-to-Peer Multi-Voting System on Ethereum Blockchain

Abstract: A decentralised, Secure, Peer-to-Peer Multi-Voting System on Ethereum Blockchain is a distributed ledger technology (DLT) that permits virtual votes to be transacted in a peer-to-peer decentralized network. Those transactions are validated and registered through every node of the network, so creating a transparent and immutable series of registered events whose truthfulness is supplied through a consensus protocol. Smart contract automates the execution of agreement that runs routinely as soon as the conditions are satisfied. Smart contract would not need any third parties consequently prevents time loss. By Eliminating the requirement for third parties, consequently, allows numerous processes to be extra efficient and economical. The system is secure, reliable, and anonymous. Smart contract is enforced for the Ethereum network using the Ethereum wallets and also the Solidity language. Users are capable of submit their votes immediately from their Ethereum wallets, and those transaction requests is handled with the consensus of each single Ethereum node. This creates a transparent environment for evoting. A lot of concerning efficiency of the peer-to-peer decentralized electoral system on Ethereum network along with application and the outcomes of implementation are provided in this paper. Keywords: Blockchain, Distributed Ledger Technology (DLT), Consensus Protocol, Smart Contracts, Ethereum, Solidity
SYSTEMITY AND SITUATIONALITY vs TRANSFORMATION OF RUSSIAN EDUCATION

Modern Russian (and worldwide) education is hostage to the controversial situation associated with the pandemic of the new coronavirus infection COVID-19, which invariably entails a reorientation of traditional methods of education. At present, higher education and the entire world education system are painfully looking for new ways and guidelines for their development. Education paradigms that were formed in the preceding historical time and effectively served the needs of this time are not relevant in the conditions of modern sociocultural realities, therefore the problem of teaching is faced with the need to develop new paradigms of one's own existence. Distance learning technologies challenge us to keep up with the times, be progressive and increasingly use high-tech products. At the same time, there is a danger that the world is becoming increasingly virtualized. The “sense of the edge” disappears, the world is mythologized. The article analyzes the existing systemity of Russian education and the need for its transformation in the light of new realities.
FERPA and disclosures of COVID‐19 data on campus: A case study

The COVID‐19 pandemic has created major compliance challenges for institutions of higher education, including in the area of student privacy. At various times during the pandemic, postsecondary institutions have been panned for their lack of transparency over COVID‐19 infection rates on campus. For example, there were reports in August 2020 that the University of Alabama instructed faculty members to keep quiet about students who tested positive for COVID‐19. That same month, the University of North Carolina was criticized for refusing to reveal rates of campus infection to its student newspaper.
TEACHING READING COMPREHENSION THROUGH DIRECT METHOD TO THE EIGHTH GRADE STUDENTS OF THE STATE JUNIOR HIGH SCHOOL 44 OF PALEMBANG

The objective of this research was to find out whether it is effective to teach reading comprehension through the direct method to the eighth-grade students. This is a quasi-experimental study. The population of this study was eighth-grade students of the State Junior High School 44 of Palembang. In collecting the data, the researcher gave the test. The result of the research, it found that the students’ score in experimental group and control group were 4.46,2 which value of t-obtained was higher than t-table. In other words, teaching reading comprehension through the direct method was effective.
Pedagogical uses of the media, approach to a transmedia education

Authors such as Robinson (2010) make one of the problems of traditional education evident by pointing out that while students’ attention decreases due to boredom, other media obtain it as a result. On the other hand, according to Jenkins (2006a), good transmedia franchises attract a large audience by presenting content in different ways through different media. To this extent, this article has as a starting point to ask about the possibilities that the convergence between education and transmedia narratives brings with it, with the aim of analyzing the relationships between these two fields. The postulates of Robinson (2009, 2010), Scolari (2009, 2011, 2013) and Jenkins (2006, 2009, 2016) on education, school boredom, transmedia narrative and participatory culture are taken as central axes. For this, three cases that account for these links were studied, these are: LobiAventura, Guardianes y Desarmados; All three are born in Colombia and are aimed at primary and secondary students, belonging to different age groups. The research includes an analysis of the relationships between case studies, participatory culture, and school boredom. The analysis could indicate that the format allows to reach experientially areas that traditional education does not usually cover. In addition, the transmedia strategy could be presented as something innovative, different and interesting to students trapped by the traditional educational model, since it could cooperate in the face of school boredom.
Paper Based Test Versus Computer Based Test: The Impact on Reading Performance

The main aim of this study is to investigate the possible difference in reading comprehension performance through PBT and CBT of Pakistani second-year ESL learners at NED University of Engineering & Technology (NEDUET). For this purpose, n=62 subjects attempted three equivalent tests on each testing mode. For the analysis, paired sample t-test is used to juxtapose the means of test results gleaned from PBT and CBT. The results illustrate, examinees performed significantly better on CBT (M = 6.17) as compare to PBT (M = 5.69) at p .05 (note: p = .621) because mostly opted for PBT. Additionally, their perceptions about the pros and cons of both the testing modes are also discussed.
IMPLEMENTASI DATA MINING UNTUK MENGKLASIFIKASIKAN PRODUK PADA SEBUAH SUPERMARKET MENGUNAKAN ALGORITMA ID3 PADA ORANGE

Technological developments are increasingly increasing or developing very rapidly. The development of technology has also affected the increasing needs of the community, so supermarkets and retailers are competing to provide various types of products or daily needs. However, in every collection or supermarket, it is necessary to know what types of products are needed by customers who will later become targets. To help shops and supermarkets, the authors will conduct an analysis to find out the types of products that customers like by implementing data mining in supermarket classification using the ID3 algorithm
How Do We Develop Modern Pre-School Education in Size 4K

Abstract: Model 4Khas benefits which can help us to identify and differentiate it. Not only has it got advantages which can develop child' brain, but also it helps to adapt a child to the kindergarten and school. Child development theories fоcus on explaining how children change and grow over the course of childhood. Such theories center on various aspects of development including social, emotional, and cognitive growth. We help people find answers, solve problems and get inspired. Parents often focus on what are known as developmental milestones, which represent abilities that most children tend to display by a certain point in development. These typically focus on one of four different areas: physical, cognitive, social / emotional, and communication. Keywords: adaptation, nursery, kindergarten, child, teaching, training, modern, level, goal, communication.
Petrographic and Geochemical Studies of the Host Rock of the Chaghoo Copper Orebody in the Southwest of Karaj

The study area is located 5 km southwest of Mahdasht city in Karaj on the Urmia-Dokhtar magmatic arc. In this area, Eocene volcanic and pyroclastic rocks are observed including basaltic andesite lavas, andesite, Trachyandesiticand trachyte lavas, tuff, and ignimbrite, along with plutonic rocks. There are two spectra of basic and acidic for the rocks in the area, of which basic rocks are chemically calc-alkaline in nature.Among the signs of subduction rocks in the area are enrichment in the Ta, Nb, and Ti lavas, as well as the anomaly of the HFSE index relative to the LILE of incompatible elements content. The geochemical and petrogenetic studies indicate the origin of the area’s plutonic rocks and the role of differential crystallization accompanied by the crustal rocks-contamination and digestion of magma in the evolution of the magma forming these rocks. This magma has been originated from the low-grade partial melting of an enriched mantle origin beneath the continental lithosphere with the lherzolite garnet composition at a depth of 100 to 110 km in a post-collision tensile environment. Investigating the fluids involved in the region, the homogenization temperature with the temperature of copper veins formation is between 120 to 306 ° C, with the salinity percentage varying between 6.45 to 15.96% of sodium chloride weight. Accordingly, this metamorphic hydrothermal orebodyis located in the mesothermal category. The presence of sub-faults, joints, and cracks in the host rock has provided a low-pressure environment for a proper place for copper mineralizationas veins.
Impact of Knowledge Economy on Economic Growth in Rwanda: An Empirical Study during the Period (2000-2019)

Impact of Knowledge Economy on Economic Growth in Rwanda: An Empirical Study during the Period (2000-2019)Abstract: Purpose- This study aims to analyze the effect of the knowledge economy on economic growth in Rwanda, using time series data over 2000-2019.Design/methodology/approach - We used the Auto Regressive Distributed-Lagged (ARDL) bound testing approach to estimate the relationship between knowledge economy and economic growth in Rwanda in the short and long run.Findings- The results show that Knowledge-Economy indicators have a significant long-run relationship with the economic growth in Rwanda.Originality/value – Actions for increasing spending on research and development with the expansion of databases and information centers within government agencies are very essential for Rwanda to increase the economic growth and competitiveness in the global markets.Keywords: ARDL model; Economic Growth ;Knowledge Economy; Rwanda; Paper type: Research paperIntroduction: The world is living through the fourth industrial revolution, which is sometimes known as the information revolution. Along with other factors of production, information is the cornerstone of the production process. A knowledge economy can produce, transmit, and apply knowledge, which is the primary factor in growth, wealth creation, and employment in various developmental sectors
Voice biometrics: privacy in paralinguistic and extralinguistic tasks for health applications

Chapter Contents: 4.1 Introduction 4.2 Paralinguistic and extralinguistic tasks 4.2.1 Speech-affecting diseases 4.2.2 Methods 4.3 Cryptographic primitives and MPC for PPML 4.3.1 Homomorphic encryption 4.3.2 Oblivious transfer 4.3.3 Secure Multiparty Computation 4.3.3.1 Yaos GCs protocol 4.3.3.2 Secret sharing 4.3.3.3 Security models 4.3.4 Distance-preserving hashing techniques 4.4 PPML for paralinguistic and extralinguistic tasks 4.4.1 PPML for non-health-related tasks 4.4.2 PPML for health-related tasks 4.4.3 Private SVM+RBF for health-related tasks 4.4.3.1 Private RBF computation 4.4.3.2 Private SVM computation 4.4.3.3 Experimental setup 4.4.3.4 Model training and parameters 4.4.3.5 Private SVM implementation details 4.4.3.6 Classification results 4.4.3.7 Security and computational performance 4.5 Conclusions Acknowledgments References
Development of Adventure Multimedia Game Based on Mobile Learning in Pyramid Topic for Junior High School

Mathematics is a difficult subject for students, causing low motivation, interest and student learning outcomes. To attract students to be more interested in learning mathematics, they must use interactive learning media so that learning is not boring and fun. This study aims to develop a multimedia adventure game in pyramid topic based on mobile learning in grade eight. This study uses the 4-D development model, however, at the stage of dissemination only limited distribution is carried out. The subjects in this study were grade eight students of one of junior school in Gorontalo District, Gorontalo Province, Indonesia. The results of the study based on the validation of topic and media experts showed that the quality of multimedia was good. Meanwhile, based on the teacher's ability for managerial to learn is also categorized as good, the activities of students during the learning process reach the ideal time criteria, the responses of all students are classified as very positive of 90.56% and learning tests show that 72.5% of students achieve completeness. This shows that the adventure multimedia game based on mobile learning in pyramid topic is valid, practise, and effective.
A Mini-review of Face Alignment - Classical Method versus Deep Learning Approach

Face alignment is one of the vital research areas to be explored specifically face tasks like face recognition, face verification, face reconstruction, and facial expression analysis.Hence, the need for robust face alignment is still in demand.Numerous classic methods have used the 2D image for the detection of facial landmarks but this task is challenging due to several reasons, for instance, large poses, semi-frontal images, and facial expression.Abundant techniques have been established to mitigate all these challenges but there are far from being solved.Hence this mini-review discussed the face alignment methods based on the classic method to the state-of-the-art that includes the 2D-face alignment along with the 3D-face alignment approach.Based on the review done, the 3D model could combat large poses, facial expressions, and semi-frontal images however some of the facial landmarks are not visible and stack together for occluded face images.Hence, this will be the research area to be explored further in ensuring robustness and better accuracy in the face alignment area.
Pengembangan Media Pembelajaran Berbasis Flash pada Materi Bilangan untuk Anak Tunarungu Kelas V

This study aims to develop flash-based learning media for whole numbers and fractions for deaf children of class V that are valid, practical, and effective in training students to be skilled in solving whole number and fraction problems. The learning media is equipped with a video using SIBI (Indonesian Sign Language System) to make it easier for deaf students to understand the content of the media. This research using 6 stages referring to the Luther-Sutopo development model, namely: concept, design, material, collection, assembly, testing, and distribution. The instruments in this development research were the media validation sheet and the student response questionnaire sheet. The results of the development research are: (1) there are no misconceptions and all media functions can run well and the media validation score is 4.63 so that the media developed is valid, (2) the student response questionnaire is declared valid with a score of 4.73 so that it can be used in the study, (3) the media practicality score after being tested was 4.74 so that the media was declared practical, (4) 75% of students obtained a KKM score, this shows that students are skilled in solving whole number and fraction problems, so the media is said to be effective.