Reviewerly/exHarmony huggingface dataset:
The Frame Response Time Interval Based Device Fingerprinting Identification

Channel state information (CSI)-based wireless device fingerprinting provides an effective authentication scheme at the physical layer of wireless communication devices using CSI short-time invariance, but appears to be inadequate for long-time communication authentication or scenarios that require intermittent authentication. To address this problem, we propose to construct a wireless device fingerprint using frame response time interval (FRTI) and combine a CSI-based wireless dynamic device fingerprint to form a multi-domain fusion wireless device identification and authentication method, which can effectively identify and authenticate wireless devices at the time of wireless device access and during continuous wireless device communication to ensure safe and reliable operation of wireless devices. The experimental results under different scenarios show that using the multi-domain fusion method of frame response interval and channel state information for wireless device identification can significantly improve the accuracy of calculation and transmission delay, and the identification rate reaches more than 95%.
Evolution of digital support for science and education in the USSR (Russia) since the 1960s until the end of the 2010s (based on the information of St. Petersburg Mining University)

The evolution of digital support for scientific research and the educational process at the St. Petersburg Mining University from the 1960s to the present is examined. Based on the analysis of scientific literature and documents stored in the archives of the Mining University, the features of providing computer equipment, as well as managing the computer center were considered in a historical retrospective.
Application of Data Mining using Naive Bayes for Student Success Rates in Learning

Education is a very important part of human life because through education quality human resources will be formed. Quality education can be read and measured by the achievement of various indicators. However, achieving these indicators is not easy, because learning success is influenced by several factors. One of the factors that can affect the success of learning is the learning system. To understand the level of student success in learning, a data mining processing technique is needed. The algorithm that will be used in this research is the naive Bayes algorithm. This study uses 601 datasets per year from Academic Year 2019/2020 to Academic Year 2021/2022, the data used are attendance score data, assignment scores, mid-exam scores, semester exam scores, and averages. The test is divided into 3, namely testing for the Academic Year 2019/2020 dataset, testing for the Academic Year 2020/2021 dataset, and testing for Academic Year 2021/2022 using the split validation operator. The test results using the Academic Year 2019/2020 – Academic Year 2020/2021 student score dataset have an accuracy value of 95.01% while the Academic Year 2021/2022 student score dataset has an accuracy value of 97.79%.
A Hybridized GA-Based Feature Selection for Text Sentiment Analysis

Recent research work has described the effectiveness of various sentiment classification techniques ranging from simple lexicon-based methods to more complex machine learning techniques. Researchers of the article develop an integrated framework that bridges the gap between dictionary-based methods and machine learning methods to achieve better accuracy and more flexibility. To solve the problem of scalability that occurs as the feature set grows, a hybrid genetic algorithm (GA)-based dimensional reduction method is proposed. With the help of this novel approach, authors can reduce the size of the feature set by reaching a remarkable value of accuracy. Here the authors have compared the proposed feature reduction method with a widely used principal component analysis and singular value decomposition-based feature reduction algorithms. In addition, the proposed sentiment analysis model is tested in other metrics, including precision, recall, F1 score, and feature size.
Financial Fraud Detection of Listed Companies Based on DNSAE Fusion and Improved Random Forest

The falsification of financial data of listed companies is easy to mislead the market, causing investors to lose their investment and the personal economy is severely damaged. In view of the above problems, this paper proposes a financial fraud detection model of listed companies based on DNSAE fusion and improved random forest to detect the financial fraud of listed companies. The experimental results show that the model has a good detection effect in the financial fraud of listed companies.
Farm Fresh – A Peer-to-Peer Mobile Application and Web-based Portal Platform for Farm Goods

Most people use E-commerce platforms to buy products and services in this day and age. Having a physical store is not enough. A lot of companies nowadays are reinventing themselves. E-commerce and M-Commerce platforms help sellers and consumers because transaction procedures are faster and more efficient. Both sellers and consumers can also sell and buy products anytime and anywhere. This research aims to develop a mobile application with a web-based portal to provide a simplified way for farmers and consumers to transact. Creating a system is always challenging, but giving farmers a chance to profit more is essential. Increased profitability for farmers can escort them into better investments and production. Farmers require easy access to good, up-to-date, and valuable agricultural marketing strategies and information.
An improved random forest order review classification method based on Word2vec

In recent years, with the continuous development of the Internet, online shopping has gradually become a mainstream shopping method for people. At the same time, people often comment on the purchased goods, which expresses their shopping feelings on the one hand and provides corresponding reference for others' shopping on the other. In order to better mine and analyze the massive review data and extract valuable reviews from them, this paper proposes an improved random forest classification method based on Word2vec, which optimizes the number of decision trees and the number of leaf node variables in the random forest algorithm by incorporating the seagull algorithm to classify the crawled e-mall review data emotionally. The results show that the word2vec+ISOA-RF classification model is improved more significantly and can effectively enhance the performance of the classification algorithm.
Fictional Modality and the Intensionality of Fictional Contexts

In (Kosterec 2021), Kosterec attempts to provide ``model-theoretic proofs'' of certain theses involving the normal modal operators $\Diamond$ and $\square$ and the truth-in-fiction (`a la Lewis) operator $F$ which he then goes on to show have counterexamples in Kripke models. He concludes from this that the embedding of modal logic under the truth-in-fiction operator is unsound. We show instead that it is the ``model-theoretic proofs'' that are themselves unsound, involving illicit substitution, a subtle error that nevertheless allows us to draw an important conclusion about intensional contexts (such as fictional contexts) and semantic equivalences.
Improving the Accuracy of a CNN Model by Preprocessing Input Images with Modified Filtering-masks

&lt;p&gt;We propose a concise method to improve the inference accuracy of a convolutional neural network model for image classification. The characteristics of the input images are sharpened by a modified 5 &amp;acute; 5 mask before training and testing. The practice data were acquired from liver cancer MRI scanning at a collaborative hospital. We established the datasets using separated scanned images, which were labeled 1 or 0 to represent images with or without a cancer focal area, respectively. Scanned files from 45 patients were adopted for this study with each of them providing hundreds of separated images. We predicted one patient&amp;rsquo;s longitudinal cancer position in the liver to illustrate the merit of our approach.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;
ANALISIS SENTIMEN PERMENDIKBUD PENCEGAHAN DAN PENANGANAN KEKERASAN SEKSUAL DI LINGKUNGAN PERGURUAN TINGGI MENGGUNAKAN SUPPORT VECTOR MACHINE (SVM)

Social media is no longer a foreign thing for people in today's technological era, one of the social media that is often used is Twitter. Twitter is used to communicate with other people and Twitter users can also give each other opinions on an issue. By involving 1252 Tweets, this study aimed to use the Support Vector Machine (SVM) algorithm on Tweet data. The processes carried out in this research are crawling, cleaning, translate, labeling, tokenizing, stop words, stemming, SVM classification. .The results showed that the accuracy level of using the SVM algorithm after the param grid was 80.3% using the parameter C = 10; gamma = 0.1; and kernel = rbf as a benchmark in the classification process. This shows that the classification process using the SVM algorithm is quite accurate.
A STUDY ON STUDENTS’ INTRINSIC MOTIVATION IN ONLINE LEARNING ENGLISH USING SHORT VIDEO OF INSTAGRAM REELS AS A MEDIA

This research was design in descriptive qualitative research to find the students’ motivation in online learning English. The data was collected and analyzed from several related of literature on the application of videos in the short videos of Instagram Reels. This research aimed that the video Reels as media can make students more enjoyed process teaching and learning. It seems using videos can give a relaxing situation for students in learning English. It also can make students more active and easy to understand the material since the video contains pictures and audio that causes students to see the material directly. The subjects were the second semester of students in Intensive English Course as the EFL Classroom. The teaching and learning activities in the class which are seems divided into three steps, e.g., Pre-activity, main activity, and activity of the last post. The analysis recommends the lecturer, as a model should have planning systematically what Lecturer should do during teaching and learning process to deliver good material in online class.
Character Education Value from Ten Folktales in Indonesia as Cyber Literature

In the development of technology, all aspects experience the same development, including literature. Technology had greatly influenced the production and reception of literature. Changes in literary works by utilizing current technological media can also be called cyber literature. However, the ease of technology might lead problems. The teacher who would use cyber literature as learning material took it without any guideline on what is the value that existed in the cyberliterature. So that this study aimed to analyze character education that appears in folklore cyber literature in Indonesia. The results of this study will be a guide for high school English teachers in choosing what characters to use in narrative learning using folklore. The approach used in this research was a descriptive qualitative approach. The data source of this research was cyber literature in the form of folklore. The selection of the title of folklore in Indonesia was based on the results of a poll from the SINDO newspaper which found that there were 10 popular folk tales. The result of the study showed that from 10 the most popular folklore in the internet, 6 out of 18 characters existed in the story. They were Responsible, hard work, honesty, self-reliance, creative, and love country. Even though, the value mostly based on the protagonist of the story, we could also see the contra value that promoted by the antagonist, such as dishonesty..
Implementasi VPN Menggunakan Metode Point to Point Tunneling Protocol

The XYZ office is a government agency covering various fields, ranging from government, economy, development, people's welfare, community life development and public service affairs. However, work activities in agencies were disrupted due to the COVID-19 pandemic which caused the government to impose a Large-Scale Social Restriction (PSBB) policy to suppress the spread of this virus, resulting in agency workers having to work from home. Therefore we need an appropriate means to be able to support these activities. One of them is making a technology design by implementing a VPN on a proxy router with the PPTP (Point to Point Tunnelling Protocol) method so that it can make it easier for employees to communicate without thinking about location. In addition, users can still remotely access the local network even though they are outside the office network. more secure. Based on the results of testing the network security at the XYZ Office before using the VPN Server, it proved that the wiretapping attackers could still obtain data in the form of website login information, proxy logins, or view data contents when exchanging data. Meanwhile, when the user connects to the VPN Server, the eavesdropper cannot see the contents of the data in it, then with the implementation of a VPN with the PPTP method, employees who are working from home can connect and communicate well with each other, with that work and information exchange will become more flexible and faster
Using AR to Create Teaching Materials, Blended Learning

In this presentation, we will first share some examples of blended learning in different scenarios, and then create some blended learning content in StoryTellAR, an exciting new blended learning platform. We will illustrate ideas on how to leverage the existing textbooks, workbooks, and teaching materials, to allow teachers to easily create lessons with blended learning […]
Comprehensive Practice of Primary Mathematics Education Based on Project Teaching Method

In primary school mathematics education, the choice of teaching and learning mode plays an important role in students' academic performance. In view of the present situation of project teaching method practice research, this paper analyzes and discusses how to use project teaching method in primary school mathematics education, the teaching effect of multiple project model […]
Cyber Crime And Its Punishment: An Analytical Study

In the present scenario, people want to live with lots of amenities such as television, laptops, mobile phone, electronic watch, Bluetooth and other etc. After the invention of androids and the touch screens, mobile phones lot of work was done by the mobile phone. With the help of social media, people get to touch each other easily. And go for the communication for personal use as well as business. Nowadays we know that all government offices work out with the help of cyber. And Private sector people also work out by the online system. Even hotel and restaurant delivery systems are online. Railway reservation, Bus reservation, flight booking also. In this article, we will find cybercrime stages and how to people steal data, materials, money, and other information with the help of electronic devices.
PENGARUH PENERAPAN METODE PEMBELAJARAN JARAK JAUH TERHADAP HASIL BELAJAR SISWA DI SD NEGERI 5 RANOMEETO, KAB. KONAWE SELATAN

Distance learning, which is the only alternative to learning during the pandemic, is faced with various problems that arise in the field. This research was conducted to examine the portrait of distance learning at SD Negeri 5 Ranomeeto and to see the effect of the use of distance learning methods on student learning outcomes at the school. This study employed quantitative research with a survey approach. The total population was 40 students with a saturated sampling technique. Data on distance learning conditions at SDN 5 Ranomeeto were collected through interview and observation methods. Meanwhile, data on distance learning methods were collected using a questionnaire, and data on learning outcomes was obtained from students' daily test scores. Data analysis was carried out by means of qualitative descriptive analysis and inferential statistical analysis consisting of classical assumption test, while hypothesis testing used a simple linear regression test. The results of this study indicate that distance learning at SD Negeri 5 Ranomeeto utilizes the WhatsApp application. This learning provides a lot of time for students to take part in learning, but parents consider that the use of the WhatsApp application in distance learning is less effective and students quickly feel bored participating in learning. The distance learning method has a significant effect on student learning outcomes with the t-count value greater than the t-table value (8.818 &gt; 2.024).
Development of learning media for minangkabau natural culture in elementary schools

This research develops learning media products in the form of Minang language story books for learning Minangkabau Natural Culture. This subject is one of the local content subjects at the Padang City Elementary School, West Sumatra Province. The development of this learning media is motivated by the learning needs of Minangkabau Natural Culture which does not yet have an alternative media in the learning process. This study uses a development research approach using the ADDIE model which consists of the Analyze, Design, Development, Implementation, Evaluation stages. This research is very important to do because it sees the lack of learning media developed for Minangkabau Natural Culture subjects for elementary school students. The results showed that the developed learning media had a good usability level with an average score of 89.1%. Testing the effectiveness of the learning media also showed a score of 85.6% in the very good category. Thus, from the results of the development carried out, it can be concluded that the use of learning media can improve students' understanding and learning outcomes of Minangkabau Natural Culture Subjects in elementary schools.
Data Protection for Users in Cloud Computing

Information technology might have simplified the way we do business, but it has also brought challenges that never before existed. Accessing data from public repositories leads to multiple difficulties. It is also necessary for the data to be available in an accurate, complete and timely manner. This paper will discuss the challenges and breaches of data protection for users in cloud computing and also explores various techniques used to address these issues.
Analisis Kinerja Private Cloud Computing Menggunakan Metode Reability, Maintanability, Availability dan Security

SMK Negeri 2 Palembang is a school based on technology techniques, the technology used is cloud computing, measurements using the RMA method performance analysis testing using the RMA scanning method were carried out on peak hours from 08.00-10.00 am obtained the availability level of ping sensors is 43.09%, http sensors are 25.32%, imap sensors are 30.8%, pop3 sensors are 36.1% then ping jitter sensors are obtained 61.4%, From the results of monitoring with a percentage of the measurement table from various sensors during peak hours, there are several sensors that have decreased, such as imap and http sensors with availability values of 30.8% and 25.32% so that it affects sensor performance so that a total of 196.71% is classified as Sufficient. tomudian on the security side obtained scanning results using Owasp ZAP Vulnerability is 8 Alerts consisting of 3 medium level risks, 2 low risk levels and 3 risk level information and scanning using NESSUS obtained vulnerabilities, namely: Http server / web server version, scanner port, Based on the results of the analysis that network traffic is very vulnerable at 08.00-10.00, so to get a more stable quality, users should access it at 13.00 – 15.00 then on security issues to minimize security gaps can add proxies to the web, upgrade libraries, activate ip and ports filter, upgrade http sever. Keywords - RMA, Private Cloud, Nessus, Owasp ZAP.
Neoliberal (In)stability and the Case of The Gambia

In this chapter, a third pathway is explored using the country of The Gambia. Analysis of The Gambia focuses heavily on the role of state instability. Neoliberal economic reforms were intended to stabilize Gambia’s economy for entrance into the global market. Instead, Gambia lacked high globalisation, and experienced increasing political, social, and economic instability. The presence of economic dominance stemming from reliance on external creditors and worsening inequality and discrimination acted as push factors for migrating “the back way” through Nigeria and into Europe. Together with corruption, this has placed many young people, in particular, at risk for human trafficking. The response to human trafficking has lacked the money and resources needed to enforce new legislation. Moreover, corruption undermines what little state action is taken on the issue.
Analysis of the Internal Control System for Goods Inventory in Vocational High Schools

The times are growing as well as human habits in doing shopping to meet their needs every day, therefore the way of selling has also changed to be more sophisticated and easy and the products are more varied to meet the demands of customers. This study aims to determine whether the internal control of merchandise inventory contained in the Bussiness Center of SMKN 2 Buduran is in accordance with the 2013 COSO theory. This study uses qualitative methods, while for data collection using documentation, interviews, observations and checklists related to this research . The data analysis technique used to answer the problems in this study is descriptive analysis. The results of the study prove that the analysis of the internal control of merchandise inventory at the Bussiness Center at SMKN 2 Buduran is mostly in accordance with the five components of COSO 2013 namely the implementation of 58.90% with an indication that it is quite effective. Some parts of the five components that are mostly not in accordance with COSO 2013 are risk assessment, control activities.
Towards a Theory of Global Security

The problem of global security acquires its integrity thanks to a holistic view of global risks (Davos Club, 2006–2022). The author’s research argues for the need to form an independent field of study, at the intersection of the sciences in global studies, which he calls “Asphatronics.” The theoretical basis of Asfatronics is research in the field of big data, the dialectic of the relationship between natural and artificial intelligence, and philosophical and psychological ideas about the ideal. Asphatronics studies the phenomenon of security, which is based on material and energy-informational processes in biological (biosphere), social, and large technical systems; however, Asfatronics also includes the ecological, military, geopolitical, technogenic, economic, social, information-psychological, cognitive, and other types of global security. Digital technologies have gone beyond information processes by penetrating material technologies and interacting with the “analog technologies” of the natural world. The author proposes two principles of research in Asphatronics: 1) analog-digital dualism and 2) gene-like quantum-wave dualism, discovered in non-classical physics of the early twentieth century. Asfatronics is aimed at identifying the patterns of formation, functioning, and development of structures (“security genes”) that ensure global security (using the language of evolutionary biology) as a stabilizing selection.