Reviewerly/exHarmony huggingface dataset:
Source monitoring twin-field quantum key distribution assisted with Hong-Ou-Mandel interference

Twin-field quantum key distribution (TF-QKD) can change the channel-loss dependence of key rates from $O(\ensuremath{\eta})$ to $O(\sqrt{\ensuremath{\eta}})$ and thus significantly increase the secure key rate compared with other existing quantum key distribution protocols. However, it does not take the source security into account in most present TF-QKD protocols. Here, we propose to employ the Hong-Ou-Mandel interference to characterize the source security, i.e., to use the interference visibility to quantify the information leakage from detectable side channels of sources. Furthermore, we establish a corresponding theoretical model and calculate the final key rate, by using the three-intensity decoy-state method and taking finite-data-size effects into account. Consequently, by employing our present scheme, the secure transmission distance can be longer than 100 km under current experimental conditions, significantly surpassing present device-independent QKD systems.
PRIORITIES OF EDUCATION DEVELOPMENT IN MODERN TIMES

This article delves into methodological considerations pertaining to the evolution of the educational system and the establishment of the educational milieu amidst significant global transformations in politics, economics, ecology, and socio-cultural dynamics. It explores novel approaches aimed at shaping a fresh paradigm for education and fostering collaborative pedagogy tailored to the exigencies of the contemporary era. Furthermore, the paper conducts an in-depth analysis of the outcomes derived from sociological surveys administered to educators. These surveys focus on key theses and approaches presented within the article, offering insights into the reception and perspectives of teaching professionals on the outlined concepts. The synthesis of theoretical exploration, practical pedagogical strategies, and empirical feedback contributes to a comprehensive understanding of the multifaceted landscape of modern educational methodologies.
The role of digital surveillance during outbreaks: the Ghana experience from COVID‑19 response

Over the years, Ghana has made notable strides in adopting digital approaches to address societal challenges and meet demands. While the health sector, particularly the disease surveillance structure, has embraced digitization to enhance case detection, reporting, analysis, and information dissemination, critical aspects remain to be addressed. Although the Integrated Disease Surveillance and Response (IDSR) structure has experienced remarkable growth in digitization, certain areas require further attention as was observed during the COVID-19 pandemic. Ghana during the COVID-19 pandemic, recognized the importance of leveraging digital technologies to bolster the public health response. To this end, Ghana implemented various digital surveillance tools to combat the pandemic. These included the 'Surveillance Outbreak Response Management and Analysis System (SORMAS)', the digitalized health declaration form, ArcGIS Survey123, Talkwalker, 'Lightwave Health information Management System' (LHIMS), and the 'District Health Information Management System (DHIMS)'. These digital systems significantly contributed to the country's success in responding to the COVID-19 pandemic. One key area where digital systems have proved invaluable is in the timely production of daily COVID-19 situational updates. This task would have been arduous and delayed if reliant solely on paper-based forms, which hinder efficient reporting to other levels within the health system. By adopting these digital systems, Ghana has been able to overcome such challenges and provide up-to-date information for making informed public health decisions. This paper attempts to provide an extensive description of the digital systems currently employed to enhance Ghana's paper-based disease surveillance system in the context of its response to COVID-19. The article explores the strengths and challenges or limitations associated with these digital systems for responding to outbreaks, offering valuable lessons that can be learned from their implementation.
Inside the virtual art classroom: Using VR design software to support drawing courses in higher education

Little research exists regarding the possibilities of using virtual reality (VR) to teach drawing skills. This report aims to compare traditional methods of teaching drawing techniques with methods for teaching digital drawing using VR design software such as Gravity Sketch and MultiBrush. Based on our experiences in a variety of workshops and courses, we observe that the VR drawing classroom can enrich existing educational formats as it offers advantages such as increased student focus, collaboration and balance between group instruction and individual feedback.
‘The dance of drawing’ and the limits of digital assistance

By looking at ‘the dance of a drawing’, this paper questions the interest and limits of digital technologies in the world of drawing and, more broadly, the visual arts. Based on the system of Effort conceived by the movement theorist Rudolf Laban (1879–1956), the author proposes a new way of apprehending pictorial and graphic form, from its expressive movements. This approach leads the author to distinguish between two modes of graphic expression, the sensory and the rational, which are both opposed and complementary. By inviting the viewer to observe the dance of paintings by Van Gogh and Seurat on the one hand and children’s drawings on the other, the paper underlines how digital technology cannot completely replace traditional drawing techniques.
Position of Blockchain

The convergence of Education 4.0 and Industry 5.0 represents a transformative paradigm shift in both the educational and industrial landscapes, driven by advanced technologies such as blockchain and the internet of things (IoT). This chapter discusses the opportunities and challenges associated with the integration of these technologies within the context of Education 4.0 and Industry 5.0. Next in the industrial sector, Industry 5.0 is characterized by the seamless integration of digital technologies, automation, and data-driven decision-making. Blockchain technology enhances transparency, security, and trust in supply chains, while IoT devices provide real-time data for optimizing processes (including few challenges like scalability, interoperability, cost, etc.). In the educational sector, Education 4.0 emphasizes personalized learning, digital literacy, and lifelong learning. Blockchain ensures the security and immutability of educational credentials, while IoT facilitates personalized learning experiences (with few challenges like data privacy, etc.).
High dynamic range 3D measurement based on the Butterworth low-pass filter and Hilbert transform

Due to the limited dynamic range of the camera, a measured object with non-Lambert reflection saturates the fringe pattern, which will lead to three-dimensional (3D) measurement error. In this paper, we propose a novel, to our knowledge, high dynamic range 3D measurement technique based on the Butterworth low-pass filter (BLPF) and Hilbert transform (HT), which is called BLPFHT for short. First, we analyze the Fourier transform (FT) spectrum of saturated fringe pattern. Then, we use the Butterworth low-pass filter to filter out the higher harmonic components introduced by fringe intensity saturation. BLPF leads to a non-sinusoidal fringe pattern in the saturated region, which introduces periodic phase error. Therefore, we establish a phase error model and use HT to correct the phase error. Experimental comparison confirms that the proposed BLPFHT can efficiently and accurately reconstruct the 3D shape of non-Lambert reflective surfaces without additional image or hardware assistance.
Navigating the Metaverse

The rise of the metaverse—a virtual world where individuals can interact with each other and digital objects in a fully immersive environment—has led to new challenges in the world of cybersecurity. As more individuals and businesses move towards this new frontier, the potential for cybercrime is also increasing. In this chapter, the authors explore the diverse types of cybercrime that may emerge from virtual theft and fraud to privacy violations and hacking. They also discuss the unique challenges faced by law enforcement and security professionals in detecting and preventing these crimes in a fully virtual environment. To aid in forecasting these crimes, the authors examine current trends and technological developments that may impact the future of the metaverse, including the growth of decentralized technologies, the increasing prevalence of artificial intelligence, and the potential for quantum computing. By understanding the potential risks and challenges of the metaverse, we can better prepare ourselves for a future where virtual and physical crime intersect.
E-Learning

E-learning is the use of technology to enable people to learn at any time and from anywhere. It is quick, relevant, and ever-changing, and it might include training and the transfer of just-in-time information, and expert advice. Semantic web technology, which allows machine-processable content to coexist and supplement the present web, makes it easier for computers and people to work together. Semantic web technology offers a wide range of applications. E-learning is one of the areas where this new web technology could be beneficial. This chapter gives an overview of e-learning and its necessity. It discusses at length semantic web technologies and how they can be utilized to develop an e-learning environment.
Network Layer Privacy Protection Using Format-Preserving Encryption

Format-Preserving Encryption (FPE) algorithms are symmetric cryptographic algorithms that encrypt an arbitrary-length plaintext into a ciphertext of the same size. Standardisation bodies recognised the first FPE algorithms (FEA-1, FEA-2, FF1 and FF3-1) in the last decade, and they have not been used for network layer privacy protection so far. However, their ability to encrypt arbitrary-length plaintext makes them suitable for encrypting selected packet header fields and replacing their original value with ciphertext of the same size without storing excessive information on the network element. If the encrypted fields carry personally identifiable information, it is possible to protect the privacy of the endpoints in the communication. This paper presents our research on using FPE for network layer privacy protection and describes LISPP, a lightweight, stateless network layer privacy protection system. The system was developed for programmable smart network interface cards (NIC) and thoroughly tested in a real network environment. We have created several implementations ranging from pure P4 to a mix of P4 and C implementations, exploring their performance and the suitability of target-independent P4 language for such processor-intensive applications. Finally, LISPP achieved line rate TCP throughput, up to 4.5 million packets per second, with the penalty of only 30 to 60 microseconds of additional one-way delay, proving that it is adequate for use in production networks. The most efficient implementation was with the FF3-1 algorithm developed in C and carefully adapted to the specific hardware configuration of the NIC.
High-Capacity Reversible Data Hiding in Encrypted Images Based on Pixel Prediction and QuadTree Decomposition

Over the past few years, a considerable number of researchers have shown great interest in reversible data hiding for encrypted images (RDHEI). One popular category among various RDHEI methods is the reserving room before encryption (RRBE) approach, which leverages data redundancy in the original image before encryption to create space for data hiding and to achieve high embedding rates (ERs). This paper introduces an RRBE-based RDHEI method that employs pixel prediction, quadtree decomposition, and bit plane reordering to provide high embedding capacity and error-free reversibility. Initially, the content owner predicts the error image using a prediction method, followed by mapping it to a new error image with positive pixel values and a compressed binary label map is generated for overhead pixels. Subsequently, quadtree decomposition is applied to each bit plane of the mapped prediction error image to identify homogeneous blocks, which are then reordered to create room for data embedding. After generating the encrypted image with the encryption key, the data hider employs the data hiding key to embed the data based on the auxiliary information added to each embeddable bit plane’s beginning. Finally, the receiver is able to retrieve the secret message without any error, decrypt the image, and restore it without any loss or distortion. The experimental results demonstrate that the proposed RDHEI method achieves significantly higher ERs than previous competitors, with an average ER exceeding 3.6 bpp on the BOSSbase and BOWS-2 datasets.
Student Performance Application in the Practice of Teaching Deaf Students Based on Reflective Maternal Method (RMM)

Teaching skills are the main skills every teacher needs to produce a generation of quality teachers. But the fact is that the performance appraisal that has been going on so far has used manual performance appraisal with a rubric. It raises a problem, namely, the evaluation becomes complicated and inefficient. The research aims to develop student performance applications in deaf student learning by conducting a needs analysis of current student skills and the material and content needed. The research design used a quantitative descriptive survey method of 120 Special Education study program students. The survey contains subject-related questions, which were distributed to 120 students. The data analysis technique uses descriptive qualitative analysis. The results showed that the level of students' skills in the teaching practice of deaf students was in the sufficient category, namely 99 respondents (82.5%). Data from material analysis showed that 75 respondents (62.5%) strongly agreed, 31 respondents (25.8%) agreed, and 2 respondents (1.7%) disagreed. Data from the content analysis showed that 79 respondents (65.8%) strongly agreed, 24 respondents (20%) agreed, and 3 respondents (2.5%) disagreed. The development of performance applications is based on the results of a needs analysis based on digital technology to assess students' abilities in teaching deaf students.
The Science, Technology, Engineering, Mathematics (STEM)-based Problem-Based Learning (PBL) Learning Model on the Numeracy Skills

The low numeracy ability of students is because the learning process carried out by the teacher is still centred on the use of the lecture method, so in the learning process, students tend to get bored quickly and find it difficult to understand the material presented by the teacher. This study aimed to identify the significant impact of the use of STEM-based PBL on students' numeracy skills in Grade V SD. This research belongs to the type of quantitative research using a quasi-experimental design with a nonequivalent control group design. The population in this study were all fifth-grade students, totalling 201 children. Sampling in the study was carried out using a purposive sampling technique, with the number of samples in this study, namely 25 students as the control group and 25 as the experimental group. Data collection in the study was carried out using the test method, with the research instrument being an essay test. The data obtained in the study were then analyzed through a prerequisite test, which consisted of the normality test, homogeneity test, hypothesis test using was T-test, and the effect size test. The results of the data analysis show that the application of STEM in PBL has a high effect on improving students' numeracy skills. Based on these results, applying the STEM-based PBL model significantly affects the numeracy abilities of fifth-grade students in elementary schools.
Effects of augmented reality on perceived motivation for struggling readers: Mix-method analysis

Higher education students who struggle with reading may find some relief via the use of technology, especially new and developing forms of technology. Even though augmented reality (AR) has been used in the classroom with great success to motivate and engage children who are difficult to teach, there hasn't been a lot of research done on how augmented print may help those who have trouble reading. The purpose of this study is to investigate the effect of augmented reality on perceived motivation for students currently enrolled in higher education, namely their engagement with and understanding of an upgraded design theory book, as well as their perceived motivation to read. This research was conducted using the mix method approach, supported with some different methodologies. The findings reveal that increased support for academic literature enhances motivation, engagement, and confidence in understanding, impacting both struggling and proficient readers. We concluded that students, regardless of their reading level, expressed a willingness to use AR reading assistance for future books. Further research is crucial given the heightened levels of motivation and confidence. This research aligns with technological advancements, and educators can influence the development of augmented reality apps for classroom use. Future studies should focus on students with reading difficulties, exploring the optimal design of AR experiences and learning games to enhance understanding and retention of art history lectures in higher education
Expand and Shrink: Federated Learning with Unlabeled Data Using Clustering

The amalgamation of the Internet of Things (IoT) and federated learning (FL) is leading the next generation of data usage due to the possibility of deep learning with data privacy preservation. The FL architecture currently assumes labeled data samples from a client for supervised classification, which is unrealistic. Most research works in the literature focus on local training, update receiving, and global model updates. However, by principle, the labeling must be performed on the client side because the data samples cannot leave the source under the FL principle. In the literature, a few works have proposed methods for unlabeled data for FL using “class-prior probabilities” or “pseudo-labeling”. However, these methods make either unrealistic or uncommon assumptions, such as knowing class-prior probabilities are impractical or unavailable for each classification task and even more challenging in the IoT ecosystem. Considering these limitations, we explored the possibility of performing federated learning with unlabeled data by providing a clustering-based method of labeling the sample before training or federation. The proposed work will be suitable for every type of classification task. We performed different experiments on the client by varying the labeled data ratio, the number of clusters, and the client participation ratio. We achieved accuracy rates of 87% and 90% by using 0.01 and 0.03 of the truth labels, respectively.
Development of Interactive Learning Media Assisted by Lectora Inspire Application in Science Subjects Class IV SDN Baru 03 Pagi

Researchers and developers are hard at work on new learning media, one of which is the Lectora Inspire application media, to counteract student indifference in homework and a rising lack of incentive to learn. The study technique is based on the 4D development paradigm (Define, Design, Develop, and Disseminate). The study's goal is to determine whether the media developed can be used and to collect data on how students react to the media. The goal of this study was to assess the performance of lecturers and professors serving as media and material validators, as well as students serving as respondents. Material experts validate 92.78% of the time, while media experts validate 91.78% of the time; expert teachers on average 85.00%; and students with an average of 89.52%. With the help of the Lectora Inspire software, it is clear that the potential for interactive learning media is enormous as a teaching tool.
Methods in Improving Students Writing in Thungkhar Primary School in Thrimshing, Trashigang

This study intended to seek methods for improving students' writing in Thungkhar Primary School in Thrimshing, Trashigang. The study used a qualitative approach to collect data from a sample of Thungkhar Primary School in Thrimshing. Qualitative data were collected through interviews and observation from the teachers and students. The findings indicated that methods in improving students' writing benefited learners. The most significant teaching method to writing practiced or implemented was the process approach which is recommended by the national curriculum. One of the interesting findings of this research is that students in my schools preferred writing to speaking as they struggle with speaking. Similar to the other study highlights, the study found that both teaching and learning writing are complex. It is imperative that there is room for improvement with suitable interventions in teaching and learning writing through a series of professional development programs.
Readability of Reading Texts for EFL Students at Al-Baha University

Reading is an important skill for EFL university students, as it reinforces their critical and analytical thinking. EFL university students rely on reading texts to expand their knowledge of the outside world and enhance their memory functions, enabling them to use the target language more effectively. EFL instructors depend on the reading texts as the basis for curricular and extracurricular activities to enhance their learners&amp;#39; language skills, enabling them to use the language in everyday situations. Therefore, selecting suitable English textbooks with appropriate reading texts is crucial for students&amp;#39; achievement and progress. Research in the areas of readability of textbooks and reading texts is very important to assess the appropriateness of different texts for learners. Many readability studies have focused on examining the suitability of readability formulas for measuring the readability level of texts provided to learners. This study measured the readability level of the reading texts of Evolve 4 special edition (published by Cambridge University Press) offered to EFL university students using online digital software that utilizes a set of the most commonly used readability formulas, including the Flesch Reading Ease Formula, Gunning Fog index, and Coleman Liau index. This study also used a set of cloze tests administered to female EFL university students, designed by the researcher to measure the readability level of the reading texts and provide suggestions and recommendations for EFL instructors who teach the textbook at the university level. The findings of this study show that the readability level of the reading texts in the English book Evolve 4 special edition is fairly challenging for EFL university students, as measured by a set of readability instruments. Consequently, the study recommends that EFL instructors should utilize a diverse set of teaching strategies and cooperative work methods to help their students read and understand the reading texts in Evolve 4 special edition. Moreover, EFL instructors should take into account significant factors that can affect the readability of English reading texts, such as learners&amp;#39; interest, prior background, style of the text, and the content itself. These considerations should guide instructors in tailoring their approach to maximize student learning outcomes.