Reviewerly/exHarmony huggingface dataset:
Underwater image enhancement by using amalgamation of colour correction, contrast-enhancing and dehazing

Authors:
raw_author_name: Mohit Dua
raw_affiliation_string: Department of Computer Engineering, National Institute of Technology Kurukshetra, National Institute of Technology, Kurukshetra, Haryana, Kurukshetra, Kurukshetra, 136119, INDIA
raw_author_name: Shelza Dua
raw_affiliation_string: Electronics and Communication Engineering, Punjab Engineering College (Deemed to be University), Chandigarh, Chandigarh, Punjab, 160012, INDIA

Abstract: Abstract Underwater images can be captured either with the help of light waves or sound waves. Images that are taken underwater typically are not of optimum quality as they suffer from issues such as low contrast, blurring of detail, colour distortion, and greenish tones. Several physical processes that take place in the aquatic environment, such as light absorption, refraction, and scattering, are responsible for the existence of such degradation in underwater images. To address these challenges, numerous researchers have put forth a range of cutting-edge techniques for enhancing and restoring such degraded underwater images, with the aim of addressing these issues. These techniques primarily focus on improving visibility and enhancing the level of detail. To achieve this, we propose a method that performs White Balancing in the LAB colour space to remove the bluish-greenish tones present in the image. Next, we enhance the contrast by first converting the RGB image into HSV (Hue, Saturation, Value) and HLS (Hue, Lightness, and Saturation) colour spaces and then by using the S &amp; V channels in HSV and L &amp; S colour channels in HLS, we apply Contrast Limited Adaptive Histogram Equalization (CLAHE). To control the brightness of the enhanced image, we apply Gamma Correction. Lastly, by using the method Dark Channel Prior (DCP), we separate the image’s red channel from the RGB colour space and perform the dehazing operation to get the final enhanced image. We have conducted a comprehensive qualitative analysis of our proposed approach as well as existing techniques, evaluating them objectively and subjectively through metrics such as Peak Signal-to-Noise Ratio (PSNR), Root-Mean-Square Error (RMSE), Structural Similarity (SSIM), and the Underwater Colour Image Quality Evaluation metric (UCIQE).&amp;#xD;
Riemannian quantum circuit optimization for Hamiltonian simulation

Authors:
raw_author_name: Ayse Kotil
raw_affiliation_string: Department of Informatics, Technical University of Munich, Boltzmannstr. 3, Garching, Bayern, 85748, GERMANY
raw_author_name: Qunsheng Huang
raw_affiliation_string: Department of Informatics, Technical University of Munich, Boltzmannstr. 3, Garching, Bayern, 85748, GERMANY
raw_author_name: Christian B Mendl
raw_affiliation_string: Department of Informatics, Technical University of Munich, Boltzmannstr. 3, Garching, Bayern, 85748, GERMANY

Abstract: Abstract Hamiltonian simulation, i.e., simulating the real time evolution of a target quantum system, is a natural application of quantum computing. Trotter-Suzuki splitting methods can generate corresponding quantum circuits; however, a faithful approximation can lead to relatively deep circuits. Here we start from the insight that for translation invariant systems, the gates in such circuit topologies can be further optimized on classical computers to decrease the circuit depth and/or increase the accuracy. We employ tensor network techniques and devise a method based on the Riemannian trust-region algorithm on the unitary matrix manifold for this purpose. For the Ising and Heisenberg models on a one-dimensional lattice, we achieve orders of magnitude accuracy improvements compared to fourth-order splitting methods. The optimized circuits could also be of practical use for the time-evolving block decimation (TEBD) algorithm.
Depth_ ASPP_ UNet++: A novel 2D ESPI phase unwrapping based on convolutional neural network

Authors:
raw_author_name: Wenke Xue
raw_affiliation_string: Shenyang Aerospace University, College of Artificial Intelligence, Shenyang, 110136, CHINA
raw_author_name: Chuanyun Wang
raw_affiliation_string: Shenyang Aerospace University, College of Artificial Intelligence, Shenyang, 110136, CHINA

Abstract: Abstract Phase unwrapping is a key step in optical metrology and physical optics to obtain accurate &amp;#xD;phase distributions. In practice, phase images obtained from electronic speckle pattern &amp;#xD;interferometry (ESPI) exhibit diverse and complex morphology, with significant shape &amp;#xD;variations and non-uniform densities among different individuals. This takes challenges for &amp;#xD;accurately extracting phase information and unwrapping the phase. With the progress of deep &amp;#xD;learning technology in optical image processing, real-time performance and accuracy have &amp;#xD;become concerned issues. In this paper, an ESPI phase unwrapping method based on &amp;#xD;convolutional neural network (CNN) UNet++ is proposed. The proposed network combines &amp;#xD;the depthwise separable convolution (DSC), atrous spatial pyramid pooling (ASPP), defined &amp;#xD;as Depth_ ASPP_ UNet++. In this model, the use of DSC improves network computational &amp;#xD;efficiency and provides better feature representation capability. In addition, ASPP is &amp;#xD;introduced to pay more attention to the phase information of the phase image, and then obtain &amp;#xD;better phase unwrapping results. The experimental results show that our proposed method can &amp;#xD;obtain excellent results, especially with various of variable density, different noise levels, and &amp;#xD;different speckle sizes.
A simplified Mølmer-Sørensen gate for the trapped ion quantum computer

Authors:
raw_author_name: Hiroo Azuma
raw_affiliation_string: Global Research Center for Quantum Information Science, National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo, Chiyoda-ku, Tokyo, 101-8430, JAPAN

Abstract: Abstract We discuss how to simplify the Mølmer-Sørensen (MS) gate which is used for the trapped ion quantum computer. The original MS gate is implemented by illuminating two ions with bichromatic coherent light fields separately at the same time. In this paper, we propose a method for transforming a separable state of two ions into one of the Bell states by illuminating the two ions with monochromatic coherent light fields individually and this point is the advantage of our scheme over the original MS gate. The length of the execution time of our proposed gate is comparable to that of the original MS gate, however, numerical calculations show that our proposed gate is weakly sensitive to thermal fluctuations of the phonons. By giving another example of a simple two-ion gate that can generate entanglement but is strongly vulnerable to thermal fluctuations, we show that our simplified MS gate is more marked than usual.
Evaluation of AI Models to Update Cybersecurity Curriculum 

Authors:
raw_author_name: Paige Zaleppa
raw_affiliation_string: Department of Computer and Information Sciences Towson University
raw_author_name: Blair Taylor
raw_affiliation_string: Towson University
raw_author_name: Siddharth Kaza
raw_affiliation_string: Towson University

Abstract: This study explores the performance of several Large Language Models (LLMs) across different facets of Cybersecurity Modules. Using prompt engineering, this work evaluates publicly available LLMs for their ability to assess the suitability of secure coding topics based on learning outcomes, categorize these topics following OWASP standards, and generate up-to-date examples for curriculum use. The findings would highlight the transformative role that LLMs would play for future advancements in Cybersecurity education.
Impact of a Cybersecurity Work-Related Course on Students' Career Thoughts and Attitudes

Authors:
raw_author_name: Randall Joyce
raw_affiliation_string: Cybersecurity and Network Management Murray State University

Abstract: This article proposes a research study conducted at Murray State University Cybersecurity and Network Management program to investigate the impact of work-related experiential learning on college students' career thoughts and attitudes within the context of cybersecurity career development. The Cybersecurity and Network Management program introduced the CNM 518 course based on the Public Infrastructure Security Cyber Education System (PISCES) project that offers practical, hands-on experiences. The proposed research project slated for Spring 2024, aims to assess how this work-related experiential learning influences students' career thoughts and attitudes, using the Career Thoughts Inventory as a measurement tool. This research project emphasizes the importance of reflective learning within CNM 518 and aims to contribute empirical evidence on the impact of work-related experiential learning on students' career thoughts and how such learning experiences positively influence the career decision-making processes and, subsequently, the broader field of cybersecurity education.
Assessing the Effectiveness and Security Implications of AI Code Generators

Authors:
raw_author_name: Maryam Taeb
raw_affiliation_string: Electrical & Computer Engineering FAMU-FSU College of Engineering
raw_author_name: Hongmei Chi
raw_affiliation_string: Computer Information & Sciences Florida A&M University
raw_author_name: Shonda Bernadin
raw_affiliation_string: Electrical & Computer Engineering FAMU-FSU College of Engineering

Abstract: Students, especially those outside the field of cybersecurity, are increasingly turning to Large Language Model (LLM)-based generative AI tools for coding assistance. These AI code generators provide valuable support to developers by generating code based on provided input and instructions. However, the quality and accuracy of the generated code can vary, depending on factors such as task complexity, the clarity of instructions, and the model’s familiarity with the programming language. Additionally, these generated codes may inadvertently utilize vulnerable built-in functions, potentially leading to source code vulnerabilities and exploits. This research undertakes an in-depth analysis and comparison of code generation, code completion, and security suggestions offered by prominent AI models, including OpenAI CodeX, CodeBert, and ChatGPT. The research aims to evaluate the effectiveness and security aspects of these tools in terms of their code generation, code completion capabilities, and their ability to enhance security. This analysis serves as a valuable resource for developers, enabling them to proactively avoid introducing security vulnerabilities in their projects. By doing so, developers can significantly reduce the need for extensive revisions and resource allocation, whether in the short or long term.
What Is Interesting and Relevant About Cybersecurity?

Authors:
raw_author_name: Cheryl Resch
raw_affiliation_string: Engineering Education Department University of Florida
raw_author_name: Jinnie Shin
raw_affiliation_string: School of Educational Development and Organizational Studies University of Florida
raw_author_name: Christina Gardner-McCune
raw_affiliation_string: Computer and Information Science and Engineering University of Florida

Abstract: Cyber attacks are a common feature of current news and many of them are the result of easy to avoid vulnerabilities in software. It is imperative that students graduating from an undergraduate Computer Science (CS) curriculum understand the consequences of vulnerable code. When developing lessons and assignments, it would be useful to have a sense of students’ attitude toward cybersecurity and appreciation of the need to write secure code. This paper describes an analysis of the results of a survey of students in core CS courses at our large public university, in which students answer free response questions about what they find interesting and relevant about cybersecurity. The survey was conducted in Fall 2022 and repeated in Spring 2023 after cybersecurity interventions were introduced into several core CS courses. We performed a Natural Language Processing (NLP) analysis of the free response answers to determine the overarching themes in the responses. We found that the most prevalent topics students are interested in are cryptography and penetration testing, and did not change over the two semesters. In answer to the question about the relevance of studying cybersecurity, we found that as students progress through the curriculum, what students find relevant moves from protecting their personal data to its importance in job duties and writing secure programs. When developing lessons and assignments, it may be helpful to introduce cryptography or penetration testing to engage students. Also, students should be taught early and often about the relevance of cybersecurity in their future job duties.
Controlled bidirectional remote implementations of partially unknown quantum operations

Authors:
raw_author_name: Miao Liu
raw_affiliation_string: Yili Normal University, The school of Mathematics and Statistics, Yili Normal University, Yili 835000, China, Yining, 835000, CHINA
raw_author_name: Jia-Yin Peng
raw_affiliation_string: Yili Normal University, The school of Mathematics and Statistics, Yili Normal University, Yili 835000, China, Yining, Xinjiang, 835000, CHINA

Abstract: Abstract By blending the ideas of controlled teleportation, bidirectional teleportation and remote implementation of quantum operations, we investigate the bidirectional transmission of quantum operations under the control of one supervisor. Firstly, we provide a method for generating a class of multi-particle entangled states, including ﬁve-particle and seven-particle entangled states, using a nine-particle entangled state as an example. Then using our constructed ﬁve-particle entangled state as a quantum channel, we propose a new controlled bidirectional protocol for remotely implementing partially known quantum operations (PUQOs for short) of one qubit within the two restricted sets satisfying speciﬁc conditions. Subsequently, exploiting a nine-particle entangled state as the quantum channel, we extend it to the case of two-qubit quantum operations which come from eight restricted sets. Replacing two PUQO of two qubits by a PUQO of one qubit and a PUQO of two qubits, we put forward another new asymmetric controlled bidirectional protocol for remotely implementing PKQOs via a seven-particle entangled state as the quantum channel. In these protocols, by using universal recovered operations performed by the receivers, the senders can simultaneously exchange their PUQOs as long as the controller collaborates, where each PUQO acts on the corresponding unknown state owned by the remote recipient.&amp;#xD;
Unsupervised Clustering on Paleochannel Detection with Curvature-Based Attribute

Authors:
raw_author_name: Fan Jiang
raw_affiliation_string: Halliburton, Houston, Texas, USA

Abstract: Abstract This research focuses on the application of advanced seismic data processing techniques and unsupervised clustering algorithms to accurately identify and map paleochannels in the high-resolution Maui seismic dataset. Pre-processing steps were applied to enhance data quality, followed by the calculation of a positive curvature attribute used as input for multiple clustering algorithms. The study evaluates four state-of-the-art unsupervised clustering methods and employs Principal Component Analysis (PCA) for result refinement and differentiation. By analysing the effectiveness of the algorithms, we demonstrate that Fuzzy C-means and Birch provide optimal segmentation of paleochannels. This automated approach not only overcomes the challenges of noisy data but also opens avenues for similar applications in seismic interpretation. The research underscores the significance of the unsupervised method in facilitating efficient resource exploration, emphasizing the integration of PCA to enhance segmentation accuracy and reduce human intervention. This study contributes to the sustainable management and extraction of natural resources, underscoring the potential of advanced techniques in remote sensing analysis.
Research on Teaching Practice of English for Science and Technology Based on Multimedia Technology

Authors:
raw_author_name: Wei Dong
raw_affiliation_string: Qinhuangdao Vocational and Technical College, China
raw_author_name: Liang Lu
raw_affiliation_string: Qinhuangdao Vocational and Technical College, China

Abstract: The purpose of this paper is to study the practice of multimedia technology in the teaching of scientific and technical English. With the rapid development and popularisation of computer technology and the deepening of educational concepts, multimedia-assisted English teaching has become one of the most important foreign language teaching modes at present. This study firstly analyses the impact of multimedia technology on English teaching, secondly faces the advantages and challenges of multimedia technology in the teaching process, and finally explores the use and effect of multimedia technology in scientific and technological English teaching based on the data of the survey and research. The results of the study show that for college English teachers in colleges and universities, they should fully explore the advantages of multimedia technology in the process of using it and use it skillfully in teaching practice, which will have a positive effect on improving the quality of English teaching and deepening the reform of college English teaching.
Exploring Colonial Heritage (EXCOTAGE) Application as a Mobile Technology-Based History Learning Education

Authors:
raw_author_name: None Joko Sayono
raw_author_name: None Didin Saripudin
raw_author_name: None Zulkarnain

Abstract: This research focused on the history learning concerns among 11th-grade Social Science students at MAN Kota Pasuruan, a senior high school. To support research activities, the instruments included a questionnaire to measure the effectiveness of the product. The questionnaire was distributed to validators and users, specifically the 11th-grade students of social science at MAN Kota Pasuruan. The participants in this study were selected using purposive sampling for validation and simple random sampling for testing. During the implementation, this research used the ADDIE research and development model. The product effectiveness analysis technique developed by Nunuk Suryani, Achmad Setiawan, and Aditin Putria was used for analysis of the collected data. Based on the comparison results, it is evident that the developed product is truly valuable, appealing, and aligned with the current advancements in learning technology. Meanwhile, in the effectiveness testing, it was concluded that the product has been highly effective based on expert or user assessments.
Mobile Applications in Otology: A Scoping Review

Authors:
raw_author_name: Lemuel Clark P. Velasco

Abstract: This scoping review aims to comprehensively synthesize current research on the use of mobile applications in otology, identify research gaps, and assess the feasibility of mobilebased applications in this field. The aim is to support and direct future research studies on harnessing the potential of mobile technology in otology. Following the PRISMA-ScR guidelines, a literature profiling approach was adopted using the Google Scholar search engine from September 2022 to January 2023. Only articles published in English between 2012 and 2023 were included, resulting in a final sample size of 32 papers. The results revealed an increasing focus on the remote delivery of healthcare, with the majority of the articles originating from the United States and authored by medical doctors. Two main categories were identified within the 32 selected journals: audiology and smartphone otoscopy. A total of 124 mobile applications were identified in these journals, with 48 applications for hearing tests and 27 applications for smartphone otoscopes being the most commonly utilized. Mobile applications have the potential to serve as valuable tools in the field of otology, especially in the context of smartphone hearing tests and smartphone-enabled otoscopes. However, further research is needed to assess their effectiveness, accuracy, and appropriate usage.
Education in the Age of Artificial Intelligence

Authors:
raw_author_name: Norbert Annuš
raw_affiliation_string: Department of Informatics, J. Selye University, Bratislavská cesta 3322, Komárno, Slovakia

Abstract: The age of artificial intelligence (AI) is just around the corner. This article presents the AI-based technologies that represent a significant change for the learning and teaching process. The article describes the potential of personalised learning, automated assessment, chatbots, predictive models, intelligent robots, and virtual and augmented reality for education, by reviewing scientific literature. Nowadays, knowledge of these technologies is essential for teachers. In this article we conducted a qualitative survey involving teachers. The aim of our survey is to assess the perceptions of educators about the use of AI in education. Our results show that educators are open to these technologies regardless of generation and discipline. The study summarizes the appropriate use of these technologies, the role of teachers, their attention to students and their active communication, as only this can lead to effective education in the age of artificial intelligence.
Media Article Text Analysis in the Context of Distance Education: Focusing on South Korea

Authors:
raw_author_name: Youngho Lee
raw_affiliation_string: Department of Computer Education, Daegu National University of Education, Daegu, Republic of Korea

Abstract: The impact of COVID-19 pandemic is far-reaching, encompassing the social, economic, and psychological aspects of the society. . In order to prevent the spread of COVID-19, various countries, including South Korea, have entered into long-term home care and distance learning systems. However, distance learning experiments conducted in many countries have raised whether face-to-face education can be replaced by distance learning. Therefore, this study analyzed public opinion, social perception, and field trends based on media reports on remote learning. For this purpose, 2,600 articles from 11 newspapers and four broadcasters related to remote learning were collected in this study. Based on this data, keyword trend analysis, topic modeling analysis, semantic network analysis, and emotion analysis were performed. This study provides valuable insights into the impacts and perceptions of remote learning during the COVID-19 pandemic. It highlights the complexities of remote education, from influencing educational policies to affecting students' and parents' emotional states. The findings underscore the potential of remote learning in driving educational innovation while also pointing out its role in widening educational disparities. This research offers essential perspectives for shaping future educational strategies in crisis situations, emphasizing a balanced approach to harness the benefits of remote learning while mitigating its challenges.