Reviewerly/exHarmony huggingface dataset:
Blockchain for Agriculture IoT

Abstract: The most fundamental promise of blockchain (BT) for the agriculture industry is the elimination of the necessity for third parties to confirm confidence in buyer seller relations, or any source-destination relationship. Transactions become peer-to-peer in a blockchain-enabled setting with no need for mediators. Apart from allowing peer-to-peer transactions, blockchain can also be used to build "smart contracts," which enforce the terms of any treaty when certain conditions are met. Any time anything of value exchanges hands, whether it's tangible goods, services, money and the transaction can be registered, providing a permanent record of the commodity or transaction from beginning to end. Blockchain technology has the potential to be very useful. In this sector, blockchain technology can be extremely beneficial as it is secure and emphasizes privacy as well, but still, it poses new security issues like double spending and majority attack. In this paper, we propose a Machine Learning (ML) based blockchain model to make accurate decisions, where machine learning uses a reasonable amount of data. Therefore, combining ML and BT can give more precise results.
Assessing costa rican children speech recognition by humans and machines

In recent years, an increasing number of studies on human-computer interaction is taking place, due to the pervasive speech interfaces implemented in systems such as cell phones, personal and home automation assistants. These studies include automatic speech recognition (ASR) and speech synthesis, and are considering a wider variety of conditions of the signals, such as noise and reverberation, and accents and age-related effects as well. For example, one of the key challenges is the development of ASR for children’s speech. Since the current systems have a dependency on language and accents, thus, to improve it, the investigations of speech recognition technologies suitable for children are needed. In this paper, we assess commercial ASR systems for the recognition of Costa Rican children’s speech, for users with ages ranging between three and fourteen years old. To establish a comparison and numeric validation of the ASR systems in recognizing children’s isolated words, we conducted a large subjective listening test that computes the differences and challenges that remains for the state-of-the art ASR systems. The results provide evident numeric differences between ASR systems and human perceptions, especially for younger children. Additionally, we provide suggestions for future research directions in the field.
Managing the Development of University Teachers’ Digital Pedagogical Competencies in Theory and in Practice

The article studies the development of higher educational institution teachers’ digital pedagogical competencies. Considering the current situation of uncertainty in higher education, the rapid change of digital platforms and services, the growing dynamics of changes and the emergence of new knowledge in the sphere of digital didactics, the authors propose a concept of forming a university digital transformation team. To meet the demand for high-quality digital educational products, there are required special organizational solutions, including the creation of pedagogical teams. The purpose of the article is to develop a model for assessing individual and team digital pedagogical competencies, which allows making managerial decisions and eliminating the lack of competencies in a team at the stage of designing digital educational products and services. The study analyzed the existing models of digital pedagogical competencies and drew the conclusion on the need to refine them with specific tools for assessing current individual and team digital pedagogical competencies for the development and implementation of an educational product or project. Based on the model proposed, the paper puts forward a general concept of a professional retraining program, which consists of three areas of assessment: technical, pedagogical, subject (area of research, direction of training). Based on the analysis of Ural Federal University’s experience of implementing distance learning using digital educational resources, the authors give recommendations on how to improve the efficiency of the development teams and the implementation of digital educational products. This publication might be of interest for managers of the higher education system, as well as for scholars and teachers interested in digitalization, digital didactics, digital transformation of universities and individualization of education.
Acrostics in Computer Networking Jargon: A Morphosemantic Analysis

Acrostics are becoming more and more widespread in computer networking jargon. Most books on computer networking, written in English or French, use them without giving their meanings in order to avoid confusion that may arise in the heads of EFL learners since the form of these acrostics resembles the one of already existing words. This phenomenon needs being tackled since there is not any research related to acrostics used in computer networking jargon. The study uses a corpus of 31 acrostics collected from different books of computer networking. It referred to a morphosemantic approach to analyze these data. Based on the analysis of data, the findings reveal that the acronyms used in computer networking have the same form with some words of English or French. However, there is not any semantic relationship between these words and the acrostics used in the computer networking jargon. Hopefully, this study will help EFL learners/teachers enhance their learning/teaching of English as they are involved in computer networking field.
Оn the implementation of a transdisciplinary approach in preparing future mathematics teachers

Introduction. The disparate study of certain areas and branches of knowledge, characteristic of the disciplinary approach, has largely lost its position, recognising the inevitability of interdisciplinary cooperation. At present, interdisciplinarity is already being comprehended at a new level, creating the prerequisites for the introduction of a transdisciplinary approach to solving complex problems, including in the educational sphere. Aim. The current research aims to present the transdisciplinary teaching means, which are relevant in the process of training future teachers of mathematics, and which are identified on the basis of an analysis of the content of education. Methodology and research methods. General scientific and empirical methods were used to develop the ideological basis of the study. The aforementioned methods allowed the authors to draw up a complete picture of the problem under study, to identify its patterns and trends, to understand the essence. The search and selection of mathematics subject content with transdisciplinary properties was based on a systematic and interdisciplinary approach. At the stage of testing the research hypothesis, the competency-based approach was decisive, and tactical tasks were solved by referring to the activity approach. In addition, the main provisions of the concepts of humanisation and humanitarisation of education, as well as the principles of fundamentalisation of mathematical education, were taken into account. Results and theoretical significance. The expediency of using inequalities and convex functions in the training of future mathematics teachers in the context of a transdisciplinary approach is substantiated. A phased description of the work carried out allows us to trace the methods of reflecting the modern scientific content of the relevant topics, conditions, means and expected results of pedagogical interaction. The theory and methods of teaching mathematics at the university are enriched with a qualitatively new vision of the educational potential of the concepts of inequality and a convex function. Practical significance. The introduction of inequalities and convex functions in the process of future mathematics teachers training at Vyatka State University made it possible to demonstrate the possibilities of a transdisciplinary approach in the development of students’ worldview and the formation of professionally significant students’ competencies. The presented means of implementing the transdisciplinary approach can also be comprehended in teaching students of other areas of training.
Exploring the potential of an audio application for teaching AI-based classification methods to a wider audience

Knowledge about artificial intelligence (AI) is becoming increasingly important for many careers, especially those based in science and engineering. Besides formal education, the impact of AI on society lead to consider educational projects for teaching the fundamental concepts of AI at wider audiences, including high school levels. This can help more general audiences to better understand how AI works, with the hope that also parents and educators can help students develop a healthy appreciation for implications and limitations, along with an appropriate relationship and deeper interest on it. In this paper, we present a pilot project for teaching an AI-based classification method that is empirically evaluated with real data of a real problem, which can be understood and tackled with basic mathematical tools and activities suitable for high school students. With this proposal, we aim to show how audio and speech applications can inform a wider audience about advances in AI, its characteristics, and its future impact on society. Results and lessons learned from this project can form the basis for further projects using different tools and data, according to students’ interests and initiative.
Application of Fischer semi discriminant analysis for speaker diarization in costa rican radio broadcasts

Automatic segmentation and classification of audio streams is a challenging problem, with many applications, such as indexing multi – media digital libraries, information retrieving, and the building of speech corpus or spoken corpus) for particular languages and accents. Those corpus is a database of speech audio files and the corresponding text transcriptions. Among the several steps and tasks required for any of those applications, the speaker diarization is one of the most relevant, because it pretends to find boundaries in the audio recordings according to who speaks in each fragment. Speaker diarization can be performed in a supervised or unsupervised way and is commonly applied in audios consisting of pure speech. In this work, a first annotated dataset and analysis of speaker diarization for Costa Rican radio broadcasting is performed, using two approaches: a classic one based on k-means clustering, and the more recent Fischer Semi Discriminant. We chose publicly available radio broadcast and decided to compare those systems’ applicability in the complete audio files, which also contains some segments of music and challenging acoustic conditions. Results show a dependency on the results according to the number of speakers in each broadcast, especially in the average cluster purity. The results also show the necessity of further exploration and combining with other classification and segmentation algorithms to better extract useful information from the dataset and allow further development of speech corpus.
GPU based approach for fast generation of robot capability representations

Capability maps are an important tool for enabling robots to understand their bodies by providing a way of representing the dexterity of their arms. They are usually treated as static data structures be- cause of how computationally intensive they are to generate. We present a method for generating capability maps taking advantage of the parallelization that modern GPUs offer such that these maps are generated approximately 50 times faster than previous implementations. This system could be used in situations were the robot has to generate this maps fast, for example when using unknown tools.
Assessing the effectiveness of diarization algorithms in costa rican children-adult speech according to age group and gender

Speaker diarization is the task of automatically identifying speaker identities and detecting their speaking times in an audio recording. Several algorithms have shown improvements in the performance of this task during the past years. However, it still has performance challenges in interaction scenarios, such as between a child and adult, where interruptions, fillers, laughs and other elements may affect the detection and clustering of the segments.&#x0D; In this work, we perform an exploratory study with two diarization algorithms in children-adult interactions within a recording studio and assess the effectiveness of the algorithms in different age groups and genders. All participants are native Costa Rican Spanish speakers. The children have ages between 3 to 14 years, and the interaction combines guided repetition of words or short phrases, as well as natural speech.&#x0D; The results demonstrate how the age affects the diarization performance, both in cluster purity and speaker purity, in a direct but non-linear fashion.
Retracted: Psychological Stress Identification and Evaluation Method Based on Mobile Human-Computer Interaction Equipment

[This retracts the article DOI: 10.1155/2022/6039789.].
Discovering Approximate and Significant High-Utility Patterns from Transactional Datasets

Mining high-utility pattern (HUP) on transactional datasets has been widely discussed, and various algorithms have been introduced to settle this problem. However, the time-space efficiency of the algorithms is still limited, and the mining system cannot provide timely feedback on relevant information. In addition, when mining HUP from taxonomy transactional datasets, a large portion of the quantitative results are just accidental responses to the user-defined utility constraints, and they may have no statistical significance. To address these two problems, we propose two corresponding approaches named Sampling HUP-Miner and Significant HUP-Miner. Sampling HUP-Miner pursues a sample size of a transitional dataset based on a theoretical guarantee; the mining results based on such a sample size can be an effective approximation to the results on the whole datasets. Significant HUP-Miner proposes the concept of testable support, and significant HUPs could be drawn timely based on the constraint of testable support. Experiments show that the designed two algorithms can discover approximate and significant HUPs smoothly and perform well according to the runtime, pattern numbers, memory usage, and average utility.
Metrics Model to Complement the Evaluation of DevOps in Software Companies

This article presents a model to complement the evaluation of DevOps in software companies. It was designed by harmonizing the elements of the DevOps process identified through a systematic mapping of the literature and aimed to know the state of the art of methodological solutions and tools to evaluate DevOps in the industry. The process elements were identified, compared, and integrated into a common process structure that was used to establish a total of 11 metrics using the Goal-Question-Metric approach. The model was evaluated by a focus group of expert DevOps professionals. They determined that the model is clear, easy to apply, and provides valuable information to companies to improve their DevOps practices.
Construction of a Video Transmission Scenario in Software-Defined Networks for QoE Estimation

The services supported by data networks have become widespread, so the architectures of the new data networks are service-oriented. They are endowed with intelligence, flexibility, and programmability. The preceding is with the aim of providing acceptability by users. Thus, this paper presents the construction of a video transmission scenario over a software-defined network (SDN, Software-Defined Networking) using free software and modifying its behavior with background traffic, on which the Quality of Experience (QoE) is estimated. Subjective and objective metrics were used for the QoE estimation. For the first one, the Mean Opinion Score (MOS) was used, while the second one was studied with the Full Reference Image Quality Assessment (FR-IQA). Finally, a correlation between the two types of metrics was proposed.
CORRELATION BETWEEN OSCILLATORY MOTION AND GRAVITY REGARDED AS EDUCATIONAL CONTENT

The author of the paper has been teaching physics at Academy of technical and educational vocationalstudies for the past seven years, of which two academic years took place during the Covid-19 pandemic. Internetresources have been applied beforehand throughout the entire period, but with fully online teaching, it gainedparticular importance. Educational approaches developed for online classes required students’ activities that wouldfurther motivate them to study. In the academic year 2021/22, educational contents were enhanced with additionallinking of certain educational contents, which resulted from the obvious need to make the material as interesting aspossible, and to awaken curiosity about the contents. In this paper it is shown how a specific digital simulation canbe used for a teaching topic for which it was not originally intended, and it was also shown that in this way a usefulcorrelation of different teaching contents can be realized. The significance of the above-mentioned correlation isreflected in the fact that it requires a teaching approach that leads to more effective learning process in class as wellas to greater motivation and greater activation of students in the class. A simulation related to the oscillation of amathematical pendulum is described in this paper, i. e. its ability to choose different strengths of gravitational fieldsin which the pendulum oscillates, i. e. different gravitational accelerations. It was researched how students thinkwhen for the given phenomena a zero gravity is approximated. It was researched whether the students realized achange in their activities both in class and in their motivation for work. It is interesting that only after theimplementation of weightlessness as an educational content in the existing educational content on oscillatorymotion, the teacher saw certain alternative conceptions that some students built when they were studying aboutoscillations.
REPRESENTATIVE OF THE STATE OF REVERBERATION IN THE SERBIAN ORTHODOX CHURCH

In this paper, the statistical analysis determined a representative of the state of reverberation in theSerbian Orthodox Church of "St. Prokopius" in Katun. The first part of the paper explains the experiment based onthe process of recording acoustic impulse responses and determines the value of the early reverberation time EDTand the reverberation time RT10, RT20, and RT30 at the central frequencies fc = {125, 250, 500, 1000, 2000, 4000} Hzusing ARTA software package. The experiment results (tabular and graphical) obtained by statistical analysis usingthe Matlab software package are also presented. In the second part of the paper, the results of the experimentanalysis were carried out. By comparing them, it was concluded which acoustic parameter is representative of thestate of reverberation in the analyses of the Serbian Orthodox church.
IMAGE INTEROLATION USING OF THE FIFTH AND SEVENTH ORDER POLYNOMIAL PARAMETER KERNELS

In the first part of the paper, one-parameter (1P), fifth and seventh order polynomial interpolationconvolution kernels, are described. In the second part of the paper an Experiment is described. The precision of theimage interpolation was tested. Interpolation of the Test images from the base, using interpolation kernels, wereperformed. The precision of the interpolation kernels was measured using the mean squared error (MSE). Next,optimum kernel parameter, α, were determined by minimizing MSE. After that, a comparative analysis of theminimum MSE values, for the fifth and seventh order polynomial kernels, was performed. The results are presentedtabularly and graphically.
Retraction Note to: Literature Review on Sign Language Generation

The Series Editor has retracted this article. After publication, concerns were raised regarding the use of inappropriate language and incorrect statements regarding the deaf community and sign language users. There was a lack of collaboration between the authors and the community described in the article. The authors apologize for any harm caused by these mistakes. Additionally, Figs. 1 and 6 contain materials that have been previously published in [1] and [2], respectively, but the citations and licence statements are missing in the figure legends. The authors have stated that they did not obtain appropriate permissions to reuse these figures. All authors agree to this retraction. [1] Veale, T., & Conway, A. (1994, June). Cross modal comprehension in ZARDOZ an English to sign-language translation system. In Proceedings of the Seventh International Workshop on Natural Language Generation (pp. 249-252). [2] Kumar, P., & Kaur, S. (2018). Online multilingual dictionary using Hamburg notation for avatar-based Indian sign language generation system. International Journal of Cognitive and Language Sciences, 12(8), 1117-1124.
DynK-hydra: improved dynamic architecture ensembling for efficient inference

Abstract Accessibility on edge devices and the trade-off between latency and accuracy is an area of interest in deploying deep learning models. This paper explores a Mixture of Experts system, namely, DynK-Hydra, which allows training of an ensemble formed of multiple similar branches on data sets with a high number of classes, but uses, during the inference, only a subset of necessary branches. We achieve this by training a cohort of specialized branches (deep network of reduced size) and a gater/supervisor, that decides dynamically what branch to use for any specific input. An original contribution is that the number of chosen models is dynamically set, based on how confident the gater is (similar works use a static parameter for this). Another contribution is the way we ensure the branches’ specialization. We divide the data set classes into multiple clusters, and we assign a cluster to each branch while enforcing its specialization on this cluster by a separate loss function. We evaluate DynK-Hydra on CIFAR-100, Food-101, CUB-200, and ImageNet32 data sets and we obtain improvements of up to 4.3% accuracy compared with state-of-the-art ResNet. All this while reducing the number of inference flops by a factor of 2–5.5 times. Compared to a similar work (HydraRes), we obtain marginal accuracy improvements of up to 1.2% on the pairwise inference time architectures. However, we improve the inference times by up to 2.8 times compared to HydraRes.
RANCANG BANGUN SISTEM INFORMASI PENGARSIPAN SURAT PADA DINAS PARIWISATA KOTA PALOPO BERBASIS WEBSITE

This study aims to produce a letter filing information system at the Palopo City Tourism Office based on a website so as to make it easier for agencies to manage mail archive data. The data collection methods used in this research are observation, interviews, documentation and literature studies. In the development of the system, the author uses the Research and Development method which refers to the Waterfall model. System design using a Unified Modeling Language (UML) approach, while creating a website using PHP, Bootstrap, CSS, Java script programming languages using MySQL databases. The assessment technique carried out in this system is Blackbox testing. The results of this study are the existence of a website-based mail guarantee information system that can make it easier for agencies to process mail archive data