Reviewerly/exHarmony huggingface dataset:
Cross-domain endoscopic image translation and landmark detection based on consistency regularization cycle generative adversarial network

The mitral valve simulator provides an important training scenario for mitral valve suture repair surgery. However, since there are differences between simulator scenarios and intra-operative scenarios, trainers may not adapt well to real surgeries. To enhance the realism of simulator scenarios, generative adversarial network (GAN) based methods can transform simulator endoscopic images into intra-operative style. Nonetheless, due to the variable number of suture landmarks and their unclear structural relationship in endoscopic images, maintaining content consistency after transformation becomes a challenging task. To address this issue, we present an improved consistency regularization cycle generative adversarial method (RegCycleGAN) in this paper. RegCycleGAN jointly optimizes CycleGAN and equivalent perturbation landmark detectors, considering that the location of suture landmarks could provide quantitative information when analyzing the consistency of image content. RegCycleGAN is capable of generating pseudo-images with consistent content and detecting suture landmarks on endoscopic images more accurately. We use a student–teacher network with exponential moving average (EMA) to provide generators with more consistent suture landmarks information. Additionally, we have developed an equivalent perturbation transformation module to improve the training stability of landmark detectors. Our method has demonstrated superior performance in image generation and landmark detection on two test datasets from the AdaptOR Challenge. The final results demonstrate that our method increases the value of F1 from 42.828% to 47.020% and from 48.776% to 50.401% on the two test set respectively. It indicates that RegCycleGAN provides a competitive performance in comparison to the state-of-the-art image translation methods in endoscopic image-to-image translation and landmark detection tasks.
NextLens—The Next Generation of Surgical Navigation: Proof of Concept of an Augmented Reality System for Surgical Navigation

Abstract Objective The aim of this work was the development of an augmented reality system including the functionality of conventional surgical navigation systems. Methods An application software for the Augmented Reality System HoloLens 2 from Microsoft was developed. It detects the position of the patient as well as position of surgical instruments in real time and displays it within the two-dimensional (2D) magnetic resonance imaging or computed tomography (CT) images. The surgical pointer instrument, including a pattern that is recognized by the HoloLens 2 sensors, was created with three-dimensional (3D) printing. The technical concept was demonstrated at a cadaver skull to identify anatomical landmarks. Results With the help of the HoloLens 2 and its sensors, the real-time position of the surgical pointer instrument could be shown. The position of the 3D-printed pointer with colored pattern could be recognized within 2D-CT images when stationary and in motion at a cadaver skull. Feasibility could be demonstrated for the clinical application of transsphenoidal pituitary surgery. Conclusion The HoloLens 2 has a high potential for use as a surgical navigation system. With subsequent studies, a further accuracy evaluation will be performed receiving valid data for comparison with conventional surgical navigation systems. In addition to transsphenoidal pituitary surgery, it could be also applied for other surgical disciplines.
Generalized polarization measurement and its connection with information energy

Abstract We generalize the polarization measurement to the projective measurements of mutually unbiased bases (MUBs). Based on this result, we reveal a direct connection between polarization measurement and information energy function. We also express the polarization measurement by means of symmetric informationally complete positive operator-valued measures (SIC-POVMs). We present an argument suggesting that polarization measurement by means of SIC-POVMs requires fewer resources than the projective measurements of MUBs.
Digital Voting System Based on Blockchain Technology

A couple of sorts of casting a ballot have existed from that point. Paper polling forms are the most often used kind of casting a ballot from one side of the planet to the other. An electronic democratic methodology has lately turned out to be notable, yet unsolvable. Security, credibility, straightforwardness, fixed quality, and helpfulness are among the issues that e-casting a ballot strategy raise. In any case, there are a couple of blockchain-based different choices. Blockchain might conceivably tackle every one of the difficulties outlined above while similarly giving benefits like consistent nature and decentralization. The fundamental load of blockchain-based e-voting progress is their restricted highlight on a singular field or the other hand a shortfall of testing and assessment. We portray a blockchain-based e-voting stage in this article that may be used for digital voting. Blockchain utilizes it, and all cycles may be done inside it. After the democratic begins, the stage was limited to a free what's more, decentralized stage with no ability to affect the digital voting framework. The data is absolutely direct, however similar form of encryption is used to protect voter's characters. In three specific blockchains, we attempted and considered our response. The disclosures suggest that public and private blockchains may be used with minor speed contracts
Cyber Security and Artificial Intelligence for Cloud-based Internet of Transportation Systems

The Internet of Things (IoT) has major implications in the transportation industry. Autonomous Vehicles (AVs) aim at improving day-to-day activities such as delivering packages, improving traffic, and the transportations of goods. AVs are not limited to ground vehicles but also include aerial and sea vehicles with a wide range of applications. To overcome this problem we are implementing Cyber Security (CS) based data transfer to Autonomous vehicle. Here a cloud is the mediator that which transfers sender files to autonomous vehicle with more security we are using CS based (Advanced Encryption Standard), and SHA-1 algorithms which are used to hide the transferred data into cipher text. The cipher text can be decrypted by the private key generated by sender to the particular AV.
Robust Image Forgery Detection Over Online Social Network Shared Images

In servers and mobile users, an image is sent over the social network or exchanged. Due to the fact that it contains delicate personal information, the privacy of that data is crucial. A hacker may use social information about a person to discredit them if their image is hacked. Text-based encryption can be used in mobile cloud computing under the current architecture. There are various ways to store data securely utilizing mobile computing, including end-to-end encryption of data transmission and dynamic credential generation that only generates text. We'll be creating a brand-new wavelet watermarking technique called the discrete wavelet transform for use in real-time social network applications like Facebook, and this study suggests an efficient image forgery detection method that recognizes a manipulated foreground or background. Using this technique, images can be used and safely kept on servers. We categorize the image as either common or delicate, and we also enhance the project to include copy right implementation. Run copyright algorithms referred to as wavelet transform algorithms when employing sensitive techniques. After that, provide the receiver secure access to download the pictures. Using C#.NET as the front end and SQL SERVER as the back end, experimental results show the efficiency of current algorithms in real-time social network contexts and a comparison of their privacy rates
BovCria: an application designed to assist breeders in the assessment of beef cattle herds

The aim of this study was to develop a technological tool in the form of a mobile application that provides functionalities for the easy calculation of reproductive and productive efficiency indices. This tool aims to assist breeders, technicians, and students of agricultural sciences in decision-making for the challenges faced in cattle production systems. The application was developed using the Android Studio development environment and the Dart programming language framework known as Flutter. The application's graphical interface follows Google guidelines in the Material Design documentation. The tool will provide a practical way to calculate recognized indexes of productive efficiency of cow-calf systems and provide information such as goals and management tips to help users achieve better results. The impact of the developed product is its use as an information platform, facilitating decision-making in the area of beef cattle production and as an efficient means of disseminating technologies generated by research institutions and popularizing science. Thus, the application is an accessible and comprehensible tool, providing a means of evaluating the technologies and management practices adopted in beef cattle farms.
Management of Geospatial Data using Blockchain

The data generated all over the world is ever increasing. With this increase, the need to secure and regulate the use of data has become necessity. This can be achieved using blockchain. In case of geospatial data, which is of very large size and mostly unaltered once generated, storing it on blockchain is a challenging task. Storing it on-chain is practically not feasible as of now but storing actual off-chain and just storing metadata on the blockchain is the most practical &amp; feasible solution available currently. To store large amount of data and at the same time provide the efficient &amp; permission-based access to it, we have proposed a solution. Our solution will maintain a record of authorized nodes and the blockchain of metadata of large geospatial data. To provide an efficient querybased access, we will use MongoDB to store the pointer to the nodes in the blockchain to directly access the block. The storage of just metadata on the blockchain will reduce the complete blockchain size considerably. This model provides both the efficient &amp; secure large scale storage while providing the efficient query &amp; access mechanism at the same time. Also, we will use graphical way to grant permission
Sign Language Detection in Voice Output

This Sign language detection is the process of recognizing and interpreting gestures, symbols, and movements used in sign language. This technology is significant in enabling communication between individuals who are deaf or hard of hearing and those who do not know sign language. Sign language detection uses video data analysis and identifies specific features such as hand and arm movements, facial expressions, and body language. Machine learning techniques, specifically convolutional neural networks, are used to recognize and classify specific signs and gestures with an accuracy rate of 80-90%. To enhance the system's usability, the policy should include record and history tabs. Additionally, the dataset can be modified to suit different sign languages. Overall, this technology offers immense potential for education and communication for individuals with hearing impairments
Analysis and Comparison of the Spring Framework, Struts Framework, Vaadin Framework, and Play Framework Performance, Used to Create Web Applications in Java

In an era of continual technical growth, accompanied by an increase in the speed of computers and the Internet, it is also vital to create methodologies and programming languages, as well as other mechanisms that assist programmers in their job. As a result, frameworks, or skeleton applications, were developed to streamline program authoring and unify the structure of multiple applications. This article aims to analyze and evaluate the performance of four prominent frameworks used to create a server element of a Java online application, namely the Spring Framework, Struts Framework, Vaadin Framework, and Play Framework
LINKING THE TEACHERS’ TECHNOLOGICAL CAPACITY ON THE INTEGRATION OF ICT AMONG THE SCHOOLS IN THE DIVISION OF LAGUNA: BASIS FOR TECHNOLOGICAL UPSKILLING PROGRAM FOR TEACHERS

This study explores the relationship between the technological capacity of teachers and the integration of Information and Communication Technology (ICT) in schools in the Division of Laguna. The research aimed to assess the level of technological competence among teachers, the readiness of schools to integrate ICT, and the adoption of ICT strategies in schools. The study used purposive sampling to select public school teachers from five municipalities in Laguna. Data were collected through a survey questionnaire and analyzed using mean, standard deviation, T-Test, Pearson-r Correlation, and ANOVA. Results show that most teachers in the sample population were relatively young and had completed college education, while the majority were junior high school teachers. There were significant differences in the ICT integration among teachers at different levels of schooling, as well as based on age, civil status, educational attainment, and trainings attended. These findings suggest the need for a technological upskilling program tailored to the specific needs of teachers at different levels of schooling. The study also revealed that technological competence among teachers is essential for the effective integration of ICT in schools. Thus, there is a need for a technological upskilling program for teachers, especially for those who are less prepared and less familiar with ICT. The significant differences in ICT integration across the three levels of schooling imply that teachers at different levels of schooling may have varying levels of preparedness and familiarity with ICT. Overall, this study provides insights into the factors that influence the integration of ICT in schools and contributes to the design of technological upskilling programs for teachers.
Research on document detection and recognition based on deep learning

As an important technology to promote office automation, document detection and recognition can improve the efficiency of business processes and user experience, make enterprise business more intelligent, and have very broad application scenarios. In this paper, a document detection and recognition system based on DB detection model and CRNN recognition model is built to detect and recognize document images using 3.64 million samples from the image dataset intercepted by ICDARD 2015 and Chinese corpus, and display the document information in the corresponding table in real time. The test results show that the system effectively improves the model inference speed while ensuring the accuracy of document recognition and detection, and completes the document information entry efficiently and quickly.
Architecture for Quantum-in-the Loop Real-Time Simulations for Designing Resilient Smart Grids

With the power grid growing more complex every day with the inclusion of new sensors and regulatory approvals that enable end-users and small local developers to participate in the grid, it is becoming challenging for conventional smart grid simulation, emulation, and testing technologies to keep up. In this work, we propose that quantum-encoded real-time simulations can be helpful under the new paradigm and operational circumstances to solve optimization problems for power grids. By leveraging the principles of quantum mechanics, the proposed quantum-in-loop (QIL) framework will enable better and faster optimization solutions based on real-world, real-time data streams, facilitating the real-time planning and operations of electrical grids that rely on millions of distributed sensors and controllers. Furthermore, QIL will allow researchers and engineers to assist utilities in designing, developing, and de-risking algorithms to optimize power grid operation and resilience by considering inputs from millions of grid-connected devices. QIL framework is being developed to have a self-limiting triage mechanism, which will help engineers and practitioners identify fundamental physical limits on quantum processors, revealing what quantum algorithms can and cannot do in utility-specific use cases and must continue to count on classical high-performance computing infrastructure.
A Prototype of Efficient Learning System for Objective-Driven Learners

Personalized learning path recommendation is widely studied to address the cognitive overload and learning disorientation problem in e-learning platforms. Yet, how to recommend learning materials for learners so that targeting their learning objectives with the highest efficiency has not been addressed. Driven by this problem, this paper proposes a prototype to generate the most efficient learning strategies in the learning process for reaching learning objectives, it takes the learning ability of learners into consideration, and adaptively generates the optimal strategy in the learning process. A case that knowledge concepts have hierarchical relationships based on difficulty in one knowledge topic is studied, which is named series learning in this paper. Specifically, a learning state transition model is designed for selecting the optimal learning strategies in the learning process with the consideration of the changing learning ability of learners. Based on this model, a dynamically programming (DP) based method and a greedy-based method are designed to generate learning strategies with high efficiency. Experiments are conducted in both simulated and real learning scenarios. Results show that the proposed scheme significantly outperforms the baseline method.
Research on Educational Cognitive Computing Model Based on Problem Solving

With the rapid development of artificial intelligence technology and educational information, cognitive computing has become a new direction of the development of The Times. At the same time, problem solving ability as the advanced wisdom skills of students' learning results, is the comprehensive embodiment of students' ability. The study of cognitive computing in the process of human problem solving will provide a path for computer combined with artificial intelligence technology to simulate peers to realize human assistance, understanding and decision-making, and also provide guidance and supervisor for personalized teaching in the process of education. This study is based on the SOAR model, from the perspective of learners cognitive problem solving process simulation to get the educational cognitive model, and specific problem solving as an example, analysis of the cognitive behavior process of the subject and the model of the internal elements of the correlation, so as to verify the accuracy of the model overall.
Experimental realization of physical reservoir computing-based mechano-intelligence in self-adaptive phononic metastructures

This research experimentally investigates the integration of mechano-intelligence into mechanical metastructures for self-adaptive wave control. We created a phononic metastructure prototype utilizing periodic buckled beam modules that has highly adjustable wave propagation characteristics via length reconfiguration using a linear displacement actuator. By utilizing the physical reservoir computing framework, we show that the proposed metastructure can recognize and self-adapt to different inputs by making decisions on appropriate actuations to reconfigure itself to achieve an intelligent wave blocking task. Overall, this research provided a promising approach for constructing and integrating functional mechano-intelligence in structures harnessing physical computing and learning, and created a new direction for the next generation of adaptive structures and material systems.
Color Extraction Module for Unsupervised Image Classification Representation

Even though working with unlabeled data has the main advantages of lower preprocessing time and resources, the drawback is that the algorithms implemented have no connection between the output and ground truth, therefore is extremely hard to represent the results. This paper proposes a deployable stand-alone module for extracting the real color of the identified classes for a more intuitive representation of the final results.
Research on Application Status and Deepening Strategy of Smart Campus in Primary and Secondary Schools: Case Study of a County in Western China

With the deep application of big data, artificial intelligence and other technologies in the field of education, smart campus has received more and more attention in theory and practice. This study establishes the logical starting point from the characteristics of smart campus, construction of smart campus, typical applications, key technologies, development strategies and other aspects. In this study, an index system including information hardware environment, platform resources and smart campus application was established, and a questionnaire was prepared for the status quo of smart campus construction. Based on a questionnaire survey of 1494 teachers from 40 schools in a province in western China, the present situation of smart campus construction is understood, and the strategies for deepening the development of smart campus are put forward to promote the deepening development of regional education informatization.
Exploration of Mathematics Education by Metaverse Technology

The development of the metaverse has been integrating metaverse technology into the current educational environment. To make metaverse technology better applied in mathematics education, we introduce four types of technologies in the metaverse and consider their application in mathematics teaching. However, how to make full use of the four categories in mathematics education needs to be further explored. Based on the literature review, we focused on the possibilities of the educational metaverse in the field of mathematical development. Taking the classic course "The Pythagorean Theorem" in mathematics as an example, we designed and experimented with new teaching methods in the context of the metaverse. We hope that through the study of our course, we can provide more theoretical support and reference for how the metaverse can promote the better development of mathematics teaching.