Reviewerly/exHarmony huggingface dataset:
Studies on Inspecting Encrypted Data: Trends and Challenges

According to Google's transparency report, 99% of the pages loaded on the Chrome browser are over HTTPS.Encrypting the data traffic becomes almost the default requirement for not only secret data transmission but also users' privacy.However, encrypting data traffic makes us face a new threat.Particularly, conventional middlebox systems such as network intrusion detection systems and other network monitoring systems cannot effectively detect malicious activities over encrypted traffic.Due to this, building middlebox systems that can monitor the encrypted traffic become an actively researched topic.Many different middlebox systems that are based on different techniques are introduced, recently.In this paper, we present the trends and challenges of deep packet inspection (DPI) over encrypted data.Particularly, we triage them into non privacy-preserving techniques and privacy-preserving techniques.Then, we explain which inspection techniques they are based on and compared their properties.Moreover, we provide the challenge that those techniques have for future work.
Pick Me Up Before You Go-Go: Sociotechnical Strategies for Waste in Music Festival Campsites

Multi-day music festivals have a waste problem with much of it centred around patron campgrounds. Interviews and co-design workshops were conducted with festival patrons (N = 19) and professionals (N = 9). The interviews indicated the factors impacting festival campground waste including the proliferation of cheap items, the continuity of management decisions, highly social camping practices, the land, and interactions between these. Co-design workshops explored these to produce sociotechnical strategies using the festival timeline as a frame, with one of these, a patron planning tool chosen for further development. This paper contributes new insights on how information and communication technologies might enhance sustainable practices by facilitating relational change through better organisation, evaluation, and feedback. It concludes with examination of the challenges and opportunities for Sustainable HCI, including how to carve out a design response to a wicked problem by situating relations, meaning making, telling invisible stories, and finding leverage points.
PENDIDIKAN KEWARGANEGARAAN BERBASIS LITERASI DIGITAL: SUATU ALTERNATIF PEMBELAJARAN KARAKTER MENUMBUHKAN KEADABAN KEWARGAAN

ABSTRACT&#x0D; Citizenship Education is held to shape the character and personality of the community by the values ​​of Pancasila. Citizenship education must reach all levels of society through information and communication technology. The quality of learning for Citizenship Education is one of the educational challenges that must be faced. Learning that involves students' activeness in the learning process is an effort to improve the quality of education. Learner-centred learning can create a system that supports students in engaging in a more attractive, dynamic, and varied learning experience. With advances in information and communication technology, efforts to improve learning can be carried out through attitudes in responding to the quality of technology application in a digital-based system known as digital literacy. The method used in the analysis of this discussion is a literature study. In this article, we discuss Digital Literacy as a Technological Competency, Citizenship Education as a vehicle for character education, and Digital Literacy-Based Citizenship Education Learning in Fostering Citizenship Civilization as National Character.
Using Smart Contracts in the Proposed Blockchain Framework for an Identity Management System Based on the Internet of Things

Blockchain technology has revolutionized various sectors such as trade finance, education, healthcare, the internet of things (IoT), and user identification with its groundbreaking potential. Its transformative influence on privacy, data integrity, and transactional reliability has significantly enhanced user authentication sharing across industries. Consequently, there is a pressing demand for a robust framework capable of providing seamless authentication between devices, cloud servers, and IoT base stations. This article presents into the critical need for such a framework, meticulously evaluating its feasibility in light of the scarce existing solutions that meet industry guidelines. The proposed framework reconciles two contrasting perspectives, thoroughly examining 11 distinct factors and highlighting key features uncovered through rigorous research. The findings have implications for the future of secure authentication.
AUTOMATIC QUESTION GENERATION SYSTEM BASED NATURAL LANGUAGE PROCESSING USING PYTHON

Natural Language Processing has seen a surge in research on Automatic Question Generation (AQG) in recent times. AQG has proven to be an effective tool for Computer-Assisted Assessments by reducing the costs of manual question construction and generating a continuous stream of new questions. These questions are usually in the format of "WH" or reading comprehension type questions. To ensure natural and diverse questions, they must be semantically distinct based on their assessment level while maintaining consistency in their answers. This is particularly crucial in industries like education and publishing. In our research paper, we introduce a novel approach for generating diverse question sequences and answers using a new module called the "Focus Generator". This module is integrated into an existing "encoder-decoder" model to guide the decoder in generating questions based on selected focus contents. To generate answer tags, we employ a keyword generation algorithm and a pool of candidate focus from which we select the top three based on their level of information. The selected focus content is then utilized to generate semantically distinct questions.
Pengembangan Media Interaktif Kvisoft Flipbook Maker Pada Pembelajaran Bahasa Indonesia

The aims this development is to produce Kvisoft Flipbook Maker Interactive Media in Indonesian as a source of information that is of particular interest and is also expected for students as a whole. The development model used in the development of this interactive learning multimedia is the ADDIE model. The development stages in the ADDIE model consist of five stages which include analysis, design, development, implementation, evaluation. The development process involves subject content experts, learning design experts and learning media experts to provide feedback and input for improvements. In addition, the Indonesian Subject teacher as a user of the Kvisoft Flipbook Maker Interactive Media also provides feedback and input. Based on the results of the research, several conclusions can be drawn as follows: (1) The development of Kvisoft Flipbook Maker Interactive Media was developed based on an analysis of the needs of teachers and students through a needs questionnaire provided by the developer, (2) Validation results of material experts, media experts, and product design experts development of Kvisoft Flipbook Maker Interactive Media with very feasible criteria to be developed, and (3) Based on the results of research on the development of Kvisoft Flipbook Maker Interactive Media it can be concluded that Kvisoft Flipbook Maker Interactive Media learning media is used in developing abilities in designing creative, innovative and interesting learning.
Building a Statistical Model to Detect Foreground Objects and using it in Video Steganography

Video steganography has become a popular option for protecting secret data from hacking attempts and common attacks on the internet. However, when the whole video frame(s) are used to embed secret data, this may lead to visual distortion. This work is an attempt to hide sensitive secret image inside the moving objects in a video based on separating the object from the background of the frame, selecting and arranging them according to object's size for embedding secret image. The XOR technique is used with reverse bits between the secret image bits and the detected moving object bits for embedding. The proposed method provides more security and imperceptibility as the moving objects are used for embedding, so it is difficult to notice the changes in the moving objects instead of using background area for embedding in the video. The experimental results showed the better visual quality of the stego video with PSNR values exceeding 58 dB, this indicates that the proposed method works without causing much distortion in the original video and transmitted secret message.
Optimization in Time and Score using IID Algorithm for K-Modes Clustering

Nowadays, there are numerous methods for analyzing data, one of which is cluster analysis. Because most practical data in today's analysis contains categorical attributes, categorical data clustering has recently received a lot of attention. To cluster categorical data, unsupervised machine learning techniques, which used frequency-based method, such as K-Mode’s clustering are used. The K-Modes algorithm takes advantage of the differences between the data points (total mis-matches or dissimilarities). The lower the dissimilarities, the more similar the data points, and thus the better the cluster. This paper aims to improve K-Mode’s clustering performance by incorporating the intercluster and intracluster dissimilari-ty measure, or IID measure, into the K-Modes algorithm rather than just using the standard simple-matching method to increase the algorithm's accuracy and execution time. This combined algorithm improves accuracy and execution time of the K-Modes algorithm. As a result, this algorithm can be used as an alternative to better cluster categorical data.
Vaccination against COVID-19 of the population of the countryside of a territory in the north region of the DF: Perceptions of residents in primary health care

The present study is part of the work on the front line of vaccination against Covid-19, which was experienced by residents of the Multiprofessional Residency Program in Family Health with an emphasis on the Campo population (PRMSFPC) of the Fiocruz Brasília School of Government, in the area rural area of Planaltina - DF. The objective is to record the perceptions of nursing, physical education and dentistry residents about this process developed with the rural population assigned to the territory of the Primary Care Health Management (GSAP) 7, responsible for UBSs 11, 12 and 19, in Planaltina -DF. This is an experience report with a descriptive qualitative approach, systematized under the principles of Oscar Jara Holliday at the PRMSFPC during the syndemic period from April/2021 to January/2022. as) residents identified adversities and characteristics of the territory assigned to the GSAP 7 of Planaltina-DF. Thus, the deficit caused by an assertive national technical-scientific conduct within the PNI and the effects of the strategic decision distanced from strengthening the performance of the PHC during the Covid-19 syndemic was raised. Thus, the consolidation of PHC based on the DF family health strategy, proposed by Converter in 2017, still faces a major challenge in its verticalized organizational culture, depending on an essentially participatory construction of the actors involved in the process, such as the team of ESF, active residents and the assisted community itself.
Digital Natives Preferences in How to Learn Mathematics: A Qualitative Study of Preservice Mathematics Teachers

The purpose of this study was to describe how digital natives as preservice mathematics teachers learn mathematics. The research subjects were 30 students of the Mathematics Education Study Program at the Universitas Negeri Gorontalo. This research is a descriptive qualitative research with data collection techniques are semistructured interview, questionnaire using Mentimeter, and documentation. Data collecting held in 2022. First, they were interviewed to obtain information on how they studied college mathematics courses such as calculus or differential equations. After obtaining the methods they used, they were then asked to fill out a questionnaire via Mentimeter. From the results of the interviews and filling out the questionare, it was found that their ways of learning were by watching YouTube, reading books, discussing mathematics material with their peers, searching for learning material from the internet, and also using mathematical applications to help them solving problems. Although everyone has different preferences for which method they like the most, in general, they combine all five learning styles. When they were asked to choose the method they liked the most, 50% of them choose watching YouTube; 43% prefer to learn from books; and 6.67% choose to use mathematical application. The mathematical applications they use are dominated by Photomath. Other applications used are Qanda, Brainly, Colearn, Mathway, MathLab, Mathenchanter, Geogebra, Snap Quiz, and Wolfram Alpha. The results show that book is still relevan to use in this digital age.
A Viability Assessment of Leveraging Large Language Models to Extract Insights into People and Culture from Language

The paper evaluates the feasibility of using large language models to automatically extract insights about people from textual data. It is the first systematic attempt to assess the viability of automated coding of textual data by GPT LLMs.
Word Network using Lexical Database

The Word Lexical Database is a vast collection of English words that categorizes nouns, verbs, adjectives, and adverbs into sets of cognitive synonyms. This database may seem similar to a thesaurus, as it also groups words based on their meanings, but there are key differences. Unlike a thesaurus that only links word forms, the Word Lexical Database links specific senses of words, thereby disambiguating words found in close proximity. Additionally, the Word Lexical Database annotates the semantic relationships between words, whereas a thesaurus does not follow any explicit pattern besides meaning similarity in the grouping of words.
Penggunaan Sistem Pakar dan Algoritma Fuzzy Tsukamoto untuk Mendiagnosis Mucopolysaccharidosis Type II

A rare condition known as Type II mucopolysaccharidosis, often known as Hunter syndrome, is characterized by defective mucopolysaccharide metabolism brought on by a lack of lysosomal enzymes. A class of methanolic illnesses known as MPS type II are inherited in a progressive and recessive way. Organs and tissues are steadily harmed by mucopolysaccharidosis type II (MPS type II). Hence early handling is recommended. Although though it progresses very slowly, the damage brought on by this illness impairs organ function, mental growth, and physical capabilities. A system known as an expert system aims to incorporate human knowledge into computers so that they can solve issues similarly way experts do. The Tsukamoto fuzzy approach, which is highly flexible and has a tolerance for data, was employed in this investigation. It is hoped that this approach will make it easier to determine if the patient has positive MPS type II or negative MPS type II. In this investigation, a value of 0.78 was produced using the Tsukamoto fuzzy method's calculating process
PyExperimenter: Easily distribute experiments and track results

PyExperimenter is a tool to facilitate the setup, documentation, execution, and subsequent evaluation of results from an empirical study of algorithms and in particular is designed to reduce the involved manual effort significantly.It is intended to be used by researchers in the field of artificial intelligence, but is not limited to those.
Limits and Performances of Algorithms Based on Simulated Annealing in Solving Sparse Hard Inference Problems

The planted-coloring problem is a prototypical inference problem for which thresholds for Bayes-optimal algorithms, like belief propagation (BP), can be computed analytically. In this paper, we analyze the limits and performances of simulated annealing (SA), a Monte-Carlo-based algorithm that is more general and robust than BP, and thus of broader applicability. We show that SA is suboptimal in the recovery of the planted solution because it gets attracted by glassy states that, instead, do not influence the BP algorithm. At variance with previous conjectures, we propose an analytic estimation for the SA algorithmic threshold by comparing the spinodal point of the paramagnetic phase and the dynamical critical temperature. This is a fundamental connection between thermodynamical phase transitions and out-of-equilibrium behavior of Glauber dynamics. We also study an improved version of SA, called replicated SA (RSA), where several weakly coupled replicas are cooled down together. We show numerical evidence that the algorithmic threshold for the RSA coincides with the Bayes-optimal one. Finally, we develop an approximated analytical theory explaining the optimal performances of RSA and predicting the location of the transition toward the planted solution in the limit of a very large number of replicas. Our results for RSA support the idea that mismatching the parameters in the prior with respect to those of the generative model may produce an algorithm that is optimal and very robust.10 MoreReceived 21 July 2022Revised 4 March 2023Accepted 23 March 2023DOI:https://doi.org/10.1103/PhysRevX.13.021011Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.Published by the American Physical SocietyPhysics Subject Headings (PhySH)Research AreasComplex systemsComputational complexityFirst order phase transitionsGlass transitionNonequilibrium statistical mechanicsPhase transitionsPhysical SystemsDisordered systemsTechniquesCavity methodsMonte Carlo methodsSimulated annealingStatistical Physics
The Role of Organizational Communicative Skills in Realizing the Goals of Media Institutions

The study discuses the organizational communicative skills in realizing the goals of media institutions, which is an applied study done on Khartoum Broadcasting for the period between 2021-2022. The research problem focuses on the lack of scientific method in dealing with organizational communicative skills. Moreover the study attempts to answer the following question:&#x0D; 'What are organizational communicative skills?'&#x0D; Also the study aims to expose the role of organizational communicative skills and their genuine relationship with the efficiency and success of work.&#x0D; The study follows the descriptive survey method, and uses interview, observation and questionnaire as tools of data collection.&#x0D; Both theoretical and applied aspects of study reach to a number of results.&#x0D; The most important organizational communicative skills required in different media institutions' managers are organizational and coordination skills in business administration up to 85.7%, academic and personal skills up to 82.7%, communicative with writing and conversational skills along with spreading teamwork spirit up 80%, and technological and technical skills up to 74%.&#x0D; The study finds out that the most organizational communication type used is (meetings). Another finding by the study is that one of the problems of administrative communication is misunderstanding of information and distortion of communicative messages. The study recommends training managers on modern technology and identifying communication channels in a clear way.
USE MODERN INTERACTIVE METHODS IN FRENCH TEACHING AND IMPLEMENT THEM IN PRACTICE

At present, great attention is being paid to the use of various innovative and pedagogical technologies in teaching the French language in higher education in our country. This article is devoted to the methodology of teaching the French language. The use of modern pedagogical technologies in the educational process is also explained.
Klasifikasi Penipuan pada Rekening Bank menggunakan Pendekatan Ensemble Learning

Accounts are a collection of numbers commonly used for all transactions in the banking world, from saving, withdrawing cash, to checking account balances either directly or online using m-banking. In bank accounts and the process of opening them, there are various kinds of criminal acts committed by individuals and groups. As a bank's obligation to prevent crime so that it can provide trust to the community. In an effort to prevent criminal acts of fraud can be solved using data mining techniques, namely classification. The purpose of classification is to predict the class label of an object based on existing attributes. The classification methods used in this research are extreme gradiant boosting (XGBoost) and random forest on 22029 records. In the classification process, this study uses a percentage ratio of 90% train data and 10% test data and tuning parameters processed by randomized search cross validation. The research stages start from preprocessing to evaluation and get a train score of 99.50% and a test score of 99.59% for extreme gradiant boosting (xgboost) while random forest gets a train score of 99.46% and a test score of 99.59%. These results show that the classification results of extreme gradiant boosting (XGBoost) are better than random forest.
Optimasi Fungsi Pembelajaran Jaringan Saraf Tiruan dalam Meningkatkan Akurasi pada Prediksi Ekspor Kopi Menurut Negara Tujuan Utama

In the learning process carried out by Backpropagation the learning function is important in finding optimal results. This study aims to optimize the learning function of artificial neural networks in increasing the accuracy of coffee export predictions according to the main destination countries as research objects. This study applies the learning function to weights in Matlab, namely Gradient Descent with Adaptive Learning Rate (traingda), Gradient Descent with Momentum (traingdm), and Gradient Descent with Momentum and Adaptive Learning Rate (trainingdx) using several hidden layers, namely 15,30 and 45. Based on a series of trials conducted, the results of the study show that by implementing the Gradient Descent learning function with an Adaptive Learning Rate (trainingda) with a hidden layer of 30 it is capable of training neural networks with a better level of optimization, performing 143 iterations which produces a truth accuracy of 83%. When compared with the use of other learning functions that only last with an accuracy of no more than 78%. In general, it can be concluded that the optimization of the Gradient Descent learning function with Adaptive Learning Rate (trainda) can be applied to predict coffee exports according to the main destination countries, because the iterative process carried out to achieve convergence in increasing accuracy performs well
S Sistem Pakar Diagnosa Gangguan Kejiwaan Menggunakan Metode Inferensi Forward Chaining dan Certainty Factor

The era of artificial intelligence AI technology is now an advantage because the system does all the work according to the human brain. Expert Systemis abranch ofartificial intelligencethat adapts the mind and reasoning of an expert to solve a problem and make a decision so that it draws conclusions based on the facts. From cases of psychiatric disorders, this expert system is highly recommended to make it easier to find out what type of disorder you are suffering from to assist the public and experts in diagnosing diseases quickly and accurately. For this reason, researcherscreated an expert system for diagnosingpsychiatric disordersusing the forwardchaining inferencemethod and certainty factor. Based on the results of the implementation and analysis thathave been carried out in this study, it produces a software system, namely an expert system that has an easy-to-understand display, and can assist experts in diagnosing psychiatric disorders