Reviewerly/exHarmony huggingface dataset:
Feature Extraction and Analysis of Speech Signal Based on Fractional Fourier Transform

The extraction of speech features is the basis of speech signal processing, and the extraction of speech features is to obtain the parameters representing speech signals through the analysis of speech signals.The shape information of the signal can be extracted and processed by selecting appropriate structural elements and adopting mathematical morphological transformation.Selecting different structural elements will result in different shape transformation results, thus extracting the shape information of different components.In this paper, the feature extraction and analysis of speech signals are further studied based on FRFT (fractional fourier transform).The simulation results show that in different noise environments, such as when the speech is bathed with signal-to-noise ratio of 0dB and 10dB respectively, the recognition rate of this method is higher than that of the traditional parametric method.In this paper, based on the strength of FRFT signal components, the component signals are detected one by one in order, and then according to the detection results, the strongest component signals are removed from the observed signals in order to reduce their influence on the weak component signals, thus improving the effectiveness and reliability of multi-component signal detection and parameter estimation.
Correction for a camera-projector 3D reconstruction system based on dithering fringe pattern

The binary defocusing technique is widely used for high-speed three-dimension (3D) reconstruction.However, the system distortion directly influences the reconstruction quality, and most of the previous works are only for the traditional digital fringe projection (DFP) technique.Based on the problems above, this paper first analyzes the distortion for the input-output response of the system and the influence of space luminance distribution uniformity of the projector, in the binary defocusing technique.Then, a novel method combining initial correction and iterative correction is proposed to obtain accurate sinusoidal fringe patterns.Finally, the experimental results show that the proposed method can correct sinusoidal fringe phase error in binary defocusing technique significantly and improve the quality of 3D reconstruction effectively.
An Adaptive Average Grasshopper Optimization Algorithm for Solving Numerical Optimization Problems

The grasshopper optimization algorithm (GOA), inspired by the behavior of grasshopper swarms, has proven efficient in solving globally constrained optimization problems. However, the original GOA exhibits some shortcomings in that its original linear convergence parameter causes the exploration and exploitation processes to be unbalanced, leading to a slow convergence speed and a tendency to fall into a local optimum trap. This study proposes an adaptive average GOA (AAGOA) with a nonlinear convergence parameter that can improve optimization performance by overcoming the shortcomings of the original GOA. To evaluate the optimization capability of the proposed AAGOA, the algorithm was tested on the CEC2021 benchmark set, and its performance was compared to that of the original GOA. According to the analysis of the results, AAGOA is ranked first in the Friedman ranking test and can produce better optimization results compared to its counterparts.
Transformer-Based Relational Inference Network for Complex Visual Relational Reasoning

Visual Relational Reasoning is the basis of many vision-and-language based tasks (e.g., visual question answering and referring expression comprehension). In this article, we regard the complex referring expression comprehension (c-REF) task as the reasoning basis, in which c-REF seeks to localise a target object in an image guided by a complex query. Such queries often contain complex logic and thus impose two critical challenges for reasoning: (i) Comprehending the complex queries is difficult since these queries usually refer to multiple objects and their relationships; (ii) Reasoning among multiple objects guided by the queries and then localising the target correctly are non-trivial. To address the above challenges, we propose a Transformer-based Relational Inference Network (Trans-RINet). Specifically, to comprehend the queries, we mimic the language-comprehending mechanism of humans, and devise a language decomposition module to decompose the queries into four types, i.e., basic attributes, absolute location, visual relationship and relative location. We further devise four modules to address the corresponding information. In each module, we consider the intra-(i.e., between the objects) and inter-modality relationships(i.e., between the queries and objects) to improve the reasoning ability. Moreover, we construct a relational graph to represent the objects and their relationships, and devise a multi-step reasoning method to progressively understand the complex logic. Since each type of the queries is closely related, we let each module interact with each other before making a decision. Extensive experiments on the CLEVR-Ref+, Ref-Reasoning, and CLEVR-CoGenT datasets demonstrate the superior reasoning performance of our Trans-RINet.
Double-Layer Search and Adaptive Pooling Fusion for Reference-Based Image Super-Resolution

Reference-based image super-resolution (RefSR) aims to reconstruct high-resolution (HR) images from low-resolution (LR) images by introducing HR reference images. The key step of RefSR is to transfer reference features to LR features. However, existing methods still lack an efficient transfer mechanism, resulting in blurry details in the generated image. In this article, we propose a double-layer search module and an adaptive pooling fusion module group for reference-based image super-resolution, called DLASR. Based on the re-search strategy, the double-layer search module can produce an accurate index map and score map. These two maps are used to filter out accurate reference features, which greatly increases the efficiency of feature transfer in the later stage. Through two continuous feature-enhancement steps, the adaptive pooling fusion module group can transfer more valuable reference features to the corresponding LR features. In addition, a structure reconstruction module is proposed to recover the geometric information of the images, which further improves the visual quality of the generated image. We conduct comparative experiments on a variety of datasets, and the results prove that DLASR achieves significant improvements over other state-of-the-art methods, in terms of quantitative accuracy and qualitative visual effect. The code is available at https://github.com/clttyou/DLASR.
Ciberacoso: una problemática emergente en el contexto escolar. Estudio muestral en octavos básicos

This is a quantitative research whose purpose is to analyze the problem of cyberbullying in eighth grade students of two educational establishments in the commune of Los Angeles in the province of Biobío, one of which is located in the urban sector and the other in the rural sector, the latter, specifically, in the Santa Fe sector. In order to analyze this problem, a survey will be conducted to obtain the students' perspective and familiarization with the topic to be investigated. On the other hand, concepts, characteristics and effects of the different modalities that this new form of virtual aggression can adopt will be analyzed. In this way, the effect of this phenomenon on students will be determined, as well as the influence of social networks on the types of human relationships and the protocols proposed by the establishments to face this situation will be identified. Similarly, the percentage of cyberbullying detected in this study varies with respect to that observed nationwide, which is indicated by the statistics. Likewise, the possible existing differences between the establishments in the indicated subject, according to their idiosyncratic characteristics.
Real-Time Vision-Based Sign Language Bilateral Communication Device for Signers and Non-Signers using Convolutional Neural Network

The use of sign language is an important means of communication for individuals with hearing and speech impairments, but communication barriers can still arise due to differences in grammatical rules across different sign languages. In an effort to address these barriers, this study aimed to develop a real-time two-way communication device that uses image processing and recognition systems to translate two-handed Filipino Sign Language (FSL) gestures and facial expressions into speech; the system can recognize gestures that correspond to specific words and phrases. Specifically, the researchers utilized Convolutional Neural Networks (CNNs) to enhance the processing speed and accuracy of the device. The system also includes a speech-to-text (STT) feature that helps non-signers communicate with deaf individuals without relying on an interpreter. The study's results showed that the device achieved a 93% accuracy rate in recognizing facial expressions and FSL gestures using CNN, indicating that it is highly accurate. Additionally, the system performed in real-time, with an overall average conversion time of 1.84 and 2.74 seconds for sign language to speech and speech to text, respectively. Finally, the device was well-received by both signers and non-signers, with a total approval rating of 85.50% from participants at Manila High School, suggesting that it effectively facilitates two-way communication and has the potential to break down communication barriers.
Digital tildes (“∼”) may convey more: analyzing innovative uses of tildes in Chinese WeChat messages

Abstract Innovative uses of punctuation in online communication have become increasingly visible in research and public awareness since the 2000s, whereas studies on the innovative use of tildes (“∼”) in digital use remain scarce. Drawing on a data set of 543 Chinese WeChat messages with sentence-final tildes, this article investigates the uses and functions of innovative tildes in online communication using quantitative data and follow-up interviews. The findings suggest that: (1) The innovative tildes are deployed in messages implying sounds and performing speech acts in online communication, and they are more frequently used in speech acts (e.g., expressives and directives in particular). (2) The innovative tildes convey sound extension, i.e., to compensate for the loss of audio information in online communication and reproduce elongated sounds; pragmatic function, i.e., to enhance or mitigate the illocutionary forces of speech acts; and entertaining function, i.e., to make messages informal, vivid, joyful, and interesting. (3) The innovative tildes are pragmalicalized as a result of their semiotic features and politeness motivation of messengers for maintaining rapport and achieving successful online communication.
Design and Implementation of a Chatbot for the Supervision of Security Events (SIEM)

Companies around the world are the first targets of cybercriminals, because the end product of their attacks is much more lucrative than that of targeted attacks against individuals.As a result, businesses have much greater and more stringent cyber security needs.Moreover, losses in cases of compromise can be evaluated in terms of tens of millions of CFA francs, which makes it a prime target for cybercriminals.Generally, in companies, all the intervention capacities are put into play through an Information System Security team in order to meet the maximum-security needs of its information system.This team is often responsible for the SOC (Security Operation Centre), i.e., the supervision of the security of the information system of a structure through tools of collection, correlation of events and remote intervention.The main mission of the SOC is to identify, analyse and ameliorate cyber security incidents.To assist this team in the continuous management of security and to improve the response time to various security incidents, we designed and implemented a conversational agent for security event monitoring using the ELK Stack SIEM tool.As a result, we obtained a conversational agent that is able to identify and analyse security incidents and events of the company's information system, centralize and have a global view of the security status of all monitored devices, create personalized and adequate rules that can detect flaws in the system, provide reports on security incidents and events through voice exchanges.This will allow the SOC to fulfil the first two terms of its main mission, i.e. the identification and analysis of incidents in order to be able to react more quickly and efficiently to them, thus fulfilling the third and last term of its main mission, remediation.
Nomadic Models of Postmodern Aesthetics: Soteriological Choice of the Teacher

Aim. The aim of the article is to define the concept of aesthetic competence of the nomad teacher of postmodern era based on a comparative analysis of two aesthetic models (metis paraesthetics and soteriological aesthetics). Methods. The subject of study is anthropotemporal methodology of acquiring aesthetic competence as an act of spiritual transformation (approaches, paradigm, priorities, criteria of effectiveness). The analysis of the stages of nomad’s dianoic choice in the process of understanding beauty as a boon was carried out using the method of epistemological design, according to which emotions function cognitively in aesthetic experience. The technology of spiritual self-coaching was chosen to activate all the structural components of aesthetic competence – the intention to correct aesthetic apperception and the competencies of emotional-reflective, value-semantic, aesthetic and worldview revaluation. Results. The implementation of the chosen technology opened up the possibility of reorientation for the nomad teacher: from the drive of the performer-trickster to a humble and grateful anticipation of the beauty as transcendent – to overcoming the power of inertia of previous dependence, responses to the calls of a pure (still “adventurous”) mind. A cluster analysis of the results of the completed tasks was carried out for the regression description of the efficiency of the technology. Conclusion. The soteriological concept of the aesthetic competence of the nomad teacher focuses attention on the essential coexistence of the teacher with students throughout the entire process of his self-determination. The practical experience of its implementation can make a positive contribution to reforming postmodern aesthetic education.
Investigation on Picture Books Reading Education in Primary School &amp;lt;br/&amp;gt;—Taking H Province for Example

Picture book reading facilitates the acquisition of reading literacy.How picture books are used in primary school education and whether picture book reading foster students' learning ability are the two questions to be discussed in the passage.According to the investigation, lack of time, difficult in choosing picture books and the renovation of teaching methods are the main problems exist.In order to promote the reading literacy: teachers should categorize picture books or stories with the same or similar topics, grammar, words and sentence structure in their ordinary teaching; Teachers or parents should know a general form of asking questions to enhance the effect of students' in picture book reading and improve students' reading literacy.
Impacto de un programa de intervención para promover la competencia digital del futuro docente: un estudio de caso

Digitally competent population increase is fundamental to promote inclusive and sustainable social development. Offering training that makes it possible must be a priority that the University must address urgently, especially the faculties of education, since its graduates will be in charge of training students of all stages and contexts. Research that illustrates how to approach this training is scarce and, although the design of conceptual models such as The European Framework for the Digital Competence of Educators DigCompEdu (Redecker, 2017) is a great step, it is necessary to carry out studies that accompany it with a pedagogy proposal that makes it possible to implement. For this, it is important to implement intervention programs and analyse its impact on initial teacher training, this being the objective of this research article; specifically, through a mixed exploratory study of repeated measures. After the intervention, the results show a statistically significant increase in the digital competence of the subjects, especially in the competence area of ​​DigCompEdu: pedagogical competences of educators.
Course construction and practice of water pollution control engineering in the background of carbon neutralization

Today, with the rapid development of the world economy, we have also made great achievements in the process of building a green ecological civilization.However, in this process, resources and environmental issues have attracted more and more attention.In recent years, problems such as haze and water pollution often occur.The growth rate of GDP has always maintained at about 10%, while China's resource reserves are relatively small and the per capita share is low.With the growth of China's economy, society and population, and the improvement of people's awareness of environmental protection, green GDP has gradually become an important indicator to measure a country's scientific and technological progress and national strength.This paper discusses the content reform and teaching practice of the water pollution control engineering course of environmental engineering specialty under the background of carbon neutralization.New concepts and new processes of sewage treatment are introduced into the teaching, so that students can establish new concepts of sewage treatment process design, make students clear the development trend of the sewage treatment industry in the future, master the new technology of sewage treatment, broaden their industrial vision, and cultivate their innovative consciousness, To enable students to have enough competitiveness and development potential in graduation employment and future professional work.
Online-based English Reading Learning Model in the New Normal Era (Post-Pandemic Covid-19)

This article is part of research entitled "Online-based Student English Learning Models in Facing Curriculum Changes in the New Normal Era." This research was conducted to see and identify online-based reading learning models for students. The research method is a descriptive qualitative method using a questionnaire and the final assignment of the Project course (Lesson Plan and Instruction). The number of samples used was 52 students who took the Project course (Lesson Plan and Instruction). Of the 52 students, 7 students chose to teach the reading skill. Data analysis includes observation, open coding, and axial coding. The results reveal that the media used by students in learning reading skills is divided into online media 57.14% (4 students) and 42.85% offline (3 students) in learning reading skills. Applications used by students in learning reading are divided into Zoom, face-to-face/ offline, Quizzes, PPT, and YouTube. The learning methods that students apply in learning reading are Communicative Language Teaching (14.28%), Guided Discovery Learning (14.28%), Audio Lingual Method (14.28%), Suggestopedia (14.28%), Discovery Learning (14.28%), Total Physical Response (14.28%) and Community Language Learning (14.28%). The topics presented included: Comparison; Narrative text; Personal Letters; Description, and Notice.
Fixed points of a family of mappings and equivalent characterizations

In the present paper we prove a fixed point theorem for a one parameter family of contractive self-mappings, of a complete metric space or a complete b-metric space, each member of which has a unique fixed point that is also the unique common fixed point of the family; the mappings may be continuous or discontinuous at the fixed point. We also prove that under the assumption of a weaker form of continuity the fixed point property for mappings satisfying the contractive conditions employed by us implies completeness of the underlying space. The characterization of completeness obtained by us not only contains Subrahmanyam?s theorem on characterization of completeness as a particular case but also extends it to b-metric spaces. Results on contractive mappings with discontinuity at the fixed point have found applications in neural networks with discontinuous activation function (e.g. Ozgur and Tas [19, 20]).
Discussion and Practice of Flexible Management in University Educational Management

Under the background of the new era, China's science and technology, economy, and comprehensive strength have all been greatly developed and further improved.The economic base determines the superstructure, so the rapid economic development puts forward higher requirements for the superstructure.Under the new situation, traditional higher education management can no longer meet and adapt to the needs of modern higher education management.In this unbalanced demand, flexible management came into being and achieved rapid development.In this context, on the basis of a brief introduction to the importance of university education management, the article will focus on the analysis and discussion of the application of flexible management in university education management, hoping to promote the multi-dimensional development of flexible management and the improvement of the quality of university education management.
Make a Match with Question Box Media for Improving the Thematic Learning Outcomes of Elementary School

Abstract: The purpose of this study was to improve thematic learning outcomes for class IV elementary school by using the Make a Match learning model assisted by the Question Box media. This type of research is Classroom Action Research (CAR) with 11 students as the research subject. The research (CAR) was carried out in two cycles, namely cycle I and cycle II. The procedure in this research is planning, implementation, observation, and reflection. Collecting data through interviews, observation, and test. Data analysis used qualitative data analysis, namely by collecting data, reducing data, presenting data, and drawing conclusions and quantitative analysis by analyzing data through test results, and measuring the percentage of completeness of test results. The results of the study after using the make a match model, the learning outcomes in the first cycle obtained an average of 73 with a percentage of 55% and in the second cycle an average of 92 with a percentage of 91%. The application of the make a match model to student learning outcomes has increased by 36%, so the results of the study indicate that the application of the make a match model assisted by the question box media can improve thematic learning outcomes at elementary school.