Reviewerly/exHarmony huggingface dataset:
Teaching Reform and Ability Cultivation of Experimental Courses in Applied Chemistry

The experimental course in the applied chemistry specialty should have the same important position as the theoretical course.In view of the problems existing in the current teaching process of the experimental course in the applied chemistry specialty in colleges and universities, the teaching content should be reformed and adjusted, and the teaching methods should be innovated, so as to establish a sound, unified and standardized experimental course teaching reform and ability training system for the applied chemistry specialty, so as to improve the quality and level of teaching, Cultivate students' practical operation ability.This paper studies and analyzes the teaching reform and ability cultivation of the experimental course of applied chemistry specialty.
Feather: 3D sketchbook light as a feather

We present Feather, a 3D drawing system that allows users to create 3D curve artworks with a pen & touch interface on a tablet. We implemented multi-view 3D sketching by applying a concept of drawing & bending a “3D guide” and a view-oriented joystick widget that streamlines tedious 3D transformations—all of which are integrated into a single web application while maintaining the usability and look of conventional 2D drawing software.
Experience with augmented reality technology in the surgical treatment of a patient with encapsulated metal foreign bodies of lower extremities

This paper presents the experience of using augmented reality (AR) technology in the surgical treatment of a patient with encapsulated foreign bodies in the lower extremities. The study aims to test a previously developed algorithm for implementing AR technology in surgery and assess its effectiveness in treating patients with encapsulated foreign bodies. The study was conducted by a multidisciplinary team, comprising the Department of Naval Surgery of the S.M. Kirov Military Medical Academy and the Technical University named after Peter the Great. The medical and technical aspects involved an AR hardware and software package, including a personal computer and Microsoft Hololens II AR glasses. An invasive fixation system was also developed, incorporating a threaded pin used as an X-ray contrast mark with a seat for attaching special markers. The clinical part of the study involved observing and subsequently removing encapsulated foreign bodies in a patient who received inpatient treatment at the clinic of the Department of Naval Surgery in October 2022. Overall, AR technology demonstrated the potential for performing minimally invasive removal of encapsulated foreign bodies in limbs. The detailed visualization provided by AR allowed for determining optimal operative access, the volume of the upcoming operation, and the exact position, skeletotopy, and syntopia of the foreign body during the preoperative stage. Consequently, various intervention options could be digitally simulated. The use of AR technology facilitated intraoperative navigation, enhancing the safety and efficiency of the operation. Thus, AR technology has proven to be a minimally invasive, safe, and effective tool in surgical treatment. However, several unresolved issues require further research.
Faster Implementation of Ideal Lattice-Based Cryptography Using AVX512

With the development of quantum computing, the existing cryptography schemes based on classical cryptographic primitives will no longer be secure. Hence, cryptographers are designing post-quantum cryptographic (PQC) schemes, and ideal lattice-based cryptography has emerged as a prime candidate. Today, as ideal lattice-based cryptography becomes more mature, its performance becomes an important optimization goal. In ideal lattice-based cryptography, polynomial arithmetic and polynomial sampling are the most time-consuming operations and therefore need to be accelerated. In this article, taking advantage of the parallelism of new 512-bit advanced vector instructions (AVX512), we present parallel implementations of polynomial arithmetic and polynomial sampling, thus comprehensively improving their performance. We conduct experiments with the Dilithium scheme(one scheme of NIST PQC Standardization Process Round-4). Our implementation gets a nice performance boost compared to its pure C language and 256-bit advanced vector instructions (AVX2) implementation.
Error Analysis of Using Combined Directional Complementary Words “下来”, “下去” and “起来” in Students of The Chinese Language Education Study Program of Widya Kartika University Surabaya

In learning Chinese, students are inseparable from language errors. Learners often encounter errors in the yufa type of complementary word (补语bǔyǔ). The word complement itself is divided into simple complementary and combined words. Researchers found that many students of the Chinese Language Education Study Program of Widya Kartika University Surabaya had difficulty in understanding the use of the combined directional complementary words “下来” , “下去” and “起来”. Therefore, the researcher analyzed the incorrect use of the combined directional complementary words “下来” , “下去” and “起来” in students of the Chinese Language Education Study Program at Widya Kartika University Surabaya to find out the types and percentages of mistakes made and the factors that influence the occurrence of mistakes. The methods used in this study are qualitative and quantitative research methods. The conclusion of this study is that quite a lot of students of the Chinese Language Education Study Program of Widya Kartika University have done a lot and the type of mistakes made are mixed mistakes. Mistakes occur due to lack of understanding of theory, the influence of the mother tongue, namely Indonesian and teaching materials used.
A Functional Classification of Forensic Access to Storage and its Legal Implications

Due to their ease of use and their reliability, managed storage services in the cloud have become a standard way to store files for many users. Consequently, data from cloud storage services and remote file systems in general is an increasingly valuable source of digital evidence in forensic investigations. In this respect, two questions appear relevant: (1) What effect does data acquisition by the client have on the data stored on the server? (2) Does the technology support delayed verification of data acquisition? The two questions refer to critical aspects of forensic evidence collection, namely, in what way does evidence collection interfere with the evidence, and how easy is it to prove the provenance of data in a forensic investigation. We formalize the above questions and use this formalization to classify common storage services. We argue that this classification has direct consequences with regard to the probative value of data acquired from them. We, therefore, discuss the legal implications of this classification with regard to probative value so that IT expert witnesses can adapt their procedures during evidence acquisition and legal practitioners know how to assess such procedures and the evidence obtained through them from cloud storage services.
E-Learning in Higher Education during the COVID-19 Pandemic: A Bibliometric Analysis

Abstract It is undeniable that the COVID-19 pandemic has caused serious problems to education on a global scale, as well as to health systems and national economies. As a result, governments around the world have had to make extraordinary efforts to solve the various problems encountered not only in the area of health and the economy, but also in education. In terms of education, the changes include, but are not limited to, curriculum revisions, the provision of technology resources and infrastructure, changes in the academic calendar, and policies regarding instructional delivery and assessment. To limit the spread of the pandemic, universities, institutes and academic schools had to switch to online education using available educational platforms. This has been reflected in the emergence of numerous publications dealing with the subject. The study aims at the quantitative evaluation of the research carried out and published in the field of e-lerning in the university environment in the context of the pandemic crisis, starting from a comprehensive bibliometric analysis based on Scopus publications. The distribution of published papers in terms of years, authors, institutions, countries, journals, the network of co-authors, co-citations, and the cooccurrence of keywords is discussed. The main conclusions regarding the research trends in the field are drawn. The study represents a useful resource for those interested in the field of e-lerning in the academic environment in the context of COVID-19 that captures the main changes produced in the field and the potential research directions.
Advanced Driver Assistance System (ADAS) on FPGA

Advanced Driver-Assistance Systems (ADAS) can help drivers in the driving process and increase driving safety by automatically detecting objects, doing basic classification, implementing safeguards, etc. ADAS integrates multiple subsystems, including object detection, scene segmentation, lane detection, and so on.In this paper, we establish a framework for computer vision features, i.e., lane detection, object detection, object distance estimation and traffic sign recognition of ADAS.Modern machine learning algorithms like Canny edge detection for lane detection and a CNN-based approach are used for object detection.The system deployed aims to achieve higher (Frames Per Second) FPS for one channel of 55 FPS.The performance of FPGA is optimized by software and hardware co-design.Realization on the DE-10 Nano board with Cyclone V FPGA and a dual-core ARM Cortex A9, which meets real-time processing requirements.An increasing amount of automotive electronic hardware and software involves significant changes in the modern automobile design process to address the convergence of conflicting goals -increased reliability, reduced costs, and shorter development cycles.The prospectus to tackle car accident occurrences is making ADAS even more critical.This paper proposes an efficient solution for ADAS on FPGA.
English Final Semester Assessment at Vocational High School in Semarang

aims to find out the supporting factors of students’ English achievements in passing the final semester examination and the teachers’ perspective about obstacles that impact the incompleteness of students learning goals. This research is qualitative, it was carried out at SMK Negeri 4 Semarang, Indonesia. Since English is an international language so, people need to be able to speak English. The data collection method in this study is cluster random sampling, and the researcher chose two classes at the vocational school. They are XI Animation and XI Electronics Engineering. The data was obtained from an interview with the teacher from both classes and the final semester examination score that belongs to the students. The result is the average scores from both of the classes is almost the same, although the two classes have different learning styles, classroom environment, teachers, and different learning method.
Natural Language Modeling with the Tsetlin Machine

The Tsetlin Machine, a recently developed supervised learning algorithm with interpretability prospect, has been used in tackling challenging problems in classification, regression, and convolution in its short presence and obtained competitive results in terms of accuracy and computational resources. In the present work, we build a statistical language model based on the Tsetlin machine, which predicts the next most likely character in a partially given word. Moreover, with an online application in mind, we train and evaluate our model as a (one-pass) streaming algorithm emphasizing adaptability and customizability. Furthermore, we provide empirical evidence that our model exhibits comparable performance regarding learning speed and accuracy to a similar model based on multi-layer perceptrons.
Exploration of Teaching Methods for the Course of Introduction to Database Systems under the Mixed Teaching Mode

With the continuous deepening and development of education in the context of new engineering, the teaching models in universities are becoming increasingly diverse.This article takes the blended teaching mode as the starting point to explore the teaching methods of the course "Introduction to Database Systems".Through practice, it has been proven that adopting blended teaching mode can better stimulate students' learning interest, enhance their autonomous learning ability, and also improve teachers' teaching effectiveness and quality.On this basis, we also proposed some teaching strategies and methods for the database introduction course under the mixed teaching mode, aiming to provide valuable ideas and insights for database enthusiasts and educators.
Boundary distribution estimation for precise object detection

&lt;abstract&gt;&lt;p&gt;In the field of state-of-the-art object detection, the task of object localization is typically accomplished through a dedicated subnet that emphasizes bounding box regression. This subnet traditionally predicts the object's position by regressing the box's center position and scaling factors. Despite the widespread adoption of this approach, we have observed that the localization results often suffer from defects, leading to unsatisfactory detector performance. In this paper, we address the shortcomings of previous methods through theoretical analysis and experimental verification and present an innovative solution for precise object detection. Instead of solely focusing on the object's center and size, our approach enhances the accuracy of bounding box localization by refining the box edges based on the estimated distribution at the object's boundary. Experimental results demonstrate the potential and generalizability of our proposed method.&lt;/p&gt;&lt;/abstract&gt;
Mixed Reality Racing: Combining Real and Virtual Motorsport Racing

In this work, we proposed a proof-of-concept system that combines real and virtual racing, allowing professional racing drivers and e-racers to compete in real time. The real race car is imported into a racing game, and the virtual game car is exported into the real world in AR. This allows e-racers to compete against professional racing drivers and gives the audience an exciting experience from the grandstand with the use of AR. Our system was deployed during an actual racing event, and we gathered initial feedback from users. Both e-racers and audience expressed excitement about our system, indicating a strong potential for this new form of mixed reality racing.
Research on the Application of Orff Music Rhythm in Rural Preschool Children's Education

In the context of rural revitalization, we aim to improve the level of rural kindergartens, allowing rural children to learn advanced music courses like children in more developed areas.We have specially innovated a set of action courses that distinguish from traditional Orff music, which can achieve the same teaching quality and learning effects while reducing costs.Preschool education is an important part of children's growth, and we need to accelerate the resolution of the current problems in music courses in rural kindergartens.Therefore, this article analyzes why it is necessary to promote Orff music rhythm in rural areas, the benefits of promoting Orff music rhythm in rural areas, and the problems of Orff music rhythm in rural gardens, in order to explore methods to solve the above problems.Orff's teaching method was proposed by Carl Orff, a famous German music educator.After years of development and dissemination, it has become a music education system that is the most widely spread and influential in China's music education.Orff music teaching combines music and games that interest young children, advocating for improvisation and free and open teaching.The teaching philosophy and methods of the Orff music teaching method are suitable for the development of children's thinking [1].In Orff music teaching, teachers abandon the traditional "replicator" mode of music teaching and allow each child to participate independently, hands-on, mouth and foot movements, singing, playing, dancing, and playing games.They independently use various music elements to design music, actions, and plot, and perceive and create music through experience and creation, Promote improvisation and free imagination in each specific educational context.The innovation that distinguishes it from traditional Orff music education is to create a set of Orff movements that children can accept, greatly reducing the difficulty of the activity and making it easier for children to master.However, the current promotion status of Orff in China should still be taken seriously. Why advocate for Orff music rhythm in rural areasPeople located in rural and remote areas, through long-term daily and production processes, have formed folk music passed down from mouth to mouth to express their longing and love for a better life.In this context, combining the rhythm of Orff music with traditional Chinese rural music can quickly make Orff music accepted and loved by rural children.From the perspective of children's interests and playfulness, Orff's music rhythm encourages them to participate in music activities,
Design and Implementation of Machine Learning Modelling through Adaptive Hybrid Swarm Optimization Techniques for Machine Management

Because of the billions of transactions that take place every day, the volumes of information is always growing.There are a plethora of categorization techniques accessible for extracting usable information from the massive quantity of information obtained.Swarm optimization methods, as well as hybridizations of these techniques, are now playing a significant role in classifications, and they do so in a very efficient way.An introduction and thorough comparison of many swarm optimization techniques & hybrid swarm optimization techniques that have been published in the academic journals are presented in this article.Bio-inspired computing is a fascinating field of machine learning that investigates how natural occurrences may serve as a rich source of motivation for the development of clever processes that can be turned into strong algorithms in the future.In categorization, prediction, & optimization issues, several of these methods have been utilised effectively.In the field of optimization, swarm intelligence techniques are a kind of microbially algorithm that has been proven to be very effective for quite some time.However, in order for these algorithms to function at their peak levels, the starting variables must be adjusted correctly by a skilled user who knows what they're doing.The development and expansion of machine management are aided greatly by the use of efficient machinery and equipment.Different research investigations are engaged in the execution of the study and reviewers have concluded that machine learning technologies are the most effective means of supporting this expansion of the research.In order to better understand machine learning technologies and machine learning algorithms, the majority of implementations are investigated using swarm intelligence optimization techniques.As a result, they may be used as an essential judgement tool in the manufacturing industry.
High-Resolution Volumetric Reconstruction for Clothed Humans

We present a novel method for reconstructing clothed humans from a sparse set of, e.g., 1–6 RGB images. Despite impressive results from recent works employing deep implicit representation, we revisit the volumetric approach and demonstrate that better performance can be achieved with proper system design. The volumetric representation offers significant advantages in leveraging 3D spatial context through 3D convolutions, and the notorious quantization error is largely negligible with a reasonably large yet affordable volume resolution, e.g., 512. To handle memory and computation costs, we propose a sophisticated coarse-to-fine strategy with voxel culling and subspace sparse convolution. Our method starts with a discretized visual hull to compute a coarse shape and then focuses on a narrow band nearby the coarse shape for refinement. Once the shape is reconstructed, we adopt an image-based rendering approach, which computes the colors of surface points by blending input images with learned weights. Extensive experimental results show that our method significantly reduces the mean point-to-surface (P2S) precision of state-of-the-art methods by more than 50% to achieve approximately 2mm accuracy with a 512 volume resolution. Additionally, images rendered from our textured model achieve a higher peak signal-to-noise ratio (PSNR) compared to state-of-the-art methods.
Security in Medical Image Management Using Ant Colony Optimization

Data encryption before transmission is still a crucial step in lowering security concerns in cloud-based environments. Steganography and image encryption methods validate the security of confidential data while it is being transmitted over the Internet. The paper presents the Ant Colony Optimization with Encryption Curve cryptography-based steganography technique to enhance the security of medical image management (ACO-ECC-SMIM). The initial stage is to create the stego images for the used cover image, the ACO algorithm-based image steganography technique is used. The creation of the encryption process is a key focus of the suggested ACO-ECC-SMIM strategy. The encryption process is initially carried out using an ECC technique, or elliptic curve cryptography. To maximize PSNR, the ACO technique is employed to optimize the crucial production process in the ECC model. The host image is subjected to an integer wavelet transform, and the coefficients have been altered. To determine the ideal coefficients where to conceal the data, the ACO optimization technique is utilized. The decryption and sharing reconstruction procedures are then carried out on the receiver side to create the original images. In image 1, the ACO-ECC-SMIM model showed an improved PSNR of 59.37dB. Image 5 has an improved PSNR of 59.53dB thanks to the ACO-ECC-SMIM model. A large-scale experimental investigation was conducted to show the improved performance of the proposed PIOE-SMIM method, and the findings demonstrated the superiority of the ACO-ECC-SMIM model over other approaches.