Reviewerly/exHarmony huggingface dataset:
Feature Deep Learning Extraction Approach for Object Detection in Self-Driving Cars

Self-driving cars are a fundamental research subject in recent years; the ultimate goal is to completely exchange the human driver with automated systems. On the other hand, deep learning techniques have revealed performance and effectiveness in several areas. The strength of self-driving cars has been deeply investigated in many areas including object detection, localization as well, and activity recognition. This paper provides an approach to deep learning; which combines the benefits of both convolutional neural network CNN together with Dense technique. This approach learns based on features extracted from the feature extraction technique which is linear discriminant analysis LDA combined with feature expansion techniques namely: standard deviation, min, max, mod, variance and mean. The presented approach has proven its success in both testing and training data and achieving 100% accuracy in both terms.
Developing Professional Creativity of Teachers Based on Problem Based Learning (PBL)

The article determined the importance and problems of developing the professional creativity of teachers of professional educational institutions in professional training courses. Moreover, the article described the method of conducting practical training based on PBL, and as a result, the indicators of the evaluation criteria were given. The purpose of the article was the methodology of practical training organized on the basis of PBL to increase the professional creativity of teachers of professional education in training courses. Innovative-methodical projects were developed for improving teachers' professional creativity, and creative educational technologies and methods were used at each stage. Based on the mathematical and statistical analysis of the research, the types of personal and professional creativity of teachers were determined and the concept of professional creativity was revealed. A module aimed at enhancing the professional creativity of teachers was included in the curriculum of personnel retraining and professional development courses, and didactic support was developed with helping creative techniques and platforms which were helpful for assessing creative abilities of teachers. As a result, the professional creativity of teachers of vocational education was enhanced by 10%.
An Approach for Data Privacy Management for Banking Using Consortium Blockchain

Banking sectors commit modern working frameworks and models smooth development based on decentralization with keeping money confront in unused ranges and differing activities. Consortium Blockchain Privacy becomes a major concern and the challenge of Most of banking sectors.Development without being hampered being a major concern it can store confirmed, Data privacy includes assuring protection for both insider ad outsider threats therefore access control of Ring signature could help to secure Privacy of inside and outside threats by secure process by RSBAC using CIA triad privacy Confidentiality, Availability, Integrity.This paper proposes a ring signature-based on access control mechanism for determining who a user is and then regulating that person's access to and use of a system's resources. In a nutshell, access control restricts who has access to a system. It also restricts access to system resources to users who have been identified as having the necessary privileges and permissions. The proposed paradigm satisfies the needs of both workflow and non-workflow systems in an enterprise setting. The traits of the conditional purposes, roles, responsibilities, and policies provide the foundation for it. It ensures that internal risks such as database administrators are protected.Finally, it provides the necessary protection in the event that the data is published.
All Physical Information Is Discretely Connected From the Beginning and All Geometrical Appearance Is a Delayed Statistical Consequence

Information is physically measurable as a selection from a set of possibilities, the domain of information. This defines the term "information". The domain of the information must be known together reproducibly beforehand. As a practical consequence, digital information exchange can be made globally efficient, interoperable and searchable to a large extent by online definition of application-optimized domains of information. There are even more far-reaching consequences for physics. The purpose of this article is to present prerequisites and possibilities for a physical approach that is consistent with the precise definition of information. This concerns not only the discretization of the sets of possible experimental results, but also the order of their definition along time. The access to or comparison with the domain of information is the more frequent, the earlier it was defined. The geometrical appearance of our space is apparently a delayed statistical consequence of a very frequent connection with the common primary domain of information.
Understanding the impact of status quo bias and the default effect on decision-making

A recommendation of: Monique Moon Ling YAM, Gilad Feldman Reference points and decision-making: Impact of status quo and defaults in a conceptual replication and extensions Registered Report of Dinner et al. (2011) https://osf.io/5ak6p
The methodological basis for increasing the internal intellectual potential of physical education and sports students

The intellectual potential of a person is closely related to the concept of intellectual capital as a component of human capital. This study aims to consider intellectual potential based on available psychometric methods and establish correlations between this potential and demographic and other easily observable factors. The study involved 128 students from universities and colleges of physical culture and sports located in Pavlodar (Republic of Kazakhstan). The study revealed a strong correlation between the level of academic achievement of the participants and the results of tests of general and implicit intellectual abilities (CCAT and IO4). Also, no significant correlations were found between the results of these tests and the factors of gender, age, and the year of study. A strong correlation was observed between the results of the two tests, which may indicate a close relationship between constantly used and hidden intellectual abilities. The research results can be used to improve the quality of training physical education teachers. The measurement and methodologically correct development of the intellectual potential of teachers multiplies the subsequent increase in human capital at the expense of their prospective students. Keywords: cognitive abilities; cross-disciplinary learning; intellectual capital; intellectual development; physical education.
Retracted: Nursing Intervention Based on Smart Medical Care on the Sleep Quality of Cardiology Patients

[This retracts the article DOI: 10.1155/2021/9947438.].
Retracted: Augmented Reality Research of Measuring X-Ray Dental Film Alveolar Bone Based on Computer Image Analysis System

[This retracts the article DOI: 10.1155/2021/5571862.].
Use of Game Theory in Decision Making in Medicine

While diagnosing patients, doctors decide together with the patient. These decisions are made by the interaction between the patient and the doctor and the modeling of this interaction. At this stage, game theory can be used to model interaction. The use of these models provides significant convenience to doctors. The aim of this study is to show the applications of the game theory approach in medicine.
Improved Phishing Detection using Ensemble Models in Machine Learning

Abstract: Phishing attack is one of the simplest ways to obtain sensitive information from innocent users who are unaware. The main motive of the phishers is to acquire critical information like username, password and bank account details etc. using a fake link which actually looks like a genuine one from an authorized source. Users who have good technical knowledge might be able to identify these links easily but for naive users, this is going to be dangerous as it might lead to loss of privacy and assets. There are other techniques of spam detection based on the sender’s information and content-based detection. In this paper we follow an efficient approach in which we can directly identify an URL if it is Phishing or not by its features using Machine Learning. The aim of this paper is to build multiple Machine Learning models, compare their performances and narrow down to best model based on its performance and efficiency.
DETERMINATION OF RUPTURE DIRECTIVITY USING THE LEVENBERG-MARQUARDT ALGORITHM: A CASE STUDY PHILIPPINE EARTHQUAKE (15 DECEMBER 2019 M_w 6.8)

Earthquake source mechanisms are used to determine local geological characteristics and hazard mitigation. There are several approaches to determine the mechanism of earthquake. In this paper, the relative time of the rupture duration is applied to determine rupture directivity. In determining rupture directivity, the Levenberg-Marquardt (LM) method is proposed to solve the inversion problem. To test the reliability of this method, teleseismic data with an epicentral distance of 40o from the Philippine earthquake on 15 December 2019 6.8, which had a good seismic station distribution with a total of 35 stations, is used. Telesismic data from each station is filtered in the range of 0.25 to 1 Hz to obtain an accurate rupture duration. Furthermore, the rupture duration data set was inverted using the LM method to obtain the direction of earthquake rupture. The results obtained by the curve fitting using the LM method had a good agreement between the observed data and the calculated data. From the curve fitting results, the rupture propagated in the NW direction with azimuth 320.60o ± 2.30o, and this had the same results from previous studies. Therefore, from rupture directivity, the actual fault plane of this earthquake was NP1 which had a strike/dip/rake value of 321o/75o/13o, respectively. The results indicate that the Philippines earthquake of 15 December 2019 had the SE-NW fault orientation, which is part of the Cotabato fault system. The implication of this research is for a preliminary study related to the characteristics of earthquake rupture in areas that have a high level of seismicity. Thus, local residents can avoid areas where ruptures propagate when carrying out earthquake mitigation.
Digital Image Text Recognition Using Machine Learning Algorithms

Abstract: Text recognition is used in various fields like document analysis, picture labeling, and text analysis, etc. The process of recognizing text from image is very crucial.. Employing Maximally Stable Extremal Regions (MSER) and Optical Character Recognition (OCR) algorithms have drastically changed the accuracy and reliability of text detection from photos. Our proposed work suggests a model for text recognition that makes use of both the MSER and OCR algorithms' benefits for the purpose of accuracy improvement and reliability of the digital text extraction procedure. OCR follows cutting-edge techniques to distinguish and identify individual characters, serving as the essential building block for text recognition. However, these algorithms may struggle when dealing with complex backdrops, blurry photos, or text that is structured in an atypical way. We use MSER approach, which excels at recognizing text sections by finding maximally stable regions across various severities and scales, to solve these constraints. The suggested model employs a multi-stage methodology. The MSER algorithm is used for extracting the likely text spots from the input image first. To boost OCR performance, these zones are then fine-tuned using pre-processing techniques including noise reduction and picture enhancement. The OCR system next processes the cleaned-up sections, identifying each region's text using machine learning and pattern recognition methods. The text that is recognized is then further processed to increase the accuracy and refine these findings. Thus, compared to most other models, the text recognition model that is built utilizing the MSER and the CNN (OCR, a component of CNN) algorithm performs better
The Effect of Nutrition Education Using E-Module Media Toward Fiber Intake in Overweight Female Adolescent

One of the factors causing excess nutritional status in female adolescent (FA) is due to the lack of fiber consumption. The West Sumatra Riskesdas 2019: 82.53% of adolescents in Padang consume less fiber and the prevalence of overweight among FA is higher than male adolescents of 16.45%. Some literature states that one of the interventions to increase the awareness and motivate the FA to consume fiber is nutrition education (NE) by using attractive media. E-module is one of the attractive media and frequently used in the learning process. The material presentation is not merely focus on the text, picture, and graphic, however it is also presenting audio, animation, and video. The purpose of this research is to analyze the effect of NE using e-module media toward the fiber intake in overweight FA. This is a mix (R&amp;D and quasi-experiment) research methods of one group pretest and posttest with control designs. The research subjects were all female students at research target schools who met the inclusion and exclusion criteria. The data instrument used the SQ-FFQ form. The data analysis is using a Mann Whitney test. The results of the study explained that the designed nutritional e-module obtained an average validation value namely 90.5% and the practical value of the overall was 92.83%. The results of the Man Whitney test showed that there was an effect of NE with the e-module and it was very effective toward the change of fiber intake for overweight FA in Padang p-value 0.017 (p&lt;0.05).
Automated SMS Classification and spam analysis

The surge in SMS usage as the primary communication method has resulted in a notable upsurge in the quantity of unwanted messages.To combat this issue, an automatic system has been created to categorize SMS messages into either spam or non-spam groups and analyze the attributes of spam messages.The system extracts pertinent characteristics from SMS messages and constructs machine learning models for message classification.Additionally, the system examines the content of spam messages to identify patterns and trends in spam activities.This abstract provides an overview of current techniques employed in spam SMS detection.It explores and diverse avenue for feature decoction and classification, encompassing rule-based methods, machine learning algorithms, and deep learning models.Furthermore, it discusses the challenges present with developing efficacious spam SMS detection systems, such that the dynamic nature of SMS spam and the requirement for substantial training data.Lastly, notable advancements in this field, including the utilization of neural networks and ensemble methods to enhance performance, are highlighted.
A Study on the Effect of Precious Commodity Prices and Macroeconomic Fluctuations on Cryptocurrency Trading in India

The role of currency in the functioning of the global economy is undeniably of utmost importance to people and governments, whose trust in monetary authorities is the sole provider of value to most of the world’s money which is in the form of fiat currencies. An alternative means of value exchange called cryptocurrencies operating entirely through the internet has the potential to dilute public trust in fiat currencies due to many advantages including fiscal decentralization among others. This study examines the relationship between key macroeconomic variables namely bond prices, dollar exchange rates and the price of gold and its derivatives and cryptocurrency trading in the Indian context. The daily frequency data is collected after the Indian Supreme Court’s judgement in March 2020 which overturned a ban on cryptocurrencies which was imposed before it. We aggregated the data using Principal Component Analysis and examined the short-run and long-run relationship between the variables and cryptocurrency trading using Toda Yamamoto Granger Causality Tests and ARDL Error Correction Model. The results reveal valuable insights about public perception of cryptocurrencies either as an investment asset or as a medium of exchange by examining the significance of individual independent variables in both the long and short run.
The informational skill in the didactics of languages-cultures

The informational skill in the didactics of languages-cultures) The study defines the concept of informational competence, within the framework of action-based approaches and project pedagogy in the teaching of culture-languages.After a diachronic presentation of the main methodological trends in foreign language teaching, the study illustrates the adequacy of the action-based approach and, implicitly, of project pedagogy, to the learners' needs in today's society.The definition of the concepts is followed by the presentation of an action-based teaching approach that implements the development of informational competence.The didactic approach proposes to students to do a project by passing through the documentation stage.Documentation involves several steps: choosing the relevant theme for the project, selecting the documentation sources, consulting the documents, writing down essential and relevant ideas for the project, mediating the information read/heard and interacting with learners who have consulted other documentary sources.The description of the teaching approach is followed by a comparative analysis, in which the principles of the communicative vision are examined in contrast with the principles of the action-based vision, in order to highlight the interdependence between the concepts: informational competence, action-based approach and project pedagogy.
Development of Contextual Integrated Electronic Temperature and Heat Modules Based on Qur’an Verses at MTsN 3 Tulungagung

This research contributes to the priorities of "Merdeka Belajar 2021", digitization of schools and learning media, and character education. This study used research and development (R&amp;D) by Borg and Gall, modified by Sugiyono. In this method, there were ten research steps, which are then limited to seven steps. The seven steps are potential problems, data collection, product design, design validation, design revision, product testing, and product revision I. The instruments used came from the validation sheets of material and media experts, as well as electronic module readability questionnaires from MTsN 3 Tulungagung students. Data analysis used linkert scales 1-4. Validation results from media and material experts show valid criteria based on the attractiveness of the appearance and depth of the material, both in terms of contextual aspects and its integration with the Qur’an. Based on the test results, the electronic module is very interesting because it is presented interactively.
Novel Concentric-Circle Technique Interrogates Implicit Category Learning

Prototype, exemplar, and boundary models compete to explain representational-level abstractions during human category learning. Vast majority of previous work use linear categories structures to evaluate learning. We present the development of a novel, circular category structure and leverage it to explore limitations of prototype, exemplar and boundary models. We find that circular categories are readily learned by human participants, and the induced representation is most likely a quadratic boundary. We deductively eliminate prototype theories as an explanation of these circular categories and show that exemplar models, though viable, provide a weaker explanation than boundary models which are best fitted to the present data. These circular category structures offer a promising new technique to studying implicit category learning.
Website Based Patient Clinical Data Information Filling and Registration System

Patient registration is very important in health care services. Various strategies have been implemented in optimizing services, one of which is by developing a web-based outpatient registration system. The purpose of this study is to build a computer-based web-based outpatient registration information system. The type of research used is descriptive by means of a survey, the variables used are flow and outpatient registration procedures, patient data, doctor data, payment method data, polyclinic data. The object of this research is the Outpatient Registration Officer. The instruments used were interview guidelines and observation guidelines, as well as using the Development Life Cycle (SDLC) system development system. Using PHP, HTML, CSS and Java script programming languages, with MySQL database. This information system can make it easier for patients to register themselves without having to go to the hospital first.
Design of the Android-Based Malaria-Mapping Application Mobfabria

Malaria represents one of the tropical diseases and a health problem in the East Nusa Tenggara (NTT) Province. Malaria cases are still high in some districts in NTT, including East Sumba, Central Sumba, West Sumba, and Southwest Sumba. Infants, children, and pregnant women are the high-risk groups to suffer from malaria. The highest number of cases was recorded in Southwest Sumba district with 4,273 cases in November 2022. This situation requires preventive and curative actions to address malaria cases in NTT. These actions include health education and malaria data mapping for high-risk groups in malaria-endemic areas. It is expected that these measures will assist in healthcare services, especially in malaria-endemic areas. Considering the current phenomenon of digital era development, the researchers have designed an Android-based mapping and education application for malaria called “mobfabria”. To develop a prototype of the mobfabria applicatio. This is research and development study. The research was conducted in 2023, where the application test took place from March to April 2023 at the Oemasi Health Center in Kupang District. The research subjects consisted of 5 individuals during the development stage and 15 pregnant women during the evaluation stage. The application created by the researchers can be downloaded from the Play Store: https://play.google.com/store/apps/details?id=com.mobfabria.apps. The research stages are approval, ethical test, instrument test, and application test. The application is developed according to the needs analysis, system design, and database. It was built using Android tools. The assessment by experts in health promotion, media, and malaria practitioners was considered good enough, leading to changes in the application's interface design and data storage units. The data was analyzed descriptively. Mapping and data collection of pregnant women with malaria can be accurately obtained. This application is expected to be used for healthcare services and facilities in malaria-endemic areas.
Pelatihan Pengelolaan Arsip Berbasis Digital Bagi Remaja Masjid Baitul Halim (RBH) Mampang Prapatan Jakarta Selatan

Community Service is a medium to bridge the world of education with society. Remaja Masjid Baitul Halim (RBH) Started as a gathering of Muslim youths, not only for spiritual interests but also as a place to exchange ideas to deal with problems that are being faced together. Information technology media is one of the media that helps a lot in the world of business or organizations, such as facilitating the processing and utilization of digital archives. This Community Service activity aims to improve the performance of the Remaja Masjid Baitul Halim, especially in the manufacture and management of the archives they have. This community service training introduces an application that has been made for archiving digital data that will be studied by Remaja Masjid Baitul Halim. The training was carried out by Lecturers and Students at Nusa Mandiri University. The main purpose of this community service is to train Remaja Masjid Baitul Halim to tidy up digital archive data.