Reviewerly/exHarmony huggingface dataset:
Improving Endoscopic Image Quality through the Use of High Dynamic Range Imaging-Like Method with Real-Time Performance

High Dynamic Range (HDR) imaging is a digital image processing technique used to produce a wider range of brightness and color by using multiple captures of a scene taken with different exposures times. It enables capturing more details and producing a more natural-looking image with less washed-out highlights and deeper, more saturated colors. In medical endoscopy, HDR imaging enhances the visibility and clarity of images captured during endoscopy procedures. It provides enhanced visualization of subtler details in both dark cavities and bright areas, resulting in a uniformly exposed view and improved contrast among various tissue types. Standard HDR imaging methods are often complex and computationally demanding, making them unsuitable for performance-critical applications like endoscopy, where real-time performance is crucial. This paper introduces a more efficient and less complex method for achieving HDR-like image quality in real time. The method takes a high-pixel-bit-depth frame and generates multiple low-pixel-bit-depth frames and uses them to generate the high quality image. The focus of the paper is to enhance endoscopic image quality using HDR imaging, and the proposed method is demonstrated to be effective in achieving this goal with real-time performance. The method is implemented in the FPGA System-on-a-Chip (SoC) of a bronchoscope video processor system, and its effectiveness is verified through a simulated study using a phantom, which confirms the improved image quality and real-time performance.
A Linear Algebraic Framework for Dynamic Scheduling Over Memory-Equipped Quantum Networks

Quantum Internetworking is a recent field that promises numerous interesting applications, many of which require the distribution of entanglement between arbitrary pairs of users. This work deals with the problem of scheduling in an arbitrary entanglement swapping quantum network — often called first generation quantum network — in its general topology, multicommodity, loss-aware formulation. We introduce a linear algebraic framework that exploits quantum memory through the creation of intermediate entangled links. The framework is then employed to apply Lyapunov Drift Minimization (a standard technique in classical network science) to mathematically derive a natural class of scheduling policies for quantum networks minimizing the square norm of the user demand backlog. Moreover, an additional class of Max-Weight inspired policies is proposed and benchmarked, reducing significantly the computation cost at the price of a slight performance degradation. The policies are compared in terms of information availability, localization and overall network performance through an ad-hoc simulator that admits user-provided network topologies and scheduling policies in order to showcase the potential application of the provided tools to quantum network design.
Cutting the Gordian Knot: Standardizing Uncrewed Systems Data Formats

The past several years has seen an explosion in the number of commercially available uncrewed systems. These systems range in size and complexity from the 5-foot Slocum glider to the 72-foot Saildrone Surveyor. While the vehicles vary widely in size, complexity and capabilities, they all share one common element: they each use a different access methodology and format for vehicle and scientific data. The data formats are typically optimized to work with the control and visualization systems provided by the manufacturer, which makes perfect sense. Unfortunately, the multiple data formats make ingesting the data into uncrewed systems portals, such as the GCOOS operated GANDALF (https://gandalf.gcoos.org) extremely difficult. Adding support for a new platform requires the portal development team to create a new data integration module that can provide translation services from the vendor's data format to a standard data format such as NetCDF. In many cases, the portals are maintained by a very small team of one to three members. Integrating a new platform is a non-trivial task and may take months to accomplish. The ramification of having this Gordian knot of differing data formats is that we are seeing a large increase in the number of observations being made, but there is no corresponding increase in the number of observations available on the GTS (global telecommunications service) or the IOOS DACs (data assembly centers) and ERDDAP servers.
Analysis and Research of Utilization Rate on Stage Machinery of Opera House

Stage machinery is an important part of theater performance, and different performances use different forms of equipment. This paper analyzes and summarizes the use rules of different performance equipment in the performance, and provides effective data reference for the construction and management of “smart theater”. Firstly, the theater and stage layout are outlined, and divided into different areas. Secondly, the stage machinery used in home-made plays of the Opera House of the National Centre for the Performing Arts from 2008 to 2023 and the external plays performed from 2014 to 2018 are counted. The evaluation index of equipment utilization rate is used to evaluate and visualize the stage equipment. Besides, the correlation analysis is conducted between the on-stage and off-stage and the fitting effect is evaluated by linear regression. Finally, the utilization rate trend charts are drawn respectively. The statistical results are within the credible range and consistent with the actual situation.
Quantum Attacks without Superposition Queries: the Offline Bernstein-Vazirani Meets Grover Algorithm

Block cryptanalysis has a major breakthrough in the model of superposition queries. For instance, Simon’s algorithm can efficiently break various constructions. In practice, Bernstein-Vaziran’s algorithm can also realize the periodic search of the vector function. Moreover, in some cases, it can have more advantages than the Simon’s algorithm.In the context of this study, we present an algorithm that combines Grover’s and Bernstein-Vazirani’s quantum algorithms. This algorithm empowers us to carry out key recovery attacks on Feistel structures. on Feistel structures, FX construction and Even Mansour construction. We exploit cryptosystems’ algebraic structure to launch successful key recovery attacks, considering that quantum attackers can only make classical queries. Through comparison, it can be concluded that this algorithm has stronger practicability in attacking block ciphers.
A Test Method for Shortening Test Time of Cloud Computing Platforms

The reliability of cloud computing platforms is crucial. Due to its numerous levels and components, testing requires a significant amount of time. The existing research aimed at shortening test time has room for improvement. They ignored a situation that not all test steps are necessary, which is our direction for improvement. We design virtual machine feature transformation method to enable it reused across test cases, thus avioding the time spent in frequent creation and deletion virtual machine. In this scenario, we abstract the problem into an Asymmetric Traveling Salesman Problem and use greedy algorithms to minimize the total testing time. According to simulation results, our method has achieved good results.
Action Recognition Based on Multi-Level Topological Channel Attention of Human Skeleton

In action recognition, obtaining skeleton data from human poses is valuable. This process can help eliminate negative effects of environmental noise, including changes in background and lighting conditions. Although GCN can learn unique action features, it fails to fully utilize the prior knowledge of human body structure and the coordination relations between limbs. To address these issues, this paper proposes a Multi-level Topological Channel Attention Network algorithm: Firstly, the Multi-level Topology and Channel Attention Module incorporates prior knowledge of human body structure using a coarse-to-fine approach, effectively extracting action features. Secondly, the Coordination Module utilizes contralateral and ipsilateral coordinated movements in human kinematics. Lastly, the Multi-scale Global Spatio-temporal Attention Module captures spatiotemporal features of different granularities and incorporates a causal convolution block and masked temporal attention to prevent non-causal relationships. This method achieved accuracy rates of 91.9% (Xsub), 96.3% (Xview), 88.5% (Xsub), and 90.3% (Xset) on NTU-RGB+D 60 and NTU-RGB+D 120, respectively.
Data as a tax base

If we are in the dawn of a ‘fourth industrial revolution’, the significance of data and information will increase in its importance in our day-to-day lives. The fourth industrial revolution is predicted to absorb technology into ‘things’ and bodies, integrating technology into machines such as motor vehicles and home appliances so they communicate with each other and also with people. In light of both the current age of information technology and these potential future developments, this chapter considers the use of data and its ability to generate wealth for those with access to large databases. In a time when excessive inequality of wealth is becoming a significant global concern, the shifts in wealth toward ‘big tech’ companies is under the spotlight. These shifts in wealth are, in large part, facilitated by the access these organisations have to large-scale databases, enabling the commercial exploitation of this data using algorithms. This chapter puts forward the case that the volume of data collected by these organisations from their users could be used as a tax base. That is, a tax could apply to the bits or bytes transferring from the user to the data recipient. Taxing the collection of data would go some way toward redistributing wealth back to the user’s jurisdiction.
THE ROAD TO AN OPEN AND SECURE DATA EXCHANGE INFRASTRUCTURE FOR SHM

OPEN JOURNAL SYSTEMS Journal Help SUBSCRIPTION Access All Papers USER You are logged in as... admin My Journals My Profile Log Out NOTIFICATIONS View (7 new) Manage JOURNAL CONTENT Search Search Scope All Browse By Issue By Author By Title FONT SIZE Make font size smallerMake font size defaultMake font size larger INFORMATION For Librarians Table of Contents Purchase Full Access Hard Cover THE ROAD TO AN OPEN AND SECURE DATA EXCHANGE INFRASTRUCTURE FOR SHM HORST TRATTNIG, LUKAS BERBUER ABSTRACT Today, structural health monitoring systems consist of various hardware and software components that are not always well synchronized. The paper emphasizes the need and challenges to synchronize multi time-domain and multi physical-phenomena data acquisition systems. On the way from a raw data sensor system to an independent decision-making edge device, there are still some challenges to be solved along the way. Identifying and combining technologies from foreign domains is the focus of the journey. Open and standardized communication protocols like OPC UA or MQTT are already wellestablished technologies with a high level of security. These communication protocols allow users to discover and receive structured data from compatible sensors and edge devices in the network. Moving the data processing and decision-making further to edge leads to reduced data transfer volume, lower latencies and improved privacy, security, and cost-effectiveness. This requires an extensible platform to embed custom feature extraction algorithms and to deploy trained machine learning models. ONNX, the open standard for machine learning interoperability, is a further puzzle piece on this journey. The paper shows the status of work, ongoing developments in the open standard community like OpenAE and platform strategies for advanced analytics and AI.
DAMAGE DETECTION OF RECTANGULAR SECTIONS BY 2D CURVELET, CONTOURLET AND WAVELET PACKET TRANSFORM

In this research, the application of 2D curvelet, 2D wavelet, and Contourlet transform for damage detection of shell structure are presented. For this study, the equation of discrete curvelet transforms using unequally-spaced fast Fourier and wrapping transforms are employed. Four scenario models with one and more damages with different percentages and locations were considered for investigation of proposed methods. As real data has noise, and the existence of noise in the input data may affect the accuracy of damage detection methods. To consider the natural conditions, white noise has been applied to the data extracted from the FEM. First, the coefficients of transforms related to the noisy signal are calculated, then thresholding the previous coefficients calculated, and finally, the de-noise signal is reconstructed. Based on the presented results, the curvelet transform better identifies the location of damage than the wavelet transforms. Wavelet transform based on the direction of the damage element may be specified in some subbands. But in curvelet and Contourlet, it can better identify different damages in different directions due to the multi-directional transform. The curvelet transform has been modified based on polar space and poses challenges for non-polar (normal) discrete space. Therefore, using the Contourlet is divided into multiple directions because of each of the available general directions. According to the obtained results, the proposed methods are sensitive to the location and percentage of damage and can identify the location of damage with a low percentage of damage. Also, to confirm the results of the proposed methods, the results are evaluated using laboratory results. The results show that the proposed methods can identify the location of damages and with a percentage of damage of up to 3%.
A Comparative Analysis of Machine Learning Algorithms on Card-Based Financial Fraud Detection with Infusion of Sigmoid and Isotonic Functions

There is no doubt that the commencement of the e-revolution in the financial sector of the economy has introduced opportunity for electronic fraud in the card payment ecosystem globally. This is occasioned by factors such as increased knowledge in the fintech space, poverty, pair pressure on the perpetrators. This study was focused on comparing of several known Machine leaning Algorithms – Logistic regression, Decision trees, Random Forest, Extra-Trees, Adaboost and Gradient boosting on how they perform comparatively when applied to Fraud detection. The raw data used were obtained from The Xente Fraud Detection data set used for the development of the financial fraud detection model which includes sample of approximately 140,000 transactions categorized into Fraud and Non-Fraud. Results from the study indicated that Adaboost Model outperformed the remaining applied models thereby making Adaboost a good model for fraud detection. Further research work can be carried out by comparing the performance with other Deep Learning Algorithms.
A Brief Overview of Genetic Algorithms

This article examines the topic of Genetic Algorithms, discussing the basic concepts and terminology related to Genetic Algorithms. The advantages, disadvantages and limitations of the mentioned algorithms are defined. The different population models and the process of parent selection are presented, as well as the areas of application of the procedure are summarized.
Development of a Test Bench to Solve a Simple Labyrinth

This paper deals with building an automatic test bench for detecting and solving a simple maze. There are many suitable sensors for detecting walls and ball, as find quick and stabile algorithm for deliver the ball to the target. Two servo motor are used to tilt the table of the maze. The first part of the paper shows the experiences of using OV7076 camera with Arduino Nano which was used for the first time to solve the problem. The final version of the maze solver contains a USB camera, an Arduino UNO platform, OpenCV and PyCharm software. Furthermore, paper reveals possibilities of decision-making-process and the direction of following research work.
A Protocol for Conversion of Path-Spin to Spin-Spin Quantum Entanglement

The present model deals with a protocol which involves the generation and conversion of entanglement from path-spin (P-S) hybrid entanglement associated with half-spin particle to spin-spin (S-S) interparticle entanglement. This protocol finds its applications in quantum information processing via a series of operations which include a beam splitter, spin flipper, spin measurement, classical channel, unitary transformations. Finally, it leads to two particles having completely entangled spin variables, without any requirement of any simultaneous operation on the two particles.
Comparative analysis of MapReduce and Apache Tez Performance in Multinode clusters with data compression

This article conducts a thorough comparative analysis of Apache Tez and MapReduce in the context of big data processing. It focuses on key performance metrics, scalability, and ease of use. The analysis begins with an overview of the architectural distinctions between the two frameworks, emphasizing their fundamental design principles. A detailed performance evaluation follows, considering factors such as execution time, resource utilization, and throughput across diverse workloads. The study explores scalability by examining how Apache Tez and MapReduce respond to increasing data volumes and computational demands. Cluster size effects, resource allocation strategies, and adaptability to dynamic workloads are scrutinized. Additionally, the article evaluates the frameworks' ease of use for developers and administrators, incorporating aspects like programming model simplicity, debugging capabilities, and system configurability. User experiences are gathered through surveys and practical use cases. The conclusions drawn from this analysis offer valuable insights for organizations and practitioners seeking suitable distributed computing frameworks. By addressing both performance and user experience, the article aims to provide a comprehensive perspective on the strengths and weaknesses of Apache Tez and MapReduce, assisting decision-makers in making informed choices for their big data processing requirements.
Electronic educational resources for teaching mathematics in primary school

The article is devoted to the study of the use of electronic educational resources in teaching mathematics in primary school. The literature review examines current trends in developing electronic learning tools and their implementation in the educational process. Different types of electronic resources are considered, and their advantages and disadvantages are revealed. The main trends and achievements in the electronic means of teaching mathematics are presented, and the advantages and disadvantages of using electronic educational resources are investigated. Examples of successful implementation of electronic means in teaching mathematics are given.
Using the opportunities of spreadsheets for computer simulation

The article examines the effectiveness of using table processors in computer modeling. The authors consider the possibilities provided by modern spreadsheet processors, particularly their power and flexibility, as a tool for creating and using various models. The article examines specific cases of using spreadsheets in educational activities, particularly during the study of mathematics and informatics in secondary education. It is noted how this approach can facilitate the process of modeling and working with data, making them more accessible and understandable for a wide range of users. The advantages and limitations of using spreadsheet processors for computer simulations are analyzed to provide a comprehensive overview of their potential in this context.
Using the Wordpress CMS in the classroom at secondary schools

The article discusses the features of using the WordPress content management system in teaching the basics of web development in general secondary education institutions where computer science is taught according to the specialized curriculum. The paper identifies the main advantages and disadvantages of using WordPress. Practical recommendations for teachers on using WordPress in computer science lessons are provided.
Measuring Digital Learning Trends and Accessibility Convenience in Enhancing Early Childhood Literacy and Language Proficiency: The Role of Smart Book Media from the Perspective of Banten Javanese Language

This study explores the relationships between digital learning trends, accessibility convenience, smart book media, early childhood literacy, and language proficiency in Banten Javanese Language. Using a quantitative approach with 140 young learners (aged 10-12), we assessed how digital learning trends and accessibility convenience impact smart book media, early childhood literacy, and language proficiency. Results show that digital learning trends notably affect smart book media’s functionality, contributing to developing early childhood literacy and language skills. Additionally, accessibility convenience is crucial in enhancing smart book media’s utility, fostering early childhood literacy and language proficiency. However, while smart book media significantly influence language skills and early childhood literacy, they don’t mediate the connections between digital learning trends, accessibility convenience, and these language-related outcomes. Educators and stakeholders can utilize these findings to shape culturally sensitive language education strategies, incorporating technology and resource accessibility. This research enriches the theoretical understanding of digital learning trends and accessibility convenience’s impact on language outcomes. It highlights the practical potential of smart book media in language education, aiding educators and policymakers in aligning strategies with contemporary trends and cultural nuances. While limited to Banten Javanese Language, the study prompts further exploration through qualitative and longitudinal studies. Future research should explore cultural influences and intervention programs for optimizing language development. By uniquely merging digital learning trends, accessibility convenience, smart book media, and language outcomes, this study contributes valuable insights to the discourse on language education and technology integration within the distinct context of Banten Javanese Language.