Reviewerly/exHarmony huggingface dataset:
Research on Machine Translation Method of English-Chinese Long Sentences Based on Fuzzy Semantic Optimization

The machine translation of English-Chinese long sentences is out of order under the constraint of the mixed corpus. In order to improve the accuracy of machine translation of English-Chinese long sentences, a machine translation method based on fuzzy semantic optimization is proposed. By adopting the method of systematic semantic configuration structure fusion, the ontology mapping model of the English-Chinese long sentence subject list under the constraint of the mixed corpus is constructed. In the distribution structure space of English-Chinese long sentences under the constraint of the mixed corpus, the method of extracting the best semantic relevance and analyzing the concept tree of context semantic mapping is adopted to mine the dynamic features of the subject list of English-Chinese long sentence translation under the constraint of the mixed corpus. In the intrinsic distribution sequence of semantic mapping between concepts, the fuzzy semantic combination features of English-Chinese long sentences under the constraint of the mixed corpus are extracted. The distribution results of word knowledge priority selection sequence, the automatic translation of English-Chinese long sentences under the constraint of the mixed corpus is realized by scheduling a grammatical error correction task list. According to the simulation results, machine translation of long English-Chinese sentences under the restriction of mixed corpora is capable of good semantic configuration. The degree of linguistic structural similarity between English and Chinese is great, which enhances the automatic translation capacity of English-Chinese long sentences under the limitation of the mixed corpus.
Couplet Analysis of Linguistic Topology Using Deep Neural Networks in Cognitive Linguistics

The work reported here primarily aims to realize the automatic generation of couplets using the linguistic topology of deep neural network (DNN). First, the symmetry, topology, and cognitive linguistics of language are explored to lay a theoretical foundation for subsequent model establishment and analysis. Then, the recurrent neural network (RNN) is employed to build the Seq2Seq model, and Liweng's Guide to Rhyme (an ancient Chinese enlightenment reading material to poetry creation) is imported into the Seq2Seq model as a basic corpus. Eventually, the entire system is implemented automatically on TensorFlow. The system undergoes tests of the five-character quatrain, the seven-character quatrain, the couplet, and the part-of-speech detection. Results demonstrate that both the first and the second lines of the couplet present an excellent correspondence regarding sentences and words. After some famous verses are entered, the second line of the couplet obtained is quite vivid and appropriate. Meanwhile, the results can be generated quickly and meet the requirements on rhyme and couplet matching. This model can input verses according to users' own needs and generate the second line of the couplet quickly, showing good correspondence in words, part-of-speech, and sentence pattern. Because the couplet belongs to Chinese traditional culture, it has a strong local Chinese cultural flavor. The system designed based on computer technology can help people learn and experience the charm of couplets.
A Blockchain-Enabled Trusted Protocol Based on Whole-Process User Behavior in 6G Network

The access of massive users and devices in the 6G networks increases the risk of network attacks. Designing a trusted protocol to control user behavior can effectively improve the security capability of the network. However, most of the existing trusted protocols focus on unilateral user behavior and lack effective control over the whole process of user behavior. In this paper, we design a blockchain-enabled trusted protocol based on the whole-process user behavior. At first, we describe the Whole-Process User Behavior (WPUB) after the user accesses the network, and model the whole-process trusted control process. The proposed model establishes a trusted chain between user identity, access action, and communication traffic, and realizes the control of WPUB. Then, based on the proposed model, we design a whole-process trusted protocol with smart agents and smart contracts in combination with blockchain. Finally, we evaluate the designed protocol in the HyperLedger Fabric-based prototype system. Evaluations show that the proposed protocol can control the WPUB and reduce the risk of the network being attacked.
Thresholding Techniques for the Biomarkers of Brain Magnetic Resonance Image

Image is an extremely compelling aid. It enhances the opportunity to resolve complex diseases based on some specific changes in a various parts called biomarkers. Human eyes are unable to classify approximate same intensities of Normal and disease parts so image segmentation helps to extract these biomarkers and reduces time for understanding the actual problem. Thresholding is an image segmentation technique. It is very simple and computationally less time consuming. The work which are going to be proposed compares the results of thresholding techniques and preprocessed through outlier, median and the proposed hybrid filter for the biomarkers of brain which exists in the scans of magnetic resonance image. These scans acquired from Alzheimer’s Disease Neurodegenerative Initiative (ADNI) brain MRI database and threshold the brain parts like White Matter, Grey Matter and Cerebrospinal Fluid by using global, variable and multilevel thresholding techniques. The adoption of threshold value is done by Otsu’s methods. These biomarkers will help to detect the Neurodegenerative diseases like Alzheimer’s disease. The nature of results is computed by the quality checking tools like Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR). Multilevel thresholding provided all these biomarkers and proposed hybrid filter de noises the brain MRI’s images comparatively better than outlier and median filter.
The Influence of AI-Assisted Learning on CAL

Reading, creating, hearing, witnessing, analyzing, testing, and other activities are all part of a diverse, multilayered, and dynamic learning experience. These layers combine to make learning a unique and personal experience for each individual. Understanding the factors that influence how people learn has a lot of power. When that expertise is combined with artificial intelligence (AI), the authors can develop learning experiences that are beneficial to all students. AI-assisted learning is a learning experience that is adaptive and enhances our natural learning style with machine intelligence (AIAL). AI can recognize trends and make decisions that are beneficial to users. There are numerous different tendencies in memory as it relates to humans in this study. This chapter explains how AI-assisted learning takes into account aspects including a student's background, the subject, modalities, and environment to produce an integrating teachable moment.
Computing the Cloud Storage for Computer-Aided Learning Access

Computer-assisted learning is a type of educational practice that involves the use of computer systems and other technology. It can take many different forms, and it involves a variety of tools and devices, including smartphones, tablets, personal computers, and others, despite its reputation. Different types of software and procedures are used in CAL. It can be used in a variety of subjects, including language acquisition and math. It is also used at all stages of education by then and now booming sectors in the coronavirus pandemic situation, particularly K to 12 programs, distance programs, skills and vocational training institutes, corporate training programs sometimes by individual broadcast trainers. Computer-assisted learning improves the teaching and learning process, resulting in higher levels of engagement and results. However, there are certain disadvantages to CAL. The authors look into the storage purpose of the CAL sessions as well as conversations. This is the time, the authors have to focus on the storage aspect of the CAL sessions, as much as the chats.
Digital Competence, Validation and Differential Patterns between Spanish and Portuguese Areas as Assessed from the Latest PISA Report as a Pathway to Sustainable Education and Social Concerns

PISA reports aim both to analyze and describe the educational reality of each country and to assess different academic competences, including digital competence. In this paper, we are committed to the vision of digital literacy as an indispensable element of sustainable education and social concerns, which, together with the environment, the economy, social justice and human rights, form the basis of the concept of sustainability. From this point of view, it is considered that an improvement in digital competence has a positive impact on the use made of ICT and also on its link with sustainable development. The aim of this research is to comparatively analyze the results in terms of literacy itself, digital skills and digital resources and experiences according to the PISA 2018 report in four OECD countries: Spain, Portugal, Colombia and Brazil, specifically, two Latin countries (Brazil and Colombia) and two Hispanic countries (Spain and Portugal), and for the enjoyment in the use of digital devices between one country in each area (Brazil and Spain). The sample is composed of 54,323 participants (18,073 participants from Brazil and Colombia, Latin America, and 36,250 from Spain and Portugal, Iberian Peninsula), using as an instrument the surveys developed and implemented in the PISA 2018 dataset for the OECD sample, which is related to some aspect of digital skills. The main findings of this study confirm that the variables related to digital resources, digital literacy and digital skills are statistically significant in the four countries. Therefore, in view of this, we want to support the promotion of digital competence as a key element in the sustainable, educational and social development of a community. At a pedagogical level, this means that we are committed to different specific programs, innovative educational practices and the creation of resources that promote inclusion and educational quality, focusing on social concerns and the fit of each country and area for promoting sustainable education.
A Multi‐Template Fusion Object Tracking Algorithm Based on Graph Attention Network

In recent years, the object‐tracking algorithm based on Siamese network has gradually become the mainstream algorithm in the field of object tracking due to its characteristics of balancing speed and accuracy. The majority of Siamese‐based trackers only use the first frame extraction template for subsequent tracking in order to prevent the introduction of noise. However, merely with a single initial template employed, it is difficult to achieve the best performance of the tracker in the face of complex tracking environments such as occlusion, motion blur, and non‐rigid deformation. Therefore, the present paper proposes a new multi‐template fusion module based on graph attention network (G‐M module), which consists of two parts: a graph‐attention‐network‐based feature‐embedding module (G module) and a multi‐template fusion module (M module). It can greatly reduce the background noise introduced by template updating while improving the tracker's ability to adapt to changes in object appearance. In addition, in order to maximize the value of G‐M module, the present paper also puts forward a two‐stage template update threshold judgment mechanism. The Pearson correlation coefficient (PCCs) is introduced and combined with APCE and the maximum response value (F‐max) to filter out reliable templates for updating. In this paper, the proposed method is applied to the SiamFC and SiamFC++ trackers. Extensive experiments on mainstream data sets, such as OTB2015, VOT2016, and GOT‐10 k, show that the proposed method can effectively update the tracking template and improve the tracker performance. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.
Stealthy path planning against dynamic observers

In virtual environments, research into the problem of stealthy or covert path planning has either assumed fixed and static motion of observers or has used relatively simple probabilistic models that statically summarize potential behavior. In this paper, we introduce a method that dynamically estimates enemy motion in order to plan covert paths in a prototype game environment. We compare our results to other baseline pathfinding methods and conduct an extensive exploration of the many parameters and design choices involved to better understand the impact of different settings on the success of covert path planning in virtual environments. Our design provides a more flexible approach to covert pathfinding problems, and our analysis provides useful insights into the relative weighting of the different factors that can improve design choices in building stealth scenarios.
A typed lambda-calculus with first-class configurations

Abstract Filinski and Griffin have independently succeeded in extending the formulae-as-types notion to deal with continuations. Whereas Griffin adopted control operators primitively, Filinski adopted the duality of functions to construct a symmetric lambda-calculus in which continuations are first-class objects. In this paper, we construct a typed lambda-calculus with first-class configurations consisting of expressions and continuations of the same types. Our calculus corresponds to a natural deduction based on Rumfitt’s bilateralism. Function types are represented as the implication and but-not connectives in intuitionistic and paraconsistent logics, respectively. Our calculus is not only logically consistent, but also computationally consistent. Our calculus with call-by-value and call-by-name strategies correspond to Wadler’s call-by-value and call-by-name dual calculi, respectively. Furthermore, we propose a notion of relaxed configurations, which loosely take expressions and continuations of different types. We confirm that the relaxedness defines control operators for delimited continuations.
Building Greibach Normal Form Grammars Using Genetic Algorithms

Grammatical inference of context-free grammars using positive and negative language examples is among the most challenging task in modern artificial and natural language technology. Recently, several implementations combining various techniques, usually including the Backus–Naur form, have been proposed. In this paper, we explore a new implementation of grammatical inference using evolution methods focused on the Greibach normal form and exploiting its properties, and also propose new solutions both in the evolutionary processes and in the corresponding fitness estimation.
Database Query Execution Through Virtual Reality

Building database queries often requires technical knowledge of a query language. However, company employees (outside of software development, generally) may not have the expertise to accurately construct and execute database queries. Moreover, in the era of Big Data, we believe that it is important to count on more flexible interfaces that may allow users interact with data in a more natural and immersive way. Our contribution is to utilize virtual reality (VR) to construct database queries and execute them on relational databases. Using natural hand or controller gestures, this approach seeks to provide easy access to build and visualize database queries. This is a first approach towards more flexible interfaces to interact with data.
Resource Oriented Programming: Design Pattern for Describing Restful Service Composition

The COVID-19 pandemic has accelerated digital transformation in the world. A consequence of this pandemic is the growing demand for the development of applications in a relatively short time. To solve this problem we present in this paper a language to simplify implementing REST resources using rewriting and code reuse. For this, we first introduce the resource-oriented programming concept in which we represent a resource as a combination of other (existing) resources. We then formalize the different possible combinations thanks to design patterns from object-oriented programming. Finally, we show the relevance of our language by presenting firstly some use cases of design patterns for solving recurring issues in web applications such as over-fetching and under-fetching and then comparing our approach to that of object programming for solving the minimalist management of a stock.
A Process Innovation: Introducing a Technology Tool into Curriculum

To successfully introduce a new technology tool into curriculum, a researcher may apply a process to increase the likelihood of adaptation of the new tool into its’ curriculum. For the purpose of this study, universal design, innovation tactics and a business model analysis have been explored in order to reveal variables of introducing a new medium (technology tool) for interior design students to use in their curriculum and self-critique. With virtual reality (VR) emerging on the horizon of many fields, the impact on interior design education is, however, unknown. Traditionally, in an interior design studio course, a student self-critiques by viewing their designs, both two-dimensional and three dimensional, on a computer monitor, a printed paper, and/or on a digital image projected up on an overhead screen. The research problem proposed is that new technology tools need an introduction process to be developed, in order to increase the likelihood of its’ adaption into curriculum. This study proposes that process and evaluation, focusing on introducing VR as a student self-critique tool to enhanced current interior design curriculum in an undergraduate midwestern United States university. Utilizing the applications of the Running Lean Canvas, Universal Design (UD) techniques and the ten categories of innovation tactics (IT), assisted in the evaluation of the innovation process of introducing a new technology tool into interior design curriculum. Last, this study leads to future research problems in emerging technology in the field of interior design education: What implications will this cause in the student’s self-critique process? Does the student's technology acceptance factor affect their intention to use the new technology?
Reverse Gutenberg Galaxy: Digital Transformation of Economy and Labor

Concepts such as blockchain, smart contracts, DeFi, NFT, DAO, Web3, and metaverse have risen in trend and are said to be revolutionary changes, especially in the field of finance. However, these just extend the modern monetary economy and would only radicalize it, but may not solve the problems the current economy faces such as widening economic gaps. This paper proposes to view general digital transformation (DX) as a paradigm shift from the intellectual framework of fixed points of view and massive homogeneous replications that has dominated our society especially since the invention of movable type, to perspectives of each and individual constructions through digital technology. This approach can explain not only the changes caused by financial technology, but also the changes represented as DX in general, foresee the demise of industrial society in the near future, and describe what the next society will look like. Toward the second half of the 21st century, social structures based on specialization and division of labor will decline, and money will end its role as a tool to drive manpower. In the process, the role of finance will change significantly, if not disappear completely.
Developing and Implementing Blockchain Identity Management to Verify Students’ Certifications and Data (VeriOn)

Every area of our life has been altered by technological improvements in the digital arena, from shopping to working, from staying in contact with friends to entertainment and not to mention managing our money. Identity management has been a major problem since the internet’s inception, with billions of dollars being spent on usability, security, and privacy. DLT (Distributed Ledger Technology) or “Blockchain Technology” is the technology underpinning decentralized databases that allow users to govern the development of data across entities, via a peer-to-peer network, employing consensus techniques to ensure data replication among nodes. The fact that each block, where data is recorded, cannot be modified is what makes blockchain safe. Official education documentation does not provide complete information regarding academic performance during a certain period of study, course or semester. Furthermore, due to the participation of middlemen, academic accomplishment papers produced by universities are not protected against unauthorized alterations. This research presents a successful platform, called VeriOn, which was built on Ethereum-blockchain open-source and a consortium type of decentralized, open-sourced blockchain Ethereum. The proposed system is built on a worldwide distributed P2P network, which enables the organization to collaborate with the blockchain network, in order to trace student / employee data, verify academic success, and exchange information with others. To solve the issues universities experience in storing and safeguarding the data, VeriOn platform was built using a consortium, blockchain architecture. Crucially, this paper presents an implementation of this architecture as a proof of concept.
Upgrade SecSLA Using Security as a Service Based on Knowledge Graph

Security as a Service (SecaaS) offers security capabilities as a cloud service. It offers the Customers the expertise of specialists in their fields, supports flexible deployment models, allows customers to focus on their business core, and leaves the security to the SecaaS provider. Besides, finding a Cloud Service that guarantees the minimum Security Service Level Agreement (SecSLA) required by the customer may be challenging. Due to the difference in the security objectives between the Cloud Service Provider (CSP) and the Cloud Service Customer (CSC). To enable the customer to use the Cloud Service without giving up security. We propose an approach to upgrade the SecSLA guaranteed by a Cloud Service using a set of SecaaS provided by a third-party CSP. Besides, based on the knowledge graph, we create a service that offers a centralized repository of Cloud Service and SecaaS. It furnishes a GraphQL API (Application Programming Interface) to allow users to search for relevant SecaaS that support their Cloud Services consumed and provide the missing Security Service Level Objective (SSLO) to achieve the minimum SecSLA. To validate our approach, we create a study case with five scenarios and evaluate the response time for each of them. We calculate the overhead of the scenarios that use our approach compared to the other ones.
State-of-the-Art Lightweight Cryptographic Protocols for IoT Networks

Due to technical improvements, the Internet of Things has enabled the networking of devices capable of collecting vast volumes of data. Consequently, IoT security requirements are crucial. Cryptography safeguards the network's identity, data integrity, privacy, and access control. Since IoT devices impose so many constraints, certain encryption methods are not suited for IoT environment. Therefore, academics have proposed a variety of lightweight cryptographic protocols for protecting data in Internet of Things (IoT) networks. This paper investigates modern lightweight cryptography techniques for IoT networks and evaluates prominent ciphers now in use. Consequently, it divided contemporary into two categories: symmetric lightweight cryptography and asymmetric lightweight encryption. In addition, the security of several newly proposed block cipher and stream cipher methods has been assessed. In addition, the key alterations and potential future study areas have been examined.