Reviewerly/exHarmony huggingface dataset:
The Use of Online Media in Learning English During the Pandemic of Covid-19: Study From Home

The aim of this study was to show student’s competence in using online Media as a tool in English Language learning. Qualitative data were collected from the students of the English Department, Faculty of Education, IAI Nusantara Batanghari. Sample of this study was selected by using purposive sampling. The data collection technique was in the form of interview and observation on learning activity. Then, the data were analyzed descriptively. The result showed that three types of online media utilized by the students such as Zoom application, Video performance and WhatsApp messenger. The most favorite media was WhatsApp messenger due to easy to use, practical, fast use, saving internet data, and can be accessed only with mobile phones. WhatsApp has various features that can be used to support communication such as New Groups, New Broadcasts, WhatsApp Web, Broadcast Messages and Settings with internet service assistance. The group menu option was used as a place for discussion activity for the teacher with students and students with their friends in solving problems, for example the teacher sends several questions to be solved according to the material that has been given.
Isu-isu Syariah bagi Aplikasi Modal Teroka di dalam Koperasi

There is a proposed method for application of shariah-compliant venture capital in cooperative society in Malaysia.As this application is not yet available in the practice of cooperatives in Malaysia, there is a need to explain the impetus of shariah through the perspective of maqasid shariah.Furthermore, the potential shariah issues will be further elaborated.This paper aims to clarify the shariah issues that will arise when islamic venture capital being applied by cooperatives.This is an exploratory study, where information on the variables related to the application of venture capital in cooperatives will be gathered and be identified.This study will raise the risk of shariah noncompliance in terms of time frames before, during and after the venture capital offering.This risk is assessed based on studies that have been conducted on the potential application of venture capital in cooperatives.The results of this paper explain the Shariah motivation according to the perspective of maqasid shariah regarding the application of Islamic venture capital in cooperatives.The study findings indicate the existence of shariah issues in the application of venture capital investment in cooperative throughout investment timeline.The shariah issues are related to the source of venture capital funds, placement of the funds, the main activity of primary cooperatives, shariah-compliant benchmarks of primary cooperatives, marketing issues, exits strategy regarding the context of cooperatives, zakat and purification of non-halal parts.Thus, the involvement of shariah advisors is a requirement as early as possible.The implication of this study is it can be a reference for the application of islamic venture capital in cooperatives in the future.This study also suggests conducting a case study on venture capital that has been conducted in the cooperative community.
EVENTUS: An App to Register for College Events

Abstract: Currently college conducts many fests that may be technical or non-technical for the students to have experience in different aspects. These events are mostly unknown to the students specially the students of different colleges. In order to advertise the events students of the organizing team visits other colleges and give a brief summary to all the students they possibly meet. This way of advertising results in waste of time and efforts as most of the advertising is done to uninterested students. In order to advertise their event to the target audience or those who are genuinely interested in the event, here is a Platform named EVENTUS which is solely made for promotion of college events tech fests etc. and avoid the less effective efforts of current practice of advertisement
Virtual Reality-Enabled Deep Learning and Communication Technology for English Teaching through Webcast and Short Video

An adaptive learning model for English vocabulary through a machine learning is proposed in this paper.The four main types of user information, including basic student information, quiz information, course video viewing information, and forum interaction information, are processed through feature engineering, and a better model on sparse data is proposed through comparison on different models, and the prediction accuracy of the model is improved through natural language processing techniques, to achieve feedback on user learning efficiency through user data and provide teachers and students with the corresponding teaching and learning suggestions for teachers and students.It is found that the quiz information has more influence than the course video viewing information, and the accuracy is improved by about 3% compared with TF-IDF after introducing word embedding.The use of mobile for English learners to learn to read in a fragmented learning context enables targeted training in weak areas of English reading, thus improving different aspects of learners' reading skills.
CyLearn: An Assistive Web-Based e-Learning System for Cybersecurity Skills Course

Distance learning has become common in Philippines as schools have started to cater to online education due to the outbreak of COVID-19. E-learning has been adapted to provide learning materials and train students over the Internet. However, for people with impairments such as hearing and vision, this can be a problem. With this situation, the study developed an e-learning application with an assistive laboratory for assessments, specifically for college students. The subject matter used for the developed system is cybersecurity. cybersecurity is now one of the most in-demand courses due to the rising cases of cyberattacks. The developed system allows students to learn cybersecurity and conduct laboratory exercises in a virtual machine with text-to-speech and closed-caption technology. The study used two post-tests in a controlled group of respondents to determine if the developed system accommodates online cybersecurity learning compared to the traditional learning methods available. Comparing scores from the first group who used the developed system to the second group who used the current learning methods shows that the former received higher scores and has deemed the developed system. The developed system that has presented a guided cybersecurity learning scenario is more effective than current learning methods. Security testing was applied in this study to identify potential vulnerabilities and possible security risks in e-learning systems like this.
CHATGTP AND ITS INFLUENCE ON MODERN HIGHER EDUCATION

CHATGTP ТА ЙОГО ВПЛИВ НА СУЧАСНУ ВИЩУ ОСВІТУThe article explores the positive and negative aspects of artificial intelligence and especially of ChatGPT's impact on modern teaching, learning and organisation of the educational process.The use of artificial intelligence in education has the potential to revolutionize teaching and learning from the personalized learning experiences to automating administrative tasks.The article analyses the impact of artificial intelligence on education and how ChatGPT can help enhance the student learning experience and support educators.The benefits of ChatGPT include personalized feedback, academic advising, and language practice, while ethical considerations include potential biases and inequalities in education.The article also discusses the potential limitations and ethical implications of ChatGPT, such as the risk of perpetuating biases and the importance of balancing technology and human interaction in education.The integration of artificial intelligence and for instance its language models like Chat-GPT in higher education has been explored as a promising tool for enhancing student engagement and academic performance.Studies have examined the use of ChatGPT in various areas, including language learning, writing assistance, and personalized education.However, the effectiveness of ChatGPT in improving academic outcomes may vary depending on the specific context and implementation of the technology.It is crucial to consider the ethical implications of using AI in education and to ensure that AI tools are used in a responsible and transparent manner.The potential uses of ChatGPT and other AI language models in higher education are still being explored and developed, and it will be interesting to see how they continue to be integrated into educational settings in the future.Further research is needed to investigate the long-term impact of AI language models on student learning and to identify best practices for their implementation.
Exploring stable diffusion and interpretability of image classification using neural features

An ongoing challenge for image processing algorithms is how to go beyond identification, detection, and classification. This idea encompasses the ability to reason about with contextual information. Including what the whole image scene represents and how it informs. The problem of current algorithms may include approaches that only focus on a single focal plane discarding peripheral elements, limitations of datasets where salient objects are captured close up but not from different angles or distances. Our research explores how to leverage not just core features but features that may have been assumed to be spurious in nature. Thus contextual information increase performance of algorithms: accuracy, interpretability and meaning. In this paper we will present research into causal reasoning and stable diffusion &#99;ite{rombach2021highresolution} utilizing synthetic data for detection with core and spurious features.
Image hiding in audio file using chaotic method

In this paper, we propose an efficient image hiding method that combines image encryption and chaotic mapping to introduce adaptive data hiding for improving the security and robustness of image data hiding in cover audio. The feasibility of using chaotic maps to hide encrypted image in the high frequency band of the audio is investigated. The proposed method was based on hiding the image data in the noisiest part of the audio, which is the high frequency band that was extracted by the zero crossing filter. Six types of digital images were used, each of size fit the length of used audio, this to facilitate the process of hiding them among the audio samples. The input image was encrypted by a one-time pad method, then its bits were hidden in the audio by the chaotic map. The process of retrieving the image from the audio was in the opposite way, where the image data was extracted from the high frequency band of the audio file, and then the extracted image was decrypted to produce the retrieved image. Four qualitative metrics were used to evaluate the hiding method in two paths: the first depends on comparing the retrieved image with the original image, while the second depends on comparing the audio containing the image data with the original audio once, and another time by comparing the cover audio with the original audio. The results of the quality metrics proved the efficiency of the proposed method, and it showed a slight and unnoticed effect between the research materials, which indicates the success of the hiding process and the validity of the research path.
A comparison between the hierarchical clustering methods for postgraduate students in Iraqi universities for the year 2019-2020 using the cophenetic and delta correlation coefficients

The educational sector is one of the important sectors in the world, and it is considered one of the means of community development.In addition, it is one of the means of making the country's renaissance and development because it represents the factory of thinking minds that make change.There is no doubt that this sector is the same as any other sector.The deficit in the studied scientific planning has been prolonged, which led to its deterioration, and the problems of education remain diverse and inherited from previous time periods, where the hierarchical cluster analysis was used on postgraduate students in universities in Iraq, except for Kurdistan region, and the number of universities that were included in the study was (30) universities.In the whole of Iraq for the year 2020, when using the comparison measures the Cophenetic Correlation Coefficient (CCC) and the Coefficient Delta (DC), it was found that the Complete Linkage Method is the best among the hierarchical methods, as the value of (CCC) is 0.952061, and the value of (DC(0.1)) it is 0.288973, and in the case (DC(0.5)) it is 0.26877, then followed by Median method, Ward's method and finally Single Linage Method.
Measurement incompatibility and quantum advantage in communication

Measurement incompatibility stipulates the existence of quantum measurements that cannot be carried out simultaneously on single systems. We show that the set of input-output probabilities obtained from d-dimensional classical systems assisted with shared randomness is the same as the set obtained from d-dimensional quantum strategies restricted to compatible measurements with shared randomness in any communication scenario. Thus, measurement incompatibility is necessary for quantum advantage in communication, and any quantum advantage (with or without shared randomness) in communication acts as a witness to the incompatibility of the measurements at the receiver's end in a semi-device-independent way. We introduce a class of communication tasks - a general version of random access codes - to witness incompatibility of an arbitrary number of quantum measurements with arbitrary outcomes acting on d-dimensional systems, and provide generic upper bounds on the success metric of these tasks for compatible measurements. We identify all sets of three incompatible rank-one projective qubit measurements that random access codes can witness. Finally, we present the generic relationship between different sets of probability distributions - classical, quantum with or without shared randomness, and quantum restricted to compatible measurements with or without shared randomness - produced in communication scenarios.
Digital citizenship for faculty of Iraqi universities

Digital Citizenship (DC) is a set of rules, controls, standards, norms, ideas, and principles followed in the optimal and proper use of technology, which citizens, young and old, need to contribute to the progress of the nation.In short, it is guidance and protection, guidance to the benefits of modern technologies, and protection from their dangers.Or more precisely, it is the smart approach to technology.The concept of digital citizenship has a strong relationship with the education system, so academics in higher education and scientific research institutions must be the most experienced, and effective among their students in this field.Especially after the Corona pandemic and the trend that the universe has gone through towards using the internet in all areas of life, including education, especially integrated education, it has become very important for a citizen to be digital.This study dealt with a sample of university professors with (200) questionnaires.All the professors who belong to colleges with a scientific and human specialization possess digital citizenship.There are no differences between genders except in the education axis, which was in favor of the teaching staff male.In addition to the specialization, it was in favor of the colleges of science.
Firearms on Twitter: A Novel Object Detection Pipeline

Social media is an important source of real-time imagery concerning world events. One subset of social media posts which may be of particular interest are those featuring firearms. These posts can give insight into weapon movements, troop activity and civilian safety. Object detection tools offer important opportunities for insight into these images. Unfortunately, these images can be visually complex, poorly lit and generally challenging for object detection models. We present an analysis of existing gun detection datasets, and find that these datasets to not effectively address the challenge of gun detection on real-life images. Following this, we present a novel object detection pipeline. We train our pipeline on a number of datasets including one created for this investigation made up of Twitter images of the Russo-Ukrainian War. We compare the performance of our model as trained on the different datasets to baseline numbers provided by original authors as well as a YOLO v5 benchmark. We find that our model outperforms the state-of-the-art benchmarks on contextually rich, real-life-derived imagery of firearms.
REGRESI LOGISTIK BINER UNTUK MEMPREDIKSI FAKTOR YANG MEMPENGARUHI NILAI AKHIR PESERTA DIDIK SMK SEPULUH NOPEMBER SIDOARJO DALAM EFEKTIVITAS PEMBELAJARAN PASCA PANDEMI

Education is the awareness to create an environment and learning process that enables students to actively develop the potential for mental strength, self-control, intelligence, noble personality, and abilities needed for themselves and society, which is a directed and planned effort. The quality of education is the most important factor in human development efforts, character growth and competency improvement. Student assessment is an activity that aims to determine the condition of personality and social and spiritual behavior. Therefore we need a statistical modeling to analyze the factors that influence student scores. Data analysis used in this study uses Ordinal Logistic Regression. Ordinal or ranking is a type of data scale that has categorical characteristics where something is better or worse and higher or lower. Ordinal logistic regression is a statistical method for analyzing response variables that have two or more categories and the measurement scale is level. This study shows that the factors that influence the final grades of students at SMK Sepuluh Nopember Sidoarjo include 8 variables, namely gender (female), origin of SMP/MTs (private), everyday language (Javanese), father's occupation (not working), mother's age (36-46 years), number of students (&gt; 35 students), no parental participation, and vocational (non-health) qualifications.
Boosting Model Inversion Attacks with Adversarial Examples

Model inversion attacks involve reconstructing the training data of a target model, which raises serious privacy concerns for machine learning models. However, these attacks, especially learning-based methods, are likely to suffer from low attack accuracy, i.e., low classification accuracy of these reconstructed data by machine learning classifiers. Recent studies showed an alternative strategy of model inversion attacks, GAN-based optimization, can improve the attack accuracy effectively. However, these series of GAN-based attacks reconstruct only class-representative training data for a class, whereas learning-based attacks can reconstruct diverse data for different training data in each class. Hence, in this paper, we propose a new training paradigm for a learning-based model inversion attack that can achieve higher attack accuracy in a black-box setting. First, we regularize the training process of the attack model with an added semantic loss function and, second, we inject adversarial examples into the training data to increase the diversity of the class-related parts (i.e., he essential features for classification tasks) in training data. This scheme guides the attack model to pay more attention to the class-related parts of the original data during the data reconstruction process. The experimental results show that our method greatly boosts the performance of existing learning-based model inversion attacks. Even when no extra queries to the target model are allowed, the approach can still improve the attack accuracy of reconstructed data. This new attack shows that the severity of the threat from learning-based model inversion adversaries is underestimated and more robust defenses are required.
Comparative study of solar flux using different empirical models at low land urban industrial zone of Biratnagar Nepal

&#x0D; &#x0D; &#x0D; &#x0D; Nepal is a developing country where sufficient clean energy is not available in our daily needs for cooking, lighting and other developmental activities. So, it is high time to promote clean and green energy, which is freely available in every corner of the country. In this regard, the present study helps to estimate the global solar radiation at the lowland region Biratnagar (lat. 26◦28′53′′N, long. 87◦15′50′′E and Alt. 72 m) using measured global solar radiation (GSR) and sunshine hours on empirical models. This paper uses the regression technique on two different empirical models Angstrom-Prescott(A-P) and Tiwari and Sangeeta, to estimate solar radiation. After analyzing the data on empirical models, the empirical constants 0.25 and 0.23 and 0.13 and 0.24 are found in A-P and Tiwari and Sangeeta models, respectively. The performance of the models was carried out by employing mean bias error (MBE), mean percentage error (MPE), root mean square error (RMSE) and adjusted coefficient of determination (R2). These statistical tools reveal that all these models are statistically significant. Such a study is relevant when reliable data for solar radiation is not adequately available. The findings of empirical coefficients can be utilized for predicting solar radiation and solar energy at similar geographical locations in Nepal.&#x0D; &#x0D; &#x0D; &#x0D;
EXPERIMENTAL METHODOLOGY FOR DEVELOPMENT OF COMPOSITIONAL THINKING IN SENIOR ARCHITECTURE STUDENTS

Analysis of a small part of methodological literature about development of compositional thinking in architecture students and its effect on development of flexible compositional activity skills in design work, acute need in development of a contemporary architect’s personality able to adapt to new technologies and challenges of a job market determined the choice of the topic for the research “Experimental Methodology for Development of Compositional Thinking in Senior Architecture Students”. The article covers the object, subject, purpose, hypothesis and tasks of the research concerning development of compositional thinking based on the proposed system of composition exercises. In the course of the research we have identified certain trends in development of compositional thinking in senior architecture students, such as: management of creative skills development was possible only on the basis of a set of various optimally compatible forms and methods, focused instruction and education on the basis of fairly wide general development of students in view of their personalities. Research prospect, in our opinion, includes further study of possibilities for use of the system of exercises on general laws of composition in development of visual thinking in architecture students and improvement of their professional qualities in creative and design projects.