Reviewerly/exHarmony huggingface dataset:
A Blockchain Query Optimization Method Based on Hybrid Indexes

Blockchain technology possesses the characteristics of decentralization and immutability, making it widely applicable in various fields. However, existing blockchain systems display weak performance in terms of data management, typically only supporting hash-based transaction querying. Current research on query methods usually involves synchronizing data with external databases, using external query engines, or building indexes to improve query performance. In index-based research methods, most blockchain systems build indexes within blocks to enhance query efficiency, but this does not reduce the time overhead of traversing all blocks. Additionally, most indexes only support a specific query type. In this paper, we propose a highly efficient indexing structure that divides data querying into two steps: first, obtaining potential blocks from the index structure that may contain the desired data, and then searching for the specific data records within those blocks. The indexes are further divided into numerical indexes and character indexes based on the attributes being indexed. We describe the construction and use of these two index structures for efficient data querying. As invalid blocks are filtered out, system query efficiency is greatly improved. The numerical index structure further supports range queries and top-k queries on this attribute, enhancing query capabilities. We also conduct experiments to verify the performance of our indexing structure. Results demonstrate that compared with baselines, our proposed index structure improves query performance, and offers a diverse range of query types.
BEAIV: Blockchain Empowered Accountable Integrity Verification Scheme for Cross-Chain Data

In recent years, while blockchain technology has the potential to revolutionize various industries, the issue of data silos presents a challenge to its development. To solve this problem, cross-chain technology is used to facilitate data sharing among different blockchain systems, promoting collaboration and integration between them. However, if the sending-chain or receiving-chain tamper with data during cross-chain interaction based on their own interests, it can severely compromise the integrity of cross-chain data, thereby rendering the entire cross-chain process meaningless. Therefore, in this paper, we propose a blockchain empowered accountable integrity verification scheme for cross-chain data(BEAIV). Considering the decentralized nature of block-chain, we adopt a supervision-chain for decentralized auditing instead of relying on a centralized third-party auditor. Notably, our scheme can not only detect the corruption of data integrity but also trace responsibility for dishonest entity. Furthermore, our proposed scheme supports batch auditing to enhance the efficiency of auditing process. Security analysis and performance evaluation show that BEAIV can verify the data integrity in cross-chain interactions, enabling secure and accurate cross-chain data sharing.
NFT-based identity management in metaverses: challenges and opportunities

Abstract A considerable number of people worldwide start their second lives in the digital world soon. The 3D Internet reflects the digital world. Metaverse, the most famous example of the 3D Internet, is very popular and practical in people’s daily lives. However, combining Metaverse with newly-emerging technologies (e.g., blockchain) provides new user-friendly features such as autonomy, accessibility, removing central authorities, etc. Despite the mentioned attractive features, blockchain-based metaverses suffer various challenges, such as one user with multiple identities, certificate issuing for users in Metaverse, authentication-related issues, and arresting malicious users. Generally, identity management in a distributed environment where no central authority exists is a challenging issue. This study focuses on the challenge of distributed identity management in Metaverses to strike a balance between users’ privacy and regulation. The study proposes the use of Non-Fungible Tokens (NFTs) as a tool for managing identities in metaverses, as they are considered an excellent choice for this purpose. In addition to explaining the importance of this idea, this paper identifies its challenges, including distributed identity management, authentication issues, and security and privacy aspects. It then proposes possible solutions (e.g., using cryptographic tools). Despite existing challenges, there are many opportunities in the popularization of Metaverse, such as relying on blockchain technology, emerging many Metaverse-related jobs, in-Metaverse investments for huge revenues, and applying digital twins to provide realistic senses. This study also highlights the critical role of artificial intelligence (AI) in metaverses.
Augmenting the Stone: Rock Art and Augmented Reality in a Nordic Climate

Sweden has some of the best-preserved Bronze Age rock art in the world, with more than 20,000 rock art sites. While there is no clear evidence indicating the origin of this tradition, in the World Heritage area of Tanum some of the rock art is enhanced with red colour. However, the practice flattens the more complex time-depth of the engravings and cements faulty interpretations, thus alternative ways for visualising the rock art are being considered. Globally, several Augmented Reality applications have been made for the visualisation of rock art; however, none have yet been developed for the Nordic context, where conditions are affected by seasonal elements. With Tanum, Sweden, as a case study, this paper discusses the challenges in applying Augmented Reality to Nordic Rock Art.
The Process of Meaning Creation: A semiotic Analysis of Facebook Posts of English Works!

Facebook posts are strategically created to achieve commercial objectives, encompassing digital advertising, content promotion, and audience engagement. A specific case in point involves the analysis of posts on the English Works! social media page. The study draws upon Kress and Leeuwen’s concept of Multimodality of signs to analyze these visual cues. The findings indicate that each image serves as a sign, conveying insights about the program's essence, updates, events, and activities to the audience. The color palettes used in these images play a pivotal role in establishing the program's agenda and thematic representation. The connotations embedded in the Facebook posts predominantly revolve around themes of learning, unity, celebration, empowerment, success, and recognition. These connotations are intricately tied to the journey of English Works! students. Future researchers could extend the application of semiotics to other forms of visual communication media, such as art photography, banners, and printed advertisements.
Pengembangan Media Buku Bantal Hitung (Bubantung) Sebagai Pengenalan Konsep Angka Pada Anak Usia 4-5

The purpose of this study was to better understand (1) practicality and (2) the effectiveness of using counting pillow books to help young children understand the meaning of numbers. The research approach of this research is the ADDIE development model. The stages in the research process include (1) analysis, (2) design, (3) development, (4) implementation, and (5) evaluation. The viability and efficacy of picture story book media products were evaluated using expert tests, individual tests, small group tests, field tests, and large group tests. This study used a nonequivalent quasi-experimental control group design. Examination of the validator test both media and content produces research findings. Based on the evaluation of the two media and material validator tests, this was found. obtained by 80.5% in the average media validation test. It is included in the development area that can be achieved from the perspective of Bubantung teaching materials. In addition, the average score obtained from the results of the material validation test was 84%, placing the expert exam from the teaching material test in the feasible category to construct. The validation average of the media test and material test was 82.25%, indicating that this category is feasible for further development
DALIA FAIR Open Educational Federation

As a funding measure of the German Federal Ministry of Education and Research and from the EU's Development and Resilience Facility, the project “DALIA - Knowledge-Base for FAIR data usage and supply" not only creates technical bridges between NFDI consortia but also an evolving approach that contributes to transdisciplinary community building in the long term. By harmonising, networking and making visible teaching and learning materials for the development and promotion of data literacy, the project makes an important contribution to education, training and cultural change.
GrainedCLIP and DiffusionGrainedCLIP: Text-Guided Advanced Models for Fine-Grained Attribute Face Image Processing

Text-guided image processing has made tremendous progress in recent years. Most existing methods generally focus on using visual-language pre-training models for text-guided image processing. However, their applications to achieve text-guided fine-grained attribute face image processing (e.g., editing a smiling face to change from showing teeth to a closed-mouth smile) lead to poor performance due to the limited fine-grained semantic knowledge learned by existing visual-language pre-training models. To alleviate this problem, we propose a novel visual-language pre-training model based on fine-grained facial attribute features, which we call GrainedCLIP. Based on GrainedCLIP, we further propose a new text-guided fine-grained attribute face image processing model, which we call DiffusionGrainedCLIP. Our experimental results showed that GrainedCLIP outperformed existing methods, achieving <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$12.61 R$ </tex-math></inline-formula> @1 and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$12.17 R$ </tex-math></inline-formula> @1 in text-to-image and image-to-text retrieval evaluation metrics, respectively, on the FFHQ dataset. Furthermore, compared to state-of-the-art text-guided face image processing methods, DiffusionGrainedCLIP significantly improved 55.37% in semantic consistency and 49.38% in face identity preservation on the FFHQ dataset.
MG-Trans: Multi-Scale Graph Transformer With Information Bottleneck for Whole Slide Image Classification

Multiple instance learning (MIL)-based methods have become the mainstream for processing the megapixel-sized whole slide image (WSI) with pyramid structure in the field of digital pathology. The current MIL-based methods usually crop a large number of patches from WSI at the highest magnification, resulting in a lot of redundancy in the input and feature space. Moreover, the spatial relations between patches can not be sufficiently modeled, which may weaken the model's discriminative ability on fine-grained features. To solve the above limitations, we propose a Multi-scale Graph Transformer (MG-Trans) with information bottleneck for whole slide image classification. MG-Trans is composed of three modules: patch anchoring module (PAM), dynamic structure information learning module (SILM), and multi-scale information bottleneck module (MIBM). Specifically, PAM utilizes the class attention map generated from the multi-head self-attention of vision Transformer to identify and sample the informative patches. SILM explicitly introduces the local tissue structure information into the Transformer block to sufficiently model the spatial relations between patches. MIBM effectively fuses the multi-scale patch features by utilizing the principle of information bottleneck to generate a robust and compact bag-level representation. Besides, we also propose a semantic consistency loss to stabilize the training of the whole model. Extensive studies on three subtyping datasets and seven gene mutation detection datasets demonstrate the superiority of MG-Trans.
Schema.org as a Lightweight Harmonization Approach for NFDI

Schema.org is a controlled vocabulary that makes it easier for web pages to describe their actual content in a semantic, structured and machine-processable way. It is recognized by major search engines and data aggregators, making it easier for researchers to expose metadata describing their research outcomes. Here we present how Schema.org is used (or planned to be) by some NFDI consortia, becoming a lightweight approach to harmonize digital objects coming from different sources so they can be connected to each other in a meaningful way
Feature Point Identification in Fillet Weld Joints Using an Improved CPDA Method

An intelligent, vision-guided welding robot is highly desired in machinery manufacturing, the ship industry, and vehicle engineering. The performance of the system greatly depends on the effective identification of weld seam features and the three-dimensional (3D) reconstruction of the weld seam position in a complex industrial environment. In this paper, a 3D visual sensing system with a structured laser projector and CCD camera is developed to obtain the geometry information of fillet weld seams in robot welding. By accounting for the inclination characteristics of the laser stripe in fillet welding, a Gaussian-weighted PCA-based laser center line extraction method is proposed. Smoother laser centerlines can be obtained at large, inclined angles. Furthermore, an improved chord-to-point distance accumulation (CPDA) method with polygon approximation is proposed to identify the feature corner location in center line images. The proposed method is validated numerically with simulated piece-wise linear laser stripes and experimentally with automated robot welding. By comparing this method with the grayscale gravity method, Hessian-matrix-based method, and conventional CPDA method, the proposed improved CPDA method with PCA center extraction is shown to have high accuracy and robustness in noisy welding environments. The proposed method meets the need for vision-aided automated welding robots by achieving greater than 95% accuracy in corner feature point identification in fillet welding.
Research on Student Achievement Prediction Method Based on Machine Learning

In the teaching process of colleges and universities, there is a general lack of early-warning technology for failing grades, and teachers cannot identify the students at risk of failing grades in advance. Thus, the targeted teaching cannot be carried out in the teaching process. In order to solve the above problems, this paper studies the method of students’ score prediction based on machine learning. This paper proposes a method to predict the grade of the next semester based on the students’ test scores in previous semesters. The recognition accuracy rate of this method reached 88.78%, and the Kappa coefficient reached the “Substantial” of classification.
Bridging the Digital Divide for Girls in India: Logging Her in!

The death by suicide of a class IX girl because she could not access online classes due to lack of a smart phone in June 2020 in Kerala is just a statistic now. But it is nevertheless a poignant reminder of how deeply we have failed our young girls. While the SDGs commit to significantly increase access to information and communications technologies and strive to provide universal and affordable access to the internet in least developed countries by 2020, the COVID-19 pandemic has exposed how far away we are from achieving this goal. The issue of digital divide has resurfaced in a big way in developing and underdeveloped countries. In India, the ‘gendered digital divide’ among adolescents has come out starkly, highlighting ways in which the harmful effects of COVID-19 are disproportionately experienced by adolescent girls. This chapter brings focus on how the digital divide is affecting adolescent girls and highlights the key areas that can help bridge the gendered digital divide for girls in India, by presenting an on-the-ground reality of adolescent girls amidst socio-economic challenges such as staggering family incomes, job insecurities, slow health services, lack of access to critical information and social benefits and loss of attendance in school, with a specific focus on state-wise differentiation in access to digital devices and services for adolescent girls.
Effect of Regular Korean Dance Program Participation improves Body Composition and Bone Mineral Density on Female University Students

The purpose of this study was to investigate the effect of regular Korean dance program participation improves body composition and bone mineral density on female university students. The subjects were of 30 female university students, they were divided into two groups: the group of 15 students with regular Korean dance habit and the group of 15 students without Korean dance habit. To analyze the results, an independent t-test was performed to compare and analyze the differences in dependent variables between groups. As a result of conducting an independent t-test to analyze the difference in body composition between groups, the % body fat was found to be significantly lower in the group with regular Korean dance habit than in the group without Korean dance habit. The BMI was in the normal range for both groups. The % body fat was in the normal range for the group with regular Korean dance habit but it was higher than the normal range for the group without Korean dance habit. As a result of conducting an independent t-test to analyze the difference in bone mineral density between groups, arm, leg, trunk and total bone mineral density were found to be significantly higher in the group with regular Korean dance habit than in the group without Korean dance habit. Both groups had the highest bone mineral density in the leg and the lowest in the trunk bone mineral density and the bone mineral density in all parts of the body was in the normal range for both groups. These results suggest that female university students of regular Korean dance habit maintain body composition and bone density at higher levels. Therefore it is important to correct one’s life habit and work out regularly to prevent osteoporosis and development of regular and systematic Korean dance programs for female university students is highly needed.
FAIRmat Guide to Writing Data Management Plans

Research data management is becoming an increasingly important topic due to the growing amounts of types, formats, and sizes of data produced by scientific research. In addition, a growing demand to make data accessible and comprehensible requires standardizing, managing, and planning the data life-cycle. For this reason, many funding agencies now require a data management plan (DMP) as part of submitted research proposals. While some of them and other scientific bodies offer DMP templates, there is no one-size-fits-all solution, due to the heterogeneity of data generated by different scientific disciplines. Here, we present as an example FAIRmat’s effort in enhancing data literacy on the topic of DMP aiming to guide physicists and materials scientists to writing DMPs that comply with the requirements of the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG).
An Automated Grading Method of Pearl Roundness based on Optical Coherence Tomography

Pearl roundness is an important index in the pearl value evaluation and classification. The existing roundness classification schemes are usually based on 2D image or mechanical methods. However, the 2D image ignores the depth or 3D information, which leads to low classification accuracy, and mechanical classification is easy to cause surface damage. An automated grading method of pearl roundness based on optical coherence tomography is proposed. Based on the high-resolution and low-cost 3D imaging of the pearl surface, through noise reduction, binarization, segmentation, 3D reconstruction, surface extraction, and the surface of pearl is fitted as sphere. A new digital rating index named global local roundness fraction is designed for roundness evaluation, based on the length of the three axes and of coordinates of the fitted sphere. Four grades of pearls were automatically classified by our method, and the results showed that the accuracy of the proposed scheme reached 95%, indicating that the proposed method can be used as an effective means of automatic classification of pearl roundness.
Digitalizing the Chemical Landscape:

The Chemistry consortium NFDI4Chem aims to digitalise key steps in chemical research, supporting scientists in managing research data throughout its life cycle. The SmartLab, embedded in a federation of services, integrates various tools such as electronic lab notebooks, data repositories, and search services, to create a smart lab environment for structured data gathering. Utilizing terminology services and adhering to data format standards, NFDI4Chem promotes secure and FAIR data sharing, fostering collaboration and expediting scientific discoveries. This development is supported by community building measures, workshops, and training initiatives, along with collaboration on international minimum information standards.
Web Based E-Commerce System Design at EXO Shop Using The Waterfall Method

Online shop websites can facilitate company or shop promotions and make it easier for consumers to get information about products from sellers or shops. Limited product merchandising prevented stores from increasing sales, and poor inventory control and manual reporting negatively impacted stores, making sales and inventory reporting difficult. The purpose of this research is to use the waterfall method to create an e-commerce website that can be opened online with an internet network. The method used by researchers in this study is the waterfall method. This method is used by researchers to develop software systems through a sequential software life cycle, starting with analysis, design, coding, and testing. System themes use PHP, HTML, CSS and Notepad while the database uses My-Sql which is accessed via XAMPP localhost. This research produces a web-based e-commerce application that provides real-time stock information, sales reports, stock reports and stores can advertise the products being sold. So that the process of reporting and controlling inventory data is carried out properly, and store marketing has a wider reach, so that store sales can increase.
Sistem Brankas Berbasis Internet Of Things Mengunakan Arduino Mega 2560

Safes in the market are usually doesn’t offer a system that can monitor the activities carried out by users on the safe. This becomes a problem when the safe has many users who can access it. We can't identify who, when or what other users are doing. In addition, safes generally have an authentication system that only offers passcodes and keys. That authentication system is considered outdated. In this study, a web-based safe monitoring system was created that uses a fingerprint sensor and passcode as authentication. In addition, this system can also send data about user activity to the website so that admins or other users can monitor anyone who accesses the safe. This system will be tested using black box testing. In the test, it was found that this safe system can only be opened if the user inputs a valid passcode and a finger print that has been registered in the system. In addition, the activity data has been successfully sent to the website. In security testing, it was found that if the safe door is opened forcibly, an alarm in the form of a buzzer will ring and a warning notification will be sent to the website.