Reviewerly/exHarmony huggingface dataset:
Mismatches removal in unmanned aerial vehicle image registration using density based method

For the problems of large viewpoint variation, heavy distortion and small overlap area in UAV images registration, this paper proposes a density analysis based method to remove mismatches in putative feature correspondences. Our method uses intra-cluster topological constraints for mismatch filtering, which is based on a density-based hierarchical clustering algorithm. Compared with other methods that perform mismatch filtering based on neighborhood topological relationship, our method is more robust to viewpoint changes both in horizontal and vertical directions. The algorithm in this paper uses a coarse-to-fine strategy, which starts with establishing putative feature correspondences based on local descriptors, such as SIFT, ORB, etc. After that we focus on removing outliers by clustering these feature points and verifying topology consistency of the clusters in different images. We view the feature point matching problem as a correspondence problem of the same visual model in two images, and clustering the feature points based on density can approximate the separation of multiple visual patterns. We tested our algorithm on a UAV image dataset which includes several pairs of images and their ground truth. These image pairs contain viewpoint changes in horizontal, vertical and their mixture which produce problems of low overlap, image distortion and severe outliers. Experiments demonstrate that our method significantly outperforms the state-of-the-art in terms of matching precision.
Interactive craft activities – elevating special needs education learning tools with “craft interactive teaching approach” / Siti Zuraida Maaruf, Nurul Syawani and Tamil Selvan Subramaniam

The aim of this study is to determine the Expert Panels agreement and consensus on the suitable items for the development of the Craft Interactive Teaching Approach (CiTA). A purposive sampling consisting of 12 Expert Teachers with more than ten years of experience in the field of Special Education were used in this research to measure their consensus on the design and development of the CiTA video module. The CiTA video module was developed using the ADDIE Model that is supported by the Delphi Technique. This study utilised the Design Development Research (DDR) approach that consisted of three phases. However, for the purpose of this article, the researchers will only discuss Phase 2: Design and Development in developing the Interactive Teaching Approach Video module. The responding twelve VAE teachers provided positive feedback towards learning and teaching using the tutorial module. With the interquartile range of 0 to 1.00 for all items included in the activities, all Expert Teachers in the field of Special Education approved with the content of the CiTA video module from the two rounds of Delphi surveys performed. The CiTA video module was developed with the inclusion of all items that were highly approved by the participating Expert Teachers in the Special Needs Education. Since the two rounds of item evaluation demonstrated a significant relationship between Round One and Round Two, the development of the video module could improve inclusive learning in the Malaysian classroom.
Early Listening Skill on Lesson Study-Based Activities

This study aimed to describe children's listening skills in lesson study-based learning activities at Telkom preschool group B1 in Ternate City. The students involved were 24 early students. The lesson study process included preparing, observing, and reflecting lessons in the context of listening skills. In data analysis, Miles and Huberman interaction model was employed to describe the data qualitatively and quantitative data analyzed using descriptive statistics. The results showed that children listening skill on lesson study-based learning activity on the ‘market day’ topic implemented at Telkom Preschool Group B1 in Ternate City was categorized as good (81.8) and sufficient (68.2). Furthermore, the data the development of a non-cognitive assessment instrument for listening ability in early childhood based on lesson study is feasible to be implemented .The result can be used as a basis for improvement and strengthening a lesson study activities dealing with listening skills in preschool that lesson study-based activities can improve children early listening skills in understanding subjects on the theme ‘market day’.
Introduction to the Musical Acoustics technical area

The field of musical acoustics encompasses all aspects of the design, construction, and performance of musical instruments (including the voice), as well as the physical and cultural environment in which they are played, with the goal of understanding how these elements contribute, separately or together, to the acoustic characteristics. While the general acoustic behavior of most musical instruments can be explained in terms of fundamental principles governing waves in strings, pipes, and plates, there is a high degree of complexity in the mechanical motion and the resulting sound that enables a rich variety of tonal character and musical expression. This presentation will provide an overview of current research areas that address the complexity and variety of musical instruments and the listener experience, including nonlinear effects, flow-structure interaction, computational modeling and machine learning, measurement techniques, performer-instrument interaction, and recording/playback technology. Along the way, the relevance of other technical areas of acoustics will be noted, including physical acoustics, structural acoustics, signal processing, computational acoustics, and psychological and physiological acoustics.
The Role of Law Enforcement Agencies and the Use of IT Tools for a Coordinate Response in Pandemic Crisis Management: The STAMINA project

European Union Horizon 2020 innovation action programme grant agreement No 883441, STAMINA project (https://cordis.europa.eu/project/id/883441); European Union Horizon 2020 research and innovation programme grant agreement No 824115, HiDALGO project (https://cordis.europa.eu/project/id/824115).
DESIGN AN AUTOMATIC SPEECH VERIFICATION BASED ON WORD DETECTION

Based on word identification and knowledge-based verification, we offer a new technique to automated speech recognition (ASR). Assuming we know the vocabulary, we begin by creating word detectors for each word in the utterance. Pruning techniques are employed to weed out improbable word candidates. These words are then grouped together to form word strings. To construct a bottom-up, detection-based voice recognition system that incorporates knowledge of acoustics, speech, and language into pruning and rescoring, the suggested strategy differs from the typical maximal a posteriori decoding method. Using phone models learned from the TIMIT corpus, the suggested method was tested on a connected digit task. Even though no digit samples were provided to train the detectors and recognizers, the suggested detection-based framework performed well when compared to current linked digit recognition methods. This detection-based technique can incorporate other knowledge-based limitations, such as the manner and location of articulation detectors, to enhance the overall system's robustness and performance.
Generation of entangled coherent states for distant Bose-Einstein condensates via Faraday rotation of the photonic polarization

We propose a potentially practical scheme to entangle two distant atomic Bose-Einstein condensates (BEC), which is respectively in an optical cavity. Due to interaction between the cavity and the atomic BEC and the cavity decay, a linear polarized single-photon, which inputs the cavity, will rotate a certain angle after the input-output process, which is called Faraday rotation. Thanks to the faraday rotation of the photonic polarization, through detecting the output photonic polarization, we will entangle two distant Bose-Einstein condensates and generate entangled coherent states. Therefore, we provide a possible way to realize long-distance macroscopic quantum entanglement.
The Representation of Sarcasm in “How I Met Your Mother Season 2”: A Pragmatics Study

The aims of this study were to investigate the maxims flouted by the major characters, the realization of sarcasm based on the scene, and the reasons for sarcastic utterances found in “How I Met Your Mother Season 2” using a pragmatics study. The study was conducted using a textual research. The data of this study were taken from the transcripts of “How I Met Your Mother Season 2”. The data of this study were the sarcastic utterances that appeared in “How I Met Your Mother Season 2”. The data analysis was taken by coding and developing theme from the data based on the theory proposed by Braun and Clarke. The findings indicated that all four maxims were flouted by the major characters in “How I Met Your Mother Season 2”. In addition, there were several sarcastic utterances in which the characters flouted more than one maxim. Based on the research results, the most frequently flouted maxim was the maxim of quality. It could be seen that the situations in which sarcasm appeared in “How I Met Your Mother Season 2” mostly occurred at night. Then, it was also found that all purposes of sarcasm were present in the sarcastic utterances. There were even several sarcastic utterances which served more than one purpose. Sarcasm which served as an evaluation was most frequently used by the characters in order to hide the negative effects of their criticism and also to create the positive effects of their sarcastic praise towards their interlocutors Normal 0 false false false IN X-NONE AR-SA /* Style Definitions */ table.MsoNormalTable{mso-style-name:Table Normal;mso-tstyle-rowband-size:0;mso-tstyle-colband-size:0;mso-style-noshow:yes;mso-style-priority:99;mso-style-parent:;mso-padding-alt:0cm 5.4pt 0cm 5.4pt;mso-para-margin-top:0cm;mso-para-margin-right:0cm;mso-para-margin-bottom:8.0pt;mso-para-margin-left:0cm;line-height:107%;mso-pagination:widow-orphan;font-size:11.0pt;font-family:Calibri,sans-serif;mso-ascii-font-family:Calibri;mso-ascii-theme-font:minor-latin;mso-hansi-font-family:Calibri;mso-hansi-theme-font:minor-latin;mso-bidi-font-family:Arial;mso-bidi-theme-font:minor-bidi;mso-ansi-language:IN;mso-fareast-language:EN-US;} Normal 0 false false false IN X-NONE AR-SA <w:LsdException Locked=false Priority=46 Nam
Spacecraft Target Recognition and Tracking Based on Ellipse Detection

A method for identifying and positioning the spacecraft is designed based on ellipse detection. The ellipse detection algorithm identifies and locates the spacecraft from the first frame in the ellipse's shape. The bounding box's size and position are calculated by the parameters of the outer ellipse and the inner rectangle. The target tracking algorithm uses the size and position information in the first frame to predict the spacecraft's location in the subsequent frames. The experiments show the superiority of the proposed ellipse detection algorithm and the effectiveness of the spacecraft target recognition and tracking method.
Percepción y utilización de las redes sociales por parte de estudiantes de Educación

In recent years, social networks have become an instrument of communication and information in which millions of people are engaged every day. Educational processes have traditionally been linked to the family, school and social spheres but nowadays the virtual context generated by the internet and, especially, by social networks, must be considered. A new educational context, in terms of time and space, has reached schools. This study analyses the perceptions of 245 students enrolled at Primary, Preschool and Physical Education Degrees from Comillas Pontifical University (Madrid, Spain). Knowing how future teachers perceive social networks and their use in education may be a good starting point to educate efficiently using them.
Image Enhancement Algorithm of Vehicle Recognition under High Light Based on Deep Learning

An adaptive image enhancement algorithm under high light conditions is proposed to solve the complex light problem of traffic checkpoint surveillance cameras. This algorithm mainly includes three modules: rapid image classification module, image enhancement module and image quality evaluation module. The rapid image classification module divides the high light image into daytime high-light type and night high-light type on the basis of SqueezeNet network of deep learning, reducing the computation burden while ensuring the classification accuracy. The image enhancement module makes use of the integrated image enhancement algorithm for secondary enhancement of the classified images by adopting the separate handling thought. The image quality evaluation module adopts objective evaluation indexes to measure and designs a weighted comprehensive evaluation index, which is measured from three aspects, namely, structural similarity, normalized mutual information, and normalized mean square error. The experimental results indicate that the proposed algorithm can still obtain a relatively accurate recognition rate for high-light images under different conditions, improving the subsequent recognition of vehicle faces and vehicles.
The Current Situation of Educational Management in China’s Undergraduate Colleges and Suggestions for Optimization

For undergraduate colleges and universities in China, education management is an important part of daily work. Its reasonable development and practice has positive meanings for maintaining teaching orders and the rational practices of educational working plans. The author, from the perspective of campus middle-level manager, summarizes the current development of education management in China’s undergraduate colleges in this article, and puts forward optimization suggestions regarding to specific problems, aiming to promote education management level in further actions.
Energy flow, connectivity and entropy in the light of fuzzy structures

Fuzzy structures, as presented in the literature, refer to a dynamic coupling between a master and a population of slave resonators of uncertain characteristics. However, the investigation of such systems opened new perspectives looking at the way energy flows between the two components, the masters and the slaves. New elements, not originally included into the concept of fuzzy, have been subject of investigations (Carcaterra-Akay, JASA, JSV) disclosing relevant questions: how the topology of connectivity between master and slaves affects the energy transfer? Can be a thermodynamic analogy established between fuzzy structures and thermal systems? Can entropy gain a role in structural dynamics, as it plays a key role in thermodynamics? This paper makes a historical reconstruction of these puzzling questions related to fuzzy structures.
Linguistic Creativity in BIPA Students (Indonesian for Foreign Speakers)

This study aims to describe the forms of linguistic creativity of BIPA students at the morphological, syntactic, and semantic levels. The research method used is descriptive qualitative research method with content analysis techniques. The research data are 78 sentences written by BIPA students at Bina Nusantara University Academic Year 2020/2021. The results showed that 50% of sentences written by BIPA students did not show linguistic creativity, and the other 50% showed linguistic creativity with details: 18% linguistic creativity at the morphological level, 17% linguistic creativity at the syntactic level, and 15% linguistic creativity at the semantic level. At the morphological level, the process of linguistic creativity in words is carried out by: (1) inserting foreign terms into sentences; (2) using non-standard words; and (3) abbreviate words. While in phrases, linguistic creativity is done by: (1) reversing the structure of the phrase; (2) forming nominal phrases with less common word pairs; and (3) forming nominal phrases by incorporating elements of student culture. At the syntactic level, linguistic creativity is carried out in the form of compiling compound sentences with the expansion of descriptions (35%), expansion of objects (9%), expansion of subjects (4%), and expansion of predicates (2%). At the semantic level, linguistic creativity is manifested in the form of figure of speech with details: 14% figure of speech, 27% of simile, 5% of hyperbole, 3% of repetition, and 6% of metaphor.
L’uso delle mappe mentali per l’apprendimento della lingua francese

It is easy to teach a good student who shows no difficulty in learning. A greater commitment is necessary however, with a learner who is unable to follow the set pace and pursue the set educational objectives. This paper is the fruit of a collaborative, didactic experience centered on the use of mental maps which has led to excellent results. This tool is often associated with didactics for learners who have specific learning difficulties. We have used mental maps in the organizational stage of learner’s study, for their presentations, in the review stage and for their written French work, increasing both the performance and concentration of university students.
Big Data Engineering Impact Towards Cloud Computing Adoption in Large Business Organizations

Cloud Computing Adoption  and Big Data Engineering can work on predictive analytics and applications of intelligence (AI) as shown in Figure 1.0, which emphasize important advantages for companies by building models, or through machine learning, deep learning, or computer vision (Chaudhari et al., 2021)Thus, it has been observed that BDE is the driver of CCA (Hashim et al., 2015)(Liu, 2013), (Hemalatha et al., 2016), (Kong et al., 2017), (Chowdhury, 2018),  and (Mirkovic, 2021)In order to examine this Claimed new model will be created that integration of the model related to BDE and other CCA variables that generated relative adoption of Technology Acceptance Model  (TAM) and Technology Organization Environment (TOE) which will be verified through the survey and collection of data from UAE by using binary logistic regression for data analysis,
Advancing towards automatic speech recognition of children innaturalistic preschool environment

The preschool classroom is a viable space for capturing young children’s interactions with teachers. Developing speech/language assessment tools will offer a non-invasive way to quantify child-teacher interactions, allowing teachers to make changes as needed and better support children’s speech, language, and cognitive skills. Building Automatic Speech Recognition (ASR) systems for child speech has been challenging, since most studies have been conducted: (1) with older children, (2) in clean and controlled settings, and (3) generally are limited to prompted or read stimuli. To date, limited research has focused on developing ASR systems for spontaneous child speech in preschool settings. For our study, spontaneous child-teacher conversations were captured in preschool classrooms using the LENA digital audio recorder. A 25-h corpus of child speech were used for experiments using an open-source ASR toolkit. Major challenges in this data for developing ASR models include noisy background environments, age and diversity of children. Our effort focuses on alternative time-delay neural networks (TDNN) for acoustic modelling to improve ASR, as well as trade-offs in language model development and lexicon/vocabulary partitioning. Results from this study across acoustic and language models will be presented using child preschool classroom data. [Work sponsored by NSF CyberLearning Grant #1918032.]
Data Quality Improvement Method of Distributed PV Generation Based on Time Correlation and Spatial Correlation

In order to solve the problem of data anomaly and data missing in distributed photovoltaic (PV) active power, this paper proposes a data quality improvement method based on time correlation and spatial correlation. In terms of anomaly detection, back propagation (BP) neural network is used to establish a correlation model based on the correlation among active power and meteorological data on the time scale, and the difference method is used to detect and eliminate anomaly data. In terms of missing data repair, Random Forest is used to establish a correlation model based on the spatial correlation among active power of power station to be repaired and its surrounding power station's, and the direct repair method is adopted to repair the missing data. The experimental results show that the anomaly detection method based on time correlation can achieve an AUC value of more than 0.93, and the repair method based on spatial correlation can achieve more accurate repair results.
LOGIC AND CRITICAL THINKING COURSE IN DEVELOPING PROFESSIONAL COMPETENCES OF LAW STUDENTS

The article analyzes the role of the course Logic and Critical Thinking in developing professional competencies of Law students, and identifies the basic skills necessary to optimize the decision-making process. Also, special attention is paid to the issue of the importance for future lawyers of not only narrow professional, but also general knowledge, which allow them to master related aspects of activities, to be in demand in the modern labor market.
EmergeNet: A Deep Neural network for Germination timing detection based on image sequence analysis

Earth and Space Science Open Archive Presented WorkOpen AccessYou are viewing the latest version by default [v1]EmergeNet: A Deep Neural network for Germination timing detection based on image sequence analysisAuthorsSrutiDas ChoudhuryiDSee all authors Sruti Das ChoudhuryiDCorresponding Author• Submitting AuthorUniversity of Nebraska-LincolniDhttps://orcid.org/0000-0001-9639-5550view email addressThe email was not providedcopy email address
Retroalimentación desde el relato docente en contexto intercultural en situación de pandemia

This manuscript analyzes the concept of academic feedback and how this process is carried out in the context of online education and pandemic from an intercultural perspective. It presents an analysis from the perspective of the trainers of trainers where the experience of the teacher and the reality of the students and the gaps that distance education has evidenced from the formative evaluation and its potential in the educational field are shown. It is concluded that the conception of feedback is still very conservative, with few indications related to classical maieutics. This is a qualitative research of the article type.
Why ASR + NLP isn't enough for commercial language technology

With an increasing commercial demand for speech interfaces to be integrated into language technology, many technologists have made an unfortunate discovery: combining existing automatic speech recognition (ASR) and natural language processing (NLP) systems often leads to disappointing results. This talk will discuss two factors that contribute to this disparity and make some general suggestions for language technologists and researchers looking to work with tem. The first is the greater degree of variation in speech than text (at least in languages like English) which can lead to higher error rates overall. The second is a mismatch in domain. Modern machine learning approaches to language technology are very sensitive to differences between datasets and (due in part to the disciplinary division between researchers working on language technology for speech and text) most NLP applications have not been trained on speech data.
A Short Review of Python

We review basic Python features with emphasis on the properties we will use to implement algebraic graph algorithms in this chapter. We start with main data structures which are the lists, arrays, dictionaries and sets. We then review control flow methods with decision and loop structures. The last part of the chapter contains module descriptions, input/output and standard library features.