Reviewerly/exHarmony huggingface dataset:
Traditional and Mass Open Online Course “Business Communication”: Perspectives for Higher Education

Digitalization transforms business by multiplying the channels of external and internal communication of companies, influencing business communication. Against this background, the study of differences in business communication training in the digital environment and in the audience is relevant. The article presents the results of a comparative study of the course “Business Communication”, implemented in the system of professional higher education and in online learning. At the first stage of the research, a register of the content characteristics of the course was compiled, such as: topics; business communication skills declared for the formation, and the planned results of the training in the traditional and online format. At the second stage, a comparative analysis was carried out according to the parameters identified at the first stage. As a result of the analysis of the content characteristics of the course revealed changes that occurred under the influence of digitalization in the topic of the online course, as well as the specificity of the skills and results of business communication training in the classroom and in the online course. The research allows the teachers of the course “Business Communication” to notice prospects in the development of the discipline.
Pengaruh Model Pembelajaran Kooperatif Tipe Jigsaw Terhadap Meningkatkan Hasil Belajar Siswa di SMA Negeri 1 Biluhu

This research uses a quantitative approach with an ex-post-facto research method. The primary dara obtained were from the distribution of questionnaires and gained 62 respondents as a sample from students in clss XI of Ips SMA Negeri 1 Biluhu in ecomonics subject. Data analysis techniques utilized simple regression analysis and were accompanied by an SPSS application. The results of this study showed that the jigsaw-type cooperative learning model has a positive influence on improving students “learing outcomes in economics subject in class XI of IPS at SMA Negeri 1 Biluhu. Through jigsaw-tipe cooperative learning model, students” learing ability might influence the learning outcomes, besides, leaering ability in economics class had a considerable influence 0f 88,5%, while the remaining 11,5% was influenced by other variables that were not studied.
Research on Decision-Making Strategies of Regional Geography Teaching in High School Based on Data-Driven

With the development of big data technology, it has become a trend to analyze students’ behavioral data to promote teachers’ precision teaching. In this context, this study cooperates with a senior high school geography teacher in Changsha City, Hunan Province, collects the students’ examination data from 2020 to 2021 academic year with the help of Zhixue.com, divides the students into four groups according to the examination results, and takes regional geography knowledge as an example to analyze the weak knowledge points, discipline core literacy and practical application ability of students at all levels. Based on the analysis results, the improvement strategies of teachers’ subsequent precision teaching were proposed, including students’ stratification should be carried out according to daily performance and examination results; The weak knowledge points of students of different grades overlap and differ, so teachers should carry out targeted teaching for students of different grades. At the same time, the multi-level teaching method should be improved to enhance students’ discipline core literacy. Pay attention to contact life reality, enhance students’ practical application ability.
Speckle photography and double aperture speckle interferometry using both sides of a suitably designed hololens imaging configuration

Abstract In the present work, both sides of a suitably designed hololens imaging configuration have been used in laser speckle photography and double aperture speckle interferometry. A speckle photographic technique has been used to measure in-plane displacement, and a double aperture speckle interferometric technique has been used to measure in-plane displacement component.
Energy-Based Cross Attention for Bayesian Context Update in Text-to-Image Diffusion Models

Despite the remarkable performance of text-to-image diffusion models in image generation tasks, recent studies have raised the issue that generated images sometimes cannot capture the intended semantic contents of the text prompts, which phenomenon is often called semantic misalignment. To address this, here we present a novel energy-based model (EBM) framework for adaptive context control by modeling the posterior of context vectors. Specifically, we first formulate EBMs of latent image representations and text embeddings in each cross-attention layer of the denoising autoencoder. Then, we obtain the gradient of the log posterior of context vectors, which can be updated and transferred to the subsequent cross-attention layer, thereby implicitly minimizing a nested hierarchy of energy functions. Our latent EBMs further allow zero-shot compositional generation as a linear combination of cross-attention outputs from different contexts. Using extensive experiments, we demonstrate that the proposed method is highly effective in handling various image generation tasks, including multi-concept generation, text-guided image inpainting, and real and synthetic image editing. Code: https://github.com/EnergyAttention/Energy-Based-CrossAttention.
STUDY OF REGRESSION MODELS WITHOUT A FREE TERM

Purpose. The aim of the article is to use the analogue of the coefficient of determination of multiple regression for a classical regression model without a free term and constructing the appropriate Fisher and Student statistics for econometric analysis. Methodology of research. Methods of general scientific and empirical techniques based on a systemic approach were used in the process of research. In addition, the following methods of scientific knowledge were used to solve the tasks: methods of analysis and observation - to identify the main social factors influencing the level of crime; methods of matrix theory, theory of probabilities and mathematical statistics - for checking the laws of distribution of random variables, building criteria for the significance of the regression equation and its coefficients. Findings. It was studied how the absence of a free term in multiple linear regression affects the Student and Fisher statistics when studying the significance of regression coefficients and the regression equation as a whole, respectively. The obtained results indicate that the introduced definitions affect the adjusted coefficient of multiple regression and the F-statistic, but do not change the standard error of the regression, including the Student's statistics. The need to calculate qualitative indicators of regression models in accordance with derived formulas and algorithms, and to be critical of the final numerical results obtained when using computer statistical packages, is substantiated. Originality. A comprehensive study of linear regression models was conducted, which takes into account the effect of the absence of a free term when evaluating the quality of empirical models. Practical value. The obtained research results allow avoiding calculation errors and acceptance of implausible conclusions, which occur in the practice of qualitative analysis of linear regression models without a free term. Key words: multiple regression model, free term, method of least squares, Student's test, Fisher's test.
SISTEM INFORMASI DATA ALUMNI DI SMAN 1 BENGKULU SELATAN BERBASIS WEB

ABSTRACT :This study time to design a Web-Based Alumni Data Information System needed at Sman 1 South Bengkulu. The data collection technique of study used questionnaire, interview and documentation. The document can be in the form of writing, pictures, or monumental works of someone. The system development of this study used the waterfall method. The collecting of alumni data was still classified as manual by using archives that is still difficult to update alumni data. Therefore, to facilitate information from alumni, a web-based alumni data information system was designed at State Senior High School 1 South Bengkulu by using Xampp, Mysql and PHP programming languages. The research location was at State Senior High School1 South Bengkulu. The results of the research show that the alumni data information system at State High School 1 South Bengkulu is easier to be found particularly about updating the alumni data information system of State Senior High School 1 South Bengkulu.&#x0D; Keywords: Web-Based System, Alumni Data, Waterfall, Information System.
A Method for Popularizing and Using Unified Information System

With the gradual deepening of information construction, a lot of information systems have been built at the government level in our country. Due to the inconsistency of system use demand and construction promotion mode, many government built information systems can not fully play their role. This paper puts forward a method of promoting, using and iterating based on the construction unit, organization and management unit and technical unit. According to the construction and promotion of the current unified construction system in China, the method in this paper clearly divides the participants according to their responsibilities. The method mentioned in this paper combines every link in the process of system popularization and use, and has the value of guiding the construction in detail. Each link in the promotion process is deepened layer by layer, and the responsibilities of the participants are clear. By using this method, it can effectively guide relevant departments to carry out information construction, and ensure that the unified information system plays the expected role and achieves the expected goals. The effective mobilization of all departments to participate in the system promotion and use stage can ensure that the system is truly used by all parties after the promotion, and play the role of informatization in promoting business work. The promotion and use of different links are advanced, new and robust, providing an effective promotion mode for the national information system.
Home-Office During COVID-19 Pandemic in Brazil: Perceived Influences on Performance and Competency Management

There has never been so much flexibility and organizational capacity to adjust to the effects of the COVID-19 pandemic on work. This article examines beliefs and perceptions related to new arrangements imposed by compulsory telework on skills and performance management practices, as well as identifying related advantages and disadvantages associated. This paper draws on 17 in-depth interviews using the collaborative interactive action research method. The authors study how leaders acted in multiple ways, aiming to reduce the negative effects on workers and work design and provide greater balance of actions. The perspective of multiple levels of action was adopted, considering human and social behavior and organizational arrangements made at a macro level. The sense of collectivity and the search for the standardization of routines were privileged in the interpretation of the answers. The main results reflect the influence of compulsory telework to performance factors, essential competencies required, and the main advantages and disadvantages associated to the construct. This study is relevant for organization studies, especially in the kinds of organizational contexts where there is still unpreparedness to deal with the effects of the pandemic or have uncoordinated telework practices.
Virtual Reality, Augmented Reality, and Video Games as Important Factors in Health and Education

Some areas of priority attention in Mexico are health and education, which open an opportunity for technology, specifically this chapter presents different projects that use augmented reality (AR), virtual reality (VR), or video games (VG), which provide an excellent contribution to education and the health for its dynamism and interactivity, these projects were developed in the faculty of basic sciences, engineering, and technology (FCBIyT). The projects presented for medicine using AR are Arachnophobia, TEAPRENDE, and SARA (food labeling), AVHI: Non-Hodkin Lymphoma uses VR, and Byoky, a video game. The projects developed for education with AR are LenSeñasMx and Industrial Revolution, the projects that uses VR are the diasporas of Tlaxcala, technological advances by James Watt and the building of a giant virtual computer with this multi-screen environment. Video games for education are Independence of Mexico and the diasporas of Tlaxcala too.
Persian Semantic Role Labeling Using Transfer Learning and BERT-Based Models

Semantic role labeling (SRL) is the process of detecting the predicate-argument structure of each predicate in a sentence. SRL plays a crucial role as a pre-processing step in many NLP applications such as topic and concept extraction, question answering, summarization, machine translation, sentiment analysis, and text mining. Recently, in many languages, unified SRL dragged lots of attention due to its outstanding performance, which is the result of overcoming the error propagation problem. However, regarding the Persian language, all previous works have focused on traditional methods of SRL leading to a drop in accuracy and imposing expensive feature extraction steps in terms of financial resources, time and energy consumption. In this work, we present an end-to-end SRL method that not only eliminates the need for feature extraction but also outperforms existing methods in facing new samples in practical situations. The proposed method does not employ any auxiliary features and shows more than 16 (83.16) percent improvement in accuracy against previous methods in similar circumstances.
Dual-view Correlation Hybrid Attention Network for Robust Holistic Mammogram Classification

Mammogram image is important for breast cancer screening, and typically obtained in a dual-view form, i.e., cranio-caudal (CC) and mediolateral oblique (MLO), to provide complementary information. However, previous methods mostly learn features from the two views independently, which violates the clinical knowledge and ignores the importance of dual-view correlation. In this paper, we propose a dual-view correlation hybrid attention network (DCHA-Net) for robust holistic mammogram classification. Specifically, DCHA-Net is carefully designed to extract and reinvent deep features for the two views, and meanwhile to maximize the underlying correlations between them. A hybrid attention module, consisting of local relation and non-local attention blocks, is proposed to alleviate the spatial misalignment of the paired views in the correlation maximization. A dual-view correlation loss is introduced to maximize the feature similarity between corresponding strip-like regions with equal distance to the chest wall, motivated by the fact that their features represent the same breast tissues, and thus should be highly-correlated. Experimental results on two public datasets, i.e., INbreast and CBIS-DDSM, demonstrate that DCHA-Net can well preserve and maximize feature correlations across views, and thus outperforms the state-of-the-arts for classifying a whole mammogram as malignant or not.
Rehearsal-Free Online Continual Learning for Automatic Speech Recognition

Fine-tuning an Automatic Speech Recognition (ASR) model to new domains results in degradation on original domains, referred to as Catastrophic Forgetting (CF). Continual Learning (CL) attempts to train ASR models without suffering from CF. While in ASR, offline CL is usually considered, online CL is a more realistic but also more challenging scenario where the model, unlike in offline CL, does not know when a task boundary occurs. Rehearsal-based methods, which store previously seen utterances in a memory, are often considered for online CL, in ASR and other research domains. However, recent research has shown that weight averaging is an effective method for offline CL in ASR. Based on this result, we propose, in this paper, a rehearsal-free method applicable for online CL. Our method outperforms all baselines, including rehearsal-based methods, in two experiments. Our method is a next step towards general CL for ASR, which should enable CL in all scenarios with few if any constraints.
Pseudo Session-Based Recommendation with Hierarchical Embedding and Session Attributes

Recently, electronic commerce (EC) websites have been unable to provide an identification number (user ID) for each transaction data entry because of privacy issues. Because most recommendation methods assume that all data are assigned a user ID, they cannot be applied to the data without user IDs. Recently, session-based recommendation (SBR) based on session information, which is short-term behavioral information of users, has been studied. A general SBR uses only information about the item of interest to make a recommendation (e.g., item ID for an EC site). Particularly in the case of EC sites, the data recorded include the name of the item being purchased, the price of the item, the category hierarchy, and the gender and region of the user. In this study, we define a pseudo--session for the purchase history data of an EC site without user IDs and session IDs. Finally, we propose an SBR with a co-guided heterogeneous hypergraph and globalgraph network plus, called CoHHGN+. The results show that our CoHHGN+ can recommend items with higher performance than other methods.
Listening and Rhythmic Cadence in Online Musical Collaborations

Since 2020, ISSUE has had a focused response to the crisis of humanity brought about by the global COVID-19 pandemic.A polyptych of four volumes was organised.Viral Mobilities (Vol.09,2020) focused on the Anthropocene as a "virus-vectorised community and economy." This was followed by two unique volumes dedicated to art and performance.Tropical Lab (Vol.10,2021) studied the impact of the pandemic on artist residencies and mobilities with a close study of Tropical Lab-an international art camp.Arrhythmia (Special Volume, 2022) looked at the impact and potentiality of isolation and determination, and severe implications for performance-making and embodied communal and social practices.Vol.11 of ISSUE, themed Emergency forms the fourth dimension of the polyptych.As a contemporary idea, an emergency is primarily borne out by sudden medicalised ruptures to the human body, severe political fractures to the body politic of society, and regular breaks to temporally attend to matters with a sense of immediacy and urgency.These ritualised signifiers form the basis on which one can help ascertain the current station of society.Humanity currently faces a pandemic, eviscerated by an increasingly simultaneous flow of newer emergencies from new and renewed diseases, ritualised lockdowns, political and memory wars, identity and equity battles, food security and supply chain blockages, climate changes, rise in the cost of living, etc.Etymologically, words such as merge, emerge, emergence, emergency, immerse and submerge draw their primordial reference from classical Latin's êmergere (to rise, bring to light).To bring to light (as Zaki Razak's essay in this volume alludes) is an integral, if not existential, consideration for artistic practices.Through careful enquiriesscanned through past and current environments-art has been a beacon to proffer ways of re-thinking the world.However, with the increasingly shrinking mind-space in an information and social medialed world, artistic considerations are crowded with an urgent need to respond to everyday concerns besides pandemics, new nationalisms or environmental concerns.
The essence and functions of cryptocurrencies

With the development of electronic systems, ideas have repeatedly arisen to create an electronic analogue of cash for remote payment. Cryptocurrency technology was originally aimed at the absence of a trusted node - one whose actions are guaranteed to be true and who can confirm the correctness of other people's operations. For the first time, this problem was solved in the Bitcoin system due to the artificial complication of making changes to the transaction history register.
A Privacy-Preserving Online Deep Learning Algorithm Based on Differential Privacy

Deep Reinforcement Learning (DRL) combines the perceptual capabilities of deep learning with the decision-making capabilities of Reinforcement Learning RL, which can achieve enhanced decision-making. However, the environmental state data contains the privacy of the users. There exists consequently a potential risk of environmental state information being leaked during RL training. Some data desensitization and anonymization technologies are currently being used to protect data privacy. There may still be a risk of privacy disclosure with these desensitization techniques. Meanwhile, policymakers need the environmental state to make decisions, which will cause the disclosure of raw environmental data. To address the privacy issues in DRL, we propose a differential privacy-based online DRL algorithm. The algorithm will add Gaussian noise to the gradients of the deep network according to the privacy budget. More important, we prove tighter bounds for the privacy budget. Furthermore, we train an autocoder to protect the raw environmental state data. In this work, we prove the privacy budget formulation for differential privacy-based online deep RL. Experiments show that the proposed algorithm can improve privacy protection while still having relatively excellent decisionmaking performance.
Virtualization of educational environments for international collaboration: students as builders of their own learning

The incorporation of communication and information technology (ICT) has been a permanent theme in the most recent decades, generating an intense debate about its implications and efficiency, the possibilities to integrate more effectively educational proposals, among other aspects. However, to think in a compulsory use of technologies as the only way to pursue studies was unthinkable. Even though multimodal education models and diverse experiences in e-learning already existed, at the beginning of 2020, the COVID-19 pandemic triggered a crisis due to the impediment of carrying out face-to-face activities in the classrooms around the world. Considering all the emerging situations due the pandemic, the spirit of this article is to share, three years after, the vision of some Mexican students, participants, and ex-participants in virtual and on-line experiences from public universities, regarding mediatized education, and how they consider their learnings in this regard.
Constant Memory Attention Block

Modern foundation model architectures rely on attention mechanisms to effectively capture context. However, these methods require linear or quadratic memory in terms of the number of inputs/datapoints, limiting their applicability in low-compute domains. In this work, we propose Constant Memory Attention Block (CMAB), a novel general-purpose attention block that computes its output in constant memory and performs updates in constant computation. Highlighting CMABs efficacy, we introduce methods for Neural Processes and Temporal Point Processes. Empirically, we show our proposed methods achieve results competitive with state-of-the-art while being significantly more memory efficient.