Reviewerly/exHarmony huggingface dataset:
The metamorphosis of machine translation: The rise of neural machine translation and its challenges

Machine translation refers to the process of using computers to translate source language into target language, which has undergone significant transformations since its inception, with the current mainstream neural machine translation achieving satisfactory translation performance. This paper overviews the three developmental stages of machine translation: rule-based machine translation, statistical machine translation, and neural machine translation, with a focus on neural machine translation. It introduces the key models that emerged in the development process of neural machine translation, namely the recurrent neural network encoder-decoder model, recurrent neural network search model, and Transformer, and compares their strengths and limitations. Other relevant technologies and models developed alongside neural machine translation are also discussed. Addressing the current challenges of neural machine translation, the paper delves into issues of overfitting, low-resource translation, structural optimization of Transformer models, and enhancement of neural machine translation interpretability. Finally, the paper explores the prospects of applying neural machine translation to multimodal translation.
Review of collaborative filtering recommendation systems

In the era of information overload, recommender systems develop rapidly. And because the needs of information consumers are full of diversity and the information data provided by information producers is too large, to enhance the efficiency and quality of recommendations, the research community has introduced numerous approaches to optimize recommendation systems. As collaborative filtering stands as a time-tested technique in recommendation systems, This paper facilitates a swift comprehension of recent advances in collaborative filtering. It does so by examining the techniques presented across the entire collaborative filtering recommendation systems research field in recent years, especially its development in the domain of deep learning, and have a solid understanding of the field of study.
Transformers: Statistical interpretation, architectures and applications

Transformers have been widely recognized as powerful tools to analyze multiple tasks due to its state-of art multi-head attention spaces, such as Natural Language Processing (NLP), Computer Vision (CV) and Speech Recognition (SR). Inspired by its abundant designs and strong functions on analyzing input data, we would like to start from the various architectures, further proceed to the investigation on its statistical mechanism and inference and then introduce its applications on dominant tasks. The underlying statistical mechanisms arouse our interests and intrigue us to investigate it in a higher level, and this surveys will focus on its mathematical foundations and then use the principles to try to analyze the reasons for its excellent performance on many recognition scenarios.
Soft and Hard Skills to Be Developed By a Pre-Service Teacher under Distance Learning: Case Study

This article reflects on the development of soft and hard skills and their importance within the academic and educational course of students who study a degree in English as a foreign language under the distance modality. At the center of this study, the opinions of 46 students from various semesters underscore the fundamental role that the cultivation of these competencies plays in distance education. The qualitative approach and NVIVO software were used in a multiple case study to carry out axial coding. In this way, the information was classified into 6 categories, supported by the opinions provided by the survey participants: Personal Growth, Assertive Communication, Professional Enrichment, Digital Management, Pedagogical Confrontation, and English Proficiency. By analyzing the perspectives of these students, the research concludes that pre-service teachers have a valuable perspective on the development of competencies and recognize the integration of these competencies in their distance learning path, promoting personal and professional growth for their future roles.
Portable Referee System for Volleyball Game Based on Pressure Monitoring and Self-Powering Communication

Sports refereeing has traditionally relied on human judgement, which can be prone to errors. However, the development of automatic referee systems has the potential to address this issue, improve training, and promote sports in the future. In this study, we present a novel and portable referee system specifically designed for volleyball games, which utilizes piezoelectric sensors to detect pressure and simultaneously harvest energy for powering the system. The system consists of two parts: a wearable glove and a device mounted on the volleyball. The glove part has five sensors fixed on the fingertips and the volleyball has eight sensors evenly distributed on its surface. The collected contact data from the sensors is wirelessly transmitted to a personal computer. Our experimental results demonstrate that the system can accurately capture a three-second contact and detect foul actions in a volleyball game. These findings highlight the potential of the system for sports and other monitoring applications.
The Impact of ChatGPT on Language Evolution: A Linguistic Analysis

This research sought to identify changes in terms of word choice, sentence structure, and semantics introduced by ChatGPT and how the functionality of ChatGPT impacts the pragmatics of the English language: politeness, deixis, and discourse markers. This study used corpus analysis as part of the methodology involving Natural Language Processing (NLP) tools for part-of-speech tagging and sentiments, analyzing changes in wordings, syntaxes, and semantic elements generated by ChatGPT as an advanced language modal. A qualitative approach, including user surveys and comparative analysis, proved useful in clarifying the changing patterns of politeness, deixis, and discourse markers in AI-supported communication. Henceforth, ChatGPT generates neologism, unique cultural references, verbal contextual adaptations, and a wide range of technical terms. Moreover, the researchers found that user preferences for communication mediums vary, which showed a complex field of users and their expectations in the context of language generated by ChatGPT. Thus, it was observed that ChatGPT contributes significantly to developing the pragmatic aspects of language use in the modern era. Hence, the study proposes that the ChatGPT polishes the usage of politeness terms and improves its deixis along with formal discourse markers. This highlights the need for continuous improvement, especially in areas such as politeness, deixis management, and integration of discourse markers for the developers.
ANALYSIS OF NEEDS FOR DEVELOPING TEACHING MATERIALS FOR WRITING ADVERTISING TEXTS BASED ON ANDROID PLATFORM APPLICATIONS FOR CLASS VIII STUDENTS

This research is motivated by the low ability of students to write attractive advertising texts. This is because the teaching materials available in schools are not yet able to facilitate students being able to write text advertisements well. The research carried out in this study was descriptive qualitative research, namely to describe students' needs for teaching materials that suit the students' needs
A Cognitive Semantic Analysis of Hausa Personifications

This paper investigates the cognitive aspect of Hausa Personifications. The objective of the study is to discover the Hausa personifications found in the language expressions as a result of feature mappings from animate concepts to inanimate ones. The other objective is to come up with a cognitive semantic analysis of the Hausa personifications. The studied personifications are metaphorical and the Conceptual Metaphor Theory of Lakoff and Johnson (1980) is used as a guide frame in mapping the attributive features of the living entity to the inanimate ones. The observation technique is used in collecting the data for the study. One of the findings of the study reveals the kind of features merged between the animate and the inanimate concepts to form the Hausa personifications. Another important finding of the research indicates that the attributive features attached to animate entities are mapped upon the inanimate concepts conceptually to make the Hausa expressions personified. And finally, the study considered the analyzed Hausa personifications as similar to dead metaphors.
Blockchain Powered Medical Sector – Application, Challenges and Future Research Scope

The recent research in the healthcare sector using computer technologies in the fourth industrial revolution helps to improve the quality of life by accessing the medical data to monitor, diagnose and treat the patient at the right time from anywhere in the world. Blockchain is one of the major recent innovations and trending research topics that plays a vital role in diverse applications like Smart cities, Healthcare industry, Smart grid, etc. Blockchain, which is fascinated with its features like secure data sharing, immutability, decentralization, and reliability in data management, has made it a prominent technology in the healthcare industry. This chapter discusses 1) The working principle of blockchain technology with its different prospectus in healthcare. 2) Advantages of blockchain technology over the Internet of Things in secured patient data management, efficient data sharing with decentralized data management accessible for authorized users using cryptography techniques. 3) Various applications of blockchain technology in healthcare, like remote patient monitoring using Internet of Things (IoT) devices for cardiac and electroencephalogram (EEG) signal monitoring to diagnose life-threatening diseases. 4) Drug traceability in the pharmaceutical drug supply chain to ensure product safety with an end-to-end tracking system and immutable transaction record. Finally, this chapter also presents the blockchain based challenges and solutions that advocate the future research scope in healthcare systems.
Consequences and Deliberations in Implementation of Blockchain and Internet of Things Integration

Blockchain technology proposes security facilities to the Internet of Things (IoT). The things or objects used in daily life are connected to the internet to form IoT. The blockchain integral safety mechanism can deliver amenities, such as authentication, accessibility, integrity, secrecy, and authorization to the IoT applications. The uses of IoT applications are the dream turning into reality. But using this IoT still faces some challenges, mainly in the areas of security such as data consistency and reliability. The objects have interacted over the internet; they can also be supervised and controlled remotely. The use of IoT reduces time, manual work, tracking and money. With the evolution of IoT, it is essential to deliver more security for enormous amounts of data. Blockchain is a circulated network with the properties of integrity and secrecy. The blockchain maintains data security in the network of IoT. Here to discover the challenges associated with the combination of IoT and blockchain, a study is taken first, then a blockchain introduction is offered, followed by the Blockchain-based IoT requirements, demand and Quality of Service (QoS) discussed. Then, tasks faced while applying this blockchain-based IoT, such as plan, progress and deployment, are discussed. Then applications of blockchain-based IoT such as throughput, efficiency, latency, privacy, fork problem, smart contracts, legal issues, security, storage and proposed solutions are deliberated. Finally, upcoming research guidelines for the combination of IoT and blockchain are designated.
Integration of Blockchain and Internet of Things

Customers can benefit from the Internet of Things in a number of ways, and it has the potential to transform the fundamental ways that consumers interact with technology. The pervasiveness and correspondences maintained for IoT might provide various conveniences and aids for people, but also open up many security loopholes. Blockchain, a distributed digital ledger, is finding uses in industries as diverse as finance, healthcare, utilities, agriculture, real estate, and Supplier Management. The middleman acting as guardians for specific applications in these enterprises can be removed in order to provide security and those equivalent applications can be run in a distributed way with practically no centralized power. Blockchain technology makes this feasible without sacrificing efficiency or safety, which was previously impossible. Blockchain and IoT seem to be best on their own in the respective sector in which it is applied, so businesses can try and exploit this powerful combination known as Blockchain Internet of Things (BIoT) to bring immense advancements, progressions and cutting edge innovations in the area of their interest. The term “BIoT” was created by fusing blockchain with IoT applications.
An Overview of Blockchain in the Field of Smart Healthcare System

Rapid Blockchain is one of the most talked about technologies in the world at the moment. The origin of blockchain is a cryptocurrency called “bitcoin”. It is a secure currency that can be used as a medium of exchange worldwide. Blockchain itself is a decentralised, peer-to-peer distributed ledger capable of storing all transactions that take place on the network. This property makes blockchain useful for any type of exchange, such as data, currency and information. Blockchain protects against potential data theft or corruption in the healthcare network. It is important to maintain the integrity and validity of patient records to ensure wellness. Artificial intelligence and blockchain will provide a smart healthcare system for people around the world by extracting useful information, protecting medical data, simplifying claims processing, using patient self-generated data and systematising procedures.
Topological features of spike trains in recurrent spiking neural networks that are trained to generate spatiotemporal patterns

In this study, we focus on training recurrent spiking neural networks to generate spatiotemporal patterns in the form of closed two-dimensional trajectories. Spike trains in the trained networks are examined in terms of their dissimilarity using the Victor-Purpura distance. We apply algebraic topology methods to the matrices obtained by rank-ordering the entries of the distance matrices, specifically calculating the persistence barcodes and Betti curves. By comparing the features of different types of output patterns, we uncover the complex relations between low-dimensional target signals and the underlying multidimensional spike trains.
Inclusive Description in the Glasgow School of Art Library’s Published Catalog

This case study provides an overview of two guidance packs that the author created for the GSA Library, the first of which concerns advisory notices and the second of which concerns subject indexing and classifications. In an effort to share good praxis, this article includes real examples of item-level advisory notice text as well as a set of flowcharts that were designed to help GSA Library staff with the tasks of inclusive description.
Security Enhancement in Cloud and Edge Computing Through Blockchain Technology

The cloud computing (CC) network is designed to tackle the security and privacy challenges of centralized cloud services by distributing computing and storage resources among networked nodes. Cloud computing, on the other hand, is restricted by the performance of linked devices, posing problems in state authorization, stats encryption, consumer privacy and more. Blockchain technology (BT) is the most popular circulated network technology right now. It is utilized in numerous fields like bitcoin, IoT, etc., to tackle the consistent issue of distributed data. The difficulties that CC networks present for security and privacy are covered in this chapter. Analysis and solutions brought to edge computing networks by BT in terms of data encryption, authentication and user privacy. In this chapter, the advantages of combining the cloud computing network with blockchain technology will be discussed. Finally, memory, workload, and latency problems for related future studies have been discussed.
Machines that work by electric current

We are surrounded by machines that work by electric current. For example, digital devices that work by electric current like clock or transducer. In order for them to work, they require current. This paper explains a simple way to make those devices.
Randomized block quasi-Monte Carlo sampling for generalized likelihood uncertainty estimation

Abstract Although hydrological model forecasts aid water management decisions, they normally have predictive uncertainties. Generalized likelihood uncertainty estimation (GLUE) is popular for constructing predictive uncertainty bounds (PUBs). GLUE is based on simple Monte Carlo sampling (SMCS), a technique known to be ineffective in establishing behavioural simulations. This study introduced randomized block quasi-Monte Carlo sampling (RBMC). In RBMC, each parameter's range is divided into a stipulated number of sub-blocks (Snb). Parameter's values are separately generated in each sub-block. Finally, the sub-blocks are shuffled while maintaining the sequence of generated values in each sub-block. When Snb is equal to the number of simulations, RBMC reduces to SMCS. Otherwise, each Snb leads to a separate RBMC configuration or sampling scheme. The number of RBMC-based behavioural solutions was often found to be greater than that of SMCS, in some cases, by up to 33.6%. The width of the 90% confidence interval on 95th percentile flow based on SMCS was often larger than those of RBMC, sometimes, by up to 23.4%. PUBs were found to vary in widths among RBMC configurations thereby revealing the influence of the choice of a sampling scheme. Thus, GLUE based on RBMC is recommended to take into account the said influence.
An assessment of the integration of ICTs into teaching processes by science teachers: The case of Albania

Many studies have recently focused on the importance of the effective integration of Information and Communication Technology (ICT) tools in science education and the need for science teachers to receive adequate training and support to use them effectively. This paper aims to explore the Albanian science teachers’ perceptions and use of ICTs in teaching processes. The study provides an interpretative analysis of the opinions of science teachers teaching in the middle and high schools of several Albanian regions expressed in an online survey. Overall, the results suggest that the use of ICT by science teachers in Albania is limited by a lack of proper infrastructure, limited access to technology, and training of teachers on integrating technology. However, there are indications that the adoption of ICT in science education may increase in the future, particularly after the boost from the COVID-19 pandemic emergency.
The use of elements of neuropedagogy in the creation of virtual simulators for in-depth study of chemistry in higher education

This study investigates the efficacy of incorporating neuropedagogical elements into virtual simulators for advanced chemistry education in universities. Utilizing a mixed-method approach, it uses questionnaires completed by 50 organic chemistry students. These questionnaires included both general and Likert scale questions, focusing on students' experiences with the PhET Interactive Simulation. The results highlight the positive impact of neuropedagogy on students' learning attitudes, cognitive abilities, and skill development, particularly in areas like critical thinking, analytical skills, and social competencies. A significant portion of students reported enhanced educational outcomes: 76% observed improved training effectiveness, 88% better understood the subject, and 96% found the virtual simulator-based learning more engaging. Furthermore, the study notes improvements in students' problem-solving abilities (68%), logical reasoning (92%), and comprehension of chemical processes (94%). These findings emphasize the value of integrating neuroscience principles in chemical education, potentially benefiting both tertiary and secondary education sectors. They indicate the necessity for educational adaptation in line with interdisciplinary research in cognitive and neurological sciences. This research not only serves as a valuable resource for chemistry teachers but also sets the stage for future empirical studies exploring neuroscience's role in teacher education. The study underscores the importance of further investigation into how teachers implement neuropedagogical techniques and the effectiveness of such applications, advocating for continuous development in educational methodologies.
Role of UPI Application Usage and Mitigation of Payment Transaction Frauds: An Empirical Study

The objective of this investigation is to analyze the intention behind user behavior toward employing Unified Payment Interface (UPI) apps and pinpointing successful solutions for mitigating frauds linked to them. This will increase safety measures, which would lead to an escalation in usage among consumers, ultimately resulting in higher financial inclusion across India through cashless transactions. The Indian digital payment system has been transformed by these platforms, including Google Pay, PhonePe, and Paytm, which together account for over 90% of all online payments made. Users are attracted primarily due to its convenience as well as ease-of-use factors along with influence from their peers who have turned into avid users themselves. Largely, due to COVID-19 lockdown disruptions many people shifted away from traditional monetary exchanges toward Internet Banking options leading to a surge-related crime involving transactional fraudulent practices costing up to 346%. The popularity itself throughout time due again mainly because it’s easy access capabilities UPI payment app development on fraudulent activities continued. A structured questionnaire was adopted during the collection phase within Chennai City among active UPI payment apps users whose data were analyzed using multivariate statistical techniques. The result proves that predictors such as perceived security, safety, risk consistent advantageous represents key inferences, supplying impetus towards utilizing technology and providing cautionary advice where deficiencies subsist. Info dissemination, emphasizing feature/benefit analysis targeting core customer groups, delivered periodically supplemented defensive protocols, incorporating trial process adaptations can mitigate further risk associated with application utilization. Reader response, demonstrating accommodative response based on familiarity, empowering generational social structure, and enabling transformation gained momentum, demonstrates structural readjustment and solidifies the benefits borne out by increased adaption ratified effective outcomes accruing overall benefits, favourably impacting a variety of demographic profiles, and guaranteeing continued use.