Reviewerly/exHarmony huggingface dataset:
The performance of VCS(volume, conductivity, light scatter) parameters in distinguishing latent tuberculosis and active tuberculosis by using machine learning algorithm

Tuberculosis is a chronic infectious disease caused by mycobacterium tuberculosis (MTB) and is the ninth leading cause of death worldwide. It is still difficult to distinguish active TB from latent TB,but it is very important for individualized management and treatment to distinguish whether patients are active or latent tuberculosis infection.A total of 220 subjects, including active TB patients (ATB, n = 97) and latent TB patients (LTB, n = 113), were recruited in this study .46 features about blood routine indicators and the VCS parameters (volume, conductivity, light scatter) of neutrophils(NE), monocytes(MO), and lymphocytes(LY) were collected and was constructed classification model by four machine learning algorithms(logistic regression(LR), random forest(RF), support vector machine(SVM) and k-nearest neighbor(KNN)). And the area under the precision-recall curve (AUPRC) and the area under the receiver operating characteristic curve (AUROC) to estimate of the model's predictive performance for dentifying active and latent tuberculosis infection.After verification,among the four classifications, LR and RF had the best performance (AUROC = 1, AUPRC = 1), followed by SVM (AUROC = 0.967, AUPRC = 0.971), KNN (AUROC = 0.943, AUPRC = 0.959) in the training set. And LR had the best performance (AUROC = 0.977, AUPRC = 0.957), followed by SVM (AUROC = 0.962, AUPRC = 0.949), RF (AUROC = 0.903, AUPRC = 0.922),KNN(AUROC = 0.883, AUPRC = 0.901) in the testing set.The machine learning algorithm classifier based on leukocyte VCS parameters is of great value in identifying active and latent tuberculosis infection.
Innovative educational policy in Ukraine: Ethnocultural aspects of school education development

The interdependence of innovative educational policy in Ukraine and the ethnocultural aspects of updating the content of school education are explored. It is established that the ethnocultural component in the content of school education remains a relevant direction of scientific research. The article presents an author's educational project developed taking into account the state tasks of innovative educational policy, the scientific, theoretical, and practical achievements of Ukrainian educators, and the analysis of educational realities in the context of the implementation of ethnocultural principles in education of school-age children based on interaction with communities. The article's author emphasizes aspects of implementing innovative educational policy, including the role in determining ethnocultural trends in the development of the content of school education, innovative approaches, modern information technologies, interactive methods, updating curricula, courses, projects, and more. Addressing ethnocultural heritage, studying true history, observing moral and domestic traditions, and knowledge of the language and art of the Ukrainian people and other ethnic groups residing in Ukraine are the desired educational outcomes of school education aimed at preserving and popularizing cultural diversity, fostering tolerance and mutual understanding in Ukrainian society as a whole. The article highlights the need to create new educational content, including the text, action, and result, and innovative educational policy must support these changes, contribute to their implementation, and provide official state documents. The author believes that contemporary school education in Ukraine, even in the context of war, is committed to a peaceful life, contributes to the sustainable development of society, is based on ethnocultural principles of youth education, and develops through interaction with communities and families.
Quizizz as a Medium on Students’ Vocabulary Mastery at SD Negeri 7 Payaraman, Ogan Komering Ilir

This study aims to determine whether or not there is an influence of quizizz media on vocabulary mastery in Indonesian class V elementary school subjects. This study used an experimental method with a research design in the form of a true experimental design. The researcher used a sample consisting of two classes, namely the experimental group in class VA with 20 students including 14 boys and 6 girls while the control group in class VB had 20 students which included 12 boys and 8 girls. In this study using data collection techniques in the form of tests and documentation. The research instrument was a multiple-choice test with 20 valid questions. Based on the results of the hypothesis test using the t-test of two independent samples (independent sample t-test) the value of t-count is 4.123 and t-table is 1.686 with α = 0.05 and df = 38, then t-count ˃ t-table so that Ha is accepted and Ho is rejected so that it can be it was concluded that there was an influence of quizizz media on vocabulary mastery in grade V Indonesian subjects.
A new approach of cryptography using taylor series of logarithm function

This study investigated a novel cryptographic approach involving the encryption of plaintext using the coefficients of a Taylor series for the logarithm function multiplied by its corresponding index. The decryption process utilized the Laplace transform of the logarithm function and its inverse. Through this methodology, several innovative mathematical encryptions and decryption formulas were derived. The study also includes a practical example to demonstrate the broader implications of the findings.
Representations of the Metaverse in the Works of Potter Jason Walker

The current research studies (representations of metaphysics in the works of potter Jason Walker) a concept that refers to To a large extent, by conveying a sense of reality to the recipient by conveying ideas, contents, and connotations. A variety of center hit, dispersion, and rejection of everything that prevails, so our position on the closed text has shifted To the open text, through the role played by cross-pollination in the works of the potter (Jason Walker), which established a clear hypothetical vision of the image represented in the construction of the ceramic work and the thought that was embodied in that image represented by the nature of its unrealistic formations for those ceramic artworks. It is thus considered a logical alternative to shake the previous structures and to find New structures thanks to new technical installations. The research included four chapters, the first chapter concerned the research problem and its importance And the need for it and the aim of the research (to know the representations of the meta virus in the works of Jason Walker), as well as included. Contemporary ceramic works by potter Jason - the chapter includes temporal boundaries for the period from (2009-2020) and Walker, which were completed in America, and the chapter also included a definition of the most important search terms. And he studied. The second chapter, the theoretical framework and previous studies, consists of two sections, the first section. It included (metaverse - cognitive), and the second topic was divided into two axes, the first of which dealt with (Artistic and aesthetic approaches in contemporary ceramics) The second axis dealt with. Contemporary (b- potter style Jason Walker), and the chapter ended with indicators of the theoretical framework and previous studies. The third chapter included the research procedures, as it included the framework of the research community and the adult.
Analysis of Concerns of the Agricultural Sector in the Philippines using Associative Rule

The Philippines is an agricultural country famous for its wide range of natural resources scattered over the archipelago. The country’s agriculture sector comprises four sub-sectors: fisheries, farming, livestock, and forestry. The COVID-19 pandemic, according to the Food and Agriculture Organization, is straining food systems and causing food insecurity across the world. This study used a mixed method that analyzed qualitative data using quantitative analysis. Concerns voiced by agricultural sectors were analyzed utilizing the frequencies of words used. The study utilized the frequency of the words was TF-IDF or Term Frequency – Inverse Document Frequency to analyze agricultural word concerns. This schema was used as a numeric measure to show the importance of using words to voice out their concerns. The next step is the determination of word patterns using association rule Association Rule Mining. The result reveals the prevalent words used to express concern by the agriculture sector are "cash" and "seed" and "assist" + "cash" is the most frequent word pattern. The word "cash," the most commonly used word used by the agriculture sector to air their concern, reveals that this sector needs cash assistance to finance their agricultural activities. The result of this study can be utilized to address concerns in the agriculture sector. Furthermore, this research can be utilized in other sectors to analyze their concerns and provide necessary interventions.
GLOBALIZATION AS A SUPPORT FOR THE GROWTH AND DEVELOPMENT OF STUDENTS

Globalization is a process that has brought many opportunities to young people who have the greatest access to information ever. The purpose of the paper is to examine the students to what extent globalization has contributed to their growth and development. The main goal is to obtain results that will show whether students are ready to acquire more knowledge, experience and skills due to the availability of information or whether the excessive availability of information has created an aversion to it. The data were obtained using a quantitative method where a questionnaire survey was used to collect data, which were interpreted using the decryption method. The results will give a clear student perception of globalization, along with all the advantages and disadvantages. The research will contribute to the knowledge of the opportunities that globalization has brought to young people and how to use the best that it can give.
Forgery Attacks on Several Beyond-Birthday-Bound Secure MACs

At CRYPTO’18, Datta et al. proposed nPolyMAC and proved the security up to $$2^{2n/3}$$ authentication queries and $$2^{n}$$ verification queries. At EUROCRYPT’19, Dutta et al. proposed CWC+ and showed the security up to $$2^{2n/3}$$ queries. At FSE’19, Datta et al. proposed PolyMAC and its key-reduced variant 2k-PolyMAC, and showed the security up to $$2^{2n/3}$$ queries. This security bound was then improved by Kim et al. (EUROCRYPT’20) and Datta et al. (FSE’23) respectively to $$2^{3n/4}$$ and in the multi-user setting. At FSE’20, Chakraborti et al. proposed $$\mathsf{{PDM}}^*\mathsf{{MAC}}$$ and $$\mathsf{{1k}}\text {-}\mathsf{{PDM}}^*\mathsf{{MAC}}$$ , and showed the security up to $$2^{2n/3}$$ queries. Recently, Chen et al. proposed $$\mathsf{{nEHtM}}_p^{+}$$ and showed the security up to $$2^{2n/3}$$ queries. In this paper, we show forgery attacks on nPolyMAC, CWC+, PolyMAC, 2k-PolyMAC, $$\mathsf{{PDM}}^*\mathsf{{MAC}}$$ , $$\mathsf{{1k}}\text {-}\mathsf{{PDM}}^*\mathsf{{MAC}}$$ and $$\mathsf{{nEHtM}}_p^{+}$$ . Our attacks exploit some vulnerability in the underlying polynomial hash function Poly, and (i) require only one authentication query and one verification query; (ii) are nonce-respecting; (iii) succeed with probability 1. Thus, our attacks disprove the provable high security claims of these schemes. We then revisit their security analyses and identify what went wrong. Finally, we propose two solutions that can restore the beyond-birthday-bound security.
Recognition of Off-Line Hand-Written Alphabets Using Knowledge-Based Computational Intelligence

The handwritten character recognition is considered an active recognition problem under the field of image processing and pattern recognition. Both area of research has gained so much popularity in few last years due to technology advancements and necessity of time. The handwritten character recognition also becomes popular due to globalization and technology improvements. In previous time, the information was stored in written form only. To utilize that information, one needs such an advanced method which can do this task efficiently and without reliance on human. This work provides such a simplified and accurate method for the recognition of handwritten characters. A system is proposed to recognize characters using convolutional neural network and is evaluated on a benchmark dataset named as EMNIST to show the performance of the proposed technique. The proposed system gained the accuracy of 97.62% which is better than various existing methods.
Sistem Web Real Time untuk Pelacakan Lokasi Pedagang Keliling

The rapid progress in technology, particularly in the realm of information technology, has significantly impacted various aspects of daily life. Despite these advancements, many street vendors continue to conduct trade within housing complexes or on smaller streets. This presents a challenge for potential buyers who find it inconvenient to purchase goods from street vendors due to uncertainties about their presence and the types of merchandise they offer. To address this issue, a viable solution is proposed: the development of a tracking system that utilizes GPS technology on smartphones to monitor the movements of street vendors. The location data of these vendors is transmitted to the internet, where it is converted into accessible information through a web interface built with the Codeigniter framework. Black Box testing confirms the effective functionality of the system, and the evaluation yields a score of 82.28%, indicating its successful implementation.
Implementasi Metode Deep Learning Untuk Klasifikasi Gambar Tulisan Tangan

The advancement of current technology has led to the widespread utilization of pattern recognition in diverse fields, such as identifying signature patterns, fingerprints, faces, and handwriting. Human handwriting exhibits variations from one person to another, often making it challenging to read or recognize, which can hinder daily activities, particularly in transactions requiring handwritten input. Handwriting, being a distinct expression of individuals, can be effectively distinguished or recognized using pattern recognition methods, particularly through computer-based classification techniques, including deep learning. In this research, deep learning was employed for the classification of handwritten characters, encompassing a total of 5200 data samples, consisting of lowercase and uppercase letters from 'a' to 'z,' with each letter represented by 100 data samples. The data underwent several stages, including pre-processing, feature extraction, classification, and evaluation. The evaluation phase employed k-fold cross-validation repeated ten times, which is a statistical technique aimed at assessing classifier performance. The study revealed that the highest accuracy, at 58.36%, was achieved using a 2-layer architecture with 512 and 256 units, while the lowest accuracy, at 43.42%, was obtained with a 5-layer architecture comprising 512, 256, 128, 64, and 32 units.
Image and Video Captioning Using Machine Learning

Abstract: Image based web crawler is the way toward looking through data by utilizing related images. The tremendous assets of images are accessible on the web in that a large number of the images are contain as with named and without named caption. The users are needed to look through the images relying upon their necessities. In that a significant number of the users can't recover the pertinent images as a result of their unpredicted appropriate inscription on their images. Our task is to generate an automatic caption for the images based on the image content. To produce an image caption, firstly, the content of the image should be fully understood; and then the semantic information contained in the image should be described using a phrase or statement that conforms to certain grammatical rules. Thus, it requires techniques from both computer vision and natural language processing to connect the two different media forms together, which is highly challenging. The paper targets producing mechanized inscriptions by learning the contents of the image. At present images are clarified with human intercession and it turns out to be almost unthinkable task for tremendous databases. The picture information base is given as contribution to a deep neural network Convolutional Neural Network encoder for creating caption which extricates the highlights and subtleties out of our image and Recurrent Neural Network decoder is utilized to interpret the highlights and articles given by our image to acquire consecutive, meaningful description of the image.
Telematics Communication Based on Blockchain Technology

In recent years, industries have experienced significant changes in vehicle-to-vehicle (V2V) communications. Vehicle-to-vehicle communication can enhance the safety of vehicles by signaling other vehicles using blockchain technology. Vehicle-to-vehicle communication has become increasingly important due to the frequent occurrence of traffic accidents and the close sharing of data in today's information age. In view of the importance of blockchain technology for vehicle-to-vehicle communication, the development trend of blockchain technology is first analyzed, and the necessity of vehicle-to-vehicle communication is further elaborated so as to analyze the commonly used blockchain communication technologies. Then, the development and future of Telematics and the scalability of vehicle collaboration technology are elaborated. Then, the existing blockchain and Telematics communication combined technologies are discussed to ensure intelligent transportation and secure communication for vehicular communication. Finally, the future research directions of blockchain vehicular communication are summarized and outlooked.
Research on super-resolution image reconstruction technology

The two key factors in super-resolution image reconstruction are the preprocessing of LR image sequences and the selection of reconstruction algorithms. Due to a series of factors such as noise and blur that may affect the captured image sequence, it is necessary to preprocess the image sequence first. For frames that cannot be processed, they should be considered as bad frames and removed to prepare for reconstruction. The selection of reconstruction algorithms is crucial, and the standard for a good reconstruction algorithm is fast reconstruction speed and good reconstruction results. This article compares the advantages and disadvantages of reconstruction algorithms both domestically and internationally, It is found that the POCS method is more suitable for this article, so more in-depth research and improvement have been conducted on the POCS method. The experimental results show that the improved POCS reconstruction algorithm has a relatively fast reconstruction speed and good reconstruction effect.
Secondary Education Teachers and the integration of ICT in the classroom

The integration of Information and Communication Technologies (ICT) at Secondary Education Centers responds to the demands of society and the need to train digitally literate citizens. However, reality tells us that, on occasions, it is mediated by aspects that generate limitations derived from teachers themselves, who recognize that themain reason for not using digital media inthe classroom is the dedication involved inintegrating them and the training required todo so. In this qualitative research, in-depth interviews were carried out with ten teachers who use ICT (“ProICT”) and teachers whodo not use them (“NICT”), so that they couldargue their reasons for not doing so. From the results obtained we detected that those whoare more in favor of using technologies in theclassroom point more to intrinsic reasons,such as attitude, dedication, and training,while those who use them less justify their decision not to use them to external factors such as lack of resources, technical problems, lack of time for training, class preparation oreven the reference group of students. Teachers emphasize that training in digital competence, to introduce technology in the classroom, is essential, means opting for a global training that involves integrating ICT in the teacher himself, in order to bring them later to the classroom.
A Front-end Requirement Engineering Framework of Social Commerce Enterprises (Design-Phase).

Social commerce (s-commerce) is a modern business model of electronic commerce (e-commerce), it is empowered by social media and Web 20. Most of the e-businesses started to transfer their respective business model, including e-commerce to enable s-commerce. The current researchers have discussed s-commerce from the social features of s-commerce building blocks, however, they don’t engineer a relevant set of generic front-end requirements of such 5commerce platforms. Therefore, there is a need to develop a framework that guides the requirements engineering (RE) process for such platforms with the use of the artifact orientation approach. This paper shows only the design of our proposed framework. In Finding, we have sketched out the generic set of front-end requirements of s-commerce platform and show how to use the generic framework to generate or to recommend an instantiation of the requirements for a specific platform. Finally, this study will assist the developers to focus on the social features which enhance the economic revenue of the enterprise and, improve the architecture of their products/services and/or their business processes (BPs).
Intelligent matching method for visible and infrared images based on style translation

Heterogeneous image matching is a hot and difficult research topic in the field of image processing. The existing visible and infrared image matching has problems such as large modal differences, difficult matching, and poor robustness. Therefore, an intelligent matching method for visible and infrared images based on BCE-CycleGAN is proposed. First, a BCECycleGAN model is proposed based on the image style translation with generative adversarial networks, it can convert visible images to infrared images. By designing a new generative network loss function, the transformation effect of the model on heterogeneous images is improved. Then, the generated infrared images are matched with the original infrared images using LoFTR and DFM algorithms. LoFTR and DFM are currently advanced deep learning-based intelligent matching algorithms. Finally, the conversion relationship is mapped to the corresponding visible and infrared image pair to obtain the final matching result. Images style translation experiments and matching experiments on the test datasets show that the BCE-CycleGAN network proposed in this paper can effectively reduce the complexity of the algorithm and improve the quality of image generation. Furthermore, combining BCE-CycleGAN with deep learning-based matching methods can effectively improve the effectiveness and robustness of the matching algorithm.
Systems and Methods: Image Encryption Using Steganography and XOR Operations

Cybersecurity is a significant part of safe data transmission, particularly through networks such as the Internet. Confidential medical or military images and personal images of individuals and organizations are a big part of such data. These images need a very high level of security to prevent access by unauthorized users. Unauthorized access to such images can lead to significant financial and life losses. To prevent this, we incorporate various encryption-decryption algorithms and concepts like steganography into a system for safe, reliable, efficient, and secure image storage and transfer. We tune each algorithm implemented in the system individually to produce the best results upon integration with other algorithms. Further, we provide users with Graphic User Interface that helps them interact with this system conveniently and efficiently. Finally, we test the system using various medical images and present the results.