Reviewerly/exHarmony huggingface dataset:
Research on the Key Technologies of Big Data Security and Privacy Protection in the Field Based on Artificial Intelligence

In the field of big data and artificial intelligence innovation and development, the collection and storage of large quantities of data information analysis have become easier, at this time to ensure data security and personal privacy has become the main topic of practical research. Since there are many security problems in the development of big data technology, it is of great importance to master more valuable contents in the analysis and mining of big data and comprehensively protect the security of data privacy. This article in the understanding of big data lifecycle model and artificial intelligence research status quo, on the basis of clear about the big data security and privacy protection data processing platform, grasp the big data safety and privacy data, the release of the framework is put forward to Spark framework as the core of difference data privacy and fractal dimension as the core of dynamic data distribution difference of privacy. The final practice results prove that the research method in this paper can correctly respond to the privacy publishing requirements of dynamic data and ensure the release of data, which has certain application value.
Assessing Graduate Academic Scholarship Applications with a Rule-Based Cloud System

Academic scholarships motivate graduates to work hard. However, the tedious application process frustrates students and brings adverse effects. The paper presents a rule-based cloud computing system to assess academic scholarship applications. The criteria can be encoded with if-then expressions. The rule-based system enables the administrator to add new standards or update existing ones flexibly. Students can upload their achievements through a web browser on different devices. Graduates know the mark of each item input into the system. The system calculates final grades automatically. Members of evaluation committees can review and return applications to applicants. All criteria are available for students. The transparency encourages students to participate in applying for scholarships. The experimental results show that the designed system was helpful in evaluating scholarship applications. Students spent less time applying for academic scholarships with the rule-based cloud system than with traditional approaches.
Sufficient Conditions for Topology-Preserving Parallel Reductions on the BCC Grid

Parallel reductions transform binary pictures only by changing a set of black points to white ones simultaneously. Topology preservation is a major concern of some topological algorithms composed of parallel reductions. For 3D binary pictures sampled on the body-centered cubic (BCC) grid, we propose a new sufficient condition for topology-preserving parallel reductions. This condition takes some configurations of deleted points into consideration, and it provides a method of verifying that formerly constructed parallel reductions preserve the topology. We present two further sufficient conditions that investigate individual points, directly provide deletion rules of topology-preserving parallel reductions, and allow us to construct parallel thinning algorithms.
Towards the Space Design for User Interface Elements of Inductive Tongue-Computer Interface

Inductive tongue-computer interface has proven the potential of being an alternative method for controlling assistive devices for individuals with tetraplegia and similar impairments who are unable to use the standard joystick. This study investigates the moving direction of activation for user interface space design. The proposed theoretical approach involves capturing and analyzing output signals from the inductive sensors of the tongue interface. In the experiment, users employ our designed software for primary two-dimensional movement control. One index based on the standard deviation of experimental results is defined and calculated. This technique prioritizes the moving direction for user interface space design. Three directions, horizontal, vertical, and diagonal, are examined. Finally, reliable results are consistently achieved through different activation units and coils. This may provide a decision-making theory for software adjustment according to the sensor hardware specification for assistive technologies.
Use of Different Machine Learning Algorithms for Hate Speech Detection

With the speedy advancement of the web, a consistently expanding number of people that utilize online social media. Subsequently, hate speech becomes uncontrolled in social media, and it is critical to group the hate speech and control it before it spread. With the presentation and the advancement of deep learning, hate speech recognition becomes practice. Many examinations use information from social platforms, for example, Twitter and Facebook along with machine learning or deep learning advances to identify and perceive hate speech. In any case, there are insufficient surveys about this area. After studying various article's and research papers, no such review is available to see assortment of feature extraction/engineering methods (FEM) and ML-Algorithms that assess, which feature extraction/engineering procedure and ML-Algorithms can perform better on open source or openly accessible dataset. Thus, the purpose of this research paper is to look at 3-FET or strategies and 8-ML-Algorithums to assess their performance on an openly accessible dataset and this dataset has 3 classes. The research outcomes exhibited that SVM-Algorithm with BIGRAM features performed better with almost 80% accuracy. This research paper shows viable ramifications what's more, can be used as a gauge concentrate on to identifying hate speech communications/messages. Also, the result of various correlations will be utilized as condition of- workmanship strategies to look at future explores for existing mechanized text classification procedures.
On Optimality of Gamma Approximation for Lognormal Shadowing Models

In this letter, we study the information-theoretic optimality of the gamma approximation for lognormal shadowing models in order to provide a rigorous mathematical ground for this useful technique. Specifically, we adopt the Kullback–Leibler (KL) divergence as the metric quantifying the distance between the original lognormal and the approximate gamma distributions. The KL divergence resulted from the moment matching criterion, the minimum achievable KL divergence of the gamma approximation, and the statistical parameter mapping relations are all derived in closed form. By these closed-form analytical expressions, we are able to rigorously examine the utility and optimality of the gamma approximation with a benchmark. Comparing the closed-form expressions of the KL divergence by moment matching and the minimum achievable benchmark, we find that the moment matching criterion, as a heuristic method, cannot guarantee the information-theoretic optimality. We also present and discuss the relevant results to substantiate the information-theoretic optimality achieved by our proposed statistical parameter mapping relations and the corresponding analytical insights.
Ideologized Identities in the Romanian e-News. A Cultural Sociolinguistic Query of Converged Media Texts on the 2022 Russia-Ukraine Conflict

"Ideologized Identities in the Romanian e-News. A Cultural Sociolinguistic Query of Converged Media Texts on the 2022 Russia-Ukraine Conflict. The design for this paper is to provide a qualitative analysis of how positioning towards the two parties directly involved in the 2022 Russia-Ukraine conflict has been the catalyst of the textual morphing of two ideologized identities in some of the Romanian e-Press. The focus was on the locus of convergence of two types of mediated texts: the production of professional press editors and journalists, and of Social Networked Sites users and prosumers. With this intent, the Romanian HotNews.ro website was scrutinized, and a number of e-news items were singled out thematically and structurally. The presumption is that the mediation process has been conducive to foregrounding two ballpark antithetic identities as underpinned by correspondent ideologies. An interdisciplinary perspective was opted for, one that joins Cultural Sociolinguistics and Critical Discourse Analysis (Agha 2007; Androutsopoulous 2006; Blommaert 2017; Herring 2013; Silverstein 2004; Thurlow 2017; Wodak 2022) with the Ethnography of Netspeak (Kozinets 2010; Markham 2016, 2020; Zappavigna 2011) and focuses on collective identities in order to diagnose how the mediated text, as part of the semiotic architecture of the said e-Press inputs, pairs up antithetic ideology-determined identities in times of crisis. Keywords: Cultural Sociolinguistics, Ethnography of Netspeak, ideologized identity, digital cultural practices, textual interpretation, e-Press, Social Networked Sites "
"Undergraduate Self-study: Discourse Analysis of Imagesets on Student Blogs "

"Undergraduate Self-study: Discourse Analysis of Imagesets on Student Blogs. Student writers’ relationship to the screen is initially grounded in their writing experiences in social media, but they come to view their course blog as a connecting space between themselves and their readership, a space which becomes one on which they self-destruct and reconstruct their identity as they learn to write (Serfaty 2004). By asking students to post a digital image of themselves, Ethna Lay initiates an important dataset, one which suggests a great deal about their relationship to writing. Through these images, students construct their independent writerly identities and simultaneously express membership in the class as a discrete discourse community. Students work collaboratively on a discourse analysis of the imageset, categorizing the class’s images as data about its relationship to writing. These imagesets are an opportunity for student writers to stage themselves; they perform how they would like to be seen (or not seen). This performing of the self is at once a private act as well as a communal and public activity (Tifentale and Manovich 2015; Rettberg 2005). The screen then has a dual nature, functioning as either a veil or mirror for student writers (Serfaty 2004). Students classify the imagesets into categories or types, which are fairly consistent across classes. Oftentimes students acknowledge the class had become its own discourse community, its deixis enabled by blogging together and by investigating their blogs, and decide that this result is only possible given the nature of the blog. The students become participant-observers in this respect, and the end result is an auto-ethnography of the pictured self in a social and academic setting. Keywords: blogging, discourse community, images, self-study, writerly self "
Scientific and Professional Degrees in Russia: Developing Traditions into the Future

When studying the history of Russian education, one becomes convinced of the validity of the dialectical principles of spiral development. The period of cyclicality in the history of attestation of scientific personnel is approximately equal to a century. In the first quarter of every century, starting from the time of the tsar Peter the Great, events took place that brought the system to a fundamentally new level. But at the same time, the fundamental foundations laid by the tsar Peter the Great and Lomonosov remain constant. Analyzing the attestation system development spiral, we find ways to solve urgent problems, and the foremost among them is ensuring Russia’s technological sovereignty. A similar problem stood a century ago. It was fully resolved in the USSR, but the foundations for its solution were laid in 1917 in the decree issued by the Russian Provisional Government: “On granting the Petrograd Polytechnic Institute the right to award academic degrees”. In the socioeconomic conditions of the modern Russia, we need new solutions. In this article we offer them
Analyzing a Software Education Experience Based on Stories Told by Elementary School Teachers

This study asked teachers to discuss their experiences with software education in elementary schools. We then explored the meanings of their stories. To accomplish this, we employed the narrative method procedure among four elementary school teachers with experience in software education, thus allowing us to collect data through in-depth interviews. We transcribed these interviews, categorized relevant information, and interpreted the meaning. In this context, we divided the results into stories pertaining to the meaningful experiences of each participant.&#x0D; Our results were as follows.&#x0D; First, the participants recognized that software education was necessary, but also reported many difficulties. Second, it began involuntarily, but then grew on its own or remained uninterested. Third, each participant had a different perspective on software education.&#x0D; In sum, this highlights three important provisions for the successful implementation of software education. First, it is necessary to create an environment in which teachers can experience software education meaningfully. Second, it is important to enhance their understanding of software education. Third, it is critical to reduce the rejection of software education and establish positive perceptions.
Study of Health Quality Coinciding with the Handwriting Process

Handwriting analysis or graphology is the science of analysing handwriting to gain insights into the mental, physical, and emotional states of the writer. It can also reveal the writer’s personality since handwriting is a product of the prefrontal cortex which plays a vital role in personality development and decision-making. Features such as strokes, size, slant, zone, margin, baseline, the shape of letters, spacing between lines and words, and pressure are taken into consideration while analysing the handwriting. The objective of this paper is to give key features in order to detect depression, a major issue consuming the productivity of people and leading them to suicide through the handwriting of the individual. An automated handwriting analysing system trained with these features, hosted on the cloud, can be of a lot of help.
Quantum State Tomography of Qudits via Hong-Ou-Mandel Interference

We propose a method to perform the quantum state tomography (QST) of an $n$-partite qudit state embedded in single photons based on the Hong-Ou-Mandel interference between the target photon and ancillary probe light. Our method requires only passive beam splitters in the target modes by shifting all of the active devices used in conventional QST methods to the probe preparation system. This feature is useful when the active optical devices for QST have large optical losses. Moreover, even when the probe is prepared by a laser light having a mode mismatch with the target photon, the method offers an accurate estimation of the target state. As a proof-of-principle, we perform the experimental demonstration using a polarization qubit. Regardless of the photon statistics of the probe light, the estimated results of state reconstruction are as accurate as those verified by the conventional QST.
Are Crypto Assets Connected to Real World Shocks? The Nexus Between Terrorist Attacks, Bitcoin and NFTs

This study investigates the impact of terrorist attacks on the price fluctuations of Bitcoin prices and NFT sales. Although the value proposition of cryptocurrencies, Decentralized Finance, and the whole blockchain revolution is a quicker, cheaper, and more transparent kind of finance, various terrorist organizations tend to use cryptocurrency anonymously to finance their terrorist activities around the world by bypassing the banking system of the regulated countries. The analyses reveal that returns of Bitcoin and NFT markets are positively associated with the organization and funding phases of the terrorist attacks but negatively associated with the post-terrorist attack circumstances, meaning that it generates positive abnormal returns (AR) prior to the attack but creates negative AR right after the attack. Furthermore, while the Bitcoin news impact curve (NIC) is nearly symmetric, the NFT NIC is asymmetric, with positive shocks having significantly more impact on future volatility than negative shocks of the same magnitude. Since previous studies claim that terrorist attack news is good news for Bitcoin returns, we will enrich our AR analysis results with NICs results.
Exploring the Methods and Limitations of Student and Parent Participation in the 2022 National Curriculum Development

The purpose of this study was to find out the actual condition of the students and parents’ participation in the operation of surveys, forums, concerts, discussions, public hearings, and intensive discussions conducted during the 2022 national curriculum development process (April 2021 to November 2021). In order to achieve the research purpose, all related data published by the Ministry of Education, the National Education Council, and the Provincial Superintendent of Education Council were collected and analyzed. As a result of the study, first, the timing, period, target selection, and connection with follow-up work were appropriate, but in the case of the questionnaire, professional content that is difficult for students, parents, and the general public to know was included. Second, problems such as one-time operation, topics requiring expertise, lack of discussion among participants, and absolute lack of time for discussion were found. Third, intensive debate run by the National Education Council can be said that participants such as students and parents lacked expertise in the curriculum. In conclusion, surveys, forums, concerts, and public hearings promoted the direction and main contents of the 2022 revised curriculum and helped to form consensus, but there are limitations in collecting wide opinions and materializing agendas.
Predicting Mitigation on Catastrophic Event Such as Tsunami—Automatization of a Model Alert

Increase of human impact on the environment entailed increase of the numbers of natural disasters and related economic and human losses in last decades. Many natural systems exhibit chaotic behavior, including the weather, hydrology, neuroscience, and population dynamics. Although many of these systems can be described by relatively simple dynamical equations, characterizing these systems can be challenging due to sensitivity of initial conditions and difficulties in differentiating chaotic behavior from noise. The prediction system is made up of several networks that learned the relationships between technical points and modelling strategies. This study aims to develop a software framework for modeling tsunami vulnerability alert developing theoretical architecture alert building from 3 types of algorithms models. We present a method combining variational technique previously used for parameter estimation in chaotic systems with hidden variables. We applied the method simulated from the interconnecting system architecture to perform communication between types of algorithms. In this paper, we explore the need for a new generation of warning products, aimed at the flooding hazard, to reduce future tsunami impacts on society.
Kerberos Golden Ticket Attack

One of the main trends in IT today is the security of user accounts and the correct procedure for authenticating them in systems [1]. As the population moves into the digital age, every user must also have a digital identity [2]. In order to use a particular service, the user must first authenticate against the system and based on this authentication, the user will be assigned rights to the service [3–5]. Back in 2014, it was estimated that the average user of web services had approximately 25 web accounts [6], nowadays it is estimated that there are approximately 80 web accounts per user, where some form of identity authentication must be implemented for each of these services [7]. In large enterprise computer networks, services are used to centrally manage users using, for example, a windows server role – Active Directory Domain Services, which uses the Kerberos authentication protocol.
Application of Automobile Antenna Simulation in Experimental Teaching based on CST

In this paper, it is proposed to construct electromagnetic compatibility of vehicle antenna in experimental teaching. Three types of vehicle antenna models are adopted, and full-wave electromagnetic simulation software CST is adopted to better show the outstanding significance of electromagnetic simulation software to assist experimental teaching, so as to better understand the application of vehicle antenna simulation in experimental teaching.
Introduction: Social Informatics in the Context of the COVID-19 Pandemic

The COVID-19 pandemic has been accelerating digital transformation around the globe since the beginning of the COVID-19 outbreak in early 2020. Individuals, organizations, and governments have experienced unprecedented information and communication technologies (ICT) adoption and use, willingly or not. The backdrop of the pandemic provides a unique opportunity for us to reflect on and reexamine our relationships with ICTs, as we envision the postpandemic future. This chapter introduces the entire book, especially the core idea of “social informatics” that serves as the underlying theoretical foundation of the book and its chapters to echo the concerns about ICT use and consequences during the pandemic. This edited volume presents empirical cases from different countries and our theoretical exploration of ICT usage and consequences by covering four major themes—governance, information behavior, community, and everyday life. These chapters shed light on the importance of ICTs and unpack the complexity of technology-related practices during the global crisis. We hope to intrigue other researchers to examine the emerging social changes and evolving use of digital tools in a still-unfolding pandemic era.
Governing Privacy as Contexts Overlap during Crisis

Technical solutions to social problems require contextually appropriate and responsive governance. As ICTs were adopted and adapted to meet social needs, supporting social distancing, and automating services and interactions throughout the COVID-19 pandemic, associated governance often lagged, especially pertaining to privacy. Further, ICT use under these emergency circumstances raised unique challenges associated with crisis contexts, and highlighted the gaps, failures, and limitations of existing contextual privacy regulations. This chapter approaches these challenges, exploring the sociotechnical nature of governance assemblages regarding privacy, as experienced in education, through healthcare, and by labor.
A Radial Basis Function Neural Network for Stochastic Frontier Analyses of General Multivariate Production and Cost Functions

Production function techniques often impose functional form and other restrictions that limit their applicability. One common limitation in popular production function techniques is the requirement that all inputs and outputs must be positive numbers. There is a need to develop a production function analysis technique that is less restrictive in the assumptions it makes, and inputs it can process. This paper proposes such a general technique by linking fields of neural networks and econometrics. Specifically, two radial basis function (RBF) neural networks are proposed for stochastic production and cost frontier analyses. The functional forms of production and cost functions are considered unknown except that they are multivariate. Using simulated and real-world datasets, experiments are performed, and results are provided. The results illustrate that the proposed technique has broad applicability and performs equal to or better than the traditional stochastic frontier analysis technique.