Reviewerly/exHarmony huggingface dataset:
Interactive Multimedia for Teaching Writing Descriptive Text to Junior High School Students

The article projected the outcome of a research and Development (R&amp;D) design on an Interactive Multimedia Computer Application which was implemented to be an English Subject learning module, teaching descriptive texts, for the students at a Junior High School, SMP Swasta Dwi Tunggal, Kota Medan. The App, “Devourlish”, is a multi-platform App, capable run-on both Personal computers (PC) and Smartphones; The Google-Play and Apple-Apps Store Ecosystems. The process was formative teaching as the evaluation phases (Analysis, Design, Development, Implementation, and Evaluation) ADDIE of R&amp;D design for the seventh grade, which was conducted in collaboration with the English teacher at the school, highlighted the students’ engagement to interactive learning apps and enlisted the students’ learning experiences on descriptive texts. The result indicated the apps was very highly practical since the average score in both phases were 3.69 and 3.74 respectively proving learning achievement as the potential effect in term of evaluated formative phases. Additionally, the apps also high potential effect after being tried out in the classroom, which is an application quality control for ADDIE in R&amp;D design, reaching out to 80 % of the students learning achievement. Eventually, the success of the app to facilitate English subject learning experiences the effort to draw the student's interest, to make the “Devourlish” accepted, and to affect ADDIE in an R&amp;D design.
INFORMATION SECURITY RISK MANAGEMENT USING OCTAVE ALLEGRO METHOD AT UNIVERSITY

Information is one of the important and valuable assets for the life of an organization's business. Information management is needed to maintain the confidentiality, integrity, and availability of the information from cyber attacks. These cyber attacks can be in form of viruses, malware, phishing, Distributed Denial-of-service (DoS), fraud, and Ransomware.The education sector is a significant contributor to the increase in cyber attacks during the COVID-19 pandemic. The use of ICT in higher education must have right information securityThis study aims to Analysis the risks of information security in higher education. Identification of information security risks necessary for the organization to take appropriate preventive and mitigating actions.OCTAVE Allegro is the framework used to perform risk management in this research. This framework focuses on the information assets owned by the organization. How the asset is used, stored, transferred, occurs and how threats (threats), vulnerabilities (vulnerabilities) and disturbances can be on the asset. The results of this study are recommendations for mitigating approach for identified risks.
Naturalistic Ecolinguistics Learning Model in the Framework of Green Ecology: Development Urgencies (Model Pembelajaran Ekolinguistik Naturalistik dalam Rangka Green Ecology: Urgensi Pengembangan)

Extreme weather phenomena have become more frequent, and the natural environment has suffered due to rampant deforestation, logging, and unchecked forest clearance. These issues have captured global attention. The primary objective of this research is to underscore the necessity for the formulation of a naturalistic ecolinguistic learning paradigm. This study is rooted in ecolinguistic theory, specifically focusing on naturalistic ecolinguistics and the creation of educational materials for higher education institutions. The research methodology employed in this investigation is characterized as descriptive quantitative research, incorporating basic statistical techniques. The target population comprises students enrolled in the language education master's program, particularly those who have participated in courses on ecolinguistics, particularly the naturalistic branch. Through purposive selection, a sample size of 30 respondents, consisting of current students and alumni from Sanata Dharma University's Master of Language Education program, who have undergone training in naturalistic ecolinguistics, was determined. Participants were presented with a series of 20 statements, rated on a Likert scale, soliciting their agreement or disagreement. The findings reveal an overwhelming consensus among respondents, with approximately 90% expressing support for the development of a naturalistic ecolinguistic learning model. The prevailing sentiment is that this initiative is of utmost importance, aligning with the university's commitment to the green ecology program
Collaborative Caching and Scheduling for Live Streaming in Mobile Edge Computing

With the vigorous increase in live video traffic today, more and more live users require low-latency high-quality video streaming. To this end, there have been many Adaptive Bitrate Streaming (ABR) algorithms to adapt video bitrate to network conditions, and most of them are implemented in the client side. Such algorithms typically can only optimize the quality of experience (QoE) for a single user, but are agnostic to the comprehensive video streaming performance of multiple users. The client-based ABR algorithms also cannot provide sufficient utilization of network resources due to the lack of multi-user perspective. Mobile edge computing (MEC) can achieve lower response latency and can obtain network states of multiple users at edge servers, which is a most applicable technology for mobile live streaming. In this paper, we propose a collaborative caching and scheduling (CCS) mechanism for live streaming services in the MEC environment, aiming to improve the overall viewing QoE for multiple users. CCS provides integrated segment scheduling and allocation of bandwidth and cache resources in the edge network to improve the utilization of resources. At the same time, CCS further explores the larger optimization space provided by scalable video coding (SVC) for enhancing the quality of caching and scheduling solutions. According to our simulation results, CCS can provide a better comprehensive QoE for users compared with counterparts.
HyperClassifier: Accurate, Extensible and Scalable Traffic Classification with Programmable Switches

Traffic classification provides substantial benefits for service differentiation, security policy enforcement, and traffic engineering. However, accurately classifying large volumes of network traffic using existing solutions is pretty challenging, as they are typically implemented on commodity servers with slow CPUs for packet processing. To address this, we leverage the opportunity provided by emerging programmable switches and propose HyperClassifier as a solution to achieve accurate, extensible, and scalable traffic classification. HyperClassifier designs an efficient classifying table with an effective flow expiration mechanism that enables lightweight packet inspection on resource-limited switches. We implement an open-source prototype of HyperClassifier on a hardware Tofino switch and conduct extensive evaluations. The results of our evaluation demonstrate that, compared to existing solutions, HyperClassifier can provide orders of magnitude higher classification throughput with comparable classification accuracy.
ONE OF THE APPROACHES TO SOLVING THE PROBLEM OF ESTABLISHING THE CHRONOLOGICAL SEQUENCE OF PERFORMING ELECTROGRAPHIC AND HANDWRITTEN DETAILS IN THE ABSENCE OF PLACES OF THEIR MUTUAL INTERSECTION

Long-term expert practice indicates that the filling of a number of documents has a strictly regulated, often violated order. In the article, the author points out the relevance in modern technical and forensic examination of documents of solving the issue of chronological drawing of strokes of the details of the document (study of the sequence of their implementation), since most often the solution of this particular issue is the only way to establish the truth about the validity or falsification of the document. Taking into account the changes in the writing materials (the addition of new and constant improvement of existing recipes) occurring in modern production, it is necessary to constantly update existing and create new methods for solving this problem. The author pointed out significant progress in the direction of applying a technique based on the use of modern capabilities of optical microscopes and embedded systems for visualization and digital registration of a picture that is observed under a microscope, taking into account the printing process of devices with laser printing technology, in which toner is used to transfer the image to paper. powder, laser beam and static electricity. The article considers an approach to the application of the method of establishing the sequence of execution of the details of documents, one of which is made by the method of electrophotography in the absence of places of their mutual cross-section. The analysis of the results obtained in the course of expert studies is presented. The scheme algorithm of the conducted experimental studies is described and a logical chain of established facts is built. The illustrations of the results of the conducted research are given. It is indicated in the article, which continues the study of the details obtained by the electrophotographic method on different brands and models of laser devices, as well as the quantitative dependence of toner microparticles within a stroke on the depth of the relief from the writing instrument assembly. The author of the article notes that even in the presence of the instrumental base, methodically competent development of the conditions of application is required, and in general, conducting expert research requires the expert not only to have knowledge of existing research methods but also the ability to correctly evaluate the results obtained.
Novel Feature Extraction and Representation for Currency Classification

In an era marked by the rapidly growing levels of international trade and tourism, the accurate recognition of various currency notes has become a necessity. This paper presents research on an image processing technique for classifying the origin of currencies. Individuals are hardly distinguishing between different currencies from various countries. Therefore, it becomes necessary to develop an automated currency recognition system that helps in recognition notes easily, accurately and efficiency. The methodology consists of five stages, which are image acquisition, image pre-processing, feature extraction, classification, and, lastly, results and analysis. The currency image will be pre-processed in grayscale and split into 100x100 blocks at selected regions of interest (ROI) on the currency. Next, binary matrix image features and representations will be extracted. Lastly, the similarity percentage of the binary matrix will be calculated and compared with all currency image matrices. The highest similarity percentage will be chosen as the currency's origin. The proposed algorithm successfully classified the currency and improved the accuracy of currency classification, achieving a 93.4% accuracy rate from the experimental results. The proposed method could be useful for various applications, including financial institutions, security agencies, and automated currency processing machines.
pengembangan Video Tutorial Make Up Flawless Pada Modifikasi Tata Rias Pengantin Sunda Putri

Abstract&#x0D; The development of this video tutorial was carried out to provide benefits and explanations to students and the public regarding the development of facial make-up for traditional Sundanese female brides, becoming modified Sundanese female brides which are currently trending, namely Flawless Make-up, flawless make-up which has characteristics such as natural make-up with use colors that are still soft natural, that is, you still look like you are wearing make up but with neater and glowing results, for example using soft pink and soft peach colors. The aim of this research is to produce a Video Tutorial for Flawless Make Up on Modifying Sundanese Women's Bridal Makeup that is suitable for production. This research method uses the ADDIE R&amp;D research model which is used to produce certain products and test the effectiveness of the video. The process in this video consists of pre-production planning, production, post-production, research process, data processing and research results. The results of making this video tutorial meet the validation criteria obtained by material and professional experts, namely 81% and by media experts, 100%. It can be concluded that this video is very suitable to be used as a learning medium for students in the Indonesian Bridal course in the Middle Part of the Cosmetology Study Program.&#x0D;
Implementation of Secure and Verifiable Access Control Procedures Using the NTRU Cryptosystem to Store Big Data in the Cloud Environment

Background: Due to their complexity and size, deploying ciphertexts for clouds is considered the most useful approach to accessing large data stores. Method: However, access to a user's access legitimacy and improving a decrypted text on the cloud depending on an improved access policy (AP) specified by the data owner are the key challenges for making large data storage realistic and effective in clouds. The traditional ways either totally remove the problem of AP development or offer renewal to arbiter power, but in real-time, enhancing the AP is essential to maximising security and handling agility. Results: In this paper, a safe and verifiable access control program characterised by the NTRU cryptographic system for large storage of data in the clouds is proposed. Primarily, an improved NTRU decryption protocol to deal with the decryption failures of the prime NTRU is established, and in addition, the program is analysed for its security strength and computational performance. When a new AP is specified by the data owner, the cloud server allows the program to improve ciphertext and allows the owner to verify the upgrade to oppose the cloud's fraudulent behaviour. Conclusion: It enables (i) checking the user's legitimacy to access the data owner and qualified users, and (ii) allowing the user to verify the data provided by other users for the recovery of the right user. Strong analysis can prevent and block delinquency from various attacks, namely the collusion attack that could potentially target fraud users.
Exploring methods to make AI decisions more transparent and understandable for humans

As Artificial Intelligence (AI) systems increasingly weave into the fabric of diverse sectors, their intricate and often opaque decision-making processes pose challenges to users and stakeholders alike. The 'black box' nature of AI, especially deep learning models, highlights a pressing need for transparency and interpretability. This paper delves into the significance of making AI decisions transparent and provides a comprehensive exploration of methods aimed at demystifying AI processes. Through the lens of Explainable AI (XAI) and advanced visualization tools, we underscore the importance of bridging the chasm between sophisticated AI operations and human-centric understanding. By fostering transparency, it is anticipated that AI systems can not only enhance efficacy but also fortify trust, ensuring that decisions are both informed and explicable.
Results of Training for Secondary School Students to the Interpretation of Educational Material in Biology

In the article, interpretation is characterized as a theoretical method and a logical procedure, which together provide increased efficiency in the cognition of living objects. Students’ mastery of interpretation is better carried out in stages – propaedeutic, basic and diagnostic. They were implemented in experimental work in grades 5–9, on the basis of which significant results were obtained in terms of knowledge and skills. For their diagnosis, criteria with corresponding indicators and control tasks of four levels of complexity have been developed. Data from a pedagogical experiment indicate an increase in the efficiency of students’ cognition of living objects using interpretation tools. Purpose of the article. Presentation of the results of preparing students in grades 5–9 to interpret educational material in biology. Research methodology. The priority methodological basis is an activity-based approach, which involves the use of interpretation by students to expand the capabilities of educational biological cognition. Research methods. Methods of the theoretical level – analysis of published sources on the stated topic, systematization and generalization of research material. Empirical level methods – pedagogical experiment, diagnostics of learning results, interpretation, elementary mathematical calculations of the obtained data. Conclusion. The use of interpretation as a theoretical method and logical procedure in the preparation of students in biology can increase the efficiency of their knowledge of living objects. The diagnostic criteria and indicators proposed by the authors, as well as multi-level control tasks, make it possible to objectively evaluate the results of preparing secondary school students to interpret educational material in biology.
Reconstruction of degraded image transmitting through ocean turbulence via deep learning

When a laser carrying image information is transmitted in seawater, the presence of ocean turbulence leads to significant degradation of the received information due to the effect of interference. To address this issue, we propose a deep-learning-based method to retrieve the original information from a degraded pattern. To simulate the propagation of laser beams in ocean turbulence, a model of an ocean turbulence phase screen based on the power spectrum inversion method is used. The degraded images with different turbulence conditions are produced based on the model. A Pix2Pix network architecture is built to acquire the original image information. The results indicate that the network can realize high-fidelity image recovery under various turbulence conditions based on the degraded patterns. However, as turbulence strength and transmission distance increase, the reconstruction accuracy of the Pix2Pix network decreases. To further improve the image reconstruction ability of neural network architectures, we established three networks (U-Net, Pix2Pix, and Deep-Pix2Pix) and compared their performance in retrieving the degraded patterns. Overall, the Pix2Pix network showed the best performance for image reconstruction.
Aberrations estimate based on diffraction patterns using deep residual network

Lenses are fundamental elements in many optical applications. However, various aberrations are inevitably present in lenses, which will affect the distribution of focused light intensity and optical imaging. Accurately predicting the aberrations of a lens is of great significance. Nevertheless, quantitatively measuring the aberrations of a lens, especially when multiple aberrations are present simultaneously, is a challenging task. In this paper, we propose a method based on a designed deep residual network called Y-ResNet to measure the astigmatism and coma of a lens simultaneously. The Y-ResNet was trained on the focused image pattern of a Gaussian beam passing through a lens with astigmatism and coma. The trained network can accurately predict the aberration coefficients of the lens with 0.99 specificity, 0.925 precision, 0.9382 recall, and a 0.9406 F1-score achieved on astigmatism and 0.99 specificity, 0.956 precision, 0.98 recall, and a 0.954 F1-score achieved on coma. Specifically, even if only part of the intensity distribution of the light spot is captured, the network can accurately estimate the aberrations of the lens with an accuracy of over 90% on coma and can identify astigmatism aberration features. This paper can provide a feasible method for correcting beam patterns caused by aberration based on deep learning.
Analysis and Design of Asset and Non-Asset Lending Information Systems in the Informatics Engineering Service Unit at Astra Polytechnic

The development of information technology is developing rapidly and has a positive impact on organizational, one of which is Astra Polytechnic, especially at UPT Informatics, which supports the operational activities of inventory lending in the form of assets and non-assets which are considered inefficient. The process of recording, submitting, and approving inventory loans is still done manually, so it takes a lot of time and is prone to errors. The process of recording inventory data is still using excel, loan applications are still made using hardcopy forms and there are no asset and non-asset reports. The aim of research is to analyze needs and design of a system for lending assets and non-assets at UPT Informatics based on Web Applications in order to overcome these problems. The design uses System Development Life Cycle (SDLC) based on Prototyping methodology until design stage. The process of analysis and design is explained using Unified Modeling Language (UML) approach. Analysis of system requirements is carried out on ongoing business processes, which are then outlined in design of asset and non-asset lending information systems, especially in documentation process to produce reports according to company needs.
A Study on The Reality of e-Learning for Chemistry Students During The COVID-19 Pandemic

In a survey conducted by the Department of Chemistry on the reality of e-learning, which became widespread in most international universities during the COVID-19 pandemic in 2020, up to 50 students participated to express their thoughts and confirm observations. This survey was crucial in determining the importance of e-learning for the continuity of education and its potential drawbacks. The students’ opinions were collected using specific questions designed for a questionnaire. The survey's key findings can be summarized as follows: Both students and teaching staff played pivotal roles in the success of e-learning. Additionally, the availability of logistical tools and infrastructure that facilitated communication between students and lecturers proved vital to the effectiveness of online learning.