Reviewerly/exHarmony huggingface dataset:
Data Collection with Mozdeh

This chapter gives a brief overview of the generic issues involved with collecting data, together with examples for Twitter and You Tube and an overview of the Mozdeh procedures. It finishes with a discussion about importing texts, with the example of academic publication metadata.
White-Box Attacks on Hate-speech BERT Classifiers in German with Explicit and Implicit Character Level Defense

Attention based Transformer models have achieved state-of-the-art results in natural language processing (NLP). However, recent work shows that the underlying attention mechanism can be exploited by adversaries to craft malicious inputs designed to induce spurious outputs, thereby harming model performance and trustworthiness. Unlike in the vision domain, the literature examining neural networks under adversarial conditions in the NLP domain is limited and most of it focuses mainly on the English language. In this paper, we first analyze the adversarial robustness of Bidirectional Encoder Representations from Transformers (BERT) models for German datasets. Second, we introduce two novel NLP attacks. Namely, a character-level and a word-level attacks, both of which utilize attention scores to calculate where to inject character-level and word-level noise, respectively. Finally, we present two defense strategies against the attacks above. The first implicit character-level defense is a variant of adversarial training, which trains a new classifier capable of abstaining/rejecting certain (ideally adversarial) inputs. The other explicit character-level defense learns a latent representation of the complete training data vocabulary and then maps all tokens of an input example to the same latent space, enabling the replacement of all out of vocabulary tokens with the most similar in-vocabulary tokens based on the cosine similarity metric.
Ontology-based Approaches to Medical Data Integration

Medical data come in a variety of forms and are stored in different types of databases. Some are structured relational database stores, while others are semi-structured and unstructured, such as the emerging NoSQL data stores. A lot of valuable data can be found in the form of unstructured text, such as clinical notes and discharge letters. To analyze and discover hidden patterns and extract knowledge from the data, they should be integrated. In the field of medicine, many ontologies have been created to provide a common basis for information exchange and to improve semantic interoperability. In this paper, we provide an overview of ontology-based integration approaches for various sources of medical data. We also identify current challenges and provide directions for future research.
Analisi lessicale degli alterati con funzione diminutiva e della varietà dei loro ruoli all’interno del Decameron

The present article deals with the use that Boccaccio makes of diminutives in his Decameron. After a brief introduction on the lexicographic studies dedicated to the works of the author, an investigation carried out thanks to the corpus TLIO (Tesoro della Lingua Italiana delle Origini) is presented. The study is aimed at reporting the occurrences of -etto, -ello, -ino, -uccio and its variant ­-uzzo diminutives in their context of use in the Centonovelle. The results outline a diverse situation where these diminutives are used in a wide range of expressive situations, spanning from affective to humorous and making their use one of Boccaccio’s key elements of writing style. The ‘passion’ for diminutives felt by the author is finally presented through a few examples of hapax legomena.
Design and Creation of Electronic Teaching Aid for Effectiveness and Attractiveness of Education Increasing

The article analyses requirements of new methods of student education at the level of secondary school with professional electrical and electronic focus. It describes the creation of a new teaching aid that incites fantasy, concentration and motivation to create interesting things by self competence of students oriented to the electrical field of study. At the same time it orientates students towards unconventional ways of thinking and non orthodox solutions. Teaching aid exploits digital form that is attractive for young people with the aspiration to focus the attention of students to study professional knowledge.
Design Driven by Sensory Perceptive Variability

Fear, anxiety, and stress of perceived or real threats of ailment, unemployment, lack of physical contacts and isolation, and movement restrictions leading to remote work and education are some of the new realities arising from the Covid-19 pandemic. New and exacerbated existing mental and physical health concerns are crucial when rethinking living spaces. This paper presents the de-sign concept for an architectural “intelligent” system that will adapt to the user. It will generate, in real time, variable “affective environments” by manipulating space perceptual parameters in order to accommodate a user’s wants, needs, and desires. Machine Learning (ML) provides the data that drives perceptual variability. The concept can be applied in healthcare (e.g., recovery rooms, care units) where sensory stimulation is key to treatment.
The Dawn of Crypto Assets: A Comet or a New Universe? Treats and Opportunities of the Upcoming Stars of the Financial Market

The aim of this elaborate is to analyse the main features of crypto assets, highlighting both the benefits and drawbacks, paying particular attention to crypto securities. Starting from an overview of these financial instruments, it focuses more specifically on different categories of tokens. Once outlined the classification boundaries, the paper narrows the key opportunities and major threats of the market presented by the literature available on the object. Starting from Security Token Offering, it delineates the steps and the entities involved throughout the life of these new instruments. Towards the end, all the features are compared to attempt to understand whether they are going to remain on the market.
Generation of entangled states between two transmon qubits via invariant-based shortcuts with constant drivings

Entanglement generation via optimal drivings is of significance for quantum information science and engineering. Here, an efficient scheme is proposed for creating entangled states between two transmon qubits via shortcuts to adiabaticity with constant Rabi drivings. Two three-level atoms of Cooper-pair box circuits are coupled to a common cavity field of transmission-line resonator and individually driven by adjustable classical microwaves. In the regime of large detuning, we obtain an effective three-state system consisting of qubits and cavity photons. By the invariant-based shortcuts with time-independent Rabi drivings, two-qubit entangled states can be rapidly induced from an easily prepared product state. Compared to the entanglement creation with time-dependent Rabi drivings, our protocol not only becomes more feasible in experiment but also needs shorter times. Moreover, high-fidelity quantum operations can be realized with the accessible decoherence rates. The scheme could pave a promising avenue towards optimal generation of entangled states between superconducting qubits.
PG3: Policy-Guided Planning for Generalized Policy Generation

A longstanding objective in classical planning is to synthesize policies that generalize across multiple problems from the same domain. In this work, we study generalized policy search-based methods with a focus on the score function used to guide the search over policies. We demonstrate limitations of two score functions --- policy evaluation and plan comparison --- and propose a new approach that overcomes these limitations. The main idea behind our approach, Policy-Guided Planning for Generalized Policy Generalization (PG3), is that a candidate policy should be used to guide planning on training problems as a mechanism for evaluating that candidate. Theoretical results in a simplified setting give conditions under which PG3 is optimal or admissible. We then study a specific instantiation of policy search where planning problems are PDDL-based and policies are lifted decision lists. Empirical results in six domains confirm that PG3 learns generalized policies more efficiently and effectively than several baselines.
Integrating Prediction and Attribution to Classify News

Recent modeling developments have created tradeoffs between attribution-based models, models that rely on causal relationships, and “pure prediction models” such as neural networks. While forecasters have historically favored one technology or the other based on comfort or loyalty to a particular paradigm, in domains with many observations and predictors such as textual analysis, the tradeoffs between attribution and prediction have become too large to ignore. We document these tradeoffs in the context of relabeling 27 million Thomson Reuters news articles published between 1996 and 2021 as debt-related or non-debt related. Articles in our dataset were labeled by journalists at the time of publication, but these labels may be inconsistent as labeling standards and the relation between text and label has changed over time. We propose a method for identifying and correcting inconsistent labeling that combines attribution and pure prediction methods and is applicable to any domain with human-labeled data. Implementing our proposed labeling solution returns a debt-related news dataset with 54% more observations than if the original journalist labels had been used and 31% more observation than if our solution had been implemented using attribution-based methods only.
Ridgeless Regression with Random Features

Recent theoretical studies illustrated that kernel ridgeless regression can guarantee good generalization ability without an explicit regularization. In this paper, we investigate the statistical properties of ridgeless regression with random features and stochastic gradient descent. We explore the effect of factors in the stochastic gradient and random features, respectively. Specifically, random features error exhibits the double-descent curve. Motivated by the theoretical findings, we propose a tunable kernel algorithm that optimizes the spectral density of kernel during training. Our work bridges the interpolation theory and practical algorithm.
Influence of socio-demographic characteristics in the self-care behavior scale of patients with arteriovenous fistula

This study aimed to identify the influence of Socio-demographic Characteristics in the Self-Care Behavior Scale of Patients with Arteriovenous Fistula. Descriptive research was carried out using a scale to assess the self-care habits of dialysis patients with CKD. The study concluded that There is a significant relationship between the age of patients and their self-care behaviors p-value. Also, significant relation founded between educational level and AVF self-care behaviors.
Regional educational environment as a factor in the formation ethno-cultural competence of students

АBSTRACTThere is a need to educate a person with an ethno-cultural and all-Russian civic identity in the conditions of multinational Russia.Awareness of one's own culture is the basis for understanding and comprehending the value of another culture.Therefore, one of the actual tasks of modern education is the formation of the ethno-cultural competence of students.The purpose of this work is to identify and substantiate the main parameters of the regional educational environment aimed at the formation of ethno-cultural competence of students.The study is based on the results of monitoring the conditions and features of the organization of ethno-cultural education in the Udmurt Republic.There were 2725 respondents, participants of ethno-cultural education relations.Methods of survey, observation, quantitative analysis, generalization of monitoring results were used by authors.The determining parameters of the regional educational environment are identified and substantiated.The ethno-cultural competence of students includes ethno-cultural knowledge, emotional formation of ethno-cultural and civic identity, ethno-cultural skills, and abilities.The study showed that the process of students' ethno-cultural competence formation and development passes effectively provided that the ethno-cultural content of education is implemented at various levels of the regional educational environment: the education system of the republic, the culture of the people, the communicative spheres of language use.It is advisable to continue comprehensive work on improving the regional educational environment to improve the quality of ethno-cultural education.
Evaluation of educational beliefs of music teacher candidates according to different variables on the basis of educational philosophy

The aim of this study is to determine the demographic and socio-cultural factors that affect the education beliefs of music teacher candidates, and to evaluate them on the basis of their educational philosophies.The participants were composed of 90 music teacher candidates at
Analysis of learning conditions and lifestyle of students of the multidiscipline university during distance learning period

The purpose of this study was to establish changes in the learning conditions and lifestyle of students of the Federal State Budgetary Educational Institution of Higher Education "Kabardino-Balkarian State University named after H. M. Berbekov" (KBSU), when switching to distance learning during the epidemic of a new coronavirus infection (COVID -19).We conducted an anonymous survey of 256 students using the online Google Forms in the period from January 27 to February 8, 2021.The study revealed changes in some components of the learning conditions and lifestyle of students with their transfer to the distance learning: an increase in preparation time for classes among 42.9 % of respondents, an increase in the number of cigarettes smoked in all smokers, a decrease in physical activity among 62.9 % of respondents.At the same time, the consumption of vegetables (36.7%) and fruits (43.8%) increased, the frequency of eating in cafes and restaurants decreased in the absence of changes in the frequency of buying or ordering ready-made food among all students, sleep duration increased among 60, 9 % of students.The nutrition changes of students were influenced by the restrictions taken in the region to prevent the spread of coronavirus infection.The results of our study indicate a need to monitor the preparation time for classes, level of physical activity, smoking and development of recommendations for students on the organization of educational and physical activities during distance learning period.
Regional component of education as the key factor of effective development of the professional orientation (based of the arctic zone of the Russian Federation)

In the higher education system, there is a tendency of continuous changes, the search for opportunities or conditions for multi-level, interdisciplinary education, additional knowledge, professions that will allow specialists to be more competitive, mobile, and able to cope with the challenges of our time.The article presents the content of "professional orientation of a person".The authors revealed the concept of "the factor of effective formation of the professional orientation of a person", determined the criteria and indicators of the formation of the professional orientation of students in the Arctic zone of the Russian Federation.The developed model of the professional orientation of students in the Arctic zone of the Russian Federation, formed during the survey of students of secondary professional and higher institutions of the Arctic zone of the Russian Federation, is presented through the example of the Murmansk region.The model was tested during special professional events with graduate students.The results of the survey and testing are presented in the article in the form of graphs.
KafkaProxy: data-at-rest encryption and confidentiality support for Kafka clusters

Apache Kafka has become a popular tool for building distributed systems. It supports a diversity of use cases that benefit from decoupled N-to-M communication such as publishing IoT data, decoupling and load-balancing microservices, and serve as a central hub for data in a distributed application. Nevertheless, Kafka's security is restricted to encrypted communications and authentication, leaving data unprotected in memory and on the disks. In this work, we design and implement a transparent, drop-in component that provides encryption to incoming and outgoing data in a Kafka cluster. Our component leverages confidential computing techniques not only to ensure data-at-rest encryption, but also to protect data and encryption keys from the operators of the Kafka Cluster. Our evaluation shows that the KafkaProxy can handle message streams with latency overhead of around 10%. Finally, in cases where throughput is impacted, simple replication of the KafkaProxy can mitigate the issue.
An infrared image super-resolution imaging algorithm based on auxiliary convolution neural network

Convolution neural network has been successfully applied to the super-resolution method of the visible image. In this paper, we propose an infrared image super-resolution imaging algorithm based on auxiliary convolution neural network, which uses the detail information provided by the visible image under low-light conditions for super-resolution imaging of infrared image. In this algorithm, infrared image and visible image are input into the convolution neural network at the same time to obtain high resolution infrared image. The results show that the super-resolution infrared image has more detailed information. Compared with other super-resolution methods, the proposed network can obtain the high super-resolution reconstruction efficiency.
STUDENTS’ PERCEPTION TOWARD ENGLISH TEACHERS’ QUESTIONING IN CLASSROOM INTERACTION

This research focused on English teachers’ questioning and students’ perception toward teachers’questioning in classroom interaction. The qualitative method was used in this research thatemphasized on discourse analysis. Two English teachers and twenty students in Senior High School 1Pinrang were the samples that were taken through purposive sampling technique. There were threesteps in collecting data such as video recording, observation checklist and interview. In process ofcollecting data, there were some steps namely observing the teaching and learning process tofind out the questioning strategies used by English teachers, recording the data by usingaudio and video recording, filling the observation checklist while recording. Thus, theinterview was done to find out the students’ perception toward the teachers’ questioning. Asthe result, there were three types of questioning that were used by the English teachers in classroominteraction namely procedural, convergent and divergent question. Furthermore, twenty students whowere the sample in this research gave positive perception toward the English teachers’ questioningsthat teachers’ questionings were the way to motivate in learning process, improve the interaction andthe English ability especially in vocabulary.
IMPROVING SPEAKING ABILITY OF THE SECOND YEAR STUDENTS OF SMK NEGERI 1 SINJAI THROUGH SMALL GROUP DISCUSSION

The objective of this research is to find out the improvement of studentsspeaking ability through small group discussion. The researcher applied quasiexperimental method. The population of this research is the second year students ofSMK Negeri 1 Sinjai. The researcher used total sampling technique, where two classeswere taken as sample, class of 2 AK 1 consisting of 20 students as the experimentalgroup, and class of 2 AK 2 with 20 students as a control class. The findings of the studyshowed that small group discussion activated the students. The result of data analysisshows that t-test value is greater than t-table value (4.81 &gt; 2.042) at level of significance(p) = .05 with degree of freedom (df) = 19. It means that there is a significant differenceof speaking skill between two groups and it indicates that null hypothesis (H0) isrejected and alternative hypothesis (H1) is accepted. It is also supported by theobservation checklist analysis that shows the students’ progress from each treatment.Therefore, it can be concluded that the use of small group discussion can improve thestudents’ speaking skill.
Sistem Pendukung Keputusan Penentuan Penerima BLT Menggunakan Metode SAW

Sidomulyo Village is a village located in the Lyric sub-district, Indragiri Hulu district, Riau Province. According to data obtained by researchers, there were 35 Regency Covid-19 BLT recipients and 51 Provincial Covid-19 BLT recipients. Then there were 95 recipients of BLT DD (Village Fund). In Sidomulyo Village, the recipients of direct cash assistance were only through data collection. This Decision Support System for Determination of Assistance uses the Simple Additive Weighting (SAW) method. The purpose of designing and making a Decision Support System for Determining Direct Cash Assistance is to assist Sidomulyo Village in receiving assistance. In the system that supports direct cash assistance, there are several criteria and alternatives used to determine direct cash assistance. The criteria used are: Occupation, Age, Number of Dependents, Income and Expenditures. While the alternative is all the people listed in the data recipients of direct cash assistance in the village of Sidomulyo. The results of this study are in the form of Determination of Direct Cash Assistance which helps Sidomulyo Village in determining.
Integrating AI Techniques in Requirements Analysis

Requirements Analysis (RA) remains one of the most central processes in requirements engineering. It is a process of evaluating and discovering possible structures to create a contracted set of broad and reliable requirements. The major aim of requirements analysis is to produce a requirements specification document with great quality. The analysis of study exposes that experts have arranged major supports by developing various methods/tools/framework/techniques of requirement analysis process. Though, one of the major problems faced by developers is poor communication and frequently changes in requirements. These issues may lead to incompetent outcome and termination of the system development. The previous investigation exposes that Artificial Intelligence (AI) methods may support in this by restricting alterations in requirements and to propose effective communication between designers and users. The purpose of this work is to categorize the challenges in every stage of the requirements analysis and incorporation of AI techniques to solve these known challenges. Moreover, the research also determines the association between such challenges and their potential AI answer/s through Venn-Diagram. Prior studies expose that more than one AI technique available for some of the challenges, and some of the challenges are still open for further research, no AI techniques has been reported yet. Keeping in observation the significance of the area, foremost analysis methods and their related issues have already been recognized in one of our prior papers. This study is an addition of our prior effort and here, an attempt is made to incorporate and describe AI techniques in various requirements analysis techniques.