Reviewerly/exHarmony huggingface dataset:
A Majorization-Minimization Approach for Image Smoothing with the Edge-Stopping Functions

Edge-aware image smoothing plays an essential role in various computer vision and graphics applications. In this paper, we propose an effective and flexible majorization-minimization (MM) approach for edge-preserving image smoothing based on the edge-stopping functions. With given edge-stopping functions, our theoretical results show that the differences between neighboring pixels in homogeneous regions of the output smoothing image are smaller than a small threshold, while they are larger than a large threshold at edges. We give the implementation process of the MM algorithm for solving the image smoothing problem in detail and discuss the convergence of the MM algorithm. Comprehensive experimental results in various practical applications are conducted to demonstrate the effectiveness and flexibility of the proposed approach in both subjective and objective evaluations.
Computing Bounds for Imprecise Continuous-Time Markov Chains Using Normal Cones

The theory of imprecise Markov chains has achieved significant progress in recent years. Its applicability, however, is still very much limited, due in large part to the lack of efficient computational methods for calculating higher dimensional models. The high computational complexity shows itself especially in the calculation of the imprecise version of the Kolmogorov backward equation.
Linearity and Time Invariance

We have left the two most important properties of systems—the properties which we will use to define the set of systems which will be our focus throughout this course for last. These properties are Linearity and Time Invariance.
Effective deep learning through bidirectional reading on masked language model

Google BERT is a neural network that is good at natural language processing. It has two major strategies. One is “Masked Language Model” to clear the word-level relationships, and the other is “Next Sentence Prediction” to clear sentence-level relationships. In the Masked Language Model, with the task of masking some words in sentences, BERT learns to predict the original word from context. Some questions come to mind. Why BERT achieves effective learning by reading in two ways from fore and back? What is the difference between the bidirectional reading? In the Masked Language Model with the task of masking some words, the middle sentence is “I ate [mask] every morning”. First, predict the masked word by forward reading. The previous sentence is “Considering my health, I decided to change the breakfast menu”. What is asked in general? We usually think about which is more realistic and reach “an apple”. The answer is “feasibility”.Next, predict the masked word by backward reading, focusing on the middle sentence and the post sentence “A month later, I lost 3 kg and became healthy.” What is asked in general? In such a situation, we are looking for success factors. We usually think about which is more relevant and reach “an apple”. The answer is causality. Therefore, BERT is learning to predict feasibility by forward reading and causality by backward reading.Besides, the bidirectional reading technique can be applied to scenario planning using back-casting from the future. Scenario planning is making assumptions on what the future is going to be. A scenario can be described in two ways, one is fore-casting and the other is back-casting. Fore-casting means viewing from the present to the future. In general, back-casting means viewing from the present to the past. But in this paper, it means viewing from the future to the present. Just as there are two different predictions for bidirectional reading, there is a big difference between fore-casting into the future and back-casting from the future. How do you feel about the first scenario using fore-casting? You tend to focus on feasibility. Therefore, a long debate starts about the feasibility, such as “Is it possible?”, “Is it difficult?”, and “How to achieve?”.On the other hand, how do you feel about the second scenario using back-casting from the future to the present? This scenario has to be written in past mode because of back-casting. If it is written in past mode, you feel it has done and someone has resolved all the problems by that time. The surrounding words in past mode change your feeling from prediction to event context. You tend to focus on causal factors of success. You can escape from the long debate.Scenario planning using back-casting from the future to the present makes a good proposition, except for long discussions. Besides, in terms of the mystery of deep learning, each answer lies in human thinking mechanism because AI is created by imitating the human brain.
Automated Analysis of Student Verbalizations in Online Learning Environments

Online learning has become desirable for many students. In the U.S., more than one-third of all enrolled students participate in at least one online course []. The most effective online learning environments allow students to work at their own pace, from any location, at any time, and to receive automated feedback. In light of these benefits and the likely protracted impact of the current public health crisis, the trend toward online learning is likely to increase.
Mengintegrasikan Metode Collaborative dan Discovery: Cara Baru dalam Pengajaran Bahasa

This study is conceptual research. It outlines the integration of collaborative model and discovery methods in language teaching. This concept has an advantage that it stimulates students to construct new knowledge through a collaborative and explorative way. This study discusses about the model of collaborative discovery method in which this model involves students to explore the knowledge both individually and in groups. The collaboration of individual and group study will encourage students’ active participation in learning. The model of collaborative discovery method becomes an ideal choice in language teaching.
Real-time Attention Span Tracking in Online Education

E-learning has changed how students grow over the past ten years by allowing them access to high-quality education whenever and wherever they need it. In any case, understudies frequently get occupied in light of different reasons, which influence the learning ability by and large. Numerous experts have been striving to address the nature of online education, but we really need a comprehensive solution to this problem. This essay aims to present a method for monitoring students' continuing attention during online classes using the surveillance camera and oral input. We investigate different picture handling strategies and AI calculations all through this review. We suggest a framework that makes use of five specific non-verbal cues to calculate an understudy's consideration score during computer-based tasks and generate continual feedback for both the association and the understudy. The output can be used as a heuristic to investigate both the speakers' and understudy' general methods of exhibiting themselves
Learning Meta Word Embeddings by Unsupervised Weighted Concatenation of Source Embeddings

Given multiple source word embeddings learnt using diverse algorithms and lexical resources, meta word embedding learning methods attempt to learn more accurate and wide-coverage word embeddings. Prior work on meta-embedding has repeatedly discovered that simple vector concatenation of the source embeddings to be a competitive baseline. However, it remains unclear as to why and when simple vector concatenation can produce accurate meta-embeddings. We show that weighted concatenation can be seen as a spectrum matching operation between each source embedding and the meta-embedding, minimising the pairwise inner-product loss. Following this theoretical analysis, we propose two \emph{unsupervised} methods to learn the optimal concatenation weights for creating meta-embeddings from a given set of source embeddings. Experimental results on multiple benchmark datasets show that the proposed weighted concatenated meta-embedding methods outperform previously proposed meta-embedding learning methods.
A Few Seconds Can Change Everything: Fast Decision-based Attacks against DNNs

Previous researches have demonstrated deep learning models' vulnerabilities to decision-based adversarial attacks, which craft adversarial examples based solely on information from output decisions (top-1 labels). However, existing decision-based attacks have two major limitations, i.e., expensive query cost and being easy to detect. To bridge the gap and enlarge real threats to commercial applications, we propose a novel and efficient decision-based attack against black-box models, dubbed FastDrop, which only requires a few queries and work well under strong defenses. The crux of the innovation is that, unlike existing adversarial attacks that rely on gradient estimation and additive noise, FastDrop generates adversarial examples by dropping information in the frequency domain. Extensive experiments on three datasets demonstrate that FastDrop can escape the detection of the state-of-the-art (SOTA) black-box defenses and reduce the number of queries by 13~133× under the same level of perturbations compared with the SOTA attacks. FastDrop only needs 10~20 queries to conduct an attack against various black-box models within 1s. Besides, on commercial vision APIs provided by Baidu and Tencent, FastDrop achieves an attack success rate (ASR) of 100% with 10 queries on average, which poses a real and severe threat to real-world applications.
On the algebraic immunity of multiplexer Boolean functions

Abstract A multiplexer generator is a device that accepts two or more inputs and based on some logic sends one of them as output. In a special case when inputs to a multiplexer generator are <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:msup> <m:mrow> <m:mn>2</m:mn> </m:mrow> <m:mrow> <m:mi>k</m:mi> </m:mrow> </m:msup> </m:math> {2}^{k} bits and one of them is selected according to the value of a <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mi>k</m:mi> </m:math> k -bit number, a multiplexer generator can be regarded as a Boolean function in <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:msup> <m:mrow> <m:mn>2</m:mn> </m:mrow> <m:mrow> <m:mi>k</m:mi> </m:mrow> </m:msup> <m:mo>+</m:mo> <m:mi>k</m:mi> </m:math> {2}^{k}+k variables. We call this generator a multiplexer Boolean function. Boolean functions serve as combiners and filters in cryptographic designs. The study of their cryptographic strength attracts the cryptographer because of the extremely simple and cost effective of their design. The study of algebraic attacks on multiplexer generators is another major concern to judging the suitability for its use in cryptographic designs. In this article, we calculate the algebraic immunity of the multiplexer Boolean function, which is not an obvious task in the case of a Boolean function like a multiplexer generator.
Exploration on the Reform of Urban Management Course System for the Cultivation of Innovation and Entrepreneurship Ability

<p style="text-align: justify;"><span style="font-size:16px;font-family: 'Times New Roman','serif'">In recent years, innovation and entrepreneurship education has been deepening reforms, and urban management professions have been continuously improved. However, due to the large number of rural population and social resources flowing to cities, urban residents' lifestyles and business ideas have undergone new changes and new requirements. The municipal construction, cultural facilities, commercial scale, and property management have all experienced great development, which requires the development of corresponding first-line innovative management talents. Based on the characteristics of urban management, this paper analyzes the necessity of the reform of professional curriculum system under the guidance of “innovation and entrepreneurship”, sorts out the problems and causes in the current urban management professional curriculum system, and explores the urban management professional curriculum for the cultivation of innovative entrepreneurship. The idea of system construction is to guide and boost the teaching of urban management in colleges and universities.</span>
Cloud Platform Assists Construction of Ecological Environment for Vocal Music Teaching in Colleges and Universities from Sustainable Perspective

<p style="text-align: justify;"><span style="font-size:16px;font-family: 'Times New Roman','serif'">Higher education is entering a new historical stage, and improving the quality of talent training is the primary issue. Curriculum is an important carrier for colleges and universities to implement the function of "cultivating people by virtue", and the reform and innovation of the curriculum system is an important foundation for realizing the quality of talent training. This article uses research methods of literature and logical deduction to analyze the problems existing in the reform of physical education curriculum in ordinary colleges and universities, and puts forward the basic concepts and strategies of physical education reform in ordinary colleges and universities under the background of the development of the times, which is beneficial to improve the physical quality of college students, psychological quality and social adaptability, and cultivate high-quality applied talents for social development needs.</span>
Tempo: Excursions in 21st Century Italian Poetry ed. by Luca Paci

Reviewed by: Tempo: Excursions in 21st Century Italian Poetry ed. by Luca Paci Daniel Rabuzzi Tempo: Excursions in 21st Century Italian Poetry Ed. Luca Paci Trans. Various. Cardigan, Wales. Parthian. 2022. 308 pages. TEMPO: Excursions in 21st Century Italian Poetry is an excellent bilingual survey of current Italian poetry's diversity and dynamism. Editor Luca Paci (co-director of the Italian Cultural Centre Wales) has selected 106 pieces by twenty-two poets (born between 1941 and 1994), most published since 2000, and translated by twenty-eight translators, most of whom are themselves poets. Tempo highlights three characteristics of Italian poetry today: unencumbered acknowledgment of the past; invention; and growing inclusiveness. Unsurprisingly, Italy's long and varied histories surface in many of the poems selected by Paci—but as points of departure or touchstones, not as anchors. Poems refer to Aeneas, the gods of antiquity, Varro, [End Page 68] Galla Placidia, and the Mons Capitolinus, but also (sometimes in the same poem) to Juventus, Fiumicino Airport, the Bologna Massacre of 1980, Miami Vice, and the Dow Jones. Traditional modes and forms are represented without being taxidermied. For instance, poems by Milo De Angelis are models of elegiac lyricism, combining universals of grief and loss with specifics of Milan's Lambrate neighborhood; the translations by Patrizio Ceccagnoli and Susan Stewart are models of balanced restraint. Patrizia Valduga writes sonnets that Geoffrey Brock renders with equivalent nerviness while replicating the rhyme scheme. Many others deploy new forms, such as the slam-born, performance-oriented poetry of Lello Voce (translated by Susanna Maggioni), Mariangela Gualtieri (Anthony Molino, Olivia E. Sears, Cristina Viti), and Rosaria Lo Russo (Serena Todesco, William Wall). Another species altogether, Marco Giovenale's rarefied, laconic pieces play with possibilities of asemic expression (translated by Linh Dinh, Jennifer Scappettone, and Giovenale himself). Tempo takes a wide view, including a poem in Sardinian by Antonella Anedda, translated by Jamie McKendrick, and poems by Fabio Franzin (translated by Cristina Viti) in Veneto-Treviso dialect. Shirin Ramzanali Fazel's originally self-published poems are a highlight of the collection. She wrote them in English, interspersed with Somali and Arabic, and then translated them herself into Italian. However, Tempo would have benefited from an even wider view: only four of the poets selected were born south of Rome, and the anthology lacks poems focused on the Mezzogiorno, let alone in Sicilian or any of the southern dialects. Regardless, Paci has done a great service: Tempo will be a welcome addition to the bookshelves of anglophones whose knowledge of Italian poetry has not been updated beyond Ungaretti, Montale, Pasolini, and other giants of the last century. Daniel Rabuzzi New York Copyright © 2022 World Literature Today and the Board of Regents of the University of Oklahoma
Multi-Level Analysis of Factors Influencing Teacher Efficacy

Objectives The purpose of this study was to analyze the level of teachers and schools for teacher efficacy using the muti-level analysis method. Methods In this study, elementary school data from the Korea Educational Development Institute's ‘School Education Status and Level Analysis Study 2014’ were used. A two-stage multi-level analysis was conducted on 250 school questionnaires and 6,060 teacher questionnaires in the data. Results First, In teacher background factors, it was found that position, homeroom teacher status, gender, educational background, and career had a positive effect on teacher efficacy. Second, In school background factors, it was found that the ratio of the budget for basic educational activities had a positive effect on teacher efficacy. Third, In teacher process factors, it was found that the degree of reflection of school education goals, the degree of participation in internal and external learning group of education, and spending time in class for teaching, the number of open classes, and preparing time for teaching had a positive effect on teacher efficiency. Fourth, in the school process factors, positive perceptions of fellow teachers, the degree of meetings for educational activities, the degree of cooperation with fellow teachers, and the degree of professional conversation with colleagues had a positive effect on teacher efficiency. However, it was found that the principal's interest in teacher participation had a negative effect. Conclusions These research results can provide implications for what efforts schools should make to improve teacher efficacy. Various efforts in schools will contribute to the improvement of teaching and changes in schools.&#x0D;
Hyperparameter tuning in echo state networks

Echo State Networks represent a type of recurrent neural network with a large randomly generated reservoir and a small number of readout connections trained via linear regression. The most common topology of the reservoir is a fully connected network of up to thousands of neurons. Over the years, researchers have introduced a variety of alternative reservoir topologies, such as a circular network or a linear path of connections. When comparing the performance of different topologies or other architectural changes, it is necessary to tune the hyperparameters for each of the topologies separately since their properties may significantly differ. The hyperparameter tuning is usually carried out manually by selecting the best performing set of parameters from a sparse grid of predefined combinations. Unfortunately, this approach may lead to underperforming configurations, especially for sensitive topologies. We propose an alternative approach of hyperparameter tuning based on the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). Using this approach, we have improved multiple topology comparison results by orders of magnitude suggesting that topology alone does not play as important role as properly tuned hyperparameters.
Construction of Cultural Soft Power Evaluation Index Education System Policy Based On AHP

Aiming at the low evaluation confidence of the traditional cultural soft power evaluation index system, a new cultural soft power evaluation index system is constructed based on AHP. This paper discusses the connotation and constituent elements of cultural soft power, designs a comprehensive evaluation index system of cultural soft power from the five aspects of cultural cohesion, cultural security, cultural productivity, cultural attraction and cultural influence, and calculates the weight of each index by using AHP analytic hierarchy process, It can be used as a reference for the theoretical research and practical operation of cultural soft power. The experimental results show that the evaluation confidence of the experimental group is significantly higher than that of the control group, which can solve the problem of low evaluation confidence of the traditional cultural soft power evaluation index system. The Bay area economy is the most significant model of current coastal economy, which has been effectively adopted across the globe. Similar natural circumstances and processes have led to several successful models, each with its own unique set of blueprints and philosophies. China's 13th Five-Year Economic and Social Development Plan identifies the Greater Bay Area as consisting of two special administrative areas and nine cities in Guangdong. It serves as both the precursor of China's reform and opening up and the growing pole for economic development in 2016.
A Study on the Legal Implications of the New Article 34-8 of the Higher Education Act to Resolve Education Inequality

This study aims to examine the new laws to provide equal opportunities for education to the people who want to receive education by applying the principle of differential compensation differentially applied to the selection of college students. The Constitution of the Republic of Korea stipulates that all citizens have the right to receive education equally according to their abilities, and the Framework Act on Education also stipulates that they are not discriminated against in education due to social status, economic status, or physical conditions. Nevertheless, social mobility is retreating due to polarization in Korean society, and the function of the class ladder in education is gradually weakening. Accordingly, universities have established a new law to provide more than a certain percentage of opportunities to apply for social consideration prescribed by Presidential Decree, such as basic living recipients, and to expand regional balanced development by more than a certain percentage. This social integration screening legislation is a measure to strengthen the public nature and social responsibility of universities, and as the amendment to the Enforcement Decree of the Higher Education Act was deliberated and resolved at the State Council on February 22, 2022. The revision of the enforcement ordinance is expected to expand opportunities for higher education for economically and socially vulnerable students who have been relatively difficult to enter college.&#x0D;
The Effect of Cloud-Based Supply Chain Integration and Information Security Initiatives on Supply Chain Robustness and Performance

The purpose of this research is to examine the relationship among cloud-based supply chain integration, information security initiatives, supply chain robustness and supply chain performance. This research gathered from 132 respondents, professional workers of seven telecommunication service provider companies in Indonesia located in the capital city of Jakarta. The study used an online questionnaire with a Likert scale of 1-5. PLS-SEM method is used to test relationship between variables with SmartPLS software version 3.0. The results show that cloud-based supply chain integration and information security initiatives have a positive and significant effect on supply chain robustness, supply chain robustness also has a positive and significant effect on the supply chain performance. In addition, cloud-based supply chain integration and security initiatives have a positive and significant impact on supply chain performance through the mediation of supply chain robustness. This research shows that companies can take opportunities to improve supply chains through the application of cloud technology in supply system integration, but still need to improve supply information security initiative in order to create a robust supply chain against various threats, disruptions, and disasters.