Reviewerly/exHarmony huggingface dataset:
Intra-session Context-aware Feed Recommendation in Live Systems

Feed recommendation allows users to constantly browse items until feel uninterested and leave the session, which differs from traditional recommendation scenarios. Within a session, user's decision to continue browsing or not substantially affects occurrences of later clicks. However, such type of exposure bias is generally ignored or not explicitly modeled in most feed recommendation studies. In this paper, we model this effect as part of intra-session context, and propose a novel intra-session Context-aware Feed Recommendation (INSCAFER) framework to maximize the total views and total clicks simultaneously. User click and browsing decisions are jointly learned by a multi-task setting, and the intra-session context is encoded by the session-wise exposed item sequence. We deploy our model on Alipay with all key business benchmarks improved. Our method sheds some lights on feed recommendation studies which aim to optimize session-level click and view metrics.
Load Forecasting of Distributed System Host Based on Linear Time Series Model

With the development of communication network, wireless data transmission technology is becoming more and more important in people's daily life.As a new structure, distributed system has strong applicability and adaptability.This paper mainly studies the load forecasting of urban cloud computing platform based on time series model.Firstly, the load forecasting method and principle are introduced.Secondly, according to the actual situation, the appropriate range of random disturbance parameters is determined and a stable and reliable index system is established.Finally, through simulation experiments, the load rate curves of different time resolution and different types of distributed systems under uniform load distribution are verified, and the stability and accuracy are improved by adjusting the load degree.From the test results, it can be seen that the host load prediction results for linear time series have small errors, which indicates that the prediction model has high accuracy.
Fault Tolerant Task Scheduling Algorithm for Distributed System Based on EDF

With the continuous development of social economy, enterprises have higher and higher requirements for production efficiency and product quality.How to complete the task assignment under the basic constraints of ensuring production capacity and low cost is the main problem faced by the manufacturing manufacturing industry.This paper presents a fault-tolerant strategy for distributed systems.Firstly, the paper gives the research background and significance.Secondly, it introduces the layered scheduling model based on EDF and the distributed system with weight weighting designed by particle swarm optimization algorithm.The simulation scheme is tested and analyzed by MATLAB software to verify the results.Finally, it is concluded that the scheme can fully ensure the stability of the scheduling process in the actual working environment.The stall error rate is also guaranteed to be within the range of failure, so it can be widely used in various fields.
Reflections on the Vision of Obiora Ike

In her article, around the vision of Obiora Ike, the author presents how multicultural education is made possible, in a world where, as university education functions as a fantastic bridge builder, it is a good catalyst for social reforms and equality. University is a place for dynamical leadership at all levels and for a peaceful engagement along the advancement of the digital revolution and reliance on information technology.
Natural and <scp>bioinspired</scp> algorithm for future communication networks

Transactions on Emerging Telecommunications TechnologiesVolume 33, Issue 10 e4670 EDITORIAL Natural and bioinspired algorithm for future communication networks Changqiao Xu, Corresponding Author Changqiao Xu [email protected] orcid.org/0000-0003-1467-1086 School of Computer Science, Beijing University of Post and Telecommunication, Beijing, China Correspondence Changqiao Xu, School of Computer Science, Beijing University of Post and Telecommunication, Beijing, China. Email: [email protected]Search for more papers by this authoron behalf of Guest Editors, on behalf of Guest EditorsSearch for more papers by this author Changqiao Xu, Corresponding Author Changqiao Xu [email protected] orcid.org/0000-0003-1467-1086 School of Computer Science, Beijing University of Post and Telecommunication, Beijing, China Correspondence Changqiao Xu, School of Computer Science, Beijing University of Post and Telecommunication, Beijing, China. Email: [email protected]Search for more papers by this authoron behalf of Guest Editors, on behalf of Guest EditorsSearch for more papers by this author First published: 17 October 2022 https://doi.org/10.1002/ett.4670Read 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 No abstract is available for this article. Volume33, Issue10October 2022e4670 RelatedInformation
Personalized Cryptography in Cybersecurity Systems

In this paper will be described a role and possible application of personalized cryptographic solutions in modern cybersecurity systems. Personalized security systems can use selected personal features and allow to create user-oriented security protocols. Such procedures can be applied in broad range of security systems, operating distributed networks and infrastructure. In this paper will be presented selected security methods dedicated to information sharing and hiding in dispersed computing
General scheme for complete high-dimensional Bell state measurement

We theoretically propose a simple and efficient scheme for the complete analysis of high-dimensional Bell states in N dimensions. The mutually orthogonal high-dimensional entangled states can be unambiguously distinguished by obtaining the parity and relative phase information of entanglement independently. Based on this approach, we present the physical realization of photonic four-dimensional Bell state measurement with the current technology. The proposed scheme will be useful for quantum information processing tasks that utilize high-dimensional entanglement.
Implement strategies to mitigate technological security risks

LAS VEGAS — From venue lighting, ticket scanners, and signage to websites, cloud services, social media accounts, and wearable devices, technology has become an increasingly critical component of college athletics operations. And in the push and rush to keep up with the latest technology, the security aspect often takes a backseat to speed. But when it comes to cybersecurity, campus departments really can't afford to cut corners, according to Erik Anderson, Assistant Director of Technical Operations, and Cass Ferguson, Associate Athletic Director for Facilities and Events, both with the University of North Carolina Charlotte Athletics Department. They spoke at the annual convention for the Collegiate Event and Facility Management Association.
Consider recording hate incidents before they escalate to hate crimes

LAS VEGAS — According to data provided by the Federal Bureau of Investigation, hate crimes have been on the rise over the past few years, rising year‐over‐year, in fact — including on college and university campuses.
ACGAN based coverless image steganography method

Aiming at the problems of low load of traditional image steganography, obvious traces of information embedding, and difficulty in carrier selection, this paper proposes a carrier free steganography method based on Auxiliary Classifier Generative Adversarial Network (ACGAN). Based on the generative adversarial network, ACGAN converts the secret information into noise and inputs it into the generator together with the category label to generate a secret image with controllable content, which belongs to the category of vector synthesis and can effectively avoid the threat of steganalysis. At the same time, the image quality and information embedding capacity of the generated dense images are also significantly improved compared with previous methods. We conducted experiments on the MNIST data set. The experimental results show that this method can complete the functions of dense image generation and message extraction. While generating controllable dense images, the accuracy of message recovery has reached 94%. Verification The security advantages and feasibility of the scheme are discussed.
Research on identification of argument relation based on Scibert and Bilstm-CRF

The identification of argument relation is an important subtask of argumentation mining. Its purpose is to identify the support or attack relationship between two argument components, so that people can understand the argument process in the argumentative text more deeply. This paper proposes a research method based on Scibert and BILSTM-CRF model. First, the pre-trained language model Scibert dynamically obtains word vectors, and then combines with the BiLSTM network to fine-tune downstream tasks to obtain contextual information. Finally, the argument relation is identified by conditional random field. Experiments were conducted on two argumentation mining datasets, Persuasive Essays and UKP Sentential Corpus, which were published in Germany. The experimental results show that our method is better than the baseline method.
OpenUNC: Collaborating to Increase the Visibility of Open Scholarship from the UNC System

This conference report covers a lightning talk from the 2022 North Carolina Serials Conference on the topic of OpenUNC, a collaborative website that shares information about and links to open access efforts and content from institutions in the University of North Carolina System. Site background, content, and opportunities for use are covered.
The Study of Socio-Psychological Factors Contributing to and Hindering the Retention of Teachers in the Profession

The profession of a teacher in modern conditions in our country is associated with a number of both positive aspects and professional difficulties. Among the most pressing problems, leading teachers point out: the constant transformation of the education system and the administrative requirements changing in this regard; the contradiction between the preservation of established pedagogical traditions and the need for constant introduction of innovations into pedagogical practice; the overload of reporting documentation, the need for constant personal growth and self-realization in the profession in combination with the threat of emotional burnout and professional deformation, the simultaneous focus of the teacher's activities on the provision of psychological and pedagogical influence on students and on reflection of their professional activities, weak socio-legal protection of the teacher from the arbitrariness of the administration of the educational institution and aggressive actions on the part of students and their parents. To date, the fact of existence and the high degree of severity of the personnel problem are officially recognized, the shortage of teachers, their high degree of overload, including bureaucratic work, the combination of diverse subjects in teaching is openly stated. Based on the above, the purpose of the study is: to analyze the reasons for the departure of teachers from the profession, in order to determine the socio-psychological factors contributing to the retention of teachers in the profession.
Curriculum SIG: LIS Curriculum from Past to Present

The curriculum SIG will examine how the history of curriculum in LIS education impacts the LIS curriculum of today. Dr. Rene Burress, Dr. Xiaofeng Li, and Holly Hebert will share results from their work answering the research question, “How did the LIS curriculum prepare librarians competencies in diversity, equity, and inclusion to address today’s social justice issues in their libraries and communities?” Dr. Suliman Hawamdeh will discuss how revisiting our understanding of data, information and knowledge impacts curriculum development and will shape the future of information and knowledge profession and the development of LIS competency-based curriculum. Dr. Elizabeth Burns will share results of a study that will explore the extent to which LIS programs dedicate attention to diversity, equity, and inclusion in their curriculum. And with the future in mind, Dr. Yong Ju Jung and Dr. Soo Hyeon Kim present thoughtful educational principles and strategies for how to provide the most effective learning experiences for students in online makerspace courses.
Network activity, account takeover and data disruption warrants: how novel law enforcement powers impact media freedom

In 2021, the Australian government enacted the Surveillance Legislation Amendment (Identify and Disrupt) Act 2021 (Cth). This Act introduced three novel law enforcement powers: the Data Disruption Warrant, the Network Activity Warrant, and the Account Takeover Warrant. This article examines how these covert powers could impact on journalists, sources and media organisations—and the implications of this for media freedom in Australia. The article finds that the warrants risk undermining media freedom and go further than previous warrants, giving law enforcement the power to access data on journalists’ computers to specifically reveal the identity of confidential sources; to access the online accounts of journalists and sources without their knowledge to collect evidence; and to modify or delete information held by journalists and sources. The article concludes by making some recommendations for reform so that the warrants pose less of a risk to independent public interest journalism.
Application of Open Science practices for strengthening the National Collection of Nonpathogenic Microorganisms

Microbiology is a branch of biological science that studies microorganisms, most of interest and important are includes in collections for maintenance and distribution. Since biotechnology science goes the requirements to the collections of microorganisms as a reliable and informationally associated biological material also increase. The digitalization, processing and standardization of National Collection of Non-Pathogenic Microorganisms scientific data facilitates their sharing and reuse between science and industry fields. As a project result digital tools of National Collection of Non-Pathogenic Microorganisms information system will be developed, respecting the Open Science practices regarding the management of scientific data.
A Multilayer Framework for Online Metric Learning

Online metric learning (OML) has been widely applied in classification and retrieval. It can automatically learn a suitable metric from data by restricting similar instances to be separated from dissimilar instances with a given margin. However, the existing OML algorithms have limited performance in real-world classifications, especially, when data distributions are complex. To this end, this article proposes a multilayer framework for OML to capture the nonlinear similarities among instances. Different from the traditional OML, which can only learn one metric space, the proposed multilayer OML (MLOML) takes an OML algorithm as a metric layer and learns multiple hierarchical metric spaces, where each metric layer follows a nonlinear layer for the complicated data distribution. Moreover, the forward propagation (FP) strategy and backward propagation (BP) strategy are employed to train the hierarchical metric layers. To build a metric layer of the proposed MLOML, a new Mahalanobis-based OML (MOML) algorithm is presented based on the passive-aggressive strategy and one-pass triplet construction strategy. Furthermore, in a progressively and nonlinearly learning way, MLOML has a stronger learning ability than traditional OML in the case of limited available training data. To make the learning process more explainable and theoretically guaranteed, theoretical analysis is provided. The proposed MLOML enjoys several nice properties, indeed learns a metric progressively, and performs better on the benchmark datasets. Extensive experiments with different settings have been conducted to verify these properties of the proposed MLOML.
47 Gender construction in children’s emotion expressions

Emotion expression helps others understand how one feels. The ability to express one’s emotions appropriately is an important element of a healthy socio-emotional development because it facilitates the establishment of effective social relationships. However, it has been suggested that there are gender differences in children’s emotion expression, which sometimes can create difficulties in social relationships. In this chapter, we present a comprehensive review of the literature on gender differences in children’s expressions of emotions. Findings show that when gender differences are found, they tend to be small, showing girls expressing emotions more frequently than boys. However, we need to be cautious when interpreting these findings because gender differences tend to be mediated by contextual factors, such as age, interpersonal context, culture, language, or task valence, underscoring the relevance of contextual factors in gender differences. This chapter helps our understanding of how girls and boys express their emotions, which in turn might help us to get a better understanding of the underlying mechanisms behind girls’ and boys’ social relationships and how gender construction in emotion expression might develop through childhood and adolescence. Limitations of the existing literature and future directions for research on gender differences in children’s emotion expression are suggested.
A Template-Based Approach to Intelligent Multilingual Corpora Transcription

Emerging linguistic problems are data-driven and multidisciplinary, requiring richly transcribed corpora. Accurate corpus transcription therefore demands intelligent protocols that satisfy the following important criteria: 1) acceptability by end-users, computers/machines; 2) conformity to existing language standards, rules and structures; and 3) representation within the context of the intended language domain. To demonstrate the feasibility of these criteria, a template-based framework for multilingual transcription was proposed and implemented. The first version of the developed transcription tool, also called SCAnnAL (Speech Corpus Annotator for African Languages), applies signal processing to pre-segment waveforms of a recorded speech corpus, into word, syllable and phoneme units, resulting in a pre-segmented TextGrid file with empty labels. Using preformatted templates, the front-end or linguistic aspects/datasets (the text corpus, vowels inventory, consonants inventory, and a set of syllabification rules) are specified in a default language. A Natural Language Understanding (NLU) algorithm then uses these datasets with a data-driven syllabification algorithm to relabel subtrees of the TextGrid file. Tone pattern models were finally constructed from translations of experimental data, using the Ibadan 400 words (a list of basic items of a language), for four Nigerian tone languages. Integration of the tone pattern models into the transcription system is expected in a future paper. This research will benefit emerging digital humanists and computational linguists working on language data, as well as open new opportunities for improved African tone language speech processing systems.
Stance and Engagement Markers in The Jakarta Post's Opinion Articles

A number of research has currently established that written texts represent interactions between writers and readers. A range of linguistic features have been identified as a contribution to the author’s projection of a stance to the material referenced by the text, and, to further extent, the strategies used to presuppose the active role of an addressee. Based on the investigation of ten (10) English written opinion articles published by The Jakarta Post, this study used a qualitative case study approach. This study attempted to address the stance and engagement markers used in the opinion-ed writers page written in English using stance and engagement theory proposed by Hyland (2005) as its framework. This model shows a comprehensive and integrated way of analyzing the means by which interaction is achieved in opinion argument and how the discoursal preferences of disciplinary communities’ construct both writers and readers. Findings show that the interaction is adequately appropriate. The use of stance markers and engagement markers is not necessarily balanced. The study found that the stance markers is used more often than the engagement markers. The writers could have been used more innovatively. The overall findings of the study have both pedagogical and future research implications.
The Impact of E-Learning on Reading Comprehension in High School Students

The purpose of this study was to determine the effect of using e-learning on reading comprehension among high school students in learning English. The quantitative approach used in this study was developed using a quasi-experimental approach. The method used in this study is quasi-experimental. The data analysis technique used in this study is to compare the two groups which are calculated statistically. As a result of the analytical test, the effect of e-learning on reading comprehension of the control group and experimental high school students was recognized at the 5% significance level (0.000 &lt; 0.05). The data shows that reading comprehension increases in the experimental class that applies e-learning. This study concludes that reading comprehension in learning English is better in the experimental group than in the control group. The use of e-learning has a positive influence on reading comprehension for high school students.
OTrecod: An R Package for Data Fusion using Optimal Transportation Theory

The advances of information technologies often confront users with a large amount of data which is essential to integrate easily. In this context, creating a single database from multiple separate data sources can appear as an attractive but complex issue when same information of interest is stored in at least two distinct encodings. In this situation, merging the data sources consists in finding a common recoding scale to fill the incomplete information in a synthetic database. The OTrecod package provides R-users two functions dedicated to solve this recoding problem using optimal transportation theory. Specific arguments of these functions enrich the algorithms by relaxing distributional constraints or adding a regularization term to make the data fusion more flexible. The OTrecod package also provides a set of support functions dedicated to the harmonization of separate data sources, the handling of incomplete information and the selection of matching variables. This paper gives all the keys to quickly understand and master the original algorithms implemented in the OTrecod package, assisting step by step the user in its data fusion project.