Reviewerly/exHarmony huggingface dataset:
Crypto Currency Price Prediction with Machine Learning Using Python

We use and study a wide range of machine learning methods to predict and trade in the daily crypto currency market. We teach the algorithms to make daily market predictions based on how the 100 cryptocurrencies with the most market value change in price. Based on our research, all of the used models are able to make estimates that are statistically sound, with the average accuracy of all crypto currencies falling between 52.9% and 54.1%. When these accurate numbers are based on the 10% most confident expectations for each class and day, they go up to somewhere between 57.5% and 59.5%. A well-known case study in the field of data science looks at how people try to figure out how much different digital currencies are worth. Stock prices and the prices of cryptocurrencies are based on more than just the amount of buy and sell orders. At the moment, the government's financial policies about digital currencies affect how the prices of these things change. People's views about a crypto currency or a star who directly or indirectly backs a crypto currency can also cause a big rise in buying and selling of that currency. This study looks at the trustworthiness of the three most famous coins on the market today: bitcoin, how well buying strategies for ethereum and litecoin that are based on machine learning work. The models are checked and tested with both good and bad market situations. This lets us figure out how accurate the forecasts are in light of any changes in how the market feels between the proof and test times.
Enhancing Pupils' Narrative Text Reading Comprehension in Mother Tongue through Directed Reading Thinking Activity

The study aimed to determine the effectiveness of the directed reading thinking activity strategy as a reading intervention strategy to enhance the reading performance of Grade 2 pupils. It utilized the one-group pretest-post-test design. The researcher employed the Early Grade Reading Assessment Tool (Pretest and Post-test) to identify whether the intervention strategy used was effective. There were 55 participants in the study who were given reading intervention. The researchers conducted the reading intervention for the pupils during their MTB-MLE class for three days every week. The results showed that there was an increase in the reading performance of the pupils after conducting the reading intervention. It was also revealed that in the study there were significant differences in the t-test result in all reading components. This further highlighted that the reading intervention which is a directed reading thinking activity strategy was effective. Thus, it is recommended that a reading intervention program that highlights the use of a directed reading thinking activity strategy will be used by teachers to improve the reading performance of their pupils.
Anomaly Detection of Liquid Level in Mold during Continuous Casting by Using Forecasting and Error Generation

Anomaly detection of liquid levels in molds is an important task in continuous casting. Data that consists of a series of liquid levels in mold during a continuous casting process can be viewed as a time series, on which Time Series Anomaly Detection (TSAD) methods can be applied. However, the abnormal and normal data in the liquid data in the mold sequence share similar features. And due to manual control limitations, the anomaly sequence in liquid level in mold data lasts longer. Therefore, using existing TSAD methods based on AutoEncoders (AEs) often results in high false positive rates. In this paper, a novel framework is proposed for anomaly detection of liquid level in mold by using unsupervised deep-learning-based TSAD. The framework decomposes a time series into normal and error sequences. A forecasting network reconstructs the normal sequence to solve the first issue, which allows the proposed method to consider the context. An error extraction network generates errors from the original sequence to solve the second issue. It removes anomalies from the original sequence during training to prevent anomaly pollution and allows the forecasting network’s training to be free from anomaly pollution. A new dynamic threshold method is proposed to identify anomalies. The proposed method is evaluated on the actual casting dataset by comparing it with baseline methods. The experiment results indicate that the proposed framework outperforms some of the best anomaly detection methods in terms of accuracy, precision, and F1 score.
Fuzzy Cognitive Map-Based Analysis for Optimizing Watermelon Production Management

This study presents an in-depth investigation of watermelon cultivation in Bangladesh, focusing on the assessment of production levels, costs, influential factors, and the application of Fuzzy Cognitive Map (FCM) technology for precision agriculture.Utilizing degree centrality and closeness centrality measures, the FCM model is employed to systematically examine the interplay among various elements involved in watermelon cultivation in Bangladesh and to elucidate the impacts of these factors on production yield.The findings contribute to the advancement of precision agriculture practices and provide valuable insights for optimizing watermelon production management in Bangladesh.
Encryption and Decryption of Images with Pixel Data Modification Using Hand Gesture Passcodes

To ensure data security and safeguard sensitive information in society, image encryption and decryption as well as pixel data modifications, are essential. To avoid misuse and preserve trust in our digital environment, it is crucial to use these technologies responsibly and ethically. So, to overcome some of the issues, the authors designed a way to modify pixel data that would hold the hidden information. The objective of this work is to change the pixel values in a way that can be used to store information about black and white image pixel data. Prior to encryption and decryption, by using Python we were able to construct a passcode with hand gestures in the air, then encrypt it without any data loss. It concentrates on keeping track of simply two pixel values. Thus, pixel values are slightly changed to ensure the masked image is not misleading. Considering that the RGB values are at their border values of 254, 255 the test cases of masking overcome issues with the corner values susceptibility.
A Romanian economic, financial and commercial glossary, as a reflection of the dynamic relationship with the Italian language: between identity and diversity

A Romanian economic, financial and commercial glossary, as a reflection of the dynamic relationship with the Italian language: between identity and diversity) This contribution is presented as a continuation and exemplification of the ideas expressed in the work Tracce e influenze italiane nella terminologia economico-finanziaria e commerciale romena.Percorsi storico-linguistici tra memoria e oblio (Quaestionaes Romanicae IX), proposing a corpus-based Romanian economic, financial and commercial glossary in order to illustrate the dynamic relationship between the Romanian and Italian language, as well as between diversity and identity.This linguistic tool also offers us the possibility to follow which Romanian terms can be identified in the Italian unique etymology and which, on the other hand, are related to the problem of "multiple etymology" in the lexicographical works consulted.Furthermore, the glossary indicates the first attestations of these terms not only in Italian and Romanian, but also in French and German, referring to valuable lexicographical works and thus also allowing a historical-linguistic comparison of the lemmas taken into consideration in the languages mentioned.
“Posando sus grandes y pesados pies”: the Translation of Verbo-Nominal Structures from Spanish into Romanian

Posando sus grandes y pesados pies": the Translation of Verbo-Nominal Structures from Spanish into Romanian)The present research aims to analyze tendencies in the translation of structures such as [V + NP/SC (direct or indirect object)] from Spanish into Romanian based on a corpus of literary translations made by students.An example of such structure would be aruncîndu-și pașii mari și greoi, proposed as a Romanian translation of posando sus grandes y pesados pies.In this case, a change of meaning at verb level and a modulation at the level of the direct object lead to the semantically anomalous Romanian version a-și arunca pașii (lit.'to cast or throw one's steps').The study aims at identifying and describing such deviant structures in order to establish a scale of dominance in the (in)proper use of translation procedures (Vinay & Darbelnet 1958;Catford 1965) under the light of similarities and differences between the two Romance languages.
Utilization of Multimedia Facilities and Internet Media as Effective Learning Tools

Utilization of multimedia facilities and internet media in the learning process has a significant advantage. Learning that uses multimedia technology and internet media can increase student effectiveness, creativity, and motivation. Although, this requires management and presentation of material according to the needs and characteristics of students. This study aims to determine the use of multimedia and internet media as effective learning tools. In writing this article, the researcher uses a qualitative method of literature study, namely searching for documents, articles, and previous research to examine references and research results related to the use of multimedia and internet technology in learning. The results of the study show that multimedia and internet technology can be effective learning tools with more interactive and interesting learning experiences. This increases students' motivation and interest in learning, thereby helping to create a more creative and innovative learning environment. In conclusion, the use of multimedia and internet technology in learning can improve the quality of learning and provide a more positive learning experience for students. Therefore, it is necessary to pay more attention to the management and presentation of appropriate material so that multimedia and internet technology can become effective learning tools
Decision Support System For The Determination Of Field Work Practice Results In Students Using The Moora Method (Case Study : Pt. Telekomunikasi Binjai)

PT. Telekomunikasi Indonesia Binjai Branch is an information and communication company as well as a complete telecommunications service and network provider in Indonesia. Acceptance of students to carry out Field Work Practices (PKL) is one of the important goals for companies to introduce the world of telecommunications in Binjai City. Street vendors are student activities directly in professional work activities at an institution, company or institution within a certain period of time in accordance with the curriculum. And to overcome these problems we need a method that can predict the number of new installations. After carrying out the Field Work Practice (PKL) in the company, students are entitled to get the results of the activities that have been carried out during the PKL. The number of students who carry out PKL in the company makes it difficult for office employees to provide PKL results from each of the existing students. Based on the results of research that has been done at PT. Telekomunikasi Indonesia Binjai Branch, the process of assigning value to the results of street vendors activities is done manually. In this study a Decision Support System (DSS) will be built using the Multi-Objective Optimization On The Basis Of Ratio Analysis (MOORA) method which is a method that has a calculation with a minimum and very simple calculation. The system is designed with the PHP programming language and MySQL database, after processing the 15 inputted data, it is found that A15 (Wiratana Sanjaya) is in the first rank. With these results it was also concluded that A15 became a student with the best Field Work Practice results at PT. Telekomunikasi Indonesia Binjai Branch.&#x0D;
Expert System Diagnosing Damage to Canon Ir5000 Copier With Forward Chaining Method

A photocopy machine is a machine that works mechanically to fulfill the function of copying one document on a machine into another paper in black-and-white copies. During the copying process, various defects often occur, so a technician is needed to repair it. While waiting for the arrival of a technician to repair a damaged machine, it takes some time. Therefore, we need a strategy that can quickly find out the type of photocopier damage and how to handle it to help repair the damage to the photocopier. with the transfer of expertise by experts to be transferred again to other people who are not yet experts is the main goal of the system. In the process of drawing conclusions the system uses the Forward Chaining algorithm where the system will display symptoms of photocopy machine damage to be selected by the user, which can finally determine the solution to the damage to the machine. The results obtained from making this application are easier to obtain by making an expert system to diagnose photocopier damage and can be used and studied easily by the general public. for handling the problem of damage to the Canon IR 5000 photocopier using the Sublime Text Application as supporting software in terms of designing the layout of the application design, using the MySQL Database as a database design place and XAMPP v3.2.1 to run the database server and php.
Application Of Sugeno Fuzzy Logic In The Determination Of Employee Incentives

Suzuya superstore is one of the marketers of human needs products that have various types of products. Suzuya already has several branches in Indonesia which are located in North Sumatra, Aceh, West Sumatra, and Riau. Suzuya was founded in 1983 and currently suzuya already has more than 22 outlets, one of which is in Pematangsiantar. Suzuya superstore Pematangsiantar has employees who are divided into several teams, one of which is the cashier team. The cashier team is the spearhead of the sale of focus items, where the focus item is the flagship product of suzuya superstore Pematangsiantar. The cashier team is also responsible for the sales transaction service process at suzuya superstore Pematangsiantar. The existence of incentives can motivate the work spirit of the cashier team in increasing sales, work speed, and good transaction processing service attitude at suzuya superstore Pematangsiantar. In determining the feasibility of the cashier team receiving incentives at suzuya superstore Pematangsiantar, three variables were used, namely sales of focus items, assessment of work attitudes, and assessment of work speed. Based on the results of processing the cashier team's data using the fuzzy logic algorithm, the Sugeno method, manually and using Matlab software, there was no significant difference. So that Fuzzy Logic with the Sugeno method can be used to determine employee incentives at suzuya superstore Pematangsiantar
Pengaruh Pengeluaran Pemerintah Bidang Pendidikan, Pertumbuhan Ekonomi Dan Kemiskinan Terhadap APM (Angka Partisipasi Murni) di Indonesia

This study aims to determine the effect of government spending on education, per capita income and poverty on net enrollment rates in Indonesia. This research is descriptive and associative. The data used is secondary data from 33 provinces in Indonesia in 2014-2021 obtained from related agencies. This study uses panel data regression with the Random Effects Model approach assisted by Eviews 9 software. The variables used are high school enrollment rates (Y), government spending on education (X1), per capita income (X2), poverty (X3). The results of the study show that (1) government spending on education has a positive and significant effect on net enrollment rates at the high school level in Indonesia (2) per capita income has a positive and significant effect on net enrollment rates at the high school level in Indonesia (3) Poverty as a measure of the percentage of poor people has a negative and significant effect on net enrollment rates for secondary schools in Indonesia
Human Development Clustering in Indonesia: Using K-Means Method and Based on Human Development Index Categories

The quality of life for Indonesia's population can be measured from the human development index in each province. People who have a good quality of life indicate a prosperous life. The government has the responsibility to advance the welfare of the nation under the mandate of the constitution. The clustering of the human development index (HDI) in Indonesia is used to determine the distribution of quality of life or the distribution of social welfare. In this study, the K-Means method, which is a popular non-hierarchical clustering method, is used to classify human development in each province based on HDI indicators, namely Expected Years of Schooling, Mean Years of Schooling, Adjusted Per Capita Expenditure, and Life Expectancy at Birth. Provinces in Indonesia are clustered into 4 clusters. These results were also compared with the clustering based on HDI categories determined by Statistics Indonesia based on certain cut-off values. According to the HDI category, provinces in Indonesia fall into the medium, high, and very high categories. The results of the two groupings show that there is a trend toward appropriate characteristics for each group. Thus, K-Means can classify provinces in Indonesia according to the characteristics of the HDI indicators.
THE USE OF VIRTUAL LEARNING SPACES AND ITS RELATIONSHIP WITH THE LEARNING OF ALGEBRA IN HIGHER EDUCATION

The research studied the relationship between the use of Virtual Learning Spaces (EVA) and the level of learning achieved in the subject of algebra by students at the University of the Armed Forces - ESPE, Latacunga extension. For this purpose, we worked with an intentional sample of students and teachers. The research was quasi-experimental with a mixed approach. To carry out the research, two groups were established: an experimental group, which used the EVA designed in the MOODLE platform; and a control group, which did not receive the stimulus. To establish the learning levels of the students, the grades of the first algebra partial (pre-test) were obtained; and the teachers were interviewed to determine the way they work and their position on the use of an EVA for the teaching-learning of algebra. To establish the relationship between the variables, an EVA designed for the learning of inequalities and functions was applied during the second partial period; once the application period was over, the grades of the second partial period were obtained (post-test); in addition, a satisfaction survey on the use of the EVA was applied to the students of the experimental group. Finally, frequency tables were used for data analysis; and a qualitative analysis of the interview with the teachers and of the satisfaction survey applied to the students of the experimental group on the use of the EVA was carried out. In the quantitative analysis, the tabulation of grades obtained by the students in the two mid-term exams was made; and from these data, using Fisher's ratio (F), the fulfillment of the hypothesis that determines that the use of the EVA improves the learning of algebra, a dimension measured with the academic performance of the students, was verified.
Research on the Influence of International Cooperation of ESI Highly Cited Papers Based on CNCI

ESI highly cited papers represent the top level of global scientific research papers, and their influence also represents the scientific research strength of institutions.Taking the highly cited papers of Northwest Polytechnical University in May 2022 as an example, this paper analyzes the distribution of countries, institutions and disciplines of international cooperation papers in highly cited papers of ESI based on the CNCI index, explores the forms and characteristics of international cooperation in highly influential papers, and provides reference for establishing high-quality research partnership.
The Influence Of The Use Of Geo-Augmented Reality On Student Learning Outcomes And Activities In Cartography Courses In The Geography Education Study Program, Faculty Of Social Sciences, Padang State University

This study aims to analyze the influence of the use of Geo-Augmented Reality on student learning outcomes and activities in the cartography course in the Geography Education Study Program. FIS UNP. The research method used is a quasi-experiment with a quantitative approach. The population in this st
Development of Multiple Intelligence Based Interactive Ebook to Improve Critical Thinking Ability and Cognitive Learning Outcomes on an Excretory System

This research aims to produce a feasible interactive ebook based on multiple intelligence for 11th-grade students of Senior high school, determine the effectiveness of an interactive ebook based on multiple intelligence on excretion system to improve the critical thinking ability of 11th-grade students of Senior High School, determine the effectiveness of interactive ebook based multiple intelligence on excretion system to improve cognitive learning outcomes of 11th-grade students of Senior High School. The multiple intelligence-based interactive ebooks are designed by Flip PDF Corporate application with html5 output converted to the android application by web2apk. The method used for this development was research and development (R&amp;D) with the 4D (Define, Design, Develop and Disseminate) research model. The sampling method for the study was conducted random sampling. Method using one experiment class and one control class. This research in SMA Negeri 1 Ngemplak. Data Collection Techniques were using interviews, visionary, pre-test, and post-test. Ebook validation was carried out by material and media validators. The data analysis technique used a quasi-experimental non-equivalent control group design with the multivariate test by IBM SPSS 24. The ebook has validation and got 92,6% from the biology teacher, that is mean the ebook is valid and possible to use in biology learning. The Effect size shows 0.290 for critical thinking and 0.159 for cognitive learning outcomes, which means ebook has a high effect on both abilities
Diversifying Emotional Dialogue Generation via Selective Adversarial Training

Emotional perception and expression are very important for building intelligent conversational systems that are human-like and attractive. Although deep neural approaches have made great progress in the field of conversation generation, there is still a lot of room for research on how to guide systems in generating responses with appropriate emotions. Meanwhile, the problem of systems’ tendency to generate high-frequency universal responses remains largely unsolved. To solve this problem, we propose a method to generate diverse emotional responses through selective perturbation. Our model includes a selective word perturbation module and a global emotion control module. The former is used to introduce disturbance factors into the generated responses and enhance their expression diversity. The latter maintains the coherence of the response by limiting the emotional distribution of the response and preventing excessive deviation of emotion and meaning. Experiments are designed on two datasets, and corresponding results show that our model outperforms existing baselines in terms of emotional expression and response diversity.