Reviewerly/exHarmony huggingface dataset:
New directions in writing research, instruction and learning

LiteracyVolume 57, Issue 3 p. 352-352 Editorial New directions in writing research, instruction and learning Ross Young, Ross Young University of Edinburgh The Writing for Pleasure CentreSearch for more papers by this authorDouglas Kaufman, Douglas Kaufman University of ConnecticutSearch for more papers by this authorFelicity Ferguson, Felicity Ferguson The Writing for Pleasure CentreSearch for more papers by this author Ross Young, Ross Young University of Edinburgh The Writing for Pleasure CentreSearch for more papers by this authorDouglas Kaufman, Douglas Kaufman University of ConnecticutSearch for more papers by this authorFelicity Ferguson, Felicity Ferguson The Writing for Pleasure CentreSearch for more papers by this author First published: 27 September 2023 https://doi.org/10.1111/lit.12351Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume57, Issue3September 2023Pages 352-352 RelatedInformation
What Money Can Do: Examining the Effects of Rewards on Online Romance Fraudsters' Deceptive Strategies

With the advent of the internet, romance fraud â or instances wherein individuals use fake identities and sham romantic relationships to defraud others â has moved online. Victims of this crime experience harms to their financial, social, and personal well-being. While researchers have made strides in exploring this crime from the perspective of victims, little research has investigated it using data drawn from the persons committing the crime. Moreover, little is known about how these offenders may alter their strategies in response to variations in perceived reward. In this study, we explore these processes utilizing data collected via a series of sequential e-mail exchanges with 94 online romance fraudsters. More specifically, we investigate the deception strategies used by these fraudsters and examine whether and how these strategies shift in response to changes in the prospect of receiving financial reward from a victim. Our results add to current understanding of online romance fraud and have implications for theories of interpersonal deception and rational choice.
A Primer on Anomaly and Fraud Detection in Blockchain Networks

A Primer on Anomaly and Fraud Detection in Blockchain Networksby Osterrieder, Joerg, Chan, Stephen, Chu, Jeffrey, and Zhang, YuanyuanHide DescriptionPublished on Jan 04, 2023papers.ssrn.comDescriptionBlockchain technology is a distributed ledger system that allows multiple parties to record and verify transactions in a secure and transparent manner. However, blockchain networks are vulnerable to anomalies and frauds that can have serious consequences for the integrity and security of these networks. In this primer, we provide an overview of the definition and properties of blockchain technology, and discuss the types and examples of anomalies and frauds that occur in these networks. We also examine the techniques and technologies that are used to detect and prevent these attacks, including statistical approaches, machine learning approaches, game-theoretic approaches, digital forensics, reputation-based systems, and risk assessment systems. We present case studies of anomaly and fraud detection in real-world blockchain networks, and discuss the lessons learned from these cases and their implications for future research and practice. We also identify emerging trends and challenges in the field, and discuss potential future research directions and technologies. This primer is intended as a resource for practitioners and researchers in the field of anomaly and fraud detection in blockchain networks, and aims to provide a technical and comprehensive overview of this growing and important field.
COMMUNICATIONS AND DIGITAL TWINS

This article discusses various types of modeling and the concept of "digital twin", as well as concepts and examples of their implementation. It is noted that computer modeling allows not only to obtain a forecast, but also to determine which control actions on the system will lead to a favorable development of events between the components of the model, which are a reflection of real relationships. Modern production processes are very complex and distributed in space and time. Therefore, models of such processes should take into account the distributed nature of the modeling objects. An analysis of the interaction of the digital model with the simulation object representing the real process is also carried out. It is shown that the interaction occurs through interfaces that provide interface between the model and the simulation object. A cross-domain model for managing telecommunications functions is considered. As an example of digital twins using time series models, a model of time delay in a telecommunications network is considered. This model is used to control the buffering system in networks for the transmission of streaming video traffic.
Exploration and Practice of Learning-centered Blended Teaching Reform

Classroom teaching is the core link of talent training and the basic guarantee to improve the quality of talent training. Learning-centered, elaborately designing the teaching process based on outcome based education, reconstructing the teaching resources, and establishing a multi-dimensional personalized assessment and evaluation mechanism can effectively change the phenomenon of "teachers are full and students listen passively", guide students to actively participate in the learning process, promote the cultivation of students' innovative and critical thinking, and encourage students to study independently, learn with interest and learn efficiently.
Evaluation on the Prospects of School Enterprise Cooperation and the Integration of Industry and Education in Vocational Education in the 5G Era

Talents are the primary resource for the progress of a country and a nation. In the context of the fifth generation mobile communication technology, cultivating high-quality and innovative technical talents is a new task entrusted to vocational colleges by the times. However, many colleges currently lack a mechanism for student employment orientation and ability cultivation, and the cooperation between schools and enterprises is not deep enough, resulting in a disconnect between the cultivation of applied talents in schools and social needs. This article analyzes the problems arising from the cooperation between vocational colleges and enterprises based on the background of the 5G era, and proposes optimization strategies from various aspects such as policies, industry enterprises, and vocational colleges themselves, so as to closely combine industry and teaching and facilitate vocational education to better meet the market demand. By designing comparative experiments, the traditional teaching settings was compared with the way of integrating production and teaching. It was proved that the employment rate of students under the two-way mode of enterprise and education increased by about 11.35%, and enterprises were also more satisfied with this new talent cultivation mode, greatly increasing their enthusiasm for participating in practical teaching and driving the reform and innovation of vocational education. School enterprise cooperation is beneficial for school to increase student employment rates and promote the transformation of talents into skilled ones. Vocational education under the help of 5G must be service-oriented, adhere to the establishment of professional industries, strengthen practical teaching, and create specialized talents urgently needed by the industry and satisfied by all parties to achieve a “win-win situation”.
IDENTIFYING FRAUD IN ONLINE TRANSACTIONS

Fraudulent credit card transactions must be when customers are charged for items that they did not purchase. Such problems can be tackled with Data Science and its importance, along with Machine Learning, cannot be overstated. This project intends to illustrate the modelling of a data set using machine learning with Identifying Fraud in Online Transactions. The Identifying Fraud in Online Transactions problem includes modelling past credit card transactions with the data of the ones that turned out to be a fraud. This model is then used to recognize whether a new transaction is fraudulent or not. Our objective here is to detect 99.99% of the fraudulent transactions while minimizing the incorrect fraud classifications. Identifying Fraud in Online Transactions is a typical sample of classification. In this process, we have focused on analyzing and pre-processing data sets by using a Random Forest Algorithm.
Surveying the Social Comfort of Body, Device, and Environment-Based Augmented Reality Interactions in Confined Passenger Spaces Using Mixed Reality Composite Videos

Augmented Reality (AR) headsets could significantly improve the passenger experience, freeing users from the restrictions of physical smartphones, tablets and seatback displays. However, the confined space of public transport and the varying proximity to other passengers may restrict what interaction techniques are deemed socially acceptable for AR users - particularly considering current reliance on mid-air interactions in consumer headsets. We contribute and utilize a novel approach to social acceptability video surveys, employing mixed reality composited videos to present a real user performing interactions across different virtual transport environments. This approach allows for controlled evaluation of perceived social acceptability whilst freeing researchers to present interactions in any simulated context. Our resulting survey (N=131) explores the social comfort of body, device, and environment-based interactions across seven transit seating arrangements. We reflect on the advantages of discreet inputs over mid-air and the unique challenges of face-to-face seating for passenger AR.
Social APF-RL: Safe Mapless Navigation in Unknown &amp; Human-Populated Environments

Safe mapless navigation of mobile robots in unknown and human-populated areas is integral for increasing their usage in our daily lives. In this paper, we consider how such a behavior can be exhibited by a mobile robot and introduce Social APF-RL (Artificial Potential Functions with Reinforcement Learning). Social APF-RL extends our previously presented approach APF-RL in which the strengths of artificial potential functions (APF) with deep reinforcement learning are combined so that the robot learns how to adjust the input parameters of the APF controller. With Social APF-RL, the model is extended to accommodate the presence of humans and to respect their comfort zones while navigating. Our experimental results including both simulation and real-life scenarios demonstrate that differing from the classical navigation methods or social navigation methods, the robot can navigate successfully on its own even in complex scenarios with moving entities while maintaining social distance to humans encountered. Hence, it has better applicability in real-life scenarios. For future work, we plan to use the proposed approach in human following while adhering to social distance norms.
Translation Processing Model of Complex Long Sentences Based on Feature Extraction Algorithm

With the development of information technology, patents or long sentences of science and technology with huge vocabulary and complex structure have widely appeared in people's daily work. This kind of long sentence often contains several clauses and non-predicate verb phrases, and these clauses and phrases often restrict and depend on each other, thus forming a complex language phenomenon in which there are phrases in clauses and clauses in phrases. This kind of long sentence plays a great role in the logic and rigor of English itself, but it brings considerable difficulties to machine translation. In order to solve this problem, this paper proposes a multilingual and general algorithm for complex long sentence translation based on multi-strategy analysis. The algorithm uses a combination of case-based pattern matching and rule analysis to comprehensively utilize a variety of relevant language features in the source language sentences, including grammatical semantic features, sentence length, punctuation marks Functional words and contextual conditions are used to simplify the segmentation of complex long sentences and compound the translation.
Optimal Recursive Reature Selection Method Based on Random Forest

To reduce the complexity of the model in feature selection and improve the classification accuracy to make feature selection more effective. In this paper, an optimal recursive feature selection method based on random forest is proposed. Multiple decision trees are constructed from random forest on the primed dataset, but the problem of overfitting occurs in the process of constructing decision trees, so search cross-validation is used to enhance the accuracy and credibility of the evaluation model. Meanwhile, the optimal recursive feature selection is obtained by the fuzzy information entropy method to eliminate noise. Cross-validation comparison is performed by dividing the training set 75% used for training and constructing the model to select the optimal parameters; the test set 25% used for testing the model to validate the assessment model. Finally, the validity of the model is verified by applying the example data of an undergraduate education index, and the feature indexes with importance greater than 0.01 are obtained by the importance calculation.
Two New Classes of (Almost) Perfect c-Nonlinear Permutations

In this short note, we present two classes of (almost) perfect [Formula: see text]-nonlinear permutations over finite fields of even characteristic.
English Teachers' Perception towards Using ICTs in ELT in Secondary Schools of Bhojpur Municipality: A Census Study

This study attempts to investigate English teachers' perception towards using ICTs in English language teaching in Secondary Schools of Bhojpur Municipality. The Census method was adopted to obtain the objectives. Likert-scale survey questionnaires and non-participation observations were adopted as the techniques and tools of data collection to answer the research questions. The result of the study exhibits that the integration of ICTS in teaching English enhances the learning of the English language. The idea of using ICTs such as YouTube videos improves the listening and speaking skills of the English language of both teachers and students. In addition, the majority of English language teachers have a positive attitude towards the use of ICTS in English language teaching. Most of the teachers had positive perceptions towards the use of ICTs in helping students to master their grammatical competence.
The Impact of Management Information Systems on Strategic Success: A Field Study in Islamic Banks Operating in Aden, Yemen

The study aimed to identify the impact of management information systems in its four dimensions (human resources, material resources, software, information security) on the strategic success in its three dimensions (survival, growth, adaptation) in Yemeni Islamic banks operating in the city of Aden (Tadhamon International Bank, Saba Islamic Bank, CAC Islamic Bank). The study adopted the descriptive analytical approach, and the study population consisted of the administrative leaders working in those banks, and their number was (56). The study used the questionnaire as a tool (f)or data collection, and it employed the statistical program (SPSS) for data analysis. The study reached a number of conclusions, the most important of which are: In general, there is an impact of management information systems on the strategic success, and there is an impact for each of the four dimensions of management information systems (human resources, material resources, software, information security) on the strategic success of the banks in the study population. The level of management information systems in banks provides the study population with a very high level on the variable itself and at the level of dimensions such as (physical resources, software, information security). Further, there is an impact of management information systems on strategic system at a high-level of a dimension such as (human resources). There is also an impact with regard to dimensions such as (growth, adaptation) and a very high level of impact on a dimension such as (survival). The study recommended that banks should make use of strengths, addressing points of weaknesses, seizing opportunities, and overcoming threats in order to achieve their objectives. It also suggested conducting another scientific study on the impact of management information systems in strategic control in other dimensions of management information systems and this can be determined according to the specialized functions of banks.
Building Multiple Classifier Systems Using Linear Combinations of Reduced Graphs

Abstract Despite great efforts done in research in the last decades, the classification of general graphs, i.e., graphs with unconstrained labeling and structure, remains a challenging task. Due to the inherent relational structure of graphs it is difficult, or even impossible, to apply standard pattern recognition methods to graphs to achieve high recognition accuracies. Common methods to solve the non-trivial problem of graph classification employ graph matching in conjunction with a distance-based classifier or a kernel machine. In the present paper, we address the specific task of graph classification by means of a novel framework that uses information acquired from a broad range of reduced graph subspaces. Our novel approach can be roughly divided into three successive steps. In the first step, differently reduced graphs are created out of the original graphs relying on node centrality measures. In the second step, we compute the graph edit distance between each reduced graph and all the other graphs of the corresponding graph subspace. Finally, we linearly combine the distances in the third step and feed them into a distance-based classifier to obtain the final classification result. On six graph data sets, we empirically confirm that the proposed multiple classifier system directly benefits from the combined distances computed in the various graph subspaces.
INOVAÇÕES TECNOLÓGICAS NO CUIDADO EM FERIDAS E CURATIVOS

The area of care for patients with wounds requires constant training and updating of scientific knowledge from nursing professionals, given the dynamic transformations in the sector with the recurrent introduction, validation or testing of technologies and forms of care. The success of care in the treatment of wounds is related to the balance of the joint application of these technologies, as these are essential for the full recovery of the clientele, and it is essential that there is no overvaluation of hard and light-hard technologies in relation to light ones.
Reklam Metni Yazımında Yapay Zekâ İnsana Karşı

This research was conducted to compare the effectiveness of human-generated advertisement text and artificial intelligence (AI)-generated advertisement texts. In this context, data were collected by applying a questionnaire to 208 university students using convenience sampling method. In the questionnaire form, consumer involvement and purchase intention scales were included. Two advertising texts produced by AI and the text used in the original advertisement of the company were presented to the participants. They were asked to answer the scale statements for each ad text. Regression analysis was applied on the collected data. According to the results of the analysis, the most effective ad text on the participants is the ad text printed on ChatGPT, even if with a small difference. As a result, AIs have shown close to human-like success in ad text writing despite using limited data. It is thought that the use of AI in ad text writing will bring efficiency and productivity to the sector.
Digital Innovation in Assessment During Lockdown: Perspectives of Higher Education Teachers in Portugal

During the COVID-19 pandemic, lockdown policies forced higher education teachers to adopt remote teaching. This disruptive situation challenged teachers to continue delivering classes and carrying out assessment online. In order to investigate higher education teachers’ perceptions about the online assessment, a survey was conducted in Portugal. The study focuses on digital tools and methodologies used in online assessment, first-time digital tools used, and the tools and methodologies that teachers intend to maintain in face-to-face assessment, as well as confidence in students’ results. Data was collected online from May to July 2021. Participants (n = 868) were from all fields of science and technology. Most of them (80%) reported the use of new assessment tools and methodologies during this period. The majority (72%) has confidence in the results obtained by the students. However, some of them (36%) reported academic fraud situations. Digital tools related to summative assessment are the most prevalent, but methodologies related to formative assessment were also used. Some teachers (49%) intend to use methodologies and tools in face-to-face classes used for the first-time during the lockdown.
TSCA on Students' Attitude toward Writing in Blended Learning of College English

English writing is an important output skill developed in college English programs. Most colleges and universities do not offer a separate college English writing course and have little time for classroom writing instruction. To cope with the solution of this dilemma, the Production Oriented Approach (POA) mentions Teacher-Student Collaborative Assessment (TSCA) which creates a new form of assessment. Through TSCA, teachers can not only ease the heavy teaching load, but also fully tap the network resources to efficiently use students' time before, during and after class to maximize and optimize the teaching effect. In this paper, the teaching concept of "TSCA" is used to conduct writing teaching experiments, to study and analyze students' attitudes towards effective writing, so as to provide inspiration for the practice of English writing teaching.
Inserting Local Wisdom In English Material: Strategies and Benefits

This study aims to describe the strategies and benefits of incorporating local cultural values in English language teaching. The type of research used is library research. Data was collected through reference collection from journals, articles, or books related to local culture in teaching. The analysis shows that the use of local cultural values is able to build student awareness of culture, encourage students to love the uniqueness and value of their culture, and improve their understanding of English material. The strategies that English teachers can apply when teaching using local culture are through materials related to products or objects typical of a region, such as using pictures or photos, conducting discussions, making video projects, practicing conversations, group learning, and making podcasts. Furthermore, the benefits that occur when including local wisdom in English teaching include increasing socio-cultural awareness, making students more aware of their culture and familiar materials, developing students' character, improving students' language skills, and increasing tolerance and mutual respect. To be successful in teaching English through local culture, teachers need to design and emphasize learning materials and activities using local culture so that students are more aware of the uniqueness of their culture.