Reviewerly/exHarmony huggingface dataset:
Phenomenon of the Regional Sense of humor in the Tuscan Poetry

The article considers the phenomenon of the national Tuscan sense of humour and the influence of local mentality on the poetry of the region. Quotes from the pieces of Guittone D’Arezzo, Rustico di Filippo, Dante Alighieri, Lorenzo de’ Medici, Francesco Berni and other authors of various periods, from the 13th to the 20th century, demonstrate in chronological order which part the specific Florentine irony takes in the process of formation, development and transformation of the Italian comic verse (or realistic verse). This genre arose not only as a poetical method but also as a reaction to the social and political situation. Comparative analysis of the poems allows us to follow the evolution of the Florentine poetic tradition and draw the conclusion about the cyclical nature of the literature process, confirmed by the regular return to the debunking of excessive tragedy in Italian poetry by the comic verse. In addition, the article reveals the common features of comic verse of different historical periods, which consist in the similarity not only of themes and motives but also of comic techniques based on the characteristic sceptical view of the life of Tuscans.
Prayatul Matrix for Evaluating Clustering Algorithms: A Direct Comparison Approach

&lt;p&gt;Performance comparison of clustering algorithms are often done in terms of different confusion matrix based scores obtained on test datasets when ground truth is available. However, a dataset comprises several instances having different difficulty levels. Therefore, it is more logical to compare effectiveness of clustering algorithms on individual instances instead of comparing scores obtained for the entire dataset. In this paper, an alternative approach is proposed for direct comparison of clustering algorithms in terms of individual instances within the dataset. A direct comparison matrix called Prayatul Matrix is prepared, which accounts for comparative outcome of two clustering algorithms on different instances of a dataset. Five different performance measures are designed based on prayatul matrix. Theoretical analysis shows proposed measures satisfy five important properties such as scale invariance, data invariance, permutation invariance, monotonicity and continuity. Efficacy of the proposed approach as well as designed measures is analyzed empirically with four clustering algorithms on widely used standard datasets. Indications of proposed measures are compared with confusion matrix-based measures as well as other three permutation invariant measures. Results are evident that the newly designed measures are capable of giving some important insight about the clustering algorithms, which were impossible with the existing measures.&lt;/p&gt;
Development of Learning Media Through Traditional Rimau Langkat Games Based on Macromedia Flash to Improve Cultural Literacy

The research aims to develop learning media through traditional Rimau Langkat games. Nowadays, character education and cultural literacy are needed to create a generation that has cooperation, togetherness, and nationalism for each other and thus local wisdom has values that can be used to teach character education. This research is research and development (R&amp;D) with the 4 D design proposed by Sivasailam Thiagarajan. 4 D design consists of define, design, development, and dissemination. The research involved experts in learning media, Langkat culture, and Rimau Langkat Games to assess the digital storytelling. The sample is fourth-semester students in English Department Study Program, STKIP Al Maksum. The research used one group pre-test post-test to know the influence of the electronic module in teaching character education to the students. Based on the discussion, the expert in learning media, Langkat culture, and language was assessed electronically in the two stages. In the first stage, the electronic module was invalid the score range was 58%. In the second stage, the electronic module was valid the score range was 90%. Furthermore, based on the t-test, the electronic module was effective to teach character education to the students.
Nutrition Counseling for Pregnant Women and Making Healthy Drinks from BIT (Beta Vulgaris L.) to Prevent and Overcome Iron Nutrient Anemia

Anemia is often caused by a lack of iron in food; parasites in the body consume substances that inhibit the absorption of iron before, during, and after eating, such as the tannins found in tea. The goal of this study is to improve mothers' understanding of pregnant women about iron nutritional anemia and understanding of making healthy drinks from beetroot (Beta vulgaris L.) and nutritional sources that contain lots of iron and factors that inhibit and facilitate the absorption of iron in the body. The method used involved pretest treatment and posttest. Results and discussion focused on increasing the knowledge of pregnant women about iron nutritional anemia and how to prevent and overcome the occurrence of iron nutritional anemia through the consumption of various sources of iron nutrition. There has been a change in understanding of the pharmacist's role as a caregiver; this can be seen in question no 1. There has been a change in understanding of how to get medicine at a pharmacy (Dagusibu); this can be seen in question no 2. There has been a change in understanding of getting drug information; this can be seen from the correct answer to question no. 3.
Matrix sketching for supervised classification with imbalanced classes

Matrix sketching is a recently developed data compression technique. An input matrix A is efficiently approximated with a smaller matrix B, so that B preserves most of the properties of A up to some guaranteed approximation ratio. In so doing numerical operations on big data sets become faster. Sketching algorithms generally use random projections to compress the original dataset and this stochastic generation process makes them amenable to statistical analysis. The statistical properties of sketching algorithms have been widely studied in the context of multiple linear regression. In this paper we propose matrix sketching as a tool for rebalancing class sizes in supervised classification with imbalanced classes. It is well-known in fact that class imbalance may lead to poor classification performances especially as far as the minority class is concerned.
A designated verifier multi-signature scheme in multi-clouds

Abstract Multi-cloud computing provides services by used different clouds simultaneously multi-signature can be used as the interactive technology between multi-cloud and users. However, the limited resources of some terminal devices make multi-signature, which based on bilinear map, is not suitable for multi-cloud computing environment. In addition, the signers are disclosure in multi-signature so there is the risk of attack. To solve this issues, this paper proposes a certificateless designated verifier multi-signature scheme based on multivariable public key cryptography (MPKC). Firstly, the formalized definition and security model of the proposed scheme are given. Secondly, it is proved that the proposed scheme is against adaptive chosen-message attacks. Finally, the analysis shows that the proposed scheme is more efficiency and suitable for multi-cloud. Moreover, the proposed scheme can hidding signature source to achieve privacy protection.
Geochemical mapping by unmixing alluvial sediments: An example from northern Australia

Alluvial sediments have long been used in geochemical surveys as their compositions are assumed to be representative of areas upstream. Overbank and floodplain sediments, in particular, are increasingly used for regional to continental-scale geochemical mapping. However, during downstream transport, sediments from heterogeneous source regions are carried away from their source regions and mixed. Consequently, using alluvial sedimentary geochemical data to generate continuous geochemical maps remains challenging. In this study we demonstrate a technique that numerically unmixes alluvial sediments to make a geochemical map of their upstream catchments. The unmixing approach uses a model that predicts the concentration of elements in downstream sediments, given a map of the drainage network and element concentrations in the source region. To unmix sedimentary chemistry, we seek the upstream geochemical map that, when mixed downstream, best fits geochemical observations downstream. To prevent overfitting we penalise the roughness of the geochemical model. To demonstrate our approach we apply it to alluvial samples gathered as part of the Northern Australia Geochemical Survey. This survey gathered samples collected over a $\sim$ 500,000 km$^2$ area in northern Australia. We first validate our approach for this sample distribution with synthetic tests, which indicate that we can resolve geochemical variability at scales greater than 0.5 -- 1$^{\circ}$ in size. We proceed to invert real geochemical data from the total digestion of fine-grained fraction of alluvial sediments. The resulting geochemical maps for two elements of potential economic interest, Cu and Nd, are evaluated in detail. We find that in both cases, our predicted downstream concentrations match well against a held-out, previously `unseen' subset of the data, as well as against data from an independent geochemical survey. By performing principal component analysis on maps generated for all 46 available elements we produce a synthesis map to identify the significant geochemical domains in this part of northern Australia. This map shows strong spatial similarities to the underlying lithological map of the area. Finally, we compare the results from our approach to geochemical maps produced by interpolating alluvial geochemical data using two standard methods: kriging and inverse distance weighting. We find that, unlike the method presented here, both these methods can generate maps that are dampened relative to expected magnitude, as well as being spatially distorted. We argue that the unmixing approach is the most appropriate method for generating geochemical maps from regional-scale alluvial surveys.
Flouting Grice’s Maxims in Some Selected Clean Jokes: A Pragmatic Study

Jokes are verbal forms that have humorous effect when told and their humorous effect causes laughing on the part of the listeners. One of the reasons that cause the humorous effect of jokes is flouting the maxims of the cooperative principle, known as Grice’s maxims. Grice’s maxims are seen as a type of agreement between the communicators to cooperate in communication. At the same time, they are not considered as rules. This research tries to explore which of Grice’s maxim(s) are flouted to create the humorous effect in jokes. It also tries to find out which maxim is flouted the most. The sample jokes were chosen randomly by the researchers and descriptive qualitative method is used to analyze the data accumulated. The analysis of the twenty clean jokes chosen is based on Grice's cooperative principle. The analysis shows that the maxim of quality is the most flouted as compared with other ones. And the maxim of relevance is flouted more than the maxim of quantity. Similar researches can be conducted on other types and forms of humor or on other types of jokes.&#x0D; &#x0D;
Analisis Penggunaan Software PlantNet Terhadap Pemerolehan Konsep Dan Keterampilan Prosedural Siswa

The purpose of this research is to assess the intensity of usefulness of technology in the form of PlantNet software on the idea and process (procedural) abilities of students in the topic of variety of living things after three practical activities. This study employed a pre-experimental design with a control and experimental group of 32 students each. This study focuses on the aspects of the idea and process/procedural responses provided by students after attending th(Prastyo et al., 2021)e practicum with and without the PlantNet software. The findings of the SPSS software study utilizing the unpaired t test (2-tailed) generated by the PlantNet program were able to substantially increase students' conceptual skills (sig. 0.0124 &lt; 0,05) and process/procedural abilities (nilai sig. 0.02523 &lt; 0,05). Further study is intended to examine motivation and gender relatedness to mastery of technologies employed during practicum.
Requirement Gathering and Classification: An Engineering Perspective

Gathering the requirement is the vital steps for every successful quality software. Requirement Engineering is the key role for gathering the requirement. The good quality software development require useful data requirement. In recent Software Engineering achieve the data centric with the involvement of big data, artificial intelligence (AI) and machine learning. The most of data gathered from different sources with the evolution of technology, social media and other sources. There are many factors while gathering the requirement to produce the product with good quality. This Paper highlights and extends the research scope of existing requirement engineering to meet the new challenges of requirement clusterization and increase the productivity of product in regards to customer requirement. There is need of applying classification and clustering technique to form requirement clusterization.
Critical Analysis of Data Privacy and Security on IoT Devices in An Organization

Everyone is trying to catch up with the changing technology world of our time. Every object has been computerized to achieve precision and accuracy in service delivery, reduce cost and eliminate error or reduced it to the barest minimum. The advent of telecommunication and inroad into the computer world has opened the space to get every object behave on predefined set of rules. Items ranging from household object to service and manufacturing material have all been programmed to understand and act digitally. The paper x-rayed the uses, challenges and breaches caused by IoT devicesin organizations. This paper took a critical study of the data privacy and security as it relates to IoT devices in an organization. It also enlightens users on the breaches caused by these devices and dangers of these breach on the organizational data security. In order to build a trust in the system, the researcher proffered ways of securing data in IoT devices in organizations to achieve maximum and needed security.
Evidence Recovery using EnCase and FTK in Forensic Computing Investigation

Evidence retrieval from digital devices using tools of forensic computing is always challenging job and an exciting new frontier awaits criminologists in the cyberspace age.The forensic tools such as EnCase and FTK that have been frequently utilized to examine cybercrime are the topic of this research.There are always digital traces of every contact.It is difficult to uncover evidence in cyber-evidence investigations.The recovery of numerous types of files and photos has been achieved after using FTK and EnCase.If AccessData FTK 7.1.0is used in conjunction with EnCase v8.08, then the accuracy of carving evidence is improved over a demo version of FTK.In this way, both tools are useful to cyber investigators for minimal data acquisition, which is applicable to potential evidence recovery from digital media.Cyber Forensics or Forensic Computing, then, is a combination of methodology and technical knowledge for early bird investigators with legal obligations.
Student Digital Literacy Competence in The Era of The Covid-19 Pandemic

Students as the next generation and living in rapid technological developments, are required to master digital literacy competencies.Not only being able to think critically, creatively, and reflectively, but also mastering digital literacy.This study aims to describe the digital literacy competencies of students in the era of the covid-19 pandemic.This type of research is descriptive qualitative research.The research subjects are the second semester students of the Faculty of Tarbiyah and Teacher Training.Data collection techniques using a questionnaire.The results showed that the digital literacy competence of students was at a good level.Although there are still some competencies that need to be explored and improved by students, especially in the competency skills to use various features that support the learning process.
PC-Expo: A Metrics-Based Interactive Axes Reordering Method for Parallel Coordinate Displays

The axes ordering in PCP presents a particular story from the data based on the user perception of PCP polylines. Existing works focus on directly optimizing for PCP axes ordering based on some common analysis tasks like clustering, neighborhood, and correlation. However, direct optimization for PCP axes based on these common properties is restrictive because it does not account for multiple properties occurring between the axes, and for local properties that occur in small regions in the data. Also, many of these techniques do not support the human-in-the-loop (HIL) paradigm, which is crucial (i) for explainability and (ii) in cases where no single reordering scheme fits the user goals. To alleviate these problems, we present PC-Expo, a real-time visual analytics framework for all-in-one PCP line pattern detection, and axes reordering. We studied the connection of line patterns in PCPs with different data analysis tasks and datasets. PC-Expo expands prior work on PCP axes reordering by developing real-time, local detection schemes for the 12 most common analysis tasks (properties). Users can choose the story they want to present with PCPs by optimizing directly over their choice of properties. These properties can be ranked, or combined using individual weights, creating a custom optimization scheme for axes reordering. Users can control the granularity at which they want to work with their detection scheme in the data, allowing exploration of local regions. PC-Expo also supports HIL axes reordering via local-property visualization, which shows the regions of granular activity for every axis pair. Local-property visualization is helpful for PCP axes reordering based on multiple properties, when no single reordering scheme fits the user goals.
FORMATION OF THE CONTENT OF PROFESSIONAL TRAINING OF FUTURE SOFTWARE ENGINEERS IN THE FIELD OF PARALLEL COMPUTING

The article describes the formation of the content of professional training of future software engineers in the field of parallel computing based on foreign fundamental works. The author highlights the problems that arise in shaping the content of professional training of future software engineers in the field of parallel computing. The difficulty of forming the content of professional training of future software engineers in the field of parallel computing is due to the constant rapid development of the theoretical basis for the use of parallel computing and tools for developing parallel and distributed programs. The following main sources were used to form the content of professional training of future software engineers in parallel and distributed computing: recommendations on the subject area of parallel and distributed computing of the ACM and IEEE-CS project, recommendations on the subject area of parallel and distributed computing with the support of NS. and the IEEE-TCPP Committee, fundamental work on parallel computing. Based on the sources described above, five main areas of knowledge were identified, covering the full range of parallel computing issues: mathematical foundations of parallel computing, parallel computing systems (computer basics), parallel programming technologies, parallel problemsolving algorithms, parallel computing, big tasks and specific subject areas. A consolidated content of professional training was formed in the form of a list of thematic sections on parallel calculations, which indicates the presence or absence of the relevant topic. ACM’s analysis of the paradigms of global computer education over the years and the work of foreign authors has led to a list of topics for training future software engineers in parallel computing and a recommended sequence of study paths.
SpecBox: A Label-Based Transparent Speculation Scheme Against Transient Execution Attacks

Speculative execution techniques have been a cornerstone of modern processors to improve instruction-level parallelism. However, recent studies showed that this kind of techniques could be exploited by attackers to leak secret data via transient execution attacks, such as Spectre. Many defenses are proposed to address this problem, but they all face various challenges: (1) Tracking data flow in the instruction pipeline could comprehensively address this problem, but it could cause pipeline stalls and incur high performance overhead; (2) Making side effect of speculative execution imperceptible to attackers, but it often needs additional storage components and complicated data movement operations. In this paper, we propose a label-based transparent speculation scheme called SpecBox. It dynamically partitions the cache system to isolate speculative data and non-speculative data, which can prevent transient execution from being observed by subsequent execution. Moreover, it uses thread ownership semaphores to prevent speculative data from being accessed across cores. In addition, SpecBox also enhances the auxiliary components in the cache system against transient execution attacks, such as hardware prefetcher. Our security analysis shows that SpecBox is secure and the performance evaluation shows that the performance overhead on SPEC CPU 2006 and PARSEC-3.0 benchmarks is small.
ACTIVATION OF STRESS-OVERCOMING STRATEGIES OF FUTURE PRIMARY SCHOOL TEACHERS WITH THE HELP OF MUSIC

The article examines the use of music in the process of students’ implementation of stress-relieving strategies during the period of martial law. A theoretical analysis of musical means (imaginative music-making, therapeutic song-writing, active music-making, joint music-making, joint improvisation, music listening, integrative music therapy techniques, in particular using the Orff approach) as factors in the activation of stress-overcoming strategies was carried out. An empirical study of the structure of personal stress coping strategies of future teachers in war conditions was conducted with the help of a survey and the Coping Strategy Indicator (CSI) method by James H. Amirkhan. The optimal musical techniques for the activation of the mentioned strategies have been found out. According to the empirical study, it was found that the vast majority of students choose musical techniques in view of their positive effect on communication processes, activation of mechanisms of social and psychological adaptation, psychophysiology. Moreover, students choose musical techniques taking in consideration the influence on the processes of excitation and inhibition, self-awareness and self-regulation, and regulation of psycho-emotional and cognitive activity. The analysis of students’ stress-coping strategies indicates a significant advantage of the stress-coping tendency of ‘problem solving’ and ‘seeking social support’, which are considered to be more effective strategies in a stressful situation compared to the ‘avoidance’ strategy, which is not often used by students. Using Spielberger – Hanin State-Trait Anxiety Inventory (STAI) the dynamics of changes of anxiety levels as a result of the musical intervention were analyzed. Based on the results obtained, a positive relationship between musical techniques and the level of situational and personal anxiety was revealed. The tendency to decrease the level of situational anxiety is more pronounced compared to personal anxiety, which corresponds to the norms of response to stressful factors in the conditions of a war situation. According to the research results, a conclusion was made about the expediency of using certain musical techniques during the performance of stress-relieving strategies, in order to do certain tasks that ensure efficiency of their introduction.