Reviewerly/exHarmony huggingface dataset:
SPAM EMAIL DETECTION USING DIFFERENT CLASSIFIERS

Due to the widespread use of social media, the amount of unwanted emails has increased, necessitating the implementation of a reliable system to filter them out. Spam emailsare now the most common issue on the internet, despite email beingone of the fastest and most cost-effective forms of communication. Over the past few years, there has been a significant increase in spam emails due to the growing number of email subscribers. This study employs four classifiers (Random Forest, XG Boost, Naïve Bayesian) to classify email data, with varying data and feature sizes. The final classification result is '1' if the email is spam and '0' if it is not. The study was conducted using Python and implemented in a Jupyter notebook. This technique can also be utilized in monitoring social media and brand activity. The paper presents a machine learning approach for identifying spam emails by detecting spam content within the message. With machine learning, computers can learn how to perform a task without being explicitly programmed. This method uses data to generate a program that performs a task, such as classification. Unlike knowledge engineering, machine learning techniques require pre-classified data to create a training dataset that is used to fit the learning algorithm in the machine learning studio. The objective of this study is to train, test, and compare various classifiers. The rest of the paper is organized as follows: Section 2 defines the researchers' contribution in this field. Section 3 describes the experimentation framework, dataset, procedures, andlibraries. Section 4 summarizes the findings, and Section 5 concludes the paper's potential for future research.
IMAGE FORGERY DETECTION

In the digital age, the ability to manipulate digital images has become increasingly sophisticated, making it challenging to detect and distinguish between authentic and forged images. Image forgery detection is an active and crucial area of research, with various methods and techniques being proposed to detect manipulated images. This paper provides a survey of current methods and techniques for image forgery detection. We begin by introducing the different types of image forgeries and their characteristics. We then discuss the various methods for detecting forgeries, including statistical methods, visual methods, and learning- based methods. We also present a comparison of the performance of different methods and techniques, and conclude with a discussion of the challenges and future directions in the field of image forgery detection.
Practical and General Backdoor Attacks Against Vertical Federated Learning

Federated learning (FL), which aims to facilitate data collaboration across multiple organizations without exposing data privacy, encounters potential security risks. One serious threat is backdoor attacks, where an attacker injects a specific trigger into the training dataset to manipulate the model’s prediction. Most existing FL backdoor attacks are based on horizontal federated learning (HFL), where the data owned by different parties have the same features. However, compared to HFL, backdoor attacks on vertical federated learning (VFL), where each party only holds a disjoint subset of features and the labels are only owned by one party, are rarely studied. The main challenge of this attack is to allow an attacker without access to the data labels, to perform an effective attack. To this end, we propose BadVFL, a novel and practical approach to inject backdoor triggers into victim models without label information. BadVFL mainly consists of two key steps. First, to address the challenge of attackers having no knowledge of labels, we introduce a SDD module that can trace data categories based on gradients. Second, we propose a SDP module that can improve the attack’s effectiveness by enhancing the decision dependency between the trigger and attack target. Extensive experiments show that BadVFL supports diverse datasets and models, and achieves over 93% attack success rate with only 1% poisoning rate. Code is available at https://github.com/xuanyx/BadVFL .
Application aspects of nature-inspired optimization algorithms

In today&apos;s time, there are numerous nature-inspired optimization algorithms (NIOAs) that help to achieve fast computation with maximum profit and minimum cost. They are widely used in various fields of engineering, management, and science due to their effectiveness in solving complex optimization problems. This chapter attempts to address the application aspects of NIOAs. It begins with the definition of NIOAs. In addition to that, it also deals with its implementation and parameter tunning. Furthermore, it also presents a study on constrained and unconstrained optimization. Later, it covers the feature selection and practical engineering applications of NIOAs.
Binary Domain Generalization for Sparsifying Binary Neural Networks

Binary neural networks (BNNs) are an attractive solution for developing and deploying deep neural network (DNN)-based applications in resource constrained devices. Despite their success, BNNs still suffer from a fixed and limited compression factor that may be explained by the fact that existing pruning methods for full-precision DNNs cannot be directly applied to BNNs. In fact, weight pruning of BNNs leads to performance degradation, which suggests that the standard binarization domain of BNNs is not well adapted for the task. This work proposes a novel more general binary domain that extends the standard binary one that is more robust to pruning techniques, thus guaranteeing improved compression and avoiding severe performance losses. We demonstrate a closed-form solution for quantizing the weights of a full-precision network into the proposed binary domain. Finally, we show the flexibility of our method, which can be combined with other pruning strategies. Experiments over CIFAR-10 and CIFAR-100 demonstrate that the novel approach is able to generate efficient sparse networks with reduced memory usage and run-time latency, while maintaining performance.
THE EFFECTS OF COMPRESSOR PLUG-INS ON THE DYNAMIC RANGE IN MUSIC PRODUCTION

This study investigated the role of dynamic processors in audio processing and music production and the effects of different types of design on the audio signal. It has been tried to give information about the designs and parameters of dynamic processors. In order to create the sound sample analyzed within the scope of the study, a mono sample recording was taken from the virtual instrument plug-in. The sound sample taken from the bass guitar model was preferred in order to contain all the general envelope structure features of an audio signal. In this direction, the sound sample was chosen from the virtual instrument in order to keep it away from external factors during the recording stages and to make the work repeatable and developable. It is used as basic tools for dynamic processors to control and balance audio signals and create sensory effects. In this context, the effects of compressors in the dynamic processor class and their basic parameters and different design types on the audio signal are examined. Differences in tonal characteristics and dynamic changes of different compressor designs have been observed. In this context, the effects of FET, VCA, Vari-Mu, Optical and Digital compressor plug-ins on the audio signal were analyzed and the results were presented. These analyzes can provide guidance for the selection of different compressor designs for lecturers, students, and those interested in and working in the field of music technology. In future studies, the role of different music genres, instruments and recording conditions on the effects of compressor designs can be explored more deeply, and more comprehensive results can be reached by collecting experimental data and using machine learning techniques.
Modern Challenges of Higher Technical Education Teachers Working with Engineer Specialty Students

The goal of a modern system of technical education is to prepare new-generation engineers capable of working under severe circumstances, such as uncertain future risks and dangers. These engineers should be in charge of designing higher-order technologies which also consider human values and ethical norms. Achieving such ambitious goal should be ensured by sophisticated teaching department, that are open to organize more innovative programs, to form professional environment for future engineers and organize different formats of interaction throughout classes. The aim of article is to revision modern teacher’s competencies and preparedness for providing new class activities under condition of innovative changes. Novelty of research is based on development of ideas about activity approaches with the recognition of specific features of technical education teacher’s activities that works with young engineers. The practical significance lies in the possibility of using the article data for conducting further research; studying the difficulties faced by teachers; forming new educational resources for lecturing students
Identification of Racial Propaganda in Tweets Using Sentimental Analysis Models: A Comparative Study

The volume and scale of data being generated by social media is incrementing exponentially day by day. Private and public outlooks on various subjects or issues are expressed on social media. Sentiment analysis is a technique of examining and recognizing the sentiment of a statement that it embodies. Over the past decade, Twitter has emerged as a global leader in the social media industry, where people from around the world share their opinions and thoughts on events that occur all across the world. Sentiment analysis is a process of recognizing the sentiment of the Twitter data (tweets) conveyed by the user. In this study, we provide a survey and comparative analysis of existing techniques for opinion mining. This research paper mentions the pre-processing steps performed on the raw twitter data, including removing URLs, usernames, emojis, and stop words, and stemming to produce morphological variants of base words. Word clouds and frequency distributions of hashtags used in Racial and Non-Racial tweets were generated. The Bag of Words model was used for feature extraction, which involved converting text into a numerical matrix. The study used several classification models, including Multinomial Naive Bayes, Support Vector Machines, Logistic Regression, and K-Nearest Neighbors. The text also briefly explains Multinomial Naive Bayes and Support Vector Machines algorithms.
METAVERSE EXPERIENCE: MEASURING PRESENCE IN VIRTUAL ENVIRONMENTS WITHIN THE SCOPE OF GASTRONOMY

The aim of this study is to measure the sense of presence in virtual environments that can provide a different gastronomic experience in the metaverse by using new technologies. In the scope of the study, a virtual restaurant was created via digital platforms as a virtual environment design for the metaverse experience and it was experienced by the participants with the help of virtual reality glasses. The universe of the study consists of instructors involved in the educational and training activities of the General Directorate of Special Education and Guidance Services. It was applied face-to- face with thirteen of the trainers who were invited to Ankara within the scope of the "Material and Content Development for the Digital Game Project in Special Education " study carried out on May 23-27, 2022. After the practice, the “Sense of Presence Scale” was applied to the participants. In addition, an interview consisting of three items was conducted in order to obtain detailed information about the experiences and opinions of the participants. The results of the study indicated that the participants were inclined to prefer virtual restaurants in their daily lives and they believed that the communication established in the metaverse environment was healthy. It is recommended that the study be carried out under conditions that can provide a more realistic experience with the support of technical infrastructure. It is believed that the study will contribute to businesses and the field that aim to offer different services in the gastronomy sector.
Parameters of Cross-linguistic Variation in Expectation-based Minimalist Grammars (e-MGs)

The fact that Parsing and Generation share the same grammatical knowledge is often considered the null hypothesis (Momma and Phillips 2018) but very few algorithms can take advantage of a cognitively plausible incremental procedure that operates roughly in the way words are produced and understood in real time. This is especially difficult if we consider cross-linguistic variation that has a clear impact on word order. In this paper, I present one such formalism, dubbed Expectation-based Minimalist Grammar (e-MG), that qualifies as a simplified version of the (Conflated) Minimalist Grammars, (C)MGs (Stabler 1997, 2011, 2013), and Phase-based Minimalist Grammars, PMGs (Chesi 2005, 2007; Stabler 2011). The crucial simplification consists of driving structure building only using lexically encoded categorial top-down expectations. The commitment to the top-down procedure (in e-MGs and PMGs, as opposed to (C)MGs, ) will be crucial to capture a relevant set of empirical asymmetries in a parameterized cross-linguistic perspective which represents the least common denominator of structure building in both Parsing and Generation.
Assemblages/Decentralised

The concept of citizenship has traditionally been associated with privilege and the rules defined by nation-states. However, the increasing integration of digital technology calls for a reconsideration of the concept of citizenship as a system of relations rather than a static condition. The assemblage theory offers a way to understand citizenship as a dynamic, temporal, and spatial concept involving continuous transformation and networks of interdependent relationships. This shift from a fixed understanding of belonging to a more fluid and dynamic concept requires a reevaluation of the role of non-human actors and the importance of multiple, shifting narratives of time. Emerging digital technologies are enabling new forms of citizenship that are no longer tied to territorial jurisdictions, but instead are based on participation in distributed virtual communities. The development of decentralised technologies such as blockchain offers the potential for creating new institutions that enable a more agile and rapid recodification of citizenship status. However, the decentralisation of citizenship also raises concerns about the potential for centralised control and the need to protect decentralised activities. A key challenge is to imagine a strategy that can combine centralisation and decentralisation in a way that enables new forms of citizenship based on belonging to extraterritorial, distributed, and decentralised values and affinities.
Cybersecurity Issues among High School Students: A Thematic Review

Cybersecurity refers to the methods and technology used to prevent unauthorised access, use, disclosure, interruption, alteration, or the destruction of computer systems, networks, and sensitive information from cyber-attacks. Cyber-attacks are among the most severe issues confronting today's fast-changing technology. Individuals well-versed in cybersecurity can identify, respond to, and limit the impact of cyber threats on them. There have been reports of people being assaulted with cyber threats despite their expertise in cybersecurity. A variety of elements, including individual characteristics, cause this cyber-attack. Therefore, this thematic study aims to emphasise the elements that encourage high school students, to incorporate cybersecurity into their daily life, mainly when using the internet. Aside from that, the elements are referred to avoid cyber-attacks. A list of keywords relevant to the scope of this study is used in two databases, namely Scopus and Science Direct, in which a total of 27 papers were finalised to be reviewed. A thematic review was conducted using ATLAS.ti version 22, the papers were coded, categorised, and themed. The finding revealed four final themes: demographic, psychological, family, and societal elements. The new results have contributed to the unique elements related to cybersecurity issues among high school students. This study benefits future research focusing on aspects that could drive high school students to practice cybersecurity so that they will not become the victims of cyber-predator.
ASSISTIVE WALKING STICK FOR VISUALLY IMPAIRED

This paper presents the smart walking cane based on ultrasonic sensors, Arduino UNO and concepts of Machine Learning and CNN for visually impaired people. There are approximately 37 million people across the globe who are blind according to the World Health Organization (WHO). People with visual disabilities are often dependent on external assistance which can be provided by Humans, trained dogs, or special aid devices. Thus we are motivated to develop a smart walking stick which not only detects object but also detect the floor, surrounding along with collision detection and raises an alarm in case of any mishap. The system was designed, programmed using C language and tested for accuracy. Our devise can detect objects within 5m of distance
Penerapan Metode Drill Dalam Meningkatkan Kanji Pada Siswa LPK Dwipayana Cipta Karya Ubud Tahun Ajaran 2022

Teaching Japanese especially in learning kanji is very difficult, so the teacher tries the drill method which aims to make it easy for students to remember kanji letters from how to read kanji and how to write the kanji for each stroke and also to find out the obstacles students experience during the kanji learning process. The method used in learning kanji is the Drill method for three weeks. The subjects in this study were 30 students of LPK Dwipayana Cipta Karya located in Bunutan Village, Ubud. The type of data in this study uses quantitative data which is used in calculating the results of students' kanji answers and qualitative data which will be presented by the results of the questionnaire and combined with the results of interviews with teachers and students. Methods and data research techniques in this study, namely using observation before knowing the weaknesses experienced by students at LPK Dwipayana Cipta Karya, then distributing questionnaires related to starch to students, after that conducting interviews with students and teachers regarding the results obtained from the results of the questionnaire. It can be concluded from the results of the analysis that the drill method is very effective in learning kanji for LPK Dwipayana Cipta Karya students. It can be seen from the fact that there are more students who get vulnerable kanji scores of 70-100 than students who get &lt;70 because after receiving kanji training at LPK and not practicing back independently.
Symbolic image in public communication of Thu Dau Mot University

Symbolic images stand for more than simply what appears before the eyes. They represent a deeper meaning behind the image – something. The symbolic images in public communications, and techniques of their application as an instrument of forming desired ideological models within social consciousness, as well as consider principles of social psychology that enable successful application of communication technologies to a target audience by appealing to their image thinking. Applied methods of the research are: sociocultural, historical, and content analysis, this article focuses on analyzing the significance of symbol image in public communication strategies and its impacts on brand building, trust establishment, and fostering a positive interactive environment with the public. Based on lessons drawn from practical public communication activities of Thu Dau Mot University, the article proposes additional measures to enhance the effectiveness of the unit's communication and their potential application to specific cases, contributing to the development of the field of public communication.
Anxiety in Speaking Japanese Experienced by the Department of Japanese Language Education Students of Unnes

Language learners, particularly foreign language learners, endure language anxiety. Language anxiety can affect learners at all levels, including early, intermediate, and advanced. Anxiety in speaking Japanese is quite noticeable in speaking abilities. It happens for Japanese language students enrolled in the Japanese language education study program as well. The causes of anxiety in speaking Japanese can be seen in a variety of ways, including vocabulary knowledge, sentence patterns, confidence level, and so on. The objective of this research is to discover how worried Japanese people are and what causes their worry. This study's subjects were Japanese language students at the beginning and intermediate levels, each of levels had 50 students. This study took a qualitative approach and collected the data through observation and questionnaires. According to the study's findings, 60% of students at the beginning level did not sense anxiety when speaking Japanese, despite the fact that their worried behavior indicated linguistic anxiety. Scratching the head and moving the hands, for example. Meanwhile, 60% of middle-level students were afraid to speak Japanese because they lacked command of vocabulary and sentence patterns.
Nobinobi Yomikaki: Teaching Materials for Japanese Reading and Writing Based on 21st Century Skills

This study aims to determine the use of "Nobinobi Yomikaki" teaching materials developed as teaching materials for beginner level reading and writing courses towards the formation of 21st century skills in elementary level students. This is based on the needs for reading and writing teaching materials for first semester students, especially students who have never studied Japanese at all. Efforts to form 21st century skills are the focus as well as the basis for developing teaching materials because the demands of students to be able to survive and perform in the digital world, especially after the Covid-19 pandemic, realize how important non-technical skills are as technical skills. The research method uses a mixed approach, quantitative and qualitative. The quantitative approach was used to measure reading speed, which is a basic literacy skill, while the qualitative approach was used to describe the results of observations of how the use of this teaching material on the formation of 21st century skills. The research population is the 2022 batch of students in the Japanese Language Education Study Program at Universitas Negeri Jakarta, with a sample of 24 people, namely students who have never studied Japanese at all. Based on the study, it is known that the structure of teaching materials supports the development of 21st century skills, namely the ability to think critically, creatively, communicatively, collaboratively, and succeeds in fostering positive character so that in this digital era students are ready to become part of global citizens or digital citizens. And as the impact of these skills development, through the activities that force students to communicate their ideas both orally and in writing, their Japanese reading and writing skills also improved.