Reviewerly/exHarmony huggingface dataset:
Enhanced Security of Advanced Encryption Standard (ES-AES) Algorithm

Encryption is a method of coding information or any other form of confidential, private and sensitive information or data to prevent from unauthorized access, use, misuse, disclosure, destruction, modification, or disruption.Now a day, it is essential to secure data that is at rest in our computer or is transmitted via web against attacks.Several of cryptographic techniques are being used to preserve security and could be classified as: symmetric and asymmetric.A symmetric algorithm named as (AES) is selected for enhancement due to its applicability and widely used algorithm.In AES, among the four stages that are used for encryption and decryption Sub Bytes and Mix Column produce more delay.On the other side, Shift Rows stage contribute to less security level of AES because it uses easy operation that is linear in nature.To overcome these challenges, in the designed symmetrical cryptography algorithm shift row stage of AES is replaced by symmetrical transposition technique to advance security.The simulation result of our Symmetrical Transposition technique has shown better security achievement, with greater than 50% avalanche effect, which means the proposed algorithm makes better confusion and diffusion.Hence, our proposed Enhanced Security of Advanced Encryption Standard (ES-AES) algorithm has better security when compared to original Advance Encryption Standard (AES) algorithm.
Instruction for Newbie Scientists on How to Prepare a Scientific Paper

The abstract is the essence of the full text.Before the main body, the purpose of the abstract is to let readers understand the full text briefly.When an abstract is used, it is always placed at the start of a manuscript or typescript, serving as the starting point for any academic paper or patent application.Abstracting and indexing services for various academic disciplines have the goal of compiling a body of literature on that subject.Furthermore, an abstract summarizes the major aspects of the entire paper in a prescribed sequence, usually in one paragraph of between 200-400 words, and includes: the overall purpose of the study and the research problem(s) you investigated; the basic design of the study; major findings or trends found as a result of your analysis; and, a brief summary of your interpretations and conclusions.Writing scientific publications is difficult for many new researchers, and few receive formal training in how to communicate their findings in writing.Nonetheless, publication is frequently necessary for employment advancement, funding, academic qualification, or a combination of these factors.Generally, an abstract is a short summary of a research article, thesis, review, conference proceeding, or any in-depth analysis of a specific subject that is frequently used to help the reader determine the paper's purpose quickly.
Internal Merge: Why Does It Work This Way? A Matrix Syntactic Approach to Argument Chain

The computational processes of natural human language (C HL ) form a physical object.The first axiom of matrix syntax (MS), which investigates linguistic structures on the complex plane using quantum mechanics-based mathematical tools, converts the [±N] and [±V] values of the Chomsky matrix to [±1] and [±i].This study analyzes the potential developments of this axiom, which has been used previously for raising examples and to describe the grammaticality algebraically.Matrix calculations were performed on elaborate geometries of grammatical and ungrammatical raising examples.Standard analysis based on the minimal computation (MC) principle of the minimalist program (MP) is on the correct track, but it can be combined with mathematical analysis to answer a fundamental question: Why does the internal merge create argument chains (A-chains) in this way, and not in other logically possible ways?With the context-sensitivity hypothesis in MP, MS provides a new perspective on A-chains.Results indicate that a chain-forming geometry contains three areas with distinct growth factors: 1) occurrences (i.e., syntactic contexts of chain members) with a constant rate; 2) backbone-structure building with an exponential rate (i.e., larger φ ~ 1.618), and 3) superposed chain-member copies with a diminishing rate (i.e., little φ ~ -0.618 or σ 1 = 0.7071).The MP-MS collaboration is a viable approach to the structure-building dynamics of C HL and approaches linguistic physics.
Prediction of Hospital Intesive Patients Using Neural Network Algorithm

This study aims to predict whether the patient deserves to be inpatient or outpatient by comparing several machine learning techniques, namely, logistic regression, decision tree, neural network, random forest, gradient boosting. The research method uses three stages of research, namely data collection, data preprocessing, and data modeling. Implementation of program code using google colab and python programming language. The dataset used as the research sample is Electronic Health Record Predicting data. Based on the accuracy results generated in this study, the use of the Neural Network machine learning algorithm to predict hospitalization decisions for patients has proven to be a machine learning algorithm that has the highest accuracy rate reaching 74, 47% compared to other comparison machine learning algorithms, namely logistic regression, decision tree, neural network, random forest, gradient boosting.
Is the Brus Equation Correct?

Research & Development in Material Science Is the Brus Equation Correct? Pao Chi Chen* Department of Chemical and Materials Engineering, Lunghwa University of Science and Technology, Taoyuan, Taiwan *Corresponding author: Pao Chi Chen, Department of Chemical and Materials Engineering, Lunghwa University of Science and Technology, Taoyuan, Taiwan Submission: May 10, 2022;Published: May 23, 2022 DOI: 10.31031/RDMS.2022.17.000902 ISSN: 2576-8840 Volume 17 Issue 1
Spatial Distribution and Sources of Dissolved Organic Matter in High-Antimony Shallow Groundwater in the Xikuangshan Mine, Hunan, China

The origin and composition of dissolved organic matter (DOM) is crucial for fate of antimony (Sb) in aquatic systems.However, there are in which DOM compositional properties, that may better explain the biogeochemical process of Sb, have been absent.This study aimed to understand the fraction, spatial distribution, and spectral characteristics of DOM in high-Sb groundwater (commonly: >0.005 mg/L) from the Xikuangshan Mine in Lengshuijiang, Hunan, China, and explore the characteristics of DOM associated with the formation process of high-Sb groundwater.Inductively coupled mass spectrometry and excitation/emission matrix-parallel factor analysis were used to determine the Sb content, DOM composition, and fluorescence characteristics of 25 shallow groundwater samples collected in May 2021.The dissolved organic carbon (DOC) values in the shallow groundwater varied from 0.38±1.89 to 9.90±1.89mg/L, with a mean of 2.49 mg/L.The DOM consisted of the following four components: C1, terrestrial humus; C2, microbial humus; C3, fulvic acid; and C4, tryptophan.DOM in high-Sb groundwater usually has a high humification index, low biological index, and low fluorescence intensity values.This result will help to understand the effect of DOM on the accumulation and migration of antimony in groundwater during biogeochemical cycling.
Performance Development for Securing the Data Sharing Services in Cloud Storage using Hybrid Encryption

Information sharing among more numbers of users especially the end clients. Preferable people will use famous and financially savvy cloud-based help for associations to share information with clients, and accomplices need of insider clients. This sort of administration further develops information accessibility and I/O execution by delivering and dispersing copies of shared information. Notwithstanding, such a strategy expands the capacity/network assets usage. At present, the Organizations have another choice to re-appropriate their monstrous information in the cloud without stressing over the size of information or the limit of memory. Be that as it may, moving classified and delicate information from believed person, area of the information proprietors by sharing with the public cloud will cause different security and protection chances. Moreover, the expanding measure of huge information reevaluated in the cloud builds the possibility to penetrate the protection and security of these data. Despite all the exploration that has been done around here, enormous information stockpiling security and security stays one of the main issues of associations that embrace computing and huge information technologies.
An Original Algorithm for Password Encryption

Nowdays the password encryption is an indispensable job used in software developing process in order to secure the important information.In this work it is proposed an original and efficient algorithm capable to encrypt a password.In this regard we considered the following terms: real password and encrypted password.The encryption algorithm is based on an original method of character processing.
Artistic and Scientific Activity Professionalization, a Trend of Contemporary Culture

Artistic and scientific activity professionalization is a characteristic and a general trend of contemporary culture that brings new solutions to the problems we face.Thus, it must be said that any work of art is closely related to the space in which the act of creation takes place.If cultural activity were to take place on the principle of the social division of labor, it would take place under ever-closer universes.Dilettantisms are a means of maintaining communication by means of figures and not to the organizational forms.The emergence of the new is not only a problem of psychology but also a more general problem, of a science of the new, which could pursue neogenesis in the material, biological, social, and cultural world, in order to extract principles and rules applicable in practice.For man, art, like science, are ways of organizing matter and at the same time they record the existence of organization and order in the world.
Modeling Parallel Transport

Abstract In 1918, the Dutch geometer Jan Arnoldus Schouten used plaster models of standard curved surfaces to illustrate a novel geometric concept of the geodesic transport of reference frames in curved spaces. This paper discusses Schouten’s use of material modeling in the context of an emerging abstract geometric concept of parallel transport.
The Teachers' Perception towards the Use of Google Translate as a Translation Tool

This study aims to determine teachers' perceptions of the use of Google Translate as a translation tool. The problem of this study is to explain the teachers' perception towards the use of Google Translate as a translation tool. This study uses qualitative descriptive as the research method. The data of this study uses Questionnaire and Interview. The subject is the teachers at Hikmatul Fadhillah and there are 23 teachers. The results of this research showed that teachers can get translation results quickly and easily from Google translate. Almost all teachers realize that Google translate as a translation tool could not be a good tool because the grammar of the translation results is inappropriate. Although this application has weaknesses, teachers still have a positive perception of its use. It is found that all respondents stated they had positive perceptions towards the use of Google translate as a translation tool. Furthermore, the accuracy of Google Translate makes teachers continue to learn and practice grammar while also increasing their translation skills.
Effectiveness of “Learn Social” Platform for Students’ Writing Skill at Universitas Sumatera Utara

The study attempts to find out the effectiveness of an online learning platform provided by the English Department language center at Universitas Sumatera Utara regarding to the English Literature class of 2018 students’ writing skill. The thesis was conducted by analyzing the result of the questionnaire given to the students via google form. The research used the qualitative descriptive method and the indicators proposed by Slavin. Based on the questionnaire result, it showed that Learn Social online platform is effective for students’ writing skill. It is shown through the students’ feedback by answering the questionnaire where the result is positive. The indicators used in order to measure the effectiveness of the online platform are instruction, the appropriate level of instruction, incentive, and time where all four of the indicators get a positive result.
Effect of caffeine on medical student’s performance during exams in Northern Border University (NBU), Saudi Arabia

Background: Caffeine is a somewhat psychoactive element that is broadly ingested.Objective: To confer consequence of caffeine on university student's performance thru exams in NBU, Saudi Arabia.Methods: This is across sectional study was conducted among 395 of the students of Northern Border University, KSA.Respondents were interviewed and filled a predesigned questionnaire.Results: The percentage of pupils that use caffeine was determined to be 92.2% in our survey.Caffeine use had no significant relationship with sex, age, BMI, study level, or GPA (P> 0.05).Coffee was the most prevalent source (89.3%), followed by chocolate (54.4%).In terms of daily caffeine use, 29.9% consume it three times a day, 28.6% two times a day, 13.7% four times a day, and 17.0% three times a day.When it comes to the rationale for daily intake, 40.9% use caffeine to improve attention, 29.7% use it to stay awake during courses, and 28.6% use it for morning vigour.When it comes to the time of day when people consume the most caffeine, 40.1% consume it in the late evening, which accounts for more than half of all cases.61.3% believed that caffeine improves his or her GPA, and 59.9% agreed that caffeine extends study time.The majority (60.4%) believe that caffeine reduces body weight, while 44% have experienced negative side effects as a result of caffeine usage.16.8% of people suffered tachycardia, while 14% felt gastrointestinal discomfort.Conclusion: Almost all studied students of NBU consume caffeine products.The most common source was coffee.Most of the students agreed that caffeine increases study hours and increases his/her GPA.
Intelligent prospector v1.0: geoscientific model development and prediction by sequential data acquisition planning with application to mineral exploration

Abstract. Geoscientific models are based on geoscientific data, hence building better models, in the sense of attaining better predictions, often means acquiring additional data. In decision theory questions of what additional data is expected to best improve predictions/decisions is within the realm of value of information and Bayesian optimal survey design. However, these approaches often evaluate the optimality of one additional data acquisition campaign at a time. In many real settings, certainly in those related to the exploration of Earth resources, possibly a large sequence of data acquisition campaigns need to be planned. Geoscientific data acquisition can be expensive and time consuming, requiring effective measurement campaign planning to optimally allocate resources. Each measurement in a data acquisition sequence has the potential to inform where best to take the following measurements, however, directly optimizing a closed-loop measurement sequence requires solving an intractable combinatoric search problem. In this work, we formulate the sequential geoscientific data acquisition problem as a Partially Observable Markov Decision Process (POMDP). We then present methodologies to solve the sequential problem using Monte Carlo planning methods. We demonstrate the effectiveness of the proposed approach on a simple 2D synthetic exploration problem. Tests show that the proposed sequential approach is significantly more effective at reducing uncertainty than conventional methods. Although our approach is discussed in the context of mineral resource exploration, it likely has bearing on other types of geoscientific model questions.
Look back, look around: a systematic analysis of effective predictors for new outlinks in focused Web crawling

Small and medium enterprises rely on detailed Web analytics to be informed about their market and competition. Focused crawlers meet this demand by crawling and indexing specific parts of the Web. Critically, a focused crawler must quickly find new pages that have not yet been indexed. Since a new page can be discovered only by following a new outlink, predicting new outlinks is very relevant in practice. In the literature, many feature designs have been proposed for predicting changes in the Web. In this work we provide a structured analysis of this problem, using new outlinks as our running prediction target. Specifically, we unify earlier feature designs in a taxonomic arrangement of features along two dimensions: static versus dynamic features, and features of a page versus features of the network around it. Within this taxonomy, complemented by our new (mainly, dynamic network) features, we identify best predictors for new outlinks. Our main conclusion is that most informative features are the recent history of new outlinks on a page itself, and of its content-related pages. Hence, we propose a new 'look back, look around' (LBLA) model, that uses only these features. With the obtained predictions, we design a number of scoring functions to guide a focused crawler to pages with most new outlinks, and compare their performance. The LBLA approach proved extremely effective, outperforming other models including those that use a most complete set of features. One of the learners we use, is the recent NGBoost method that assumes a Poisson distribution for the number of new outlinks on a page, and learns its parameters. This connects the two so far unrelated avenues in the literature: predictions based on features of a page, and those based on probabilistic modelling. All experiments were carried out on an original dataset, made available by a commercial focused crawler.
Comparison of the quality of sampling algorithms from discrete normal distribution on NTRU lattices

Post-quantum cryptography is a field of research that studies cryptographic transformations protected against attacks using quantum computers. For many years, lattice-based cryptography has become one of the most promising solutions to protect against the threat of quantum computing. An important feature of the post-quantum period in cryptography is the significant uncertainty about the source data for cryptanalysis and countermeasures in the capabilities of quantum computers, their mathematical support and software, as well as the application of quantum cryptanalysis to existing cryptocurrencies and cryptoprotocol. The main methods are mathematical methods of electronic signature, which have undergone significant analysis and justification in the process of extensive research by cryptologists and mathematicians at the highest level. The security of signature schemes depends strongly on the standard deviation of the discrete Gaussian distribution, which has a sampling algorithm. In this paper, the most common variants of sampling algorithms were considered and analyzed, because the quality of all algorithms depends significantly on the structure of the lattice for which sampling takes place. A comparison of the quality of lattice sampling algorithms is highlighted. In particular, the paper considers Klein's algorithms (its modification is the Thomas Prest and Dukas algorithm), Peikert's algorithm and the floating-point sampling algorithm. Klein's sampling algorithm, in particular its modification, namely, the Dukas-Prest algorithm, gives the smallest vectors. Theoretically, it is much better than Klein's algorithm on NTRU lattices, but it requires the use of floating-point arithmetic, which complicates greatly the analysis of its security and tocreation of software or hardware implementation.
Analysis of partial key recovery attack on multivariate cryptographic transformations using rank systems

The Rainbow signature scheme, proposed by Ding and Schmidt in 2005, is one of the oldest and most studied signature schemes in multidimensional cryptography. The Rainbow, based on the unbalanced Oil and Vinegar signature scheme, has the necessary cryptocurrency since 1999 with the right parameters. Interest in multivariate cryptography has increased in the last decade, as it is considered to be quantum-stable.&#x0D; Cryptanalysis of the Rainbow and its predecessors was actively developed in the early 2000s. Attacks from this era include the MinRank attack, the HighRank attack, the Bill-Gilbert attack, the UOV agreement attack, and the Rainbow bandwidth attack. After 2008, cryptanalysis seemed to have stopped, until the Rainbow's participation in the NIST PQC project, which motivated the continuation of cryptanalysis. During the second round of NIST, Bardett and others proposed a new algorithm for solving the MinRank problem. This dramatically increased the effectiveness of MinRank's attack, although not enough to threaten the parameters provided to NIST. A less memory-intensive version of this algorithm was suggested by Baena et al. Perlner and Smith-Tone analyzed the Rainbow bandwidth attack in depth, which showed that the attack was more effective than previously thought. This prompted the Rainbow team to increase slightly the parameters for the third round. During the third round, Bellens introduced a new attack that reduced the Rainbow's security by 220 times for SL 1. The Rainbow team claimed that despite the new attacks, the Rainbow's parameters still met NIST requirement.&#x0D; The purpose of this article is to present two new (partial) key recovery attacks on multivariate cryptographic transformations using rank systems.
Second language processing of errors in Korean-to-English machine-translated output

While previous investigations on online machine translation (MT) in language learning have analyzed how second language (L2) learners use and post-edit MT output, no study as of yet has investigated how the learners process MT errors and what factors affect this process using response and reading times. The present study thus investigates L2 processing of MT errors that are caused by syntactic, morphological, and semantic differences between the source and target language and also examines how L2 proficiency and visual display affect this process. Forty-seven Korean learners of English participated in an acceptability judgment task in which they read a Korean sentence and then its translated counterpart in English and had to judge the accuracy of the translated sentence on a four-point scale. The response latencies for the accuracy judgment as well as the total reading times of source and target sentences were measured. The results revealed that (1) learners generally find it harder to reject mistranslations than to accept correct translations, (2) high vs. low proficiency learners focus on different aspects of language when processing translated output, and (3) constant visual access to the source text does not facilitate but rather interferes with processing MT errors.
Recent Trends in Knowledge Graphs and its Applications

In the area of the Intelligent Network, the representations of an information graph have sparked a lot of research interest.Language-based approaches treat each relationship as a single translation from head to tail like Trans E, Trans H and Trans R are simple, efficient and achieving the art state efficiency.Information graphs convey knowledge as a graph with marked edges (relationships) between nodes (entities).The completion of the information graph is an essential activity aimed at predicting the missing relationship between entities.