Reviewerly/exHarmony huggingface dataset:
A New Imbalanced Encrypted Traffic Classification Model Based on CBAM and Re-Weighted Loss Function

The accurate classification of traffic data is challenging for network management and security, especially in imbalanced situations. The limitation of the existing convolutional neural networks is that they have problems such as overfitting, instability, and poor generalization when used to classify imbalanced datasets. In this paper, we propose a new imbalanced encrypted traffic classification model. The proposed model is based on the improved convolutional block attention module (CBAM) and re-weighted cross-entropy focal loss (CEFL) function. The model exploits the redefined imbalance degree to construct a weight function, which is used to reassign the weights of the categories. The improved CBAM based on the redefined imbalance degree can make the model pay more attention to the characteristics of the minority samples, and increase the representation ability of these samples. The re-weighted CEFL loss function can be used to expand the effective loss gap between minority and majority samples. The method is validated on the public ISCX Tor 2016 dataset. The experimental results show that the performance of the new classification model is better than the baseline methods, and the proposed method can remarkably push the precision of the minority categories to 93.28% (14.63%↑), recall to 91.71% (16.98%↑), and F1 score to 92.49% (16.23%↑).
Guidelines for Bimodal Virtual Assistants

Multimodality is a widely studied topic that involves communication modes such as speech, writing, gestures, touching, etc. In the field of Conversational User Interfaces, researchers emphasize both advantages and disadvantages in developing either text-based virtual assistants (visual mode) or voice-based virtual assistants (auditory mode) in terms of cognitive effort, memory load, satisfaction, or enjoyment. We also find extant guidelines which are specialized in the development of either text-based or voice-based assistants. However, there is an evident gap in Multimodal Virtual Assistants research, since there are no specific guidelines for the development of Bimodal Virtual Assistants (BVAs) that combine both writing and speech modes. In this paper, we analyze and synthesize those existing guidelines and we propose 22 guidelines sorted into four categories concerning key design issues in the development of virtual assistants with the aim of providing a unified model that helps raise awareness among designers who want to develop BVAs.
A Multiuser Ciphertext Search Scheme Based on Blockchain and SGX

To ensure the security of data, more and more users encrypt data for storage, which makes the high-efficiency ciphertext search problem in the context of cloud storage a research hotspot. Existing solutions still suffer from many vexatious problems, such as the need to maintain complex index structures and the unsatisfactory application of homomorphic schemes. To solve the above problems, this paper proposes a multiuser ciphertext search scheme based on blockchain and SGX. Our scheme uses blockchain and SGX to protect keywords and data privacy and complete decryption and keywords search of ciphertext data which does not need pregenerated indexes or preselected keywords. Second, for a multiuser scenario, a smart contract is designed to verify authorization requests and manage multiple authorized users. Finally, we give security analysis, function comparison, and performance analysis to prove the security and feasibility of our scheme. Experiments show that our scheme has effectively met practical requirements.
Document Image Forgery Detection Using RGB Color Channel

Using advanced digital technologies and photo editing software, document images, such as typed and handwritten documents, can be manipulated in a variety of ways. The most common method of document forgery is adding or removing information. As a result of the changes made to document images, there is misinformation and misbelief in document images. Forgery detection with multiple forgery operations is challenging issue. As a result, special consideration is given in this work to the ten-class problem, in which a text can be altered using multiple forgery types. The characteristics are computed using RGB color components and GLCM texture descriptors. The method is effective for distinguishing between genuine and forged document images. A classification rate of 95.8% for forged handwritten documents and 93.11% for forged printed document images are obtained respectively. The obtained results are promising and competitive with state-of- art techniques reported in the literature.
Personalized Search Using User Preferences on Social Media

In contrast to traditional web search, personalized search provides search results that take into account the user’s preferences. However, the existing personalized search methods have limitations in providing appropriate search results for the individual’s preferences, because they do not consider the user’s recent preferences or the preferences of other users. In this paper, we propose a new search method considering the user’s recent preferences and similar users’ preferences on social media analysis. Since the user expresses personal opinions on social media, it is possible to grasp the user preferences when analyzing the records of social media activities. The proposed method collects user social activity records and determines keywords of interest using TF-IDF. Since user preferences change continuously over time, we assign time weights to keywords of interest, giving many high values to state-of-the-art user preferences. We identify users with similar preferences to extend the search results to be provided to users because considering only user preferences in personalized searches can provide narrow search results. The proposed method provides personalized search results considering social characteristics by applying a ranking algorithm that considers similar user preferences as well as user preferences. It is shown through various performance evaluations that the proposed personalized search method outperforms the existing methods.
Efficient Workflow Scheduling using Social Networking Website Awareness Big Data Management

Cloud server farms global organization empowers expansive-scale logical job procedures to strengthen execution and transmit rapid responses. This exceptional topographical appropriation of the calculation is enhanced by associated expansion within the range of the information taken care of by such apps, conveying title new problems recognized crosswise over locations with efficient info administration. High quantity, low potential or price-related exchange offers area unit only one or two concerns intended to take care of information cross-sectional over server farms along with cloud providers and buyers. Cloud-gave capacity that provides low execution in lightweight fixed cost plans is impacted by existing provisions. Work process motors therefore necessitate the formation of alternates, carrying out execution at the cost of negative framework set-ups, maintaining costs, reducing strong quality and reusability. We tend to give overflow, associate unchanging information management structure for logical job procedures running across topographically disseminated locations, desiring to obtain economic benefits from these geo-differing characteristics. Our response is conscious of the condition, as it screens and displays the global cloud framework, the contribution of extraordinary and expected info taking care of execution for exchange value and quantity, within and across sites. Overflow suggests a meeting of pluggable administrations, assembled in an info-scientific cloud set. They provide an opportunity for applications to screen the essential framework, to endeavor to swish info pressure, reduplication and geo-replication, to assess info administration costs, to align the exchange between costs and periods and, consequently, to improve the exchange procedure.
Pengembangan Sistem Informasi Desa Terpadu Menggunakan Metode Rapid Application Development (RAD) Studi Kasus Desa Arjasa

Information systems are now an important part of a government agency. One of the government agencies that have used the information system is Arjasa Village. Arjasa Village has implemented a village service information system website that contains news, history, galleries, and certificate services. The village admin or operator in managing the village information system has several problems. The certificate service feature here is still less flexible in adding or making a certificate because it cannot move paragraphs, sentences, entries in the event of an error in position, and cannot change the certificate that has been printed by residents if there is an error in data entry. The historical feature is requested to be replaced with the village government information feature because it can be filled with village history, vision and mission, village profiles, institutions, and others related to village government. Then the village government wants the transparency feature of village funds or APBDes and features of population management. Therefore, the development of the Arjasa village information system is very necessary. In developing this system, the researcher uses the Rapid Application Development (RAD) method, because RAD is a method used in system development to overcome a condition where the development process uses a short and fast development cycle because the process is divided into several components. that can be reused, so that the developed system can find out the results without waiting a long time. RAD is also very suitable for small scale system development as in this case.
A Semi-automatic Data Generator for Query Answering

Question Answering (QA) is a critical NLP task mainly based on deep learning models that allow users to answer questions in natural language and get a response. Since available general-purpose datasets are often not effective enough to suitably train a QA model, one of the main problems in this context is related to the availability of datasets which fit the considered context. Moreover, such datasets are generally in English, making QA system design in different languages difficult. To alleviate the above-depicted issues, in this work, we propose a framework which automatically generates a dataset for a given language and a given topic. To train our system in any language, an alternative way to evaluate the quality of the answers is needed, so we propose a novel unsupervised method. To test the proposed technique, we generate a dataset for the topic "computer science" and the language "Italian" and compare the performance of a QA system trained on available datasets and the built one.
Leveraging TikTok and other new media for optics educational outreach

New media, like the video-sharing application TikTok, are powerful tools for optics education and outreach on a large scale. Public optics outreach is crucial for spreading awareness of the industry and developing the workforce that will tackle the photonics challenges of tomorrow. This paper will cover the strategies that Edmund Optics used to build and scale a company-sponsored optics educational outreach TikTok program that currently has over 35,000 followers and receives up to 2 million views per video. The benefits of launching such a program for any company, educational institution, or national lab and key selling features to get executive buy in are also discussed. Additional benefits to launching such a program include the development of employee/student communication skills, brand awareness both inside and outside of the photonics industry, and improving brand image. With 1.4 billion global users, TikTok presents a promising platform for simultaneously reaching a large audience while targeting people who have demonstrated an interest in STEM topics. Sharing the outreach content made on TikTok across professional platforms like LinkedIn also leads to industry awareness, respect, and collaboration outside the scope of the common perception of TikTok as a casual, business-to-consumer medium. Meeting students, parents, and communities on the platforms they already use greatly simplifies building an audience for educational content. The Edmund Optics TikTok program was started as an experiment during school closures caused by COVID-19 but has now cemented itself as an integral part of the company's larger outreach program.
The Role of the Experimental Operating Room (Wetlab) in the Educational and Scientific Activities of a Medical University

Teaching medical students to provide medical care to the population faces the ethical problem of teaching manual skills on patients. This problem is partly solved by simulation technologies in medical education, one of the promising areas of which is the use of educational and experimental operating rooms (WetLab). This technology makes it possible to quickly master surgical and anesthesiology skills without harm to patients in conditions as close to real as possible, as well as to adapt students to further education and work at clinical sites.
Prediction of emotional competence in future education teachers through a multiple logistic regression model and classification trees

In order to know the level of emotional competence of future education teachers and evaluate the incidence that different personal and academic factors, we have used binary logistic regression and classification trees. Non-experimental design was carried out, with a sample of 359 students from the Faculties of Education of the University of Malaga and Almería. The results show that variables such as university access scores, the average mark of the first four-month period of the first year of the degree, the effort before the study, being a repeater, the choice of the degree as the first option and having siblings are significant predictors in the logistic model, where the last variable has the greatest determination capacity. Furthermore, in the segmentation tree it has been obtained that those students who do have siblings have a higher level of development of emotional competence, with a probability of 69.2% and if they have also chosen the degree as the first option, this percentage is increased to 75.9%. It can be concluded that it is essential to institutionally establish sufficient conditions so that teachers can detect the predictor variables and establish training strategies that allow increasing the level of development of the competence emotional.
How the smartphone is being used as a medium of expression by women’s population of rural India, especially the hill region of Uttarakhand, India

Expression has been a natural quality of human beings since ancient times.Whether it is a woman or a man, he finds an opportunity to express his inner thoughts in one way or the other.The way of presentation of expression creates different forms of art like music, singing, dance, painting, sculpture, writing, playing and all other forms of art through which we express our expression.This study will be helpful to understand how the expression of rural women of Uttarakhand is being recorded on social media platforms by recording them through smartphones, as well as how the user friendly technology of smartphones has made them so popular."We define self-expression as the expression of one's thoughts and feelings and these expressions can be accomplished in words, choices or through actions.(Kim & Ko, 2007)."(1) Expressing oneself through an action then that act an art form is formed and the artist is the expressive.Social media, especially Facebook, has emerged as a platform to make the expression of such performers public.
Emotion Detection using Text with Approaches of Machine Learning

A system for automatic face identification or facial expression recognition has been developed by a human-computer interaction system.Researchers in psychology are paying closer attention to its languages, neurology, and other relevant field disciplines.An Automated Facial Expression is presented in this research.The suggested technique contains three stages: face detection, feature extraction, and identification of facial gestures The early phase the YCbCr colour system is used to detect the color of a person's skin model, lighting compensation to achieve face consistency, and morphological operations to keep the desired appearance portion.The first phase's output is used to extract data.AAM (Active Augmentation Method) was used to enhance facial features such as the eyes, nose, and mouth.The appearance Model is a method for calculating the appearance of a person.The automatic facial recognition stage is the third stage.Simple expression recognition is required.CLAHE (Contrast Limited Adaptive Histogram Equalization) is used for preprocessing in the recognition phase, then HOG, which is a classic technique for feature extraction.The test picture and the training images both have HOG features extracted.Finally, in this Naïve Bayes, KNN and CNN are used for categorization.The findings of this research demonstrate the feasibility and usefulness of improving facial recognition performance.
Cyber Espionage Aims, Tactics and Threat Management Opportunities in the Georgian Public Administration

There are number of cases against the states among the cyber-attacks occurred in the recent years, when there was a breach of diplomatic secrets, confidential or personal data with various malicious aims from the perpetrator’s side. With the development of technologies, not only the frequency, but also the severity of such cyberattacks is rising, giving an alarm to the governments. The victims have been both developed and developing countries, including Georgia, which was one of the first to be addressed and the strong tactics of the malicious attack deserved to be noted by several cyber security experts. One of the methods of compromising information security is cyber espionage, which, as recent cases have demonstrated, is one of the most important cyber threats the states are facing. The focus of the article is on the aims of cyber espionage, as well as on the methods and means used by criminals to achieve malicious goals. In the process of demonstrating the goals, the reader will be shown relevant statistics and information on crime tactics. Well-known examples of cyber espionage and their consequences are presented. The case of cyber espionage against Georgia, which was one of the first in the world, is also considered. It is through such examples that we learn about experiences that, on the one hand, provide the basis for fear and, on the other hand, makes us able to think and develop a methodology for dealing with the threat. Finally, attention is drawn to the possible methods that can avoid such cases in the public administration and minimize the harmful consequences.
Knowledge Access through Libraries in the United Digital Market

The European Open Science Cloud and the strategy for unified digital market are corner stones in the way of Europe's economy, industry, and society to the new digital era. In this paper, we will analyze how digital libraries can be best utilized for knowledge access and sharing in the new digital market.
On the Impact of Data Selection when Applying Machine Learning in Abstract Argumentation

We examine the impact of both training and test data selection in machine learning applications for abstract argumentation, in terms of prediction accuracy and generalizability. For that, we first review previous studies from a data-centric perspective and conduct some experiments to back up our analysis. We further present a novel algorithm to generate particularly challenging argumentation frameworks wrt. the task of deciding skeptical acceptability under preferred semantics. Moreover, we investigate graph-theoretical aspects of the existing datasets and perform some experiments which show that some simple properties (such as in-degree and out-degree of an argument) are already quite strong indicators of whether or not an argument is skeptically accepted under preferred semantics.
Digitalization for Preserving the Book Heritage of the University Library at “Angel Kanchev” University of Ruse

This paper presents the project “Creating a digital collection in the fund of the University library in University of Ruse “Angel Kanchev” (Centre for digitalization), contract number No 2022- РУ -04, funded by the National Research Fund. Aim of the project is digitizing the first book collection in the University library’s fund and presenting it to the wide audience.
Measurement of the starting level and assessment of the starting factors of financial literacy of vocational education students (on the example of the Smolensk college of industrial technologies)

Modern realities of life dictate the need for graduates of secondary vocational education to have not only professional competencies, but also to be functionally literate. Financial literacy is one of the components of functional literacy. The purpose of the work is to determine the starting level of financial literacy of students of the Smolensk College of Industrial Technologies and compare it with the national indicators, as well as to assess the starting factors of students' financial literacy. Materials and methods. When developing the materials of the diagnostic study, the open international methodology for measuring the level of financial literacy of the Organization for Economic Cooperation and Development in 2018 was taken as a basis, and the Unified Framework of Financial Literacy competencies for students aged 15-18 was also taken into account. The toolkit developed on the basis of these methods consists of three blocks – “financial knowledge” (17 points), “financial skills” (17 points) and “financial attitudes” (16 points). To achieve the target of the Russian Financial Literacy Index, which is 57%, respondents needed to score 28.5 points. The results of the study showed that the threshold of 28.5 points was not reached. The average score was 18.6 points, which is 37%. In part, the low performance of college students can be explained by starting factors – lack of financial experience, low starting level of general education, low motivation to study, peculiarities of social and economic status. Conclusions. The task of the secondary vocational education system is to increase the level of financial literacy of students. The introduction of elements of financial literacy into curricula and programs must necessarily take into account the specifics of students. It is necessary to focus not only on age characteristics, but also on the starting factors of the target audience