Reviewerly/exHarmony huggingface dataset:
Implementing Multisensory Approach to Overcome Reading Difficulties in 4th Grade Students

Reading is one of the language skills that students must possess. The purpose of this study is to address difficulties in learning to read through multisensory methods for participants. The study was conducted at SD Inpres Lisabheto (a public elementary school), Sikka Regency. The research method employed a qualitative approach with a descriptive method. The subjects targeted in the study were fourth-grade students. To gather data, the researcher used observation techniques, documentation, and reading practice tests. The results of the study obtained by the researcher through the use of multisensory methods on fourth-grade students who still experienced difficulties in learning to read using visual (sight), auditory (hearing), tactile (touch), and kinesthetic (movement) sensory tools. The use of multisensory methods proved to be an improvement in the reading learning ability of fourth-grade students who still struggle with reading. The study found that implementing the multisensory approach in reading instruction had a positive impact on the reading speed of fourth-grade students at Inpres Lisabheto Elementary School. The guidance provided by the classroom teacher and researcher was effective in improving the students' ability to memorize the alphabet, spelling, combining words, and recognizing symbols in writing. The use of the multisensory approach also increased the students' confidence and motivation to become more active and interactive in their learning.
Moving from discourse to Praxis: Situating academics at the centre of decolonisation struggle

As part of contributing to the decolonisation debate to reclaim and re-purpose the universities as public good institutions, drawing from Freire’s notion of praxis we argue that there is a need to move from theorisation of concepts or what we refer to as discourses to praxis, and academics must drive the decolonisation project. Unlike students, academics have immense power to influence choices of pedagogical approaches, processes of curriculum design, and knowledge production. Academics enjoy academic freedom. This implies that they have the freedom to teach and conduct research without external control in their area of expertise, which gives them special protection within the classroom and the parameters of their field of expert knowledge. Thus, we argue that the freedom that academics enjoy puts them in a good position to be drivers of the project of decolonising higher education. As key role players on processes of teaching and learning as well as knowledge production in higher education, they have some degree of power that they are better positioned to drive the decolonial project. They can use their roles as teachers and researchers to advance the decolonisation agenda.
An Investigation into Google Translates Translation of English Proverbs into Vietnamese

When learning English, once in a while, learners may need help to cope with English proverbs, and the dictionary may not help them explain the proverbs’ meaning. Then, it leads them to find Google Translate (GT) as a safe place to help translate proverbs. The present study attempts to discover how GT renders English proverbs into Vietnamese. To have the data for the study, the author adopted 17 proverbs from an educational website full of explanations of such proverbs. The data was collected in about 45 minutes from the GT translation platform. The results revealed that GT could translate all the words in each proverb and put them in acceptable Vietnamese structures. However, GT needs to provide Vietnamese readers with the intended meaning of the proverbs, which is to give advice to people on work and work effort. The study also includes some limitations for further study.
Machine-learning assisted topology optimization with structural gene inheritance

A machine-learning assisted topology optimization approach is proposed for structural design with structural gene inheritance.This work establishes a novel framework to systematically integrate structural topology optimization with subjective human design preferences.To embed the structural gene into the design, neural style transfer technique is adopted to measure and generate the prior knowledge from a reference image with the concerned structural gene (such as biological characteristic, artistic flavor and manufacturing requirement, etc.).By using different convolutional layers in the VGG-19 model-based CNN, both the style and content of the structural gene can be constructed from low to high levels of abstraction.The measured knowledge can then be integrated into pixel-based topology optimization as a formal similarity constraint.Both 2D and 3D problems are solved to illustrate the effectiveness of the proposed approach where the inheritance of the structural gene can be achieved in a systematic manner.
TKG: Telecom Knowledge Governance Framework for LLM Application

Abstract The emergence of ChatGPT and the competition among various Large Language Models have drawn significant attention from society. The success of Natural Language Processing (NLP) in the general field has captured the interest of researchers and engineers from academia and industry. In the telecom industry, Large Language Models (LLMs) have found extensive use in intelligent customer service and data search, contributing to the improvement of work efficiency in product delivery and operation. Nevertheless, it is important to note that while generic large models are versatile, their application to specific domains is hindered by the lack of high-quality domain-specific data. This often results in LLMs being unable to provide high-quality answers to specific problems. In this paper, we aim to investigate knowledge data governance in the telecom field, build high-quality domain-specific corpus, and utilize the dataset to fine-tune the large language model, which can enhance its ability to solve downstream practical problems such as Q\&amp;A, search, and text generation. To address the challenge of model hallucination, we propose a data solution, namely Telecom Knowledge Governance (TKG), for intelligent application scenarios. TKG constructs a large-scale telecom domain corpus that ensures the accessed data is up-to-date, comprehensive, and of the highest quality. Moreover, we recruit five technical experts in the telecom field and develop automated generation tools to create a high-quality telecom Q\&amp;A dataset that includes over 100,000 domain-specific questions and answers. Finally, we use this dataset to fine-tune the model, allowing it to learn how to apply telecom knowledge to specific scenarios more effectively. The results show that our knowledge data can greatly improve the model performance.
Breast Cancer Detection by Using VGG19 Deep Learning Network with Image Filtering and Histogram Equalization Methods

Abstract Deep learning techniques, one of these machine learning techniques, are also at a very important point. Thanks to the classification made with deep learning techniques, high accuracy rates can be obtained for cancer diagnosis and faster results can be obtained. In this study, VGG19 network architecture, one of the deep learning methods, was used to classify mammogram images. In addition, image equalization and image filtering methods were applied to the images used. In this way, it was also determined which method achieved higher accuracy when the image filtering and image synchronization methods used were run together with the VGG19 deep learning network architecture. The combination of CLAHE histogram equalization and VGG19 deep learning network gave the highest accuracy. The accuracy rate of the training data in the created network is 99.82%. In addition, the loss rate of the training data in the network is 0.76% and the validation rate of the test data in the network is 99.63%. The number of correct positive images is 796, the number of false positive images is 0, the number of correct negative images is 798, and the number of false negative images is 6. These image numbers belong to the test data. The number of correctly classified images in the test data is 1594. These values ​​are very good values ​​for classification of mammogram images.
Shepard’s Validation of Antitrust Relief Framework on Patent Infringement of Novartis’ Cancer Drug Using Genomic Architectures of Legal Literature Based on UK Intellectual Property Law

Purpose: Comparative law is designed for alignment of constitutional law with other countries advocating public welfare and safety. The United States has an Intellectual Property provision under U.S. Fair Clause using their constitution as pre-emptive doctrine. The aim of this paper is to evaluate the applicability of UK Intellectual Property Law based on their complexed policies on Artificial Intelligence. Hence, it leads to problem statements questioning: (1) the eligibility of matters of facts did not meet UK IP Law; (2) the standard for evidence towards invention using Artificial Intelligence does not conform with UK IP Law; (3) Liability in AI patent infringement is not subsistent in UK IP Law; and (4) AI’s compliance is not subject for responsibility under creativity and non-obviousness criteria.&#x0D; Methodology: The Trade-Related Aspects of Intellectual Property Rights (TRIPS) Agreement promotes the public welfare and safety under constitutional laws. India, as a member, is obliged to comply with the standard of evidence in patentability under World Trade Organization (WTO). The study employs comparative contextual assessment using Novartis’ case as trial proceedings for disclosing theoretical framework vital to socio-legal integration of WTO principles.&#x0D; Findings: The World Trade Organization is a committee responsible to advocate business law. Invention for marketability of patent product has its own complexed policy to comply for acceptance of an Intellectual Property creation. Constitutional law is designed to be made comparable with other countries promoting monetary success of their nation exhibiting economic progress in industrial and technological advancements. Hence, authorless works marking artificial intelligence towards public health and safety must be done in lack of any dedication to human connections resulting to immersion of their “new” product as a work of an art making non-obviousness skills to people as part of common logic and interests, hence, a product of convenience.&#x0D; Recommendations: WTO is an intergovernmental task force important to implement constitutional laws comparable to other countries resulting to theory integration of socio-legal aspects based on trade-related principles. Hence, the advocacy of business ethics is a highly acknowledged means of making the lives of people to be technologically advanced with convenience, thus, inventions should be made affordable for public access.
Implementasi Pembelajaran Aktif, Kreatif, Efektif dan Menyenangkan pada Mata Pelajaran PAI (Studi Kasus di Kelas X.E7 SMAN 1 Painan)

The problem of this research is how to implement active, creative, effective and fun learning in improving the quality of PAI learning at SMA N 1 Painan, beceuase there are still many conventional learning implementasions. The research method used is qualitative research which refers to the problem study approach and the focus or core of this research is to see and know how teachers are able to create an active, creative, effective and fun learning atmosphere in PAI subjects. Then for the types of data that exits in this study are data in the from of primary data and secondary data, while the information obtained is data generated from observasion in the field and also interwiws with informants. The informants selected by the researcher included : Deputy Curriculum, Teachers who teach in class X.E7 an students in class X.E7 SMA N 1 Painan. As for the result, the researchers found that the PAKEM learning model was able to improve student learning outcomes.
Towards Effective Ancient Chinese Translation: Dataset, Model, and Evaluation

Interpreting ancient Chinese has been the key to comprehending vast Chinese literature, tradition, and civilization. In this paper, we propose Erya for ancient Chinese translation. From a dataset perspective, we collect, clean, and classify ancient Chinese materials from various sources, forming the most extensive ancient Chinese resource to date. From a model perspective, we devise Erya training method oriented towards ancient Chinese. We design two jointly-working tasks: disyllabic aligned substitution (DAS) and dual masked language model (DMLM). From an evaluation perspective, we build a benchmark to judge ancient Chinese translation quality in different scenarios and evaluate the ancient Chinese translation capacities of various existing models. Our model exhibits remarkable zero-shot performance across five domains, with over +12.0 BLEU against GPT-3.5 models and better human evaluation results than ERNIE Bot. Subsequent fine-tuning further shows the superior transfer capability of Erya model with +6.2 BLEU gain. We release all the above-mentioned resources at https://github.com/RUCAIBox/Erya.
Calibration Methods in Imbalanced Binary Classification

Abstract The calibration problem in machine learning classification tasks arises when a model's output score does not align with the ground truth observed probability. There exist several parametric and non-parametric post-processing methods that can help to calibrate an existing classifier. In this work, we focus on binary classification cases where the dataset is imbalanced, meaning that the negative class significantly outnumbers the positive one. We propose new parametric calibration methods specific to this case and a new calibration measure focusing on the primary objective in imbalanced problems: detecting infrequent positive cases. Experiments on several datasets show that, for unbalanced problems, our approaches outperform state-of-the-art methods in many cases.
Should the Federal Reserve Issue a Digital Currency as Virtual Legal Tender? An Econo-legal Analysis Based on China’s Master Plan for De-dollarization

Mainstream discussion on whether the Federal Reserve should issue a central bank digital currency (CBDC) as virtual legal tender focuses on five aspects related to the American domestic environment -- efficiency, privacy, safety and security, financial inclusion and exclusion, and impact on the current economic systems and monetary policies. This article takes a new and broader perspective on this critical issue by investigating how China, being the arch-international competitor of the US, has formulated a well-designed and structured master plan supported by various econo-legal strategies to pursue the objective of de-dollarization through the utilization of a China-currency-based CBDC with “controllable anonymity” and different multicurrency exchange and settlement platforms. Given the reality that de-dollarization will inevitably weaken the ubiquitous platform of international trade and payment of the US dollar (USD), can the Federal Reserve use the same tool, a USD-based CBDC, to counteract or even reverse the declining trend of the American currency’s versatility and far-reaching capability? This article recommends that the Federal Reserve can slow down the de-dollarization movement by issuing a CBDC at both the wholesale and retail levels, emphasizing the control of the former while having more cooperation with private banks for the latter.
Knowledge, Attitude and Use of Information Communication Technology (ICT) Among Teachers at SK LKTP Tenang, Labis, Johor

Over the years, the emergence of Information and Communication Technology (ICT) has resulted in significant benefits in the field of education. ICT is used to provide a synchronous and asynchronous teaching and learning platform for both teachers and students. The purpose of this study is to assess teachers' knowledge, attitudes, and use of information and communication technology at SK LKTP Tenang, Labis, Johor. It was carried out to assist teachers in implementing a variety of ICT supported methods and resources in the classroom to improve the teaching and learning process. Teachers at SK LKTP Tenang, Labis, Johor received a survey questionnaire with five sections. The study's findings indicate that the study respondents lack sufficient knowledge of how to use ICT. This is because, there are several challenges faced by teachers when implementing ICT in the teaching and learning environment.
Teaching Chemistry in Universities: A Modern Approach

The relevance of the study is to explore how visual modelling in education can enhance the process of understanding and retention of information in the context of globalization and increasing feasibility of multimedia content. The purpose of the study was to find ways to improve the methods of teaching chemistry to students using modern educational technologies implemented on the basis of multimedia and the Internet. The study conducted at Abai Kazakh National Pedagogical University aimed to improve the teaching methods of chemistry to undergraduate students using multimedia and internet-based educational technologies. The study involved 50 students over a period of six months and was divided into several stages. The results of the study showed that the use of these technologies had a positive impact on the cognitive, behavioral, and affective development of the students. The study provides strong evidence in support of the integration of multimedia and internet-based educational technologies in chemistry education, which can enhance students' interest, motivation, and understanding of the subject. Therefore, the implementation of educational technology is a scientifically grounded choice of teaching methods that maximizes the development of the personality as a subject of the surrounding reality. The practical significance is due to the fact that the most effective innovative teaching technologies identified in the course of the study can be applied by introducing them into the educational system not only of the Republic of Kazakhstan, but also of the leading countries in medical education.
The Role of Cryptocurrencies in Shaping the Future of Mobile Money Services in Lusaka, Zambia.

Purpose: This research provides a comprehensive exploration of the intersection between cryptocurrencies and mobile money services, particularly in the Zambian context. The study illuminates both the potential and the challenges of integrating cryptocurrencies with mobile money services, providing a novel contribution to the existing body of knowledge.&#x0D; Methodology: Utilizing descriptive and inferential statistics, the study reveals a moderately strong positive correlation between cryptocurrency usage and both the volume and frequency of mobile money transactions. However, it also identifies significant barriers to adoption, including a lack of user awareness, security concerns, regulatory ambiguity, and the volatility of cryptocurrencies.&#x0D; Findings Through thematic, content, and comparative analysis, the study underscores the regulatory challenges, increased security risks, and the added burdens of compliance with anti-money laundering (AML) and know-your-customer (KYC) regulations associated with the integration of cryptocurrencies. Moreover, the research identifies the potential disruption of existing mobile money systems by blockchain technology and the significant infrastructural investments and regulatory adaptation that it necessitates.&#x0D; Unique contribution to theory, policy and practice: The research proposes two strategies for aligning the regulatory frameworks for mobile money services and cryptocurrencies in Zambia: development of specific regulations or guidelines for cryptocurrencies that align with existing mobile money rules, and establishment of a separate regulatory framework that addresses the unique characteristics of cryptocurrencies. In highlighting the transformative potential of blockchain technology and the importance of user perspectives and regional variables in the integration process, the study offers valuable insights for researchers, policymakers, and practitioners. The research underscores the necessity for a responsive approach, continuous review, and update of regulatory frameworks, emphasizing consumer protection, market stability, and the promotion of innovation. While the research confirms the promising opportunities, cryptocurrencies offer to enhance mobile money services, it also emphasizes the need for careful consideration of potential adverse effects. Future research is encouraged to continue exploring this rapidly evolving field, broadening the geographical scope, and focusing on user education and robust security measures.
Secret Information Sharing using Multipartite Entanglement in Monty Hall Game

Abstract Quantum computing has emerged as a useful resource for winning random games. Monty Hall problem is one such game where the powers of quantum mechanics can be utilized for winning the prize. Our paper depicts this problem as a two-player game, where the two players, i.e. the host and the participant share an entangled quantum state. The entangled state is closely knit with the position of the prize containing door, and the decision of the player i.e. either switch or stay from his initial choice of door. The two players are part of one team as they share a quantum communication channel among them by sharing the entangled state as a quantum resource. This enables them to share share secret information about the position of the price as well as the strategy to opt for winning the game. The article shows a unique way of utilizing three different type of entangled states, 3-qubit symmetric W state, 3-qubit X state, and 5-qubit highly entangled Brown state. Further, the effectiveness of each quantum state as a source of communication in disguise is also compared. All the entangled states under study assure winning the price by the participant. However, each quantum state has different entanglement degree and offer varied merits as per the game setting.
A Collaborative Ledger Storing Model for Lightweight Blockchains based on Chord Ring

Abstract A Blockchain is one distributed ledger system, and keeps the high redundancy of ledger copies to make the assurance of network security. However, the continuously duplicated full copies also impose a tremendous amount of demand on some nodes for data storage. The development of blockchain technologies in the IoT(Internet of Things) application scenario is hampered by the restricted storage capacities of terminal devices used in the IoT edge computing scenario, which makes it difficult to load the full copy with infinite growth. Our paper suggests a collaborative ledger storing model based on Chord Ring to address the issues with lightweight blockchains in data storage. On-chain blocks are split by Chord Ring structure and stored in various node clusters in a decentralized manner, and off-chain blocks at various levels are provided with PoW(Proof of Work) consensus asynchronously and archived centrally to the cloud storage on a regular basis. The theoretical and experimental analysis indicates that this model can reduce the data storage redundancy of blockchains while ensuring the high availability of data and the high decentralization of the network.