Reviewerly/exHarmony huggingface dataset:
An Analysis About Factors for Enhancing, Decreasing, and Retarding Learning Experience Level in Higher Education

This study’s purpose was to clarify methods of effectively promoting student engagement within higher education classes in Japan. To that end, a qualitative survey was performed of university students, based on the concept of learning experience (LX) levels. Via textual analyses of collected data, respective factors were extracted that affect the increase, decline, and stagnation of learning-experience levels. Then, differences between these factors were verified. Consequently, the following were found to have positive effects on increasing learning experience levels: interesting subject, value recognition, sense of progress in learning, clarity of attended classes, class format, and relatedness to the future. Moreover, the following were suggested as positively affecting a decrease of LX level: decline of interest/motivation regarding the subject and the study circumstances of other classes. Also observed as contributing to the stagnation of LX level were a decline of interest/motivation around the subject and study circumstances in other classes.
Science Learners‟ Perspective towards the Use of Module and Social Media as a Tool for Remote Learning

This study aimed to present the perspective of senior high school students towards the use of modules and social media for remote learning and find out if there would be a significant difference in the student performance after the use of modules and social media. The modules were composed of a series of topics distributed to participants and were followed up with the users of social media, especially messenger and Facebook. The participants of the study were classified according to strand and grade levels: the HUMSS and STEM students who are grade 11 and 12 students. A total of 87 students participated in this study. Researchers created 15 items checklist form that is divided according to namely; Perceived Based on Usefulness of Module and Social Media, Perceived Student Self- Efficacy of Using Module and Social media, and Perceived Ease of Use of Module and Social Media was prepared and validated by the experts in subject matter for gathering data. The findings revealed that there was an increase in the performance of students in the pretest and post-test after the use of modules and follow-up through social media. T-test results revealed that there was a significant difference in the test scores of the students before and after using the module which can be used as a future reference for remote learning and as an additional teaching tool in physics.
Chapter 6 Digital tracing, validation, and reporting

Abstract Manual contact tracing has been a key component in controlling the outbreak of the COVID-19 pandemic. The identification and isolation of close contacts of confirmed cases have successfully interrupted transmission chains and reduced the disease spread. Even though manual contact tracing has been widely used, its practice has shown that it is slow and cannot be scaled up once the epidemic grows beyond the early phase. In this case, digital contact tracing can play a significant role in controlling the pandemic. In this chapter, based on our experience and lessons learned from the Smittestopp project, we discuss the main prerequisites for the efficient implementation and validation of digital contact tracing in a population. Specifically, we discuss how to translate a close contact defined for manual tracing to proximity events discovered by a phone, that is, how to define a meaningful risk score and validate the digital contact tracing. We discuss challenges related to each step and provide solutions to some of them, even though questions still remain.
Advanced Machine Learning in Recursive Data-based Modelling

Recursive data-based modelling is needed for making decision online in varying operating conditions.Recursive algorithms are useful in adapting the parameters within selected memory horizons.Abrupt changes can be handled when the situation change is approved to be drastic.The nonlinear scaling based on generalized norms includes additional alternatives: the norm orders adapt to the gradually changing operating conditions.The drastic shape changes of the scaling functions require full analyses of the orders.The orders can also be stored for different situations and re-used later.Fuzzy inequalities are useful in finding out if the feasible ranges of the most recent period are different from the current active ranges or similar with some of previous feasible ranges.Machine learning is integrated in the system in three levels: (1) finding the appropriate time windows, (2) interactions of feasible levels, and (3) finding decision support when some of feasible ranges need to change.These decisions are supported by expert knowledge.Other model parameters can be included in the analysis.The solution has been tested with measurement data from several application cases.The recursive approach is beneficial in the control and maintenance in varying operating conditions.
A STUDY ON LEARNING PLANS OF SENIOR HIGH SCHOOL ENGLISH TEXTBOOKS BASED ON THE BIG CONCEPT-TAKE GETTING ALONG WITH OTHERS AS A CASE STUDY

This study is aimed at researching learning plans of Senior High School English textbooks based on the big concept, promoting the overall English teaching design of Senior High School, and encouraging students to carry out deep study. It mainly uses discourse analysis method for English unit teaching designs, arranges the content of unit teaching reasonably, and promotes the quality of English teaching in high schools through a complete unit theme teaching. This study, by sorting out the connotation, characteristics and relevant literature of big concept, takes Unit 4, Compulsory 1 of New Yilin Senior High School English textbooks as an example to explore the overall teaching design of units pointing to deep study. Findings of the research include: learning plans of Senior High School English textbooks based on the big concept makes English teaching from scattered to interrelated, promoting students’ deep study, and implementing core English literacy; learning plans based on the big concept are quite beneficial to the development of both teachers and students.
THE MEDIATING ROLE OF EXPERIENCE IN THE EFFECT OF EMOTIONAL INTELLIGENCE IN MUSEUMS ON REVISIT INTENTION

This research aims to test whether the museum experience mediates the effect of emotional intelligence and revisit intention.In this context, 373 data were collected from the Batman Archeology Museum between 1 June 2021 and 1 August 2021 with the drop-collect convenience sampling technique.Quantitative research methods were used, and Hayes' Process Macro model was used for mediating effect.As a result, emotional intelligence in museums does not affect revisit intention; it has been determined that the sub-dimensions of emotional intelligence affect the museum experience.Museum experience was also found not to affect revisit intention.On the other hand, it was observed that regulation of emotion had a mediating role in the mediation effect.According to these results, some theoretical and practical implications have been developed.
Improving the Usability of Small Motion Platforms

With the development of VR technology and HMDs, many MPs have been developed. However, in real space, it is sometimes difficult to map the movement of the MP to that in the virtual space. In this study, we examined the feasibility of using an MP based on an electric wheelchair to allow passengers to move freely in a virtual space while providing a less uncomfortable experience. As a result of the experiment, we confirmed the possibility of obtaining the same experience as moving in a large space even in a restricted real space by using continuous rotation.
Communicative Interactions: Analytic Review

For many years, communicative interactions between people have been the subject of conceptual and heuristic consideration in the frameworks of the psychological and social sciences. About ten years ago, the study of communicative interactions began using the methods of experimental neurosciences. Until now research in this area has focused on the accumulation of various phenomenа and the development of methodology. Basic directions and perspectives of communicative interactions research by means of experimental neuroscience methods and mathematical modeling have been considered.
An Enhanced Sine–Cosine Algorithm with Balanced Exploration and Exploitation

Metaheuristic optimization methods should have a balance between exploitation and exploration capabilities. The sine–cosine algorithm for metaheuristic optimization is not tuned for this balance and, hence, performs poorly for efficiency and accuracy. The paper proposes an enhanced variant of the algorithm by introducing three modifications. First, it modifies the classic sine–cosine position update operator to make only exploitation-oriented moves. Second, it adds the ocean current strategy of jellyfish search optimizer for exploration, and third, it adopts a switching strategy to switch an iteration between exploration and exploitation. The proposed variant has been tested on 20 benchmark functions. The results are also statistically validated. Later, the variant has been used to solve the classic 72-bar multi-story truss design problem. All results show improved convergence speed and accuracy of the proposed variant.
Application of artificial intelligence in blockchain technology: A perspective of financial decision making

Blockchain technology has brought a reform in the data industry all over the world. The packet data synchronization within networks is doing wonders these days. Artificial Intelligence on another end has its technological advancement. The latest application of Blockchain and Artificial Intelligence together can help NBFCs and FinTech for better modeling and Financial Decision Making. This research paper throws light on the application of AI &amp; Blockchain in the Finance Industry.
Organizational and Technological Solutions for Managing the Processes of the Certification System

Purpose: A huge amount of factual material has been accumulated in the field of certification: theoretical proposals and practical recommendations have been developed. However, this system was not subject to reform for a long time. Therefore, the studies considered in the work on improving the certification system are relevant, have novelty, contribute to the development of the certification system with the introduction of a method that allows predicting the period between repairs of asphalt concrete pavements based on standard indicators. Aim: on the basis of existing linear and artificial structures, to assess the regulatory impact of the certification system on the quality of structural layers of asphalt concrete. Object: the current certification system and factors affecting the quality of asphalt concrete mixtures and structural pavement layers from them.
New Lattice-Based Short Proxy Signature Scheme With Fewer System Parameters in the Standard Model

Proxy signature schemes safely ensure that an original signer transfers the signing right to a proxy signer, and a variety of these schemes have been developed for secure applications. Constructions of proxy signature schemes vary; recently developed schemes utilize lattices to safeguard against quantum attacks. However, existing lattice-based proxy schemes proved secure in the standard model have many public system parameters, reducing the efficiency of these schemes. To solve this problem, we utilize an admissible hash function with compatible algorithms (AHFwCA) and lattice trapdoors as an initial framework to propose a new lattice-based proxy signature scheme. While maintaining a similar key and signature size as prior schemes, this new proxy signature scheme requires fewer public system parameters. Compared with requiring linear basic matrices as public system parameters found in other standard model schemes, the proposed new scheme depends upon logarithmic basic matrices. Under the standard inhomogeneous short integer solution (ISIS) assumption, we prove that the scheme is existentially unforgeable against chosen message attacks and chosen warrant attacks (EUF-CMA-CWA) in the standard model by using the generalized partitioning proof technique. Thus, this paper partially solves the many parameters problem existed in the standard model lattice-based signature schemes.
Կյանքը՝ QR կոդով կամ կանաչ անձնագրով/Life with QR Codes or a Green Passport

In the current situation, it is imperative to live with COVID-19, which means living with QR codes. After a long period of restrictions, which were fraught with financial consequences, green passports appear as a logical continuation of vaccinations to get out of this situation. Green passports are a purely digital age-appropriate work tool: process management facilitator, coordinator, COVID-19 control tool. The QR code in the green passport is the digital processing of personal information related to COVID-19. However, the implementation of green passports is imperfect in terms of software. Vaccination of vaccines, inequality of vaccines and inaccessibility hinder the full operation of green passports. In particular, in Armenia there is a problem of perception of green passports and QR codes due to inaccessibility of information: inequality. Thus, the use of green passports as a tool to regulate the process will help remove the restrictions and restore normal life. This is evidenced by the experience of countries that have already undergone the process of perceiving green passports, and, as a result, proved to be fully operational.
Physical and Hydro Geochemical Impact Assessment of Inactive Mines in and Around Southwestern Part of Cuddapah Basin Using a Conceptual Site Model (CSM)

Inactive mines have a tremendous influence on the environment and human health, and are frequently the result of a lack of attention and planning. As a result, this report outlines all of the inactive mine site characteristics in terms of physical and chemical consequences, community safety, and human and environmental health threats. To that purpose, this work develops a conceptual site model that may be used to locate, describe, and map inactive mining locations. Inactive mines are creating haphazard dangers to local communities and the environment in the research area, based on site characteristics such as vertical and horizontal openings, toxic impoundments, and steep waste dumps. Water chemistry studies have been undertaken near inactive mines in terms of chemical impact evaluation. Groundwater in the vicinity of inactive mining zones has a high pH and alkalinity, and the dissolved ion concentration (TDS) of 2% is more than the permitted limit, according to the analytical data. Sulfate and chloride are two anions that are within the acceptable range. The nitrate concentrations in the research area ranged from 0.14 to 589 mg/L, and anthropogenic input from inactive mining areas caused 45% of the groundwater samples to exceed the permissible range. As, Ni, Pb, and Sr all have greater heavy metal concentrations than the permissible limit. This suggests that the greater concentration of heavy metals in the research area is due to human input from inactive mine disposal sites. As a result, the rehabilitation program must be carried out in order to eliminate haphazard difficulties in the research region caused by inactive problems.
[Paper] Restoration of JPEG Compressed Image with Narrow Quantization Constraint Set without Parameter Optimization

Various techniques have been proposed for restoring JPEG compressed images degraded with inevitable artifacts. Convex optimization is often used for such techniques, where a prescribed function is minimized over the narrow quantization constraint set (NQCS) characterized by a scaling parameter. Although the scaling parameter significantly affects the restoration quality, the optimal determination of the scaling parameter is actually difficult because it is highly dependent on the target JPEG compressed image. To overcome this difficulty, we propose a novel NQCS-based artifact reduction framework requiring no explicit parameter optimization. In our framework, a set of candidate images is first obtained, whereupon the restored image is computed by applying simple statistical operations for the set. The advantages of our approach are demonstrated by comparing it with several existing approaches in terms of the theoretical error bounds and experimental restoration results.
Investigation of the Application of Nudge Theory in Real World

Under the background of the economic downturn brought by COVID-19 pandemic, the research is carried out after the 2020 COVID-19 pandemic in order to investigate the application of nudge theory, which is the method of changing consumer spending habits through the various method except for legislation and regulation, by analyzing the sales of three different shops after applying nudge theory, aiming to increase their sales revenue.The data of the article would be first-hand data collected by the author from the owners of the shop through face-to-face interviews.The result of the research would help improves the credibility of nudge theory by giving out real-world examples.The study suggests that there is a correlation between the nudge theory shops adapted and the change in sales revenue.
Autonomous English Online Learning System based on Web

With the update and development of the Internet, online English learning has gradually become the mainstream teaching method.At present, the traditional form of teaching has been difficult to meet the needs of modern education, so more and more students begin to use the network environment platform, which is both advanced and common learning methods to meet the needs of the development of modern education.This paper introduces an English online learning system based on Web, and details the design scheme and key technical problems of the system.
Comparing Artificial Intelligence Algorithms in Computer Vision: The Weapon Detection Benchmark

The following work proposes a benchmark of performances of state of art AI algorithms for the weapons detection. Particularly, it is aimed to test three CNN based models on the task of detecting specific types of weapons. In order to accomplish this goal, four datasets are employed. Additionally, due to the lack of rich amounts of well-structured datasets in these field of research, new labeled data are produced as a new resource to test specific hypotheses about their impact on the performances of the models: different transfer-learning approaches are studied to understand how specific types of data could increase the generalization of the trained algorithms, with a peculiar attention to realistic scenarios. The whole work is designed with the intention to select the state-of-art algorithms that truly could be employed for realistic applications.
PRAGMATIC POTENTIAL OF AUDIOGUIDES AS A FEATURE TO BE PRESERVED IN TRANSLATION

The article makes an attempt to analyze multilingual audio guides as a convenient tool for tourism industry and determine their role in presenting the country's image.It describes the evolving tendency, developed in a recent decade, to publish the audio guides online to reach a bigger and more versatile audience.The article also discusses the issue of the pragmatic potential of the text applying it to the content of multilingual audio guides.Additionally, it describes the role that proper translation of audio guides and preserving their original pragmatic influence on the target audience plays in providing foreign tourists with the proper information and reaching the desired communicative effect.The article describes the most important functions of the tourist texts: to inform the readers, to attract them to the specific destination, to portray its authenticity and uniqueness, as well as to induce the tourists to come and experience all the charms of the advertized places in person.In this regard, several excerpts of the texts, taken from the audio guides presented via an izi.TRAVEL platform are analyzed in detail to find out if the pragmatic potential of the original audio guide is preserved and to what extent it is rendered in the target version.The issue of pragmatic adaptation as the way to make the text with a lot of culture-and geography-specific information more understandable and interesting for the multicultural audience is touched upon.Such translation transformations as addition, omission, generalization, sentence fragmentation, etc. were revealed to be utilized as the means of pragmatic adaptation within the translation of tourist audio guides.
SEA-SURFACE SLOW SMALL TARGET DETECTION BASED ON POLARIMETRIC MULTI-DOMAIN FEATURE FUSION

A target detection method based on polarimetric multi-domain feature fusion is proposed in this paper to improve the detection performance of slow small targets on the sea.Firstly, a complex symmetric matrix was established based on the Pauli scattering vector.On the basis of an analysis on the matrix, the Takagi decomposition method was adopted to extract the normalized polarimetric maximum eigenvalue to characterize the echo signal.Secondly, a real symmetric Hurst exponent matrix was constructed by processing the echo signal of the polarimetric radar, and the normalized polarimetric Hurst exponent was extracted by the eigenvalue decomposition method.Thirdly, the normalized polarimetric Doppler peak height was extracted through the Doppler peak height algorithm.Finally, by fusing multi-domain features, a false alarm controllable detector was constructed through the convex hull algorithm.The results of experimental analysis on the measured datasets indicate that when the parameters are the same, compared with the traditional detection methods based on polarimetric features, the proposed method presents better robustness in the case of short observation time and low signal to clutter rate.
Prospects

Abstract The failure of GOFAI created a vacancy for a new guiding philosophy for AI.
Design of Gaze-Based Alarm Acknowledgement by Parameter Characteristics

Alarms in industrial control rooms are defined by their ability to alert an operator of abnormal events that require prompt response. However, when vigilant, operators may anticipate upcoming alarms, rendering those alarms less informative if not a nuisance. Three gaze-based alarm acknowledgement methods were designed by estimating operator awareness based on their eye fixations on the parameter/area of interest and parameter behavior shortly before the alarm. The three designs differed in acknowledging the types of parameter behaviors, which could be: a) near the alarm threshold, b) fluctuating drastically, or c) trending towards an alarm threshold. These three parameter behaviors correlate with increased visual sampling, which suggests higher operator awareness or expectation of alarms. In a simulator study comparing the three gaze-based acknowledgement methods against no gaze acknowledgement, 24 participants completed 24 trials of alarm monitoring task while maintaining a single parameter within a predefined range. Analysis of variance revealed that usability ratings were higher for conditions with than without gaze acknowledgements, demonstrating promise for this alarm management approach.