Reviewerly/exHarmony huggingface dataset:
Cultural Studies Of Education: Innovation Of A Competence Approach Or Pedagogical Models

The authors focused on resolving the contradictions between European trends, existing in the global educational space, and the need to preserve the originality of Russian pedagogy and culture. They realized the need to improve competitiveness, expand opportunities for professional self-realization, actualizing the importance of professional and cultural competence of university students, and insufficient elaboration of the theoretical foundations and practical mechanisms of its formation. Human perception of culture is a product of how much a person can identify himself, identify one’s belonging to it, correlate with the cultural norms and values that have formed in him. The discussion field that arose at the junction of philosophy, culturology and pedagogy on the issue of the relationship between education and culture led to a new scientific direction – culturology of education. Its uniqueness lies in the fact that it is education, the center of which is a person who cognizes and creates culture through dialogical communication, exchange of meanings, creation of works of individual and collective creativity. The authors pointed out that such education supports the individuality, uniqueness of each child's personality, relying on its ability to self-change and cultural self-development”. The development of those abilities of the individual that are needed by himself and society, his inclusion in social activity, providing opportunities for effective self-education outside the institutionalized educational systems.
Study on the Performance of Image Color Style considering Brushstroke Control Factors

To address the issues of high time consumption, low recall rate of image color styles, and poor image color processing outcomes in existing methods, we proposed an image color style performance analysis method that takes brushstroke control elements into account. We investigate the connection between brushstroke control parameters and picture color style performance. Furthermore, assuming that the brushstroke components are completely considered, we evaluate the image’s color composition to derive the R, G, and B values and apply the cloning process to prejudge the image’s color style. Based on the color style prejudgment, the median segmentation method for color quantization is used to increase the efficiency of image color style extraction, and the cumulative histogram is used to categorize the image color style. The experimental findings reveal that the suggested technique has low time complexity, good picture color accuracy, and recall and does not generate uneven image color brightness.
Macro Skills in English of Grade 11 Senior High School in Balayan, Batangas: A Guided Learning Activities

English instruction should not be limited to the four corners of the classroom only it may be held inside and outside the campus, where maximum learning takes place. Students must be exposed to a lot of activities which will allow them to experience by themselves and understand the concepts that they need to learn especially in improving their macro skills. This study was a descriptive method research which was conducted to determine the way of improving the macro skills to increase the English performance of students. The following are the results of the study: Many of the respondents utilize in this study belong to 15 and 16 age range and equal number of male and female, belonged to 5000 and below family income and have 75 to 79 grade in English in the first grading. The respondents agree that the development of macro skills in their English performance. The respondents agree on the challenges they experienced on developing macro skills increase their English performance. There is no significant difference on developing macro skills in their English performance when profile is considered, however there was a significant difference in term of family background and grade in English in the first grading. There is no significant difference in the challenges on developing macro skills in their English performance when profile is considered, however there is a significant difference in grade in English in the first grading. There is a significant relationship on developing macro skills in their English performance and the challenges experienced by the respondents. The guided learning activities are made by the researcher to develop more the macro skills of the students.
Credit Card Fraud Detection System

Abstract: Credit Cards are quite useful for day to day life. The main aim of this project is to detect fraud accurately. With the increase in fraud rates, researchers have started using different machine learning methods to detect and analyze frauds in online transactions. 'Fraud' in credit card transactions is unauthorized and unwanted usage of an account by someone other than the owner of that account. Fraud detection involves monitoring the activities of users in whole in order to estimate, perceive or avoid objectionable behavior, which consist of fraud, intrusion, and defaulting. The problem itself is more challenging with respect to data science since the number of valid transactions far outnumber fraudulent ones. Also, the transaction patterns often change their statistical properties over the course of time. However, the massive stream of payment requests is quickly scanned by automatic tools that determine which transactions to authorize. Also, Messages are generated to confirm with the owner about the transactions. Machine learning algorithms are employed to analyze all the authorized transactions and report the suspicious ones. These reports are investigated by professionals who contact the cardholders to confirm if the transaction was genuine or fraudulent. This project also designs and develops a novel fraud detection method for Streaming Transaction Data, with an objective, to analyze the past transaction details of the customers and extract the behavioral patterns. To name a few techniques which we are going to implement are Isolation Forest Algorithm, Random Forest Algorithm, Logistic Regression, Confusion Matrix and Sliding-Window method. Keywords: Credit card fraud, isolation forest, local outlier factor, random forest, confusion matrix
Software Security for the People: Free and Open Resources for Software Security Training

The enormous growth in software development affects every facet of our lives, creating urgent need for training in software security. In response, we have developed free and open software security education and training materials from the student to experienced professional.
Investigation of Different Deep Neural Networks for the Diagnostics of Brain Tumor, Skin Cancer and Breast Cancer

Abstract: Early disease detection cannot be neglected in the healthcare domain and especially in the diseases where risk is associated with a life of a person. As per the WHO, if diseases can be predicted ahead of time, death rates can be reduced. The paper's goal is to investigate how to detect Breast Cancer, Skin Cancer, and Brain Tumor at the early stages with the help of Deep Learning techniques. The authors of different papers have used different techniques and Algorithms like Convolutional Neural Network (CNN) algorithms, Visual Geometry Group (VGG16) and Residual Network (ResNet). We tried to investigate these three algorithms and compared them to find out the most efficient amongst them for each disease. Keywords: Breast Cancer, Skin Cancer, Brain Tumor, Deep Learning, CNN, VGG and ResNet
Drought Index Determination Using the Batulayar Watershed Hydrology Model

The Batulayar sub-watershed, also known as the Bongomeme sub-watershed, is one of the most important sub-watersheds in the Limboto watershed. Because there are oil palm and other plants in the Batulayar Sub-upstream watershed's area that cause drought and natural harm. The goal of this study was to assess the severity of the drought and develop a hydrological model for calculating the drought index in the Batulayar sub-upstream watershed's area. The mix approach was utilized, which combines Soil and Water Assessment Tool (SWAT) modeling with field survey methodologies. The study's findings suggest that land conversion in the Batulayar Sub-upstream watershed's area may have an impact on the watershed's function. The Batulayar Sub-SMDI watershed's value in the SWAT Model results shows that it ranges from -0.50 to -2.99 in March, April, May, November, and December over a 10-year period, and is classified as "Slightly Dry" and "Slightly Dry." The Hydrological Model's role in determining the drought index can be seen in the results of calibration and validation using the NSE Model (Nash Sutcliffe Coeficient of Efficiency). An NSE value of 0.9 is obtained in calibration and validation, implying that the NSE value obtained belongs to the "good" class or that the discharge model and research observation discharge are similar.
Javanese Politeness Experience as Depicted in Its Speech Levels of the Transactional Communication

Javanese interactions are bound by politeness speech levels. Ngoko, the lowest form, reflects the interactions between close equals, or persons of higher status towards those of lower status, whereas krama, the highest form, is used to address elders or those of higher status. This study aimed to disclose communication politeness as expressed by Javanese users in the public place. Twelve participants were enlisted, among them seven males and five females. Data were recorded from a smartphone and transcribed orthographically to obtain natural data, while data analysis used the interpretative approach, aiming to identify and code the transcripts. The results showed that five females consistently communicated with the krama speech level when dealing with other parties, whilst one female conveyed her ngoko speech level. On the other hand, one participant out of seven accordingly engaged in the krama speech level, whilst the other six participants consistently employed ngoko. These politeness patterns advocated both the interlocutor and hearer’s genuine interests and behavioral reflections within adaptable consequences, and expressed a sense of intimacy, respectfulness, functionality, and equality using various words, expressions, and meaningful talks that made up the existence of their social status. Females complimented others’ appearances, whereas males focused on predominance to show a sense of familiarity. This study concludes that Javanese politeness levels naturally constitute users’ daily speech habits that govern Javanese diglossia through their contextual adoption, adaptation, and reinterpretation. &lt;w:LsdException Locked="false"
Beyond Classical

The term Beyond Classical is now the preferred term to describe computation that can be run efficiently on a quantum computer but would be intractable to run on a classical computer. A seminal paper by Google claimed to have reached this goal by computing a result in 200 seconds that a supercomputer would need 10,000 years to compute. Soon after publication, IBM claimed that the same computation could be done in just a few days on the Summit supercomputer. In this chapter, we analyze this disagreement. We discuss the proposition, implement and simulate the circuit, estimate simulation time for 53 qubits, and contrast Google’s claim against our implementation and IBM’s estimation result.
A Conceptualization of Online Collaborative English Learning for Undergraduate Students in the New Normal Post Covid-19 Era

Changing the way of learning process during the pandemic have made a point to find an appropriate approach in online leaning. This study aims to analyze language learning process in the first year of the pandemic, where the language needs a practice in the process of learning. In other words, language learning really requires direct interaction, this condition is added that not all colleges are ready for online learning either through LMS or other online forms which are already familiar by offline interactions. This study uses qualitative descriptive with deeply observations during the classes, and used the diffusion of innovation by Rogers which consists on stages of innovation. The research found the conceptualization of learning through online-collaborative, and using the online collaborative exam between groups has proven the willingness in interactive e-learning language and to be able to improve the competence of language skills, both listening, writing, reading, and speaking which are needed in the language process of university students whose vocabulary and English are still unfamiliar used in the introduction in each course in Indonesia
A Robotic vision system emulating fixational eye movements and retinal sampling

Recent studies on visual physiology have suggested that fixational eye movements contribute to the information processing function of the retina.In this study, we built a robotic vision system that emulates the characteristics of fixational eye movements and retinal sampling as an assistant tool for clarifying information processing through the collaboration of eye movements and neural circuits.The proposed robotic vision system consists of two galvanometers, a field-programmable gate array (FPGA) board, and a high-speed, high-resolution camera.We measured the frequency response of this robotic vision system, and the results showed that the system satisfied the requirements for emulating the frequency characteristics of biological eye movements.In addition, we generated command signals in the FPGA to emulate biological eye movements and confirmed the satisfactory operation of the system.
Authorship Obfuscation System Development based on Long Short-term Memory Algorithm

Stylometry is an authorship analysis technique that uses statistics.Through stylometry, the authorship identity of a document can be analyzed with high accuracy.This poses a threat to the privacy of the author.Meanwhile, there is a stylometry method, namely the elimination of authorship identity, which can provide privacy protection for writers.This study uses the authorship method to eliminate the method applied to the Federalist Paper corpus.Federalist Paper is a well-known corpus that has been extensively studied, especially in authorship identification methods, considering that there are 12 disputed texts in the corpus.One identification method is the use of the support vector machine (SVM) algorithm.Through this algorithm, the author's identity of disputed text can be obtained with 86% accuracy.The authorship identity elimination method can change the writing style while maintaining its meaning.Long-short-term memory (LSTM) is a deep learning-based algorithm that can predict words well.Through a model formed from the LSTM algorithm, the writing style of the disputed documents in the Federalist Paper can be changed.As a result, 4 out of 12 disputed documents can be changed from one author identity to another identity.The similarity level of the changed documents ranges from 40% to 57%, which indicates the meaning preservation from original documents.Our experimental results conclude that the proposed method can eliminate authorship identity well.
Transparency and Accountability in Data Analytics

Transparency, for data analytics, means providing enough information so that others can understand the performance of the program. Here we are going to explore transparency in service of an explanation, for accountability, and for contestability. First, transparency may be in service of explaining the data analytics program. This idea is usually countered with a claim that the program is difficult if not impossible to explain—but we also know that’s not exactly correct. Second, transparency is needed in service of accountability to understand the role of a human to be responsible for the outcomes. This brings us to the third reason we request transparency—to ask questions. And our readings cover the idea of contestability as an ethical design principle. In the readings, Karen Hao explores how humans are inserted in technological systems for accountability and Deirdre K. Mulligan, Daniel Kluttz, and Nitin Kohli offer “contestability” as the ultimate goal of the many discussions around transparency. The related cases included are (1) the case of Houston teachers rated by an algorithm, and (2) a cheating detection program used on students taking tests online.
NATURAL LANGUAGE PROCESSING FOR PLAGIARISM DETECTION – A SURVEY

I.L. Rodriguez Moncada1, V.A. Fernandez Rodriguez2 1Riga Technical University (LATVIA) 2University of Latvia (LATVIA)
Encryption based Watermarking Technique for Security of Medical Image

This paper proposes an encryption-based image watermarking scheme for medical images using a customized quantization of wavelet coefficient and a crypto system based on the chaotic cipher of Singular Value Decomposition (SVD). In order to spread the robustness of our algorithm and provide extra security, an improved SVD-CHAOS embedding and extraction procedure has been used to scramble the watermark logo in the preprocessing step of the proposed method. In the process of watermark embedding, an R-level discrete wavelet transform was applied to the host image. The high frequency wavelet coefficients are selected to carry these scrambled-watermarks by using adaptive quantization low bit modulation (LBM). The proposed image watermarking method endures entirety attacks and rightly extracts the hidden watermark without significant degradation in the image quality, Thus, when the Peak Signal to Noise Ratio (PSNR) and Normalized Correlation (NC) performance of the proposed algorithm is compared with other related techniques.
Optimization of Multi-Layer Perceptron Deep Neural Networks using Genetic Algorithms for Hand Gesture Recognition

Applications of wearable sensors for Hand Gesture Recognition (HGR) have been gaining popularity in recent years.Among the proposed methods, deep neural networks with many hidden layers are promising to address the requirements of this wearable activity recognition.They can directly uncover features tied to the dynamics of HGR, from simple motion encoding in lower layers to more complex motion dynamics in upper layers.However, these methods require many efforts of researches to build an efficient neural network architecture.This study proposes an integrated method that allows finding the best neural networks for HGR using wearable sensors.The proposed method consists of two parts: (i) A generic Multi-Layer Perceptron (MLP) deep neural network and (ii) A genetic algorithm.We applied the genetic algorithm to find the best network architecture in terms of accuracy.At each generation of the algorithm, a new set of architecture was created with different Hyper parameters (the activation, optimizer, the number of layers, neurons and epochs).Extensive experiments were conducted on a dataset containing 18.000 gesture samples from 20 subjects.Experimental results demonstrated the performance and efficiency of the proposed methods in finding deep neural network architectures for HGR.The obtained neural network achieves 89.21% of accuracy and outperforms the previous study on the same dataset.
TEKNIK PENGAMBILAN GAMBAR DALAM PRODUKSI FEATURE BERITA TELEVISI “SETENGAH HATI KURANGI PLASTIK”

Feature included in journalistic products that explain the problem in depth and sharp but with an interesting and mild language style. The television news feature ‘Setengah Hati Kurangi Plastik’ carries the theme of environmental issues that focus on the problem of plastic waste, which is a serious problem in the world including Indonesia. The results of research from researchers from the University of Georgia, United States, Dr. Jenna Jambeck, Indonesia is the second of 192 countries that produce the most plastic waste in the world. While the title 'Half a Heart Reduce Plastic' is a satirical word aimed at people who are still half-hearted in their commitment to reduce the use of plastic. In addition, government regulations are also considered not to be a solution and are still applied unevenly. In making this work, the writer acts as a Camera Person. The shooting technique used is The Developing Shot technique, where this technique is a combination of all the elements contained in the camera, such as lens movement, camera movement, mounting movement.
Earthquake detection in time-series of laser strainmeter measurements as a first step towards automatic signal classification.

&amp;lt;p&amp;gt;Geophysical observatories around the world collect data on various natural phenomena within the Earth and on its surface. Many of these measurements are made automatically, sometimes at high sampling rates, so that enormous amounts of data accumulate over the years. Continuous analysis is important to classify current phenomena and decide which data are important and which can be downsampled later.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;At Moxa Geodynamic Observatory, located in central Germany, several laser strainmeters have been installed in subsurface galleries in order to measure strain of the Earth's crust. These instruments run in north-south, east-west, and northwest-southeast directions. Nano-strain rates are determined with a sampling rate of 0.1 Hz almost continuously over distances of 26 and 38 m, respectively, since summer 2011.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Signals of tectonically induced crustal deformation are superimposed by other signals of greater amplitude, e.g., tides, changes in atmospheric pressure, hydrologic events such as heavy rainfall, and earthquakes. Classification of these events is important to better associate jumps in the temporal vicinity and to distinguish anomalies from instrument failures. To avoid time-consuming pattern recognition by hand, algorithms are required to do most of the work automatically. Due to recent advances in the field of artificial intelligence, it is possible to implement time series algorithms that are capable of unifying and automating many steps of data analysis. Although artificial intelligence applications are increasingly used to support data analysis, their use for time series of geophysical origin so far is not widespread outside of seismology.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In this contribution, an approach to automatically detect earthquakes in the strain data using 1D Convolutional Neural Networks is presented, including the generation of artificial training data with time series data augmentation. Also the training process and generation of new training data, based on classification by hand and false predictions of the trained model is described. The 1D Convolutional Neural Networks are able to identify almost all earthquakes in the strain data and have F1 values &amp;gt; 0.99, showing that their application has the potential to significantly reduce the time required in signal classification of observatory time series data.&amp;lt;/p&amp;gt;
Security Measures to Protect Information Technology Assets

Information systems security is very important to help protect against this type of theft. Organizations are especially vulnerable hence there is need to have appropriate measures to protect the information technology assets. The objectives of this paper include. To review risk mitigation measures and To identify techniques used to safeguard information assets Methods/Statistical analysis: Primary data was used drawn from mobile social users in Nairobi and Mombasa Counties in Kenya.481 respondents, both descriptive and inferential statistics was used to analyze the data. Findings: From the study it was found out that user education is important to safeguard information technology assets the study indicated that 65.6% of the respondents agreed user education can mitigate threats and risks. Further 62.3% who emphasized that authentication of various users is also important to safeguard the information technology assets. The study findings indicated that 73.8% of the respondents acknowledged encryption protects data from unauthorized access recommendations there is need to explore digital forensics security so that to enhance the security of information technology assets