Reviewerly/exHarmony huggingface dataset:
C'mon feel the Moys: a trip through the orange book

Abstract This article is based on a course on how to use Moys classification scheme, 1 delivered by Helen Garner and Felicity Staveley-Taylor on behalf of the British and Irish Association of Law Librarians (BIALL) in November 2022. The article, which is also written by Helen and Felicity, provides guidance on how to use Moys classification, explaining the features that enable the scheme to be expanded to accommodate new subject areas. The article also explains some of the features which ensure the scheme remains relevant to legal libraries today. Sections from the classification scheme, as published in the fifth edition, appear in the article text. In addition, any references to page numbers are to the fifth edition.
User Research with Generative Tools: Understanding users' latent needs and desires

Generative research tools are qualitative research methods that are not focused on a specific service or product, but more on end users’ lives, supporting the creation of well- rounded pictures of those users, including their aspirations, dreams and desires.
Effectiveness and Difficulties of E-Learning as Viewed by The Secondary Stage Students During COVID-19 Pandemic in Jordan

The study aimed to evaluate E-learning pattern between effectiveness and obstacles as viewed by the secondary stage students during COVID-19 pandemic in Jordan.The study population consisted of 326 eleventh grade students from the private schools in Madaba, Jordan.A sample of 142 eleventh grade students was purposefully selected from Al-Rashad Schools in Madaba during the second semester of 2020/2021.The study used the descriptive methodology approach represented by a questionnaire that was developed to achieve the objectives of the study.The study concluded that the difficulties and barriers of e-learning were, in general, at a moderate level.Similarly, the usefulness of e-learning activities and the effectiveness of e-learning activities were at a moderate level.The study also concluded that there were no statistically significant differences in the level of evaluation e-learning activities as viewed by the secondary stage students during COVID-19 pandemic in Jordan.
An Analysis of the Proposing Trends for the Social News Topics Section in HSK Level 6 Based on the Graded Standards: Focusing on the Previous Exam Papers of HSK Level 6 from 2010-2018

This study aims to explore the proposition trends of the social news section in the HSK Level 6 examination from 2010 to 2018, based on the Chinese Proficiency Grading Standards for International Chinese Language Education. By examining the authentic HSK Level 6 test questions from 2010 to 2018, the social news topics covered in the listening, reading, and writing sections were classified and analyzed qualitatively and quantitatively, in conjunction with HSK Syllabus and Grading Standards. The study investigates the proposition trends of social news topics in the HSK Level 6 examination since 2010. The findings reveal a wide range of topics covered, an overall increase in the number of questions, and a broader distribution of question types. All topics belong to the social life category within the social news domain, with social issues embedded within social life topics, and an increasing focus on internet-related topics. However, there are also topics that are not representative. It was also observed that 51% of the language materials selected contained new information while considering timeliness, and there was no presence of sensitive, biased, or obscure content based on the Grading Standards. Overall, the language difficulty level of the materials was appropriate. This research hopes to provide valuable insights and references for the reform and adjustment of the social news section in the HSK Level 6.
A Study on the Topic Sentence “First Chapter of Mencius’ King Hui of Liang”

In Chinese Language, sentence with grammatical order ‘NP1+(AdvP)+NP2+(AdvP)+VP’ becomes special sentence to shows judgmentality when it has specific conditions. Linguistics have diverse points of view for this case. In modern Chinese, since “Topic sentence Theory” and “S-P Predicate Sentence Theory” appeared, these sentence structures have been organized systemically so that it can be referenced when analyzing structure or translation; On the other hand, studies focusing on sentence structure like ‘王年少’ are able to be found in ancient Chinese(Gabelentz(1881), MaJianZhong(1898), ZhaoYuanRen (1948), ZhouFaGao(1961)). However, in terms of Korean’s point of view, there are elements to be supplement until becoming indicator as reference. Therefore, this study will provide direction how to analyze and translate ancient Chinese Topic Sentence by considering 4 main contents as followings: First, the limitation which existing theories have will be studied by analyzing pilot studies related to sentence structure ‘‘NP1+(AdvP)+NP2+(AdvP)+VP’. Second, ‘Ancient Chinese language Topic Sentence Theory’ with applying to supplement elements will be suggested. Third, this will secure the validity based on suggested theories, through ‘NP1+(AdvP)+NP2+(AdvP)+VP’ by『First chapter of Mencius’ King Hui of Liang』. Last, this will establish system to appropriately translate to compliance with the main purpose of originals by referencing how Korean ancestor analyzed and accepted sentence structure ‘NP1+(AdvP)+NP2+(AdvP)+VP’ via ‘Hyunto glosses(懸吐)’ of ‘Naegagbon (Cabinet book of published in the Joseon Dynasty)’
Enigmas of Various Techniques to Implementing Authentication and Integrity in Blockchain-Based Wireless Sensor Networks

Wireless sensor network (WSN) is a part of wireless network containing large number of sensor nodes with limited computation capability to handle sensing data. A major challenge in WSN is security and privacy of user data, as this data is transferred through sensor nodes on wireless medium at the command station. This paper discusses enigmas of security to prevent the data from unauthentic and unauthorized nodes by using communication rule-based, association rule-based and block validity-based techniques. The purpose of using these three techniques is for proper communication and secure transmission in WSN using blockchain-based technology where communication rule-based technique is used for proper communication, whereas association rule-based techniques is used to maintain the links for proper data transfer and block validity-based technique is best for proper data transmission in WSN.
A Systematic Assessment on 3D-Based Deep Learning Models and Challenges in FER

Face expression recognition (FER) is a widely emerging research area in today’s era. The previous 2D-based techniques contain some drawbacks like illumination in data, variation in pose, and use ordinary feature extraction processes on scaled images. So, to overcome these kinds of hazards, 3D-based techniques have come to provide optimal solutions. The 3D-based techniques provide solutions for solving the face as well as video recognition problems with less pose variation problems and with optimal accuracy. This paper makes an attempt to provide a systematic review of various 3D techniques for FER with pros and cons, as well as different categories of emotions. The paper presents and analyses various existing FER-based models proposed by researchers and compares them with performance parameters. Furthermore, the paper provides a review of the different datasets used for FER.
Survey on IoT Based Secure Health Care Framework Using Block Chain Technology

The Internet of Things (IoT) is becoming increasingly popular in today’s world, with applications in a wide range of disciplines, including healthcare. Internet of things-based healthcare solutions have benefited the healthcare industry by utilizing wearable and mobile devices. This results in the most accurate and timely diagnosis of healthcare data. Smart healthcare systems, on the other hand, are extremely susceptible to a variety of security vulnerabilities and malicious assaults such as data loss, tampering, and forging. Recent developments in the block chain technology in combination with IoT offer a viable defense against these flaws and challenges. Combining both the techniques provides better security, hence enhancing performance. This paper focuses on many challenges and the traditional security procedures used in the healthcare domain. Advantages of collaborating block chain with IoT have also been elaborated.
Investigating difficulties and enhancing understanding in linear algebra: Leveraging SageMath and ChatGPT for (orthogonal) diagonalization and singular value decomposition

We explored some common challenges faced by undergraduate students when studying linear algebra, particularly when dealing with algorithmic thinking skills required for topics such as matrix factorization, focusing on (orthogonal) diagonalization and singular value decomposition (SVD). To address these challenges, we introduced SageMath, a Python-based open-source computer algebra system, as a supportive tool for students performing computational tasks despite its static output nature. We further examined the potential of dynamic ChatGPT, an AI-based chatbot, by requesting examples or problem-solving assistance related to (orthogonal) diagonalization or the SVD of a specific matrix. By reinforcing essential concepts in linear algebra and enhancing computational skills through effective practice, mastering these topics can become more accessible while minimizing mistakes. Although static in nature, SageMath proved valuable for confirming calculations and handling tedious computations because of its easy-to-understand syntax and accurate solutions. However, although dynamic ChatGPT may not be fully reliable for solving linear algebra problems, the errors it produces can serve as a valuable resource for improving critical thinking skills.
On skew cyclic codes over $ M_{2}(\mathbb{F}_{2}) $

&lt;abstract&gt;&lt;p&gt;The algebraic structure of skew cyclic codes over $ M_{2} $($ \mathbb{F}_2 $), using the $ \mathbb{F}_4 $-cyclic algebra, is studied in this work. We determine that a skew cyclic code with a polynomial of minimum degree $ d(x) $ is a free code generated by $ d(x) $. According to our findings, skew cyclic codes of odd and even lengths are cyclic and $ 2 $-quasi-cyclic over $ M_{2}(\mathbb{F}_{2}) $, respectively. We provide the self-dual skew condition of Hermitian dual codes of skew cyclic codes. The generator polynomials of Euclidean dual codes are obtained. Furthermore, a spanning set of a double skew cyclic code over $ M_{2}(\mathbb{F}_{2}) $ is considered in this paper.&lt;/p&gt;&lt;/abstract&gt;
Generative Adversarial Networks

Generative adversarial networks (GANs) are very popular frameworks for generating high-quality data and are immensely used in both the academia and industry in many domains. Arguably, their most substantial impact has been in the area of computer vision, where they achieve state-of-the-art image generation. This chapter gives an introduction to GANs, by discussing their principle mechanism and presenting some of their inherent problems during training and evaluation. We focus on these three issues: (1) mode collapse, (2) vanishing gradients, and (3) generation of low-quality images. We then list some architecture-variant and loss-variant GANs that remedy the above challenges. Lastly, we present two utilization examples of GANs for real-world applications: data augmentation and face images generation.
Discovering Top-K Partial Periodic Patterns in Big Temporal Databases

Partial periodic pattern mining involves discovering all the patterns in a temporal database that satisfy the specified minimum periodic support (minPS) and period (per) constraints. The minPS controls the minimum times a pattern must occur periodically in a database. The per controls the maximum inter-arrival time within which a pattern must reappear to consider its reoccurrence to be periodic in a database. Setting appropriate minPS and per values for any database is an open research problem. This paper addresses this open problem by proposing a solution to discover top-k partial periodic patterns in temporal databases. Top-k partial periodic patterns represent a total of k number of partial periodic patterns having the highest minPS value in a database. An efficient depth-first search algorithm, called top-k Partial Periodic Pattern Miner (k-3PMiner), which takes k, and per thresholds as an input was presented to find all desired patterns in a database. Experimental results on synthetic and real-world databases demonstrate that our algorithm is memory and runtime efficient and highly scalable.
Monitoring ACEND KRDNs/CRDNs Using Canvas Learning Management System

Upon completion, participants will be able to identify ways to use Canvas directly out-of-the-box to monitor achievement of individual students' ACEND knowledge and competency standards.
Hardware-Efficient Decomposition of Qudit Gates

prefactor, avoiding the need for numerical optimization. Numerical studies demonstrate that the infidelity of the generated gate sequence $$V_k$$ per Givens rotation $$G$$ scales as approximately $$O(\theta^6)$$. We find numerically that the error on compiled circuits can be made arbitrarily small by breaking each rotation into $$m$$$\theta/m$$ rotations, with the full $$d\times d$$ unitary infidelity scaling as approximately $$O(m^{-4})$$. This represents a significant reduction in the computational effort to compile qudit unitaries either to SNAP and displacement gates or to generate them via direct low-level pulse optimization via optimal control.
Accelerating the Worldwide Adoption of Blockchain Technology

“To understand innovation you should ask "why not?" and not "why?" Selling (blockchain) is a problem and people and companies are blocking adoption which prevents innovation within a company, and stymies costs savings and efficientcy - that is the problem. It's a problem to be stuck in an innovation department - blockchain needs to be used in operations. Scientists and technologists need to understand one another better to create opportunity and success" - Raja Sharif, CEO, ATMPS&#x0D; In 2022, the team at ATMPS launched a potential game changer with a new approach to cell and gene therapy tracking, allowing more streamlined applications, payment options, and opportunity to realize true manufacturing safety and trust at scale, faster for personalized medicines and regimen treatments. The speaker highlights his experiences, and overcomes market challenges empasizing the need for better commercialization strategies for blockchain. In addition, the fllowing topics are addressed in the keynote:&#x0D; &#x0D; Automated Processes&#x0D; Regulatory Visibility &amp; Compliance, FDA 21 CFR , HIPAA, GDPR&#x0D; Putting Together Blockchain Architecture for IRTS &amp; ERH Integration&#x0D; Patient Apps and Mobile Device Issues&#x0D; Supply Chain&#x0D;
Exploring the Impact of YouTube Videos on Improving Listening Skills for EFL Secondary School Students in Sudan

This study was carried out with the participation of forty-seven (47) high school students who were required to take English in order to continue their education at the university level. The participants were asked to respond to a given questionnaire composed from (5) axes, each axis has many items, the target was to explore the effect of watching YouTube on listening skills. Their responses were analyzed statistically, the results showed that some students were aware of the importance of listening skills and few do not have the sufficient perception about how these videos can help them. Their ability to interact with the speaker was showed as one of the most required skills, mastering this skill helps the students to interact with speakers. Students' ability to process information has been boosted by watching YouTube videos, and most will speak up if the presenter requests it, but many still struggle to come up with an appropriate answer to what was said, and many more are unable to adapt to differences in delivery style. We recommend watching the videos in the accompanying table.
How Much Vulnerable is a Cryptocurrency?

The purpose of this paper is to suggest the uses of a simulator to evaluate how vulnerable is a cryptocurrency. It is called “The Cryptocurrency Vulnerability Evaluator (CV-Evaluator)”. The main objective of the CV-Evaluator is to evaluate how vulnerable is a cryptocurrency in case of a deep financial crisis, war, inflation, unemployment, economic desgrowth, corruption, large trade and government deficit, natural disasters, or pandemic. Hence, our final target is to observe WHEN to buy or sell cryptocurrencies (Angel & McCabe, 2015) in the right timing under different circumstances and environments. It is based on the uses of different levels of risk through the visualization of a cube that keep in constant movement and warp stage all the time. Finally, we are using Bitcoin such as an experimental laboratory to test our simulator.
Simulation in Python

This is the last chapter of this book, but an old debate, proprietary software vs open-source software. Most of the engineers of my generation have grown up using MATLAB for their design and simulation tasks. We have become so comfortable with it that we now even think in terms of vectors and matrices. We apply an averaging filter all the time in our daily life, taking out the inherent randomness.
Financing with Crypto Assets

Money appears to cover the deficiencies of barter, and cryptocurrencies appear, as an evolution of money. Entrepreneurs have in cryptocurrencies a new asset to invest their treasury and an alternative means of payment to “fiat” money. Moreover, blockchain technology has multiple applications in the real world that are very useful for the entrepreneur. Security and utility tokens are a new source of financing and a tool to foster relationships with their customers or fans, and NFTs allow a safe and no fake art market.
Moving Target Location Method Based on Machine Vision

Aiming at the defects of existing moving target detection algorithms, a moving target location method based on machine vision is proposed in this paper. Firstly, we adopt a target detection method combining background difference and inter frame difference, and provide the extraction and formal description of moving target features. Then, based on the accurate detection of moving targets in video images, an adaptive Camshift algorithm is designed to establish the tracking target template, and it improves the shortcomings of such algorithm which is sensitive to color and illumination. The experimental results show that the strategy can track moving targets quickly and effectively, and it has good real-time performance.
Research on the construction of log parsing system based on regular expression

With the construction of various information systems and IT equipment, the types and contents of logs generated by systems and equipment are becoming more and more complex. The structures of log data generated by different systems and equipment are different, and most of them are unstructured data, which brings difficulties to log analysis and access. In order to solve the problem of heterogeneous log data identification and parsing, this paper proposes a log data grouping extraction method based on regular expression. This method adopts the strategy of separating log format description from log content parsing, and uses XML language to write script documents for log format description and log data item attribute description, As the log parsing configuration document, the script corresponds to the log type and is separated from the specific parser. Taking Apache log as an example, this paper develops a prototype system. The results show that this method not only has high parsing efficiency, but also improves the flexibility and scalability of log parsing.
Research on Personalized News Recommendation System Based on Collaborative Filtering Algorithm

The news that users are interested in changes over time. The current personalized news recommendation system does not consider the timeliness of news, which affects the recommendation effect. A personalized news recommendation system is designed based on collaborative filtering algorithm. In the hardware part, FPGA is used as the core logic control chip, the crystal oscillator output is directly connected to the global clock pin of FPGA, and the high and low level of output data is determined by the data byte control pin (LB, UB). In the software part, the overall architecture of the system software is designed based on the user log, and the personalized news recommendation model is established based on the collaborative filtering algorithm. The time decay function is introduced into the model to obtain the interest model belonging to each user, and find the news similar to the user’s preferences and push it to the user. The test results show that the recommendation effect of the system is the best when the number of users’ nearest neighbors is 30. The MAE of personalized news recommendation system based on collaborative filtering algorithm is 0.7488, which is 0.0648 and 0.0795 lower than that based on association rules and knowledge map. Therefore, the design system has better recommendation effect.
Research on Accounting Information Credit Risk Measurement System Based on Blockchain

The accounting information credit risk measurement system has the problem of difficult information sharing, resulting in low ROC index. An accounting information credit risk measurement system is designed based on blockchain. The hardware part adds the support of a variety of high-speed interfaces in the module integration, selects the SoC chip as the main control chip of the processor module, and designs the clock circuit to realize the functions of timer and clock output. In the software part, the risk measurement system database is established, and the logarithmic processing method is used to describe the rate of return, so as to provide a data basis for risk measurement. A node uploads data to the network platform, establishes an accounting information credit risk measurement model based on the blockchain, and contracts with information circulate in the block to realize credit risk measurement. The system test results show that the ROC of the accounting information credit risk measurement system based on blockchain is higher than that based on SVM and random forest, and has good default prediction effect.
Testing the API

Testing an API means verifying that it functions as expected by testing its inputs, outputs, and behaviors. This involves making requests to the API using a variety of input values and verifying that the API responds with the expected output.
A Decentralized and Cooperative Methodology For Organ Donation Management Based on Ethereum Blockchain

The digital world is a vast and ever- evolving ecosystem that encompasses a wide range of technologies, applications, and platforms. Blockchain has played a significant role in bringing the healthcare business forward. Blockchain may significantly enhance the traceability, efficiency, and safety of confidential data such as organ donation and transplantation, as well as the administration of electronic health data. This paper presents a secure and efficient web application for organ donation that uses private Ethereum blockchain technology to create a proof of authority (PoA) model for this consortium and also to automate a number of processes, including matching donors and recipients. The fairness of all the entities—patient, donor, hospital, or insurance company—involved in the system is guaranteed without the involvement of a third party. The security and privacy of the patient’s details are protected. The logic of the application is implemented using smart contracts and deployed in Ganache. It depicts various interactions and transactions among the participants, thus helping to automate these processes, promote transparency, improve efficiency, and minimise service time.