Reviewerly/exHarmony huggingface dataset:
Uso de las herramientas tecnológicas para el desarrollo de la interactividad como competencia clave en los estudiantes universitarios

The research analyzes the incidence of the use of technological tools in the development of the key competence called: "use technology interactively" in university students. The study is methodologically based on an exploratory and descriptive type of research, from a quantitative approach, with a non-experimental design. Two questionnaires were applied: one at the beginning of the investigation and another at the end of it. The results evidenced the satisfaction of the students for the support received through the technological tools used in the teaching-learning process, specifically for the availability of materials and the development of skills, for the motivation in carrying out activities, the flexibility in reading and writing and ease in the formation and use of the electronic portfolio. It concludes with the importance of using technological tools in this process to develop the aforementioned key competence and, to facilitate the insertion of the university student in the labor field, expanding the skills and abilities required and thus offering greater contributions in their professional performance.
Feature based image registration using CNN features for satellite images having varying illumination level

In the image registration, the sensed image is aligned to the reference image to find the subtle changes in the two images.These images may be of the same scene, but it can be multi-view or multi-sensor or multi-temporal.Various fields in which image registration is required are remote sensing, where registration is required for image mosaic, landscape planning, etc. *Author for correspondenceThe medical field, where image registration is required for monitoring of tumor growth/treatment, magnetic resonance image, etc., and computer vision, where image registration is required for automatic change detection, target template matching, etc.Based on various criteria, image registration methods can be categorized.Brown divided image registration into four classes based on image acquisition [1], while Zitova and Flusser classified image registration techniques into area-based methods and feature-based methods [2].Area based methods are applied on pixel intensity values which provide distinctive information.Feature based methods use features of the image where distinctive information is provided
INSTANT CONTACTLESS COVID TESTING USING BOOTH AUTOMATION

In view of current epidemic Covid testing plays a crucial part in fighting the epidemic.The main end of this design is to design a fully automated instant contactless Covid testing cell system by which person details is covered using RFID technology.This design makes use of micro regulator.It acts as heart of the design.This onboard computer can efficiently communicate with the affair and input modules which are being used.We use regulator memory to leave some set of assembly instructions.When the micro regulator gets the data from the RFID Reader, Automatically the label details related to the person along with the sample collection details will be transferred as an SMS along with the test results to the stored mobile number.The system also provides both audible and visual cautions using TV and Buzzer.During the epidemic period, testing of Covid is a crucial part in order to fight the contagious contagion.It's relatively significant that this Covid testing is being carried out only in the Covid testing centers, but there are a lot of disadvantages with regard to homemade testing methodology.The reason being some of the tests are time consuming and delayed, wherein it's subordinated to mortal crimes due to a large quantum of sample collection.
Improved Data Encryption Standard Algorithm using Zigzag Scan for Secured Data Transmission

The cryptosystem is a combination of cryptographic algorithms used to provide security services for the information. One of them is the data encryption standard also known as DES which is a symmetric-key block cipher released by national bureau of standard (NBS). DES is a block cipher and perform encryption of each block of size 64 bits. Encryption of the data by using an algorithm which translates the original data into an unreadable format which is not easy for the intruder to attack. The DES is secure than the other cryptosystems, because the time required for processing cryptanalysis has minimized and because of the development in the hardware technique, the traditional DES may be unsafe by different kinds of attacks by the different cryptanalysis. This paper implements a new design of DES called the Improved DES which exhibits that the improved DES is secure than the DES against differential cryptanalysis. It divides each substitution box into four sub blocks of 16 bits and then executes the zig-zag function of each of the 4-sub blocks. It improves the standard encryption levels by columnar transposition.
Virtual Business Simulation as a Tool Fostering Modern Teaching Methods in Higher Education Institutions

Contemporary methods for education have always been the main point in offering the best practices on teaching and learning in higher education institutions. Recently during, and after the pandemic, digitalisation of teaching as a process has accelerated to a new level. Different companies are working and developing new digital and even virtual simulations that are offering not only to students, new and modern ways of enhancing their skills in managing different situations just like in real life. These new technologies are providing students and higher education institutions with opportunities to bring ’‘close to real life ’’experiences with lower costs and fewer procedures. Learning-based virtual simulation games belong to a new developing approach in education. This paper demonstrates the use of a business simulation game in the process of flourishing skills and managerial competences. We describe the tool - Revas Business Simulation Game as a potential instrument facilitating change in competences, skills and attitudes, crucial on labour market.
Algorithm Configuration Problem

The field of algorithmic optimization has significantly advanced with the development of methods for the automatic configuration of algorithmic parameters. This article delves into the Algorithm Configuration Problem, focused on optimizing parametrized algorithms for solving specific instances of decision/optimization problems. We present a comprehensive framework that not only formalizes the Algorithm Configuration Problem, but also outlines different approaches for its resolution, leveraging machine learning models and heuristic strategies. The article categorizes existing methodologies into per-instance and per-problem approaches, distinguishing between offline and online strategies for model construction and deployment. By synthesizing these approaches, we aim to provide a clear pathway for both understanding and addressing the complexities inherent in algorithm configuration.
Enhanced Fuzzy Logic Pre-Processing Technique Using Hybridized Bat and Particle Swarm Optimization Algorithm for Feature Selection

In the modern era, the number of diseases is increasing and it is very crucial to diagnose them.One among them is the hepatitis virus in which the proper identification of symptoms is tedious.Machine learning algorithms are essential in recognizing the disease in the earlier stages.In this paper, a novel pre-processing technique and feature selection (FS) method are proposed to achieve improved accuracy with less time complexity.The proposed methodology is divided into three phases: In the first phase, the pre-processing technique such as Multiple Imputation with weight based fuzzy logic (MI-WFL) is applied to decrease the classification error.In the second phase, the correlation-based hybridized bat and particle swarm optimization (CHBPSO) FS algorithm is used to minimize the time complexity and maximize the accuracy rate.In the third phase, the poly kernel support vector machine (PK-SVM) classifier is implemented to avoid overfitting issues.According to the results of the experiments, the CHBPSO algorithm outperforms in the accuracy rate of 96.15%, and classification error for the following metrics mean absolute error (MAE) is 0.17, root mean squared error (RMSE) is 0.23, relative absolute error (RAE) is 49.66, and root relative squared error (RRSE) is 54.62 are lower than the existing algorithms.Furthermore, the proposed solution has attained less processing time of 1.6 sec due to the reduced optimal features.
Application of The Drill Method to Improving Science Learning Outcomes

The purpose of this study is to describe the application of the drill method in teaching science at the same time knowing the goodness drill method on learning outcomes of students. Subjects chosen because statistics by developing the notion among students that this course is difficult to understand at once a few of those who obtain superior value (A). Through the pre-experimental study, one group pretest-posttest design in the sixth semester students of class D PGSD FKIP Unram regular afternoon, with 44 samples of 50 students purposive random sampling. Performed drill application of the method to the class VI/D through the afternoon, integrative stage, fixation and autonomous learning statistics. The mean pretest and posttest results to the 44 students of the samples obtained through three implementation pretest and posttest then compared. The results showed a mean posttest learning outcomes (69.41) is better than the average learning outcomes pretest (53.05). Test results found the normalized gain &lt;g&gt; g = 0.348 (moderate classification). Indicated drill method can improve student learning outcomes statistics, indicated by differences in learning outcomes and pretest posttest at 16.36 and significant in the medium category
Ontological Engineering Overview

In order to understand the stigmatic nature of mental health, a forensic simulation of the mental health system is under development. This presentation provides an overview of the subject mater associated with the understanding of Ontological Engineering. Ontological engineering is expected to provide a foundation of so-called Content-Directed Artificial Intelligence which relies on the development of an integrated World Knowledge DataBase (WKDB) necessary for the understanding of mental health.
Research on Strengthening Self-education and Self-management of Higher Vocational Students in the New Era

In recent years, with the continuous promotion of education reform, the importance of higher vocational colleges in the whole higher education has been highlighted.With the continuous popularization of higher education in China, the enrollment of higher vocational colleges has been expanding, and the education and management direction of college students proposed in the process of college education reform has also changed accordingly.In order to strengthen the talent training strategy of the times, we must enable college students to achieve self-education and self-management.Influenced by the development of information technology, students' learning mode and thinking mode have been greatly affected.The traditional teaching mode that takes school education as the whole has been difficult to adapt to the current educational requirements.Information network and other means also provide applicable conditions for students' selfeducation and self-management.At the same time, in the process of self-education and selfmanagement, students' thinking forms and self-consciousness can be developed, and their personal ability and comprehensive quality can also be greatly improved.
A study on the relationship between college students' academic participation and academic achievement: Focusing on the comparison of academic data of low-achieving students and high-achieving students

Objectives The purpose of this study is to compare the differences in academic participation between the low-achievement group and the high-achievement group according to the level of academic achievement, and to identify the relationship between the factors of academic participation and academic achievement. This is to preemptively identify academic participation factors related to academic achievement at the university level and prepare strategies for customized learning support for each learner's characteristics.&#x0D; Methods For the purpose of this study, a total of 306 students from A University located in Gyeonggi-do were selected as subjects of study, one with a score of less than 2.5 and those with a score of 4.0 or higher based on the GPA, which is the average GPA of the semester. In addition, cumulative academic data related to academic participation and academic achievement were collected and analyzed. Independent variables The variables for academic participation are attendance score, course credits, number of LMS accesses, number of access to the non-department integrated system, number of times to participate in the non-department program, the number of consultations with advisors, and the number of book loans. Dependent variables are GPA, which is academic achievement, and whether or not academic achievement is low or high. For data analysis, SPSS 28.0 statistical program was used. An independent sample t-test was conducted to compare the difference in academic participation between low-achieving students and high-achieving students, and multiple regression analysis was performed to verify the relationship between academic participation and academic achievement.&#x0D; Results According to Research Question 1, the degree of academic participation was found to be statistically significantly higher in the high-achieving group than in the low-achieving group in attendance score, number of credits taken, the number of LMS accesses, the number of access to the non-departmental integrated system, the number of times of participation in the non-departmental program, and the number of consultations with the advisor. According to Research Question 2, It was confirmed that the higher the attendance score, the number of credits taken, and the number of consultations with the advisor, the higher the academic achievement level.&#x0D; Conclusions In this study, the fact that the difference in academic participation between the two groups according to the level of academic achievement was identified and the relationship between academic participation and academic achievement was reconfirmed has educational significance as the justification for differentiated educational support for each group and the establishment of evidence. In addition, by recalling the importance of academic data, it can be used as a reference material for educational use of academic data in universities in the future.
SECURE VOTING ON BLOCKCHAIN-BASED CLOUD COMPUTING SHOW FOR EVM EXCHANGE

Secure voting may be a crucial application of blockchain advancement, but guaranteeing the astuteness and protection of voting can be a complex issue.This record proposes a blockchain-based cloud computing appear on the Ethereum Virtual Machine (EVM) trade to address this issue.Our dissidents will utilize savvy contracts to screen vote preparation, but the votes themselves will be put away off-chain in a secure cloud capacity framework.We utilize agreement calculations based on Proof-of-Stake (PoS) measures to guarantee voting preparation choices.This degree guarantees that authorized centers can take part, so to talk, within the preparation of votes, which votes are numbered precisely.Moreover, we propose a novel cryptographic plot that permits for exact numbering of votes whereas ensuring vote mystery.Our appear is outlined to be versatile and successful in arrange to form it reasonable for large-scale voting scenarios.demonstrate.Our comes about show up to supply a flexible and able include for secure voting whereas guaranteeing voting precision and secrecy.
G<scp>eophysics</scp> Bright Spots

Welcome to the latest installment of Geophysics Bright Spots. There are a number of interesting research articles in the recent issue of Geophysics. Here is an article that piqued the editors’ interests.
A Detection Method of Self Explosion Defect of Transmission Line Insulator Based on Cascade R-CNN

In this paper, a method for detecting the self explosion defect of transmission line insulator based on Cascade RCNN is proposed. This method is proposed to improve the accuracy of insulator defect detection based on deep learning. The ResNeXt101 network is used as the feature extraction network of this method. This method improves the generalization ability of the network. It reduces the number of super parameters without increasing the network parameters, and reduces the difficulty of network design and computational overhead. It improves the detection accuracy of the self explosion defect of transmission line insulator. This paper selects three common methods for comparison: Cascade RCNN detection method with ResNet101 as feature extraction network, Faster RCNN detection method with ResNeXt101 as feature extraction network and RetineNet detection method with ResNeXt101 as feature extraction network. Through experimental analysis, the proposed method has higher reliability, average accuracy and stronger generalization ability. It significantly improves the detection accuracy of self explosion defects of transmission line insulators.
VGTC Virtual Reality Best Dissertation Award

His research interests lie at the intersection of optics, graphics, perception, optimization and machine learning.Dr
Determination of Generator Maintenance Level on Motor Tanker Using Fuzzy Logic

The electricity necessity on the motor tanker are supported by generators with a capacity of 3x1,225 MVA. This generator is used to drive the load of the main engine, pump, cargo plant, and steering system. The problem is how to know the condition of generator performance to be standardized because the generator operation must be available to use to support the ship operation. Consequently, if the generator does not work optimally, the ship operation will be hampered and can be detrimental to the company’s operation. The solution to this problem is the need to carry out appropriate and standardized maintenance. This study focuses on determining the maintenance level for a 3x1,225 MVA ship generator. The model is specified as a scheme of the generator maintenance system. The parameters set include: vibration, insulation resistance, power, and fuel consumption. Fuzzy logic is used to define maintenance actions: corrective, planned, and predictive. The object of this investigation is on MT Salmon Mustafa. The results of this research are that fuzzy logic can be used to determine the level of maintenance actions. The average percentage of the error or uncertainty level measured both by four input variables and by Fuzzy logic consisting of three conditions is 6.9952%. The truth level of the calculation results is 93.0048%. This indicates that the calculation results are sufficiently accurate and reliable.
Feature integration and feature enhancement based object detector

A one-stage object detector based on SSD, named FIFENet (Feature Integration and Feature Enhancement Network), is proposed in this paper to settle the deficiency of SSD in small objects detection. Two blocks are designed in FIFENet: a feature integration block and a feature enhancement block. Feature integration block fuses the feature map in shallow layers to improve the performance on small objects. Feature enhancement block adopts the residual network (Res2Net) and attention mechanism to enhance feature integration. Experimental result shows that the mean average precision (mAP) on PASCAL VOC2007 data set is 3.1% higher than vanilla SSD, and the accuracy improvement on birds, bottles, chairs, and plants are 3.6%, 9.5%, 5.4%, and 5.5% separately. Results demonstrate that the FIFENet can achieve high detection accuracy while maintaining real-time performance.
Confianza: E-commerce Blockchain Website ebsite

Blockchain in an enterprise is a growing trend in the tech industry. Blockchain is an era that is used to transfer and keep information in a green and secure manner. It is used to create and confirm transactions on a distributed ledger. Many demanding situations are confronted by using e-commerce websites, including information breaches, fake reviews, spyware, and many others. For that reason, blockchain is applied to securely keep and affirm data. Through this, proper statistics are attained. Deciding on the appropriate blockchain that is on hand, adaptable, and within your means is pivotal in growing any commercial enterprise model. With the use of an e-commerce website based totally on blockchain technology, the organization will use the generator to create a new way of selling items and services in the future. The term era can also be used to describe the improvement of recent services and products. Therefore, it is a powerful and consumer-pleasing tool.
Analyzing Negation Markers in the Online News Article

By looking at their smart phones people automatically read what they find on the internet. People today tend to choose digital newspaper than traditional newspaper, from the economy side it is cheaper, and of course it is paperless, in short it is so much easy than reading the traditional one. There are many online newspapers that we can get easily from the internet. The focus in here is by knowing the negation markers used in Indonesian online newspapers. As reader, we can easily get the point of what the article said. Related to such problems above, the aim of the research is to analyze the negation markers in the online News. This research is conducted by using descriptive qualitative method. The data are collected from Indonesian “Jakarta Globe” Online article. Literature review and relevant research have been observed to obtain the description of the data. From the data gained, it can be concluded that the most frequently used of Negation is found in Tenses (41.18%), followed by the used of Negation in Words (39.22%), and the least is found in Modal-auxiliaries (19.61%).&#x0D;
IMPROVING EFFICIENT STUDENT CAREER RECOMMENDATIONS USING MACHINE LEARNING

This research aims to develop and improve the model's efficacy for student career recommendations using feature selection, data sampling, and machine learning techniques.The results showed that the wrapper approach improved the model's performance when applied to over-sampling techniques.In particular, a model combining k-mean, Synthetic Minority Over-sampling Technique, and Edited Nearest Neighbor methods will significantly improve model performance.Additionally, the model developed based on machine learning showed that the model using the Multi-Layer Perceptron Neural Network technique had a higher efficiency than other classifiers in this experiment.Finally, when developing the model using the wrapper, k-mean, Synthetic Minority Over-sampling Technique, Edited Nearest Neighbor, and Multi-Layer Perceptron Neural Network, the model is suitable predicts student careers.This model has a prediction accuracy of 95.88% and a root mean squared error of 2.0968.The most accurate models using the classifier are Support Vector Machine, k-Nearest Neighbors, Random Forest, Decision Tree, Naïve Bayes, and Logistic Regression.
Market View: Fresh Focus

Nursery WorldVol. 2023, No. 5 ManagementMarket View: Fresh FocusArun KanwarArun KanwarManaging partner at Cairneagle, on the latest trendsSearch for more papers by this authorArun KanwarPublished Online:3 May 2023https://doi.org/10.12968/nuwa.2023.5.44AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareShare onFacebookTwitterLinked InEmail View article FiguresReferencesRelatedDetails 2 May 2023Volume 2023Issue 5ISSN (print): 0029-6422ISSN (online): 2059-9358 Metrics History Published online 3 May 2023 Published in print 2 May 2023 Information© MA Education LimitedPDF download