Reviewerly/exHarmony huggingface dataset:
Integration and Open Access System Based on Semantic Technologies

The aim of this work is the development of an information system that, by integrating data from different sources and applying semantic technologies, makes it possible to publish and share with society the scientific production generated in the university environment, promoting its dissemination and thus contributing to the knowledge society, among others. In practice, this is the implementation of a CRIS (current research information system). This CRIS presents advanced features. On one hand it applies semantic technologies, providing a query service through a SPARQL Point, besides the reuse of shared data by exporting them in different formats. In this sense, it is also based on a European ontology or semantic standard such as CERIF, which facilitates its portability. On the other hand, CRIS also presents an alternative to the lack of a single data system by allowing data from different sources to be integrated and managed.
Anti-jamming Method of Satellite Navigation Based on Synthetic Aperture

A new method to extend the satellite navigation anti-jamming degree of freedom based on synthetic aperture is proposed. In this paper, by means of using the motion characteristics of single antenna, the time-domain sampling of signal is converted into spatial sampling and virtual array is synthesized. When the number of virtual elements in the array is limited, the number of interferences which can be suppressed can be greatly increased, which can solve the problem that the freedom of anti-interference is limited by the number of elements. Combined with the optimal anti-jamming weighting criterion, the space-frequency anti-jamming algorithm is used for anti-jamming processing, and the covariance matrix broadening algorithm is used to optimize the anti-jamming processing results, which solves the problem of how to deal with robust anti-jamming under the condition of unfixed anti-jamming degree of freedom. The simulation results verify the effectiveness of the method.
Tower Building Technique on Elliptic Curve with Embedding Degree 36

Recent progress on pairing based cryptography was the use of extension of finite fields of the form F p k , and it was a lot secure and efficient when k ≥ 12.In this paper, we will use the tower building technique to study the case of k=36 to improve arithmetic operation.We will use a degree 2 or 3 twist to carry out most operations in F p 2 , F p 3 , F p 4 , F p 6 , F p 9 , F p 12 , F p 18 and F p 36 , many paths will be found.Finally we will take the optimal case to improve the computation in optimal ate pairing
RFID Authentication System Based on User Biometric Information

Traditional authentication technologies usually perform identity authentication based on user information verification (e.g., entering the password) or biometric information (e.g., fingerprints). However, there are security risks when applying only these authentication methods. For example, if the password is compromised, it is unlikely to determine whether the user entering the password is legitimate. In this paper, we subdivide biometric information into physiological and behavioral information, and we propose a novel user authentication system, RF-Ubia, which utilizes the low-cost radio frequency identification (RFID) technology to capture unique biological or behavioral information rooted in the user and can be used in two schemes for user authentication. Consisting of an array of nine passive tags and a commercial RFID reader, RF-Ubia provides double assurance for security of identity authentication by combining user information and biometric characteristics. It first verifies the user’s password, and then identifies the biometric characteristics of the legitimate user. Due to the coupling effect among tags, any change in tag signal caused by the user’s touch will affect other tag signals at the same time. Since each user has different fingertip impedance, their touch will cause unique tag signal changes. Therefore, by combining biometric information, the tag array will uniquely identify users. The evaluation results show that RF-Ubia achieves excellent authentication performance with an average recognition rate of 93.8%.
Adaptive Distributed Parallel Training Method for a Deep Learning Model Based on Dynamic Critical Paths of DAG

AI provides a new method for massive simulated data calculations in molecular dynamics, materials, and other scientific computing fields. However, the complex structures and large-scale parameters of neural network models make them difficult to develop and train. The automatic parallel technology based on graph algorithms is one of the most promising methods to solve this problem, despite the low efficiency in the design, implementation, and execution of distributed parallel policies for large-scale neural network models. In this paper, we propose an adaptive distributed parallel training method based on the dynamic generation of critical DAG (directed acyclic graph) paths, called FD-DPS, to solve this efficiency problem. Firstly, the proposed model splits operators with the dimension of the tensor, which can expand the space available for model parallelism. Secondly, a dynamic critical path generation method is employed to determine node priority changes in the DAG of the neural network models. Finally, the model implements the optimal scheduling of critical paths based on the priority of the nodes, thereby improving the performance of parallel strategies. Our experiments show that FD-DPS can achieve 12.76% and 11.78% faster training on PnasNet_mobile and ResNet_200 models, respectively, compared with the MP-DPS and Fast methods.
Mathematical Expressiveness of Graph Neural Networks

Graph Neural Networks (GNNs) are neural networks designed for processing graph data. There has been a lot of focus on recent developments of graph neural networks concerning the theoretical properties of the models, in particular with respect to their mathematical expressiveness, that is, to map different graphs or nodes to different outputs; or, conversely, to map permutations of the same graph to the same output. In this paper, we review the mathematical expressiveness results of graph neural networks. We find that according to their mathematical properties, the GNNs that are more expressive than the standard graph neural networks can be divided into two categories: the models that achieve the highest level of expressiveness, but require intensive computation; and the models that improve the expressiveness of standard graph neural networks by implementing node identification and substructure awareness. Additionally, we present a comparison of existing architectures in terms of their expressiveness. We conclude by discussing the future lines of work regarding the theoretical expressiveness of graph neural networks.
Research on Multi-UAVs Route Planning Based on the Integration of Improved Elastic Band and A-Star Algorithm

UAV collaborative task assignment and route planning are essential for UAV collaborative mission planning. It is difficult for multiple UAVs to simultaneously plan route while achieving real-time route planning to meet the dynamic performance of multiple UAVs. This paper optimizes the multi-UAV route planning model in view of the situation that the UAV route planning fails due to situation and mission changes in complex battlefield environments, proposes a multi-UAV route planning algorithm based on the integration of Elastic Band and A-Star algorithm, and establishes a simulation environment for dynamic verification, so as to provide technical support for improving the success rate and adaptability of UAV systems in combat missions.
IoV Enabled Route Optimization Technique for Combat Vehicles

The Internet of Things (IoT) has become a vital part of everyone's daily lives thanks to rapid advancements in wireless technological advancements. The most exciting IoT application is location-based services. Sensor networks have been established, and they are now capable of gathering and sending data in a way that allows them to detect target locations. This article will also show how location is crucial in today's IoT applications, induding as smart cities, smart transit systems, and potency. Managing 3D routing is one of the most difficult components of Combat Vehide (CV) design. This is due to the CVs' inherent complexity, as well as the expanding number of design constraints that must be adhered to, as well as the CVs' reliance on any changes in the design of something like the solid frame and system implementation. For scenarios featuring device and communication technology heterogeneity, a 3D underlay routing technique is presented. It gives capabilities for dynamic and diverse ad hoc networks to work together in a seamless manner. Unlike motion planning, which must account for dynamics, the goal of route planning is to identify a motion optimal path in the shortest amount of time while also understanding the surroundings completely. This work also aims to provide a useful comparison of these algorithms and techniques, as well as to identify the best ones for a specific application. Traditional and node-based algorithms were discovered to be a preferred alternative for path planning in the investigation. To that end, we'll go through how these concepts are conceived and developed in order to ensure smooth connectivity for such type of upcoming networking situation, which will fully automate 3D route models.
A Method of Trading Strategies for Bitcoin and Gold

The price of Bitcoin has soared from $10,000 in 2021 to an all-time high of $60,000 in 2022, with a total market capitalization of more than $1 trillion, and gold has been used as the ultimate asset to protect the economy and protect against inflation.Therefore, it is predicted that gold and Bitcoin Investors can gain more income by monitoring the price trend of the currency and formulating a reasonable investment strategy.In order to obtain a better prediction effect, this paper divides the analysis of gold price prediction into two stages: before the epidemic and after the epidemic.Before the epidemic, the CEEMDAN-WD-WOA-BiLSTM model was used, and after the epidemic, the neural network was used in this paper.For Bitcoin prediction, PCA is used to select indicators with greater impact, and the ARMIA model is used to predict.After the prediction, this article combines various situations, uses the bull and bear market model, pricing index strategy and quantitative evaluation model to decide the amount of gold and Bitcoin to buy, and finally the profit obtained by this method has reached more than 30 within five years times, to provide investors with a practical and effective investment plan.
Flexible, Safe and Trusted Agricultural Product Blockchain Traceability System

Agricultural product traceability involves multiple links and identity information of multiple subjects, and the data flow is more complicated, making it difficult to trace and supervise the operation. The traditional agricultural product traceability system depends on a central database, the data is easily tampered with, and the reliability of the data cannot be guaranteed. A safe, reliable, open, and transparent traceability system needs to be established. A traceability system for agricultural products is built with the aid of blockchain technology to ensure data authenticity, tamper-proof, and the accuracy of traceability data. Based on the existing agricultural products supply chain structure, this paper proposes a flexible agricultural products traceability system scheme, which can realize the flexible jumping of traceability links. The sensitive data is encrypted based on the SM4 encryption algorithm to protect data confidentiality. The access control tree is set based on user attributes, and access control of data is realized according to the logical relationship of the access control tree to protect data privacy. The experimental results indicate that the proposed scheme ensures the traceability, tamper-proof, and data security of agricultural products.
The Complexity of Blockchain Risks Simplified and Displayed: Introduction of the Johns Hopkins Blockchain Risk Map

Blockchains have ushered in the next stage in the evolution of the Internet, transitioning us from Web 2.0 to 3.0. However, given the complex nature of this innovative technology and the inability to clearly measure and properly communicate the risks in blockchains, arguably this murkiness has hampered the development, growth, proper regulation, and, ultimately, the true societal beneficial contributions of blockchains. In an attempt to clear the confusion, the authors propose the Johns Hopkins Blockchain Risk Map. The authors present their risk map prototype, their current multidimensional exhibit of risks across the various stakeholders, and their current modest progress with some data on their current risk measures. The authors are attempting to create a safe space whereby blockchain risks are defined, displayed, debated, researched, fine-tuned, standardized, and freely shared. The authors believe that such a platform would be an ideal mechanism for education, networking, and collaboration for the next generation, specifically those who are underrepresented in the current blockchain development community. By increasing the transparency and debating risk issues in a safe academic environment, the authors hope that this risk map will help move blockchain adoption forward and spur more entrepreneurial activity across this industry. In this article, the authors lay down their initial thoughts and current progress and challenges. Although this article is in no way exhaustive, the authors provide several categorizations of blockchain risks: operational, decentralization, security, social sentiment, investment, and systemic, to name a few.
The Functional Role of Traditional Music and Dance in Xhosa Traditional Healers’ Ceremonial Rites

African societies have always used traditional music and dance to celebrate events, interface, and connect with divinity, especially during communal ceremonies. The central thesis of this paper is that traditional music and dance are transforming agents used by Xhosa traditional healers during ceremonies to gain insights into the nature of a society’s experiences and to connect with supernatural beings. This study, therefore, investigates the functional role of traditional music and dance used during Xhosa traditional healer’s ceremonies, employing direct observation, video recordings, and interviews, as well as a descriptive qualitative research design. The findings revealed that traditional music and dance provide a safe environment for divinity practices and healing. Furthermore, traditional music and dance bring traditional healers closer to their ancestors, increasing acceptance and self-discovery during ritual proceedings. Even though music and dance are vital parts of various aspects of Xhosa cultural life, they have received limited scholarly attention. This paper, therefore, provides commentary on the functional role of traditional music and dance during Xhosa traditional healer’s ceremonies and offers reflections on the functionality of traditional music and dance in contemporary Xhosa culture. Keywords: Xhosa; traditional music and dance; traditional healers
User Interface Evaluation in Metvaerse Gamelan Virtual Reality Using Heuristics Evaluation Method

The increase in information technology in today's era makes the availability of Augmented Reality or Virtual Reality enabled devices, which can become a gateway to exploring various applications, increase. For the example is the virtual reality application of Gamelan Slenthem, which is currently being developed with the aim of making Indonesian cultural musical instruments. Even though what is developed is not an application or an ordinary website, the user interface is still one of the most important stages in the development of an augmented reality or virtual reality application. Every information technology has an interface that can be a link between the user and the technology itself. The interface is influenced by needs, and information technology has a design that makes it easy for users to operate information technology and can make users feel comfortable using the application or technology. In this study, we will use heuristic evaluation to evaluate the application of the virtual reality gamelan metaverse game. Heuristic evaluation itself is a method of evaluating user interfaces and usability that can be used to determine the extent to which a system is used by users to achieve certain goals effectively, efficiently, and satisfactorily. This research focuses on evaluating the use of heuristics in user interface design based on usability aspects through observation and interviews with users.
Educational constellations: a systematic review of macro-networks in education

Purpose Nowadays, networks are the basic core of social organization and interaction; consequently, networking has become an indispensable requirement in today's societies. In education, the development of different types of collaborative networks has been observed, leading, in recent years, to the creation of educational macro-networks that generate links between schools and different types of institutions. Therefore, this study consists of a systematic review to examine the most relevant findings on this type of educational macro-networks. The authors’ objectives were: to examine the main characteristics of this type of networks; to analyze the consequences they cause; and to determine which aspects contribute to or hinder their construction and development. Design/methodology/approach A bibliographic search was carried out in Web of Science , SCOPUS and Education Resources Information Center , which yielded a total of 29 studies that were analyzed thematically using Nvivo software. Findings Among the most noteworthy results are: the wide variety of existing structures; the benefits they generate in terms of learning outcomes, educational equity and the reduction of inequalities; and the influence exerted by the type of leadership and policies in the development of this macro-networks. Finally, future lines of research and policy implications for practice are highlighted. Originality/value In this society, networks have become the basic core of an organization and the new form of social interaction. As a result, networks have begun to play a fundamental role in today's societies, even permeating various spheres such as education. In this context, it is essential to analyse this type of relationship in the field of education in order to truly understand its implications in this sector as well as its development and structure.
Automatic Generation of Grover Quantum Oracles for Arbitrary Data Structures

The steadily growing research interest in quantum computing - together with the accompanying technological advances in the realization of quantum hardware - fuels the development of meaningful real-world applications, as well as implementations for well-known quantum algorithms. One of the most prominent examples till today is Grover's algorithm, which can be used for efficient search in unstructured databases. Quantum oracles that are frequently masked as black boxes play an important role in Grover's algorithm. Hence, the automatic generation of oracles is of paramount importance. Moreover, the automatic generation of the corresponding circuits for a Grover quantum oracle is deeply linked to the synthesis of reversible quantum logic, which - despite numerous advances in the field - still remains a challenge till today in terms of synthesizing efficient and scalable circuits for complex boolean functions. In this paper, we present a flexible method for automatically encoding unstructured databases into oracles, which can then be efficiently searched with Grover's algorithm. Furthermore, we develop a tailor-made method for quantum logic synthesis, which vastly improves circuit complexity over other current approaches. Finally, we present another logic synthesis method that considers the requirements of scaling onto real world backends. We compare our method with other approaches through evaluating the oracle generation for random databases and analyzing the resulting circuit complexities using various metrics.
TSPNet-HF: A Hand/Face TSPNet Method for Sign Language Translation

Sign Language is the language that the Deaf adopted to communicate. However, most hearing people do not know how to communicate in sign language, creating natural barriers between these groups. Aiming to reduce such barriers, Sign Language Translation (SLT) interprets sign video sequences into spoken language sentences. A recent SLT model, called TSPNet, explored sign videos’ temporal and contextual semantic structures to learn more discriminative features. Although the TSPNet has reached promising results on the RWTH-PHOENIX-Weather 2014T (PHOENIX14T), the model only considers hand signs, ignoring facial and body information. Facial expressions reflect the extent of signs and play a relevant role in translation. The current work proposes the TSPNet-HandFace (TSPNet-HF), which considers hand and facial features in the SLT process. The proposal has two novel components: facial feature extraction and hand/face feature aggregation to combine hand and facial features. It was assessed on the PHOENIX14T in BLEU and ROUGE, and it was compared to TSPNet and CNN2dRNN. The results showed that the TSPNet-HF overcame the competing methods in all the translation metrics, showing that the inclusion of facial features positively impacts the SLT process.
Studying electronic blood pressure monitor digital recognition algorithm based on computer vision and design

This study proposed an intelligent algorithm based on digital image processing and character recognition to address the current situation in which the National Medical Products Administration promulgated the relevant regulations on the complete prohibition of the use of mercury sphygmomanometers in 2020 and the currently widely used electronic sphygmomanometers need to undergo regular verification and quality testing. The intelligent algorithm made it possible to automatically acquire the electronic sphygmomanometer indication value during quality assurance or verification. The images of the electronic sphygmomanometer were captured using a Raspberry Pi-connected video camera head; in the software development, automatic detection of the electronic sphygmomanometer's indication value was achieved by running the computer vision-based OpenCV library on the Raspberry Pi and utilizing image preprocessing techniques like scale transformation, grayscale conversion, Gaussian smoothing and edge detection, and character segmentation. The development of intelligent devices for the automatic verification of electronic sphygmomanometers has a technical foundation in the research and design of the digital recognition algorithm, and it has a certain reference value for character recognition of electronic instruments or the creation of automatic instrument indication value recording devices.