Reviewerly/exHarmony huggingface dataset:
Fifa Ticketing System using Blockchain Hyperledger Sawtooth Platform

In this paper we present an approach to investigate how Blockchain Hyperledger Sawtooth platform can be used in ticketing system to process a secure transaction over a network environment. A framework for a ticketing industry has been proposed to overcome the transactional issues between distributors, vendors, and the customers. A discrete three-layer architectural model is presented that is suitable for the application design development. The Blockchain architecture allows us to maintain the list of records contained in the distributed data base on the network and the validator validates the transaction allowing the transaction processor to authorizes the nodes. The outline of Docker compose demonstrates on how to start the transaction processor from the console for the ticketing application. The methodology indicates the use of algorithm to generate a unique key by importing the python software development kit in our design implementation Finally, the paper also provides the detail analysis of how the transactions are initiated, retrieved, and exported to view the complete block of encrypted data and achieve safe and secure transaction between two parties over a network.
Intelligent Correction System of Students’ English Pronunciation Errors Based on Speech Recognition Technology

With the increasingly frequent international exchanges, English has become a common language for communication between countries. Under this research background, in order to correct students’ wrong English pronunciation, an intelligent correction system for students’ English pronunciation errors based on speech recognition technology is designed. In order to provide a relatively stable hardware correction platform for voice data information, the sensor equipment is optimized and combined with the processor and intelligent correction circuit. On this basis, the MLP (Multilayer Perceptron) error correction function is defined, with the help of the known recognition confusion calculation results, the actual input speech error is processed by gain mismatch, and the software execution environment of the system is built. Combined with the related hardware structure, the intelligent correction system of students’ English pronunciation error based on speech recognition technology is successfully applied, and the comparative experiment is designed the practical application value of the system is highlighted.
Das Ngrowo-Ngasinan: Pengaruh dan Manfaatnya Terhadap Tinggalan Arkeologi Di Trenggalek

The Ngrowo-Ngasinan watershed is one of the Brantas watersheds covering an area of ​​1,188,800 hectares located in the Trenggalek Regency. The Ngrowo-Ngasinan watershed consists of forests, fields, irrigated rice fields, plantations, and settlements which are flooded every year. Flood conditions that occur have an influence on archaeological remains around the Ngrowo-Ngasinan watershed, namely Brongkah Temple, Semarum Site and Kamulan. Most of the archaeological remains are buried by alluvial deposits due to flooding and the overflow of the Ngrowo – Ngasinan River. The results of research conducted by Balar DIY in 2012-2015 through survey and excavation data collection methods indicate that the Semarun and Kamulan sites were abandoned because they were inundated and drowned due to the overflow (flood) of the Ngrowo and Ngasinan rivers. The purpose of this article is to determine the effect of the existence of the Ngrowo-Ngasinan watershed on the loss or damage of archaeological sites around the Ngrowo-Ngasinan watershed. Morphologically, the archaeological sites in the Ngrowo-Ngasinan watershed have a very ideal position as a place of settlement, because their location is in a basin and sloping area, fertile, and close to water sources. The conclusion should be at the end of the abstract. Avoid the word 'disaster' (adjust title). Conclusion: The selection of residential locations around the Ngrowo-Ngasinan watershed has a very significant impact or great risk for flood disasters because of its location on the banks of the river. Keywords: Ngrowo-Ngasinan Watershed, archaeological remains, flood.
Co-Curing Noisy Annotations for Facial Expression Recognition

Driven by the advancement in technology that can facilitate implementation of deep neural networks (DNNs), and due to the availability of large scale datasets, automatic recognition performance of the machines has increased by leaps and bounds. This is also true with regard to facial expression recognition (FER) wherein the machine automatically classifies a given facial image in to one of the basic expressions. However, annotations of large scale datasets in FER suffer from noise due to various factors like crowd sourcing, automatic labelling based on key word search etc. Such noisy annotations impede the performance of FER due to the memorization ability of DNNs. To address it, this paper proposes a learning algorithm called Co-curing: peer training of two joint networks using a supervision loss and a mimicry loss that are balanced dynamically, and supplemented with a relabeling module to correct the noisy annotations. Specifically, peer networks are trained independently using supervision loss during early part of the training. As training progresses, mimicry loss is given higher weightage to bring consensus between the two networks. Our Co-curing does not need to know the noise rate. Samples with wrong annotations are relabeled based on the agreement of peer networks. Experiments on synthetic as well real world noisy datasets validate the effectiveness of our method. State-of-the-art (SOTA) results on benchmark in-the-wild FER datasets like RAF-DB (89.70%), FERPlus (89.6%) and AffectNet (61.7%) are reported.
Integrated Teaching Competency Framework for General Education Program: Suggestions and Recommendations for Natural Science Teachers

This article investigated the general structure of teaching competencies and integrated teaching competencies of natural science teachers in high school education, the actual situation of integrated teaching in Vietnam and some other countries in the world, and the designing of assessment templates to recognize difficulties of natural science teachers in integrated teaching. It is shown that natural science teachers are facing various challenges in integrated teaching: a lack of professional knowledge and skills in building integrated topics and teaching with this approach, problems in putting integrated teaching techniques into practice. On this foundation, the article presents a procedure for building an integrated teaching competency framework for natural science teachers, then proposes such a framework. This framework consists of 4 competencies and ten criteria with detailed indicators. Natural science teachers can use this framework to develop tools (checklists, rating scales, or questionnaires) to assess their integrated teaching quality and their “colleagues”, henceforth fostering their competencies as required by the General Education Program.&#x0D;
SOCIO-PSYCHOLOGICAL ASPECTS OF THE TRANSFORMATION OF THE PEDAGOGICAL KNOWLEDGE INTO INNOVATION

The article dwells on various socio-psychological aspects necessary for the transformation of the pedagogical knowledge into innovation, highlights the patterns of this process, focuses on the integration of knowledge, the development of intelligence and self-efficacy of an individual, creating a social context that is favourable for fostering innovations and the development of the innovative activities of a teacher. The essence of the emergence of pedagogical innovation and the stages that must take place: the search for appropriate innovation and its implementation; repetition, dissemination of innovations; application in professional activities. The results of the diagnostics of the innovative competence of lecturers of Borys Grinchenko Kyiv University are presented.
Ordered weighted average based grouping of nanomaterials with Arsinh and dose response similarity models

In the context of the EU GRACIOUS project, we propose a novel procedure for similarity assessment and grouping of nanomaterials. This methodology is based on the (1) Arsinh transformation function for scalar properties, (2) full curve shape comparison by application of a modified Kolmogorov–Smirnov metric for bivariate properties, (3) Ordered Weighted Average (OWA) aggregation-based grouping distance, and (4) hierarchical clustering. The approach allows for grouping of nanomaterials that is not affected by the dataset, so that group membership will not change when new candidates are included in the set of assessed materials. To facilitate the application of the proposed methodology, a software script was developed by using the R programming language which is currently under migration to a web tool. The presented approach was tested against a dataset, derived from literature review, related to immobilization of Daphnia magna and reporting information on several nanomaterials and properties.
Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR

Self-supervised monocular depth prediction provides a cost-effective solution to obtain the 3D location of each pixel. However, the existing approaches usually lead to unsatisfactory accuracy, which is critical for autonomous robots. In this paper, we propose a novel two-stage network to advance the self-supervised monocular dense depth learning by leveraging low-cost sparse (e.g. 4-beam) LiDAR. Unlike the existing methods that use sparse LiDAR mainly in a manner of time-consuming iterative post-processing, our model fuses monocular image features and sparse LiDAR features to predict initial depth maps. Then, an efficient feed-forward refine network is further designed to correct the errors in these initial depth maps in pseudo-3D space with real-time performance. Extensive experiments show that our proposed model significantly outperforms all the state-of-the-art self-supervised methods, as well as the sparse-LiDAR-based methods on both self-supervised monocular depth prediction and completion tasks. With the accurate dense depth prediction, our model outperforms the state-of-the-art sparse-LiDAR-based method (Pseudo-LiDAR++) by more than 68% for the downstream task monocular 3D object detection on the KITTI Leaderboard.
The Production-oriented Approach to Teaching Translation Between English and Chinese in Vocational and Technical Colleges

The research is about applying Production-oriented Approach to teaching translation between English and Chinese in vocational and technical colleges.Starting from general introduction of POA and the current situation of teaching translation, this paper analyzes the reasons why to apply POA to teaching translation and also suggests making a micro-lesson in motivation, to create a situation when enabling, and to apply Teacher-Student Collaborative Assessment when assessing.At the same time, teachers need to guide students to make full use of mobile technology to select the updated information and to learn knowledge they need, or they want.
Using Full Field Data to Produce a Single Indentation Test for Fully Characterising the Mooney-Rivlin Material Model

A theoretical testing method for fully characterising the Mooney-Rivlin three-parameter hyper-elastic material model is proposed by capturing full-field digital image correlation (DIC) data, namely displacement field and indentation force data. A finite element model with known parameters will act as the experimental model against which all data will be referenced (a preliminary test case). Going forward this stand-in model will be replaced with physical test data. This paper also introduces a new concept, the concept of hyperplanes. These hyperplanes represent regions in the force and displacement field data where all the objective function values are equal. The paper concludes that the Mooney-Rivlin material model can theoretically be fully characterised in a single indentation test. By applying the methods discussed in the paper when using full-field data operating under the assumption of hyper-planes.
Penerapan Data Mining Untuk Analisis Daftar Pembelian Konsumen Dengan Menggunakan Algoritma Apriori Pada Transaksi Penjualan Toko Bangunan MDN

Everyday the MDN Building Shop has sales transactions but these transactions are only used as data reporting, MDN Building Stores do not manage sales transaction data and analyze a relationship between building material products purchased by consumers in the future. The purpose of this study is to process sales transaction data from consumer purchases by utilizing the Apriori Algorithm, one of the data mining processing methods. From the Apriori algorithm that will be used, it will find an association rule by finding the minimum value of support and confidence. The final result is that if the minimum support value is 50% and the minimum trust is 90%, then 10 patterns of consumer purchase transactions are obtained with 100% confidence. From the association rules, it was found that the transactions that occurred were the purchase of Knie In Grest, Tee in grest, gelam 10 x 12, thinner bottles, knie grest 3 in, waving aw pipes, speck gloves, 3 mm polywood, and 1 nail in a keris.
A new merged segmentation technique used for X-ray chest images

Image processing techniques of a chest X-ray image includes noise removal followed by segmentation, feature extraction to locate regions and classification.The chest image appears differently when viewed from different angles or under different lightings.Diagnosing TB stays a challenge.The customary medical specialty, even so count, variety ways, they are gradual and frequently unreliable.In ancient poster anterior chest radiographs, several clinical and diagnostic functions build use of computationally designed algorithms that assist in scientific diagnostic analysis by victimization acquisition of pictures.The Digital image may be a necessary medium for analyzing, annotating, patient's demographics coverage in screening of TB via chest radiography.This paper deals with the essential segmentation methods of TB.In our methodology, this disease can be fastly and accurately identifiable by the merge segmentation methods of K means with Marker-based Watershed segmentation which has highest precision and recall values when compared to the several other segmentation methods which is been is discussed.More than 80 chest Xray images output for recall and precision is discussed here.
Information and communication technologies as an actual resource of educational activity

Cybernation of the world, which began in the middle of the 20th century, encompassed all spheres of the life of society, becoming an essential component of the environment. Electronic technologies are used in various industries and services, including education. The implementation of the idea of e-education has contributed to the change in educational technologies, the dominant component of which are information and communication technologies. The research problem lies in the need to disclose modern information and communication technologies as an actual resource for educational activities. The purpose of the research is to substantiate the effectiveness of the use of information and communication technologies in the educational process. The research methods are analysis, synthesis, generalization, description. The basic research method is a pedagogical experiment. The research results: the concept of "information and communication technologies" has been considered, their tools have been described; the advantages of using information and communication technologies in educational activities in the direction of training 44.03.02 Psychology and Pedagogy of primary education have been disclosed; the efficiency has been substantiated and the possibilities of using informatization means in the educational process on the basis of the branch of FSBEI HE "Adyghe State University" in the city of Belorechensk have been determined; examples of the use of information and communication technologies in the educational process in the disciplines "Modern information technologies", "Information and communication technologies in education" have been given; the results of experimental work have been presented, that confirm the increase in the efficiency of the quality of knowledge. Key conclusions: information and communication technologies include the integration of methodological techniques, technological processes, software and hardware that interact with each other in the process of using information for a specific purpose, determined by the interests of its consumers; the advantages of information and communication technologies in educational activities are the expansion of the possibilities of the educational process, the development of positive educational motivation and interest of students, an increase in the quality of knowledge, etc.
Implementation of Support Vector Machine Algorithm with Correlation-Based Feature Selection and Term Frequency Inverse Document Frequency for Sentiment Analysis Review Hotel

Purpose: The study aims to reduce the number of irrelevant features in sentiment analysis with large features. Methods/Study design/approach: The Support Vector Machine (SVM) algorithm is used to classify hotel review sentiment analysis because it has advantages in processing large datasets. Term Frequency-Inverse Document Frequency (TF-IDF) is used to give weight values to features in the dataset. Result/Findings: This study's results indicate that the accuracy of the SVM method with TF-IDF produces an accuracy of 93.14%, and the SVM method in the classification of hotel reviews by implementing TFIDF and CFS has increased by 1.18% from 93.14% to 94.32%. Novelty/Originality/Value: Use of Correlation-Based Feature Section (CFS) for the feature selection process, which reduces the number of irrelevant features by ranking the feature subset based on the strong correlation value in each feature
A detailed survey on cyber security and its challenges

Cyber security is a way of protecting our useful information, entire network, and the system from different attacks to avoid damage.The cyber security threat is peculiar towards the Government, Military, Corporate, Financial and Medical organizations because they collect, process, and store unprecedented amounts of data on computers and other devices.In this research paper researcher discuss about the technologies and challenges towards the Cyber Security.Researcher also discusses about the benefits of Cyber security.
The Future Biology Teachers Training for the Implementation of Sustainable Development Ideas in Ecological Education

The article presents the results of the experimental study targeted at the scientific substantiation and experimental verification of the methodology of the future biology teachers’ ecological competence development. It is grounded and proved that ecological education resulting in ecological competence is an integral part of education for sustainable development. In order to integrate sustainable development education into the future biology teachers’ training, the methodology for the ecological competence development has been suggested. The methodology involves the environmentalization of the educational content and the use of a modular object-oriented dynamic learning environment. A pedagogical experiment was conducted in order to determine the effectiveness of the methodology of future biology teachers training for the implementation of sustainable development ideas in ecological education. Four hundred and twenty-seven students participated in the experimental study. Control and experimental groups of students were allocated for conducting the experiment. In experimental groups the author’s methodology was implemented. The experimental data were processed using mathematical statistics. As a result of the generalization of the results of the study, it was found that in the experimental groups, the percentage of students with high and medium levels of ecological competence increased, and with low levels – decreased compared to the control groups. This testifies to the effectiveness of the future biology teachers’ ecological competence development.
Method of Step Detection and Counting Based on Measurements of Magnetic Field Variations

Basic human activity recognition (HAR) and analysis is becoming a key aspect of tracking and identifying daily habits that can have a critical impact on healthy lifestyles by providing feedback on health status and warning of deterioration. However, current approaches for detecting basic activities such as movements or steps rely on solutions with multiple sensors which affect their size and power consumption. In this paper, we propose a novel method that uses only a single magnetic field sensor for basic step detection, unlike the well-known multisensory solutions. The approach presented here is based on real-time analysis of magnetic field sensor measurements to detect and count steps during a walking activity. The approach is implemented in a system that integrates a digital magnetic field sensor with software blocks: filter, steady state detector, extrema detector with classifier, and threshold comparator implemented in an embedded platform. Outdoor experiments with volunteers of different ages and genders walking at variable speeds showed that the proposed detection method achieves up to 98% accuracy in step detection. The obtained results show that a single magnetic field sensor can be used to detect steps, and in general offers the possibility of simplifying the current solutions by reducing the device dimensions, the cost of a system and its power consumption.
Japanese Translation Quality Evaluation System Based on Deep Neural Network Algorithm

The current translation quality evaluation system relies on the combination of manual and text comparison for evaluation, which has the defects of low efficiency and large evaluation errors. In order to optimize the defects of the current quality evaluation system, a Japanese translation quality evaluation system based on deep neural network algorithm will be designed. In order to improve the processing efficiency of the system, the USB3.0 communication module of the hardware system will be optimized. Based on the hardware design, the reference translation map is used to extend the reference translation of Japanese translation. The evaluation indexes of over- and under-translation are set, and the evaluation of Japanese translation quality is realized after the parameters are determined by training the deep neural network using the sample set. The system functional test results show that the average data transmission processing time of the system is improved by about 31.27%, and the evaluation error interval is smaller and the evaluation is more reliable.
A Novel Privacy-Preserving Scheme in IoT-Based Social Distancing Technologies

The COVID-19 pandemic has swapped the world, causing enormous cases, which led to high mortality rates across the globe. Internet of Things (IoT) based social distancing techniques and many current and emerging technologies have contributed to the fight against the spread of pandemics and reduce the number of positive cases. These technologies generate massive data, which will pose a significant threat to data owners’ privacy by revealing their lifestyle and personal information since that data is stored and managed by a third party like a cloud. This paper provides a new privacy-preserving scheme based on anonymization using an improved slicing technique and implying distributed fog computing. Our implementation shows that the proposed approach ensures data privacy against a third party intending to violate it for any purpose. Furthermore, our results illustrate our scheme’s efficiency and effectiveness.