Reviewerly/exHarmony huggingface dataset:
CONTINUING EDUCATION: VALUATION FROM THE VIEW OF TEACHERS OF RADIOLOGY TECHNOLOGY

Education in the area of health has been undergoing many changes in its conceptions and concepts, in parallel with the evolution that has been taking place in all sciences, being directly influenced by the country's socioeconomic and political moment.The general objective of this research was to analyze the level of appreciation of continuing education in the area of radiology technology teachers.This study was carried out through qualitative, quantitative, descriptive, bibliographic and field research.The study was carried out at the following private institutions: Faculdade Santa Emília de Rodat (FASER); Integrated Faculty of Pernambuco (FACIPE); Integrated Faculty of Patos (FIP).The population consisted of professors from the radiology technology courses at these institutions, who agreed to participate in the research and sign the Free and Informed Consent Form (ICF).Data collection was performed through the application of a questionnaire, containing objective and subjective questions, about some aspects related to continuing education.The ethical aspects contained in resolution 510/16 of the National Health Council, which guides and regulates research with human beings, were taken into account.Through this study, the importance of investing in the continuing education of the group of teachers surveyed was perceived, since they show, through the data, the need to continue in the training process with the aim of building a personal and professional profile of the educator, meeting the socio-educational needs, bringing countless benefits to educators and students.
Swarm of drones exploration in confined area

Drones are used as helpful machine for the use of human in various mission to successfully complete the required work in less time .The swarm of drones is the advancement of the mission which are time typical and time complexity centered problems. Typical application with swarm drones are civil security ,distant and extended area, observation of hostile and other wide applications. While the Paper, used the lightweight and economical way to use swarm drone. Ad-hoc network is used as medium for the communication of multi drone for the exploration in confined areas. This paper the main point is that the swarm technology in the time complex missions and use it other than commercial purpose. The required data is collected form the real time flight of the drones and interpreted to find the successful path in completion of the required work. Predefined path defined to the multi drone in ordered for exploration in desired path. The purpose of this paper, acquisition and pattern formation in efficient manner of the successful path finding in confined areas for better exploration strategy. This work is developed with in framework to support robot operating system.
Interactive Display of New Media’s Intelligent Robots for the Music Culture Industry

This article mainly studies the interactive display that the new media intelligent robot can bring to us in the context of today’s music culture industry. In view of the topics that people are more concerned about today, the main channel of this article is to effectively combine music and intelligent robots. First, the music needs to be transmitted to the robot as a wave signal. Before that, the music is specially processed, and then the music identification function of the relevant robot is systematically loaded. Secondly, the relevant robot can express the music in time and correctly. During the experiment, light music, heavy music, slow music, and fast music were used. A total of 6 groups of light music and light music were compared for input. Two groups of normal music were placed for comparison. The lighter the music, the more the robot in the interactive display process. The performance is not obvious. With the continuous increase of the corresponding coefficient, the accuracy of music robot’s signal recognition gradually increases. When the coefficient is 0.8, the accuracy is the highest. The accuracy of the music robot in the heavy music environment is 88%, and light music is in a slow rhythm. The accuracy rate is the lowest under the condition of only 60%. From the experimental results, it can be seen that the characteristics of different music have an impact on robot identification and its correlation. Popularizing new media robots in the music industry can promote the sustainable development of the music market.
Deep Learning-Based Idiomatic Expression Recognition for the Amharic Language

Abstract Idioms are used in Amharic to conceal information or to express ideas indirectly. However, most natural language processing models used with the Amharic language, such as machine translation, semantic analysis, sentiment analysis, information retrieval, question answering, and next word prediction, do not consider idiomatic expressions. As a result, in this paper, we proposed a conventional neural network (CNN) with a FastText embedding model for detecting idioms in an Amharic text. We collected 1700 idiomatic and 1600 non-idiomatic clause datasets from Amharic books to test the proposed model's performance. The proposed model is then evaluated using this dataset. With testing and training datasets, the proposed model achieves an accuracy of 80% and 98%, respectively. We compared the proposed model to other machine learning models like K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Random Forest classifiers. According to the experimental results, the proposed model produces promising results.
Ethnic Fractionalization, State Fragility and Economic Growth in Developing Countries: A Case of Sub Saharan Africa (SSA)

Abstract This study was aimed to investigate the link between ethnic fractionalization, state fragility, and economic growth in developing countries. 80 countries (41 from SSA and 39 from HICs) were chosen obtaining panel data spanning the years 2007 to 2020. The relationship between the three variables was estimated using the Seemingly unrelated regression (SUR) approach, with the direct influence of ethnic fractionalization on economic growth assessed first, followed by an estimate of its indirect effect via the transmission channels. The estimated empirical results revealed that ethnic fractionalization had a minimal effect on economic growth in both SSA and high-income countries. In terms of the indirect effects of the two elements on growth, there were mixed results, with some transmission channels putting a negative strain on economic growth and others imposing a positive one. In addition, we fail to confirm the assumption that ethnic fractionalization would have a strong negative impact on growth in countries where state fragility is higher. Thus, we assert that “the conventional wisdom” in the literature about the negative relationship between growth and ethnic variety could not be well-founded and robust, and that further investigation could clear up the impurity in the field.
Zen and the Art of Persistent Identifier Service Development for Digital Specimen

One of the most desired (and still missing) elements to enable the concept of Digital Extended (Webster et al. 2021) Specimens is a persistent identifier (PID) for the new digital specimen object. Digital Specimens are created to act as a digital surrogate of the physical objects. Digital Specimens contain all data relevant to the specimens as well as derived data like genetic sequences, trait information, and references to publications, species and environmental information. A PID for the Digital Specimen is thus essential to link it to the extended information. Furthermore, the extended information also needs PIDs to create unique and resolvable references to enable bidirectional linking. DiSSCo, Distributed System of Scientific Collections, has done extensive work to select the most appropriate PID scheme (Hardisty et al. 2021) and design a PID infrastructure for the pan-European specimen collections. The design was created in the Biodiversity Community Integrated Knowledge Library project (BiCIKL) with funding from the European Commission. The draft design has been discussed with technical specialists in the joint DiSSCo and Consortium of European Taxonomic Facilities (CETAF) community, with international stakeholders like GBIF and iDigBio. The draft was also presented at the 2022 conference of SPNHC (the Society for the Preservation of Natural History Collections) for further feedback, after which it was finalised. This talk will provide a short overview of the key elements in the design of the Persistent Identifier system for Digital Specimens such as the metadata schema, a human friendly string format, and PID lifecycle with support for state changes of the physical object such as splitting and merging. We will illustrate this by showing the current status of development. The Digital Specimen forms the backbone of the FAIR (Findable, Accessible, Interoperable, Reusable) services (Addink et al. 2021) in development by the DiSSCo Prepare project, a project to prepare for the new research infrastructure which currently involves 170 institutions in 23 countries holding an estimated 1,5 billion specimens. The Digital Specimen is a FAIR Digital Object with a PID and machine actionable metadata to make it FAIR. The PID service ensures the identifiers’ integrity and preserves these linkages, improving the FAIR quality of all specimen data. The talk will describe the system design and current test deployment setup, as well as delve into a few technical details of the Handle Server architecture, PID Kernel records, and a roadmap for the service development. The design and test work are done under the auspices of the BiCIKL project that aims to foster collaboration between infrastructures and develop bidirectional connections between the data so that they become part of a big FAIR data pool seamlessly available to researchers (Penev et al. 2022).
Constructing a Culinary Tourism Recommendation System Based in Palembang, Indonesian Using Weighted Product Method

Based on the survey that conducted on 33 respondents from the Palembang peoples and non-Palembang peoples, got the result that state, most respondents state they had trouble to deciding which restaurant to go to when visiting Palembang and most respondents need 20 to 60 minutes to determine which restaurant that they want to order the food in Palembang area. Therefore, this study will construct a restaurant recommendation system based on the Palembang region and implementing the Weighted Product method and also adding window maps features. This study aims to assist Palembang and non-Palembang users to choosing system-recommended restaurants in Palembang. The result of this study shows that the recommendation system has successful outcomes in helping the users with great overall feedback showing a high satisfaction level of 89.93%.
A FAIR based approach to data sharing in Europe

Abstract The European fusion research activities have, over recent decades, generated a vast and varied set of data. The volume and diversity of the data that need to be catalogued and annotated make the task of organising and making the data available within a broader environment very challenging. Nevertheless, there are strong scientific drivers as well as incentives and mandates from national research agencies suggesting that a more coherent approach to data referencing, dissemination and sharing would provide strong benefits to the fusion research community and beyond. Here, we discuss the technical requirements and developments needed to transition the current, and future, range of fusion research data to an open and Findable, Accessible, Interoperable, and Reusable data sharing structure guided by the principle ‘as open as possible, as closed as necessary’. Here we propose a set of recommendations and technical implementations needed to form a European data sharing environment for the fusion research programmes. Consistency with the emerging IMAS (ITER Integrated Modelling and Analysis Suite) infrastructure is considered to facilitate future deployments.
An Improved Logistic Regression Method for Assessing the Performance of Track and Field Sports

Track and field is an important part of sports. Track and field athletes are an important reserve force for the development of national sports. An accurate assessment of track and field athletes' performance can help them develop more appropriate training programs and improve their performance. In order to assess the performance of track and field athletes better, this paper proposes an improved logistic regression method. Firstly, this method uses factor analysis to reduce the data dimensions of the factors that affect the performance of track and field athletes, and uses the principal component analysis to select common factors and their corresponding values. Then, according to the common factors, a binary logistic regression model is established to evaluate the performance of track and field athletes. Experiments show that the method can effectively evaluate the performance of track and field athletes and is suitable for athletes of different track and field sports. It has high accuracy, fast evaluation efficiency, and good universality of performance evaluation. For different numbers of athletes, the proposed method has a lower error evaluation index, higher evaluation accuracy, and better evaluation quality. Compared with the other two methods, the proposed method has the shortest evaluation time and is more effective for the performance evaluation of track and field athletes.
Review Made on the Content-Based Image Recovery

Abstract: Images recovery mean that recovering the authentic images from which the images recovered from the feature database, as you will see inhere we talked in the paper all about the latest methods and technique in the field based on image recovery and image processing. Content Based Image Recovery (CBIR) is fastest and fastest developing research in field and in the place of the Graphic Processing. Translated methods facilitate faster image recovery, queries for image recovery system, image based on image processing (CBIR) in combination with multimedia encoded features, and outside many image recovery techniques out there. Some futuristic researches guide us to the present here to evaluate the research in this area and infield of image recovery.
A Survey on Approach for Efficient and Secure Data Encryption Scheme for Spatial Data

Abstract: In spatial applications location data of the users continuously processed in un-trusted servers, this may cause to user privacy. Location information of the users is very sensitive data like their meeting information, residential and official location information’s. In present solutions of the un-trusted servers may have the several problems and limitation like data security, data availability, request processing etc. In general cloud environment provides lot of features to solve many problems with low cost. Elastic cloud environment will provide successful solutions for spatial data and user’s data. Many security algorithms were proposed and for cloud data security and many Locations Based services (LBS) security functionalities were proposed in many researches. In this paper we survey on various secure location-based techniques and cloud data security architectures.
Reduction of Speckle Noise in SAR Images With Hybrid Wavelet Filter

Abstract: Images produced by synthetic aperture radar (SAR) are crucial for observing and visualizing situations. However, speckle noise makes it difficult to assess SAR images since it reduces image quality and leads to incorrect interpretation. Multiplicative noise features can be found in speckle noise. For the past few years, experts have concentrated on despeckling or speckle reduction. However, the majority of the current efforts showed a loss of edge information. Since wavelet transform and bivariate shrinkage functions have many advantages, this study is devoted to designing a method for speckle removal. After performing a logarithmic transformation to turn multiplicative noise into additive noise, the suggested approach next applies a Lee filter. Then, a wavelet transform was used to breakdown the filtered image. Prior to applying the median filter, the bivariate shrinkage function was used to estimate each coefficient. The simulation results demonstrate that the suggested approach outperforms previous work and several traditional methods
PENERAPAN MODEL PEMBELAJARAN KOOPERATIF TIPE MAKE A MATCH UNTUK MENINGKATKAN HASIL BELAJAR PADA SISWA TENTANG PERSATUAN DAN KESATUAN DI KELAS V UPT SDN 211 PINRANG

PThis research is motivated by the learning outcomes of students who have not reached SKBM in class V UPT SDN 211 Pinrang. The approach applied is a qualitative approach using the type of classroom action research. The subjects in this study were teachers and students of class V UPT SDN 211 Pinrang, totaling 10 students. Data collection techniques used are observation, tests, and documentation. This research was conducted in two cycles. Based on the data obtained, the results of the research in the first cycle show that the learning process is in good qualification (B), student activities are in good qualification (B) and the learning test results are in sufficient qualification (C). While in cycle II the research results on the learning process have increased with good qualifications (B), student activities are in qualification (B) and learning test results also increase to good qualifications (B). apply the make a match type cooperative learning model to the fifth grade students
CertiSafe: A Blockchain Based Certificate Validation and Safety System

Abstract: In every career progression, we receive certificates of degrees and achievements. In the recent times as the technology advances, we also have people cheating by forging and duplicating certificates. We see people duplicating certificates by forging their names on the genuine certificates. As mostly institutions have digitalised the paper certificates and now by adding this system at the issuing and receiving party can make the entire process safe and reliable. This paper proposes a system where the issuing party of the certificate can use this system to safeguard the certificates from duplication and the third party or receiving party can reupload and check if the certificate is genuine and not tampered.
Intricate Twitternlp Modelling

Abstract: In this research, we introduce TweetNLP, a platform for social media Natural Language Processing (NLP). An extensive range of NLP tasks are supported by TweetNLP, including standard focus areas like sentiment analysis and named entity recognition as well as social media-specific tasks like emoticon prediction and offensive language detection. Task-specific systems run on moderately small Transformer-based language models that are focused on social media text, particularly Twitter, and don't require specialized hardware or cloud services to operate. TweetNLP's major contributions are: (1) an integrated Python library for a contemporary toolkit supporting social media analysis using various task-specific models tailored to the social domain; (2) an interactive online demo for codeless experimentation using our models; and (3) a tutorial covering a wide range of typical social media applications.
A Study on Astrometeorological Relationship between Planet Azimuth and Temperature

Temperature is one of the key weather parameters, which is a necessity for all life on Earth. Any variation from the normal can impede the physical, chemical, and biological processes of life. Extremes would produce permanent changes that would halt the plant's growth and may cause complete withering. Advance information on temperature events will be helpful in protecting the plant and sustain the productivity under any temperature related disasters. Astrometeorology is one of the oldest organized knowledge systems that interplay between planetary movement and weather. In Tamil Nadu Agricultural University (TNAU), Astrometeorological weather forecast rules for rainfall, wind speed and cyclone events were already well defined. In continuation of this research, identification of Astrometeorological rules for the temperature events had been taken up during 2021-2022 at Agro climate Research Centre, TNAU, Coimbatore. Hourly temperature data from 2011-2016 was collected for 30 districts of Tamil Nadu. In each districts one particular location is selected and is correlated with ephemeris developed for a particular location using Alcyone ephemeris calculator. The findings clearly demonstrated the differential impact of individual planets and their azimuth on the temperature events. The study revealed that low temperature events were influenced when most planets are away (271- 300 degree azimuth) whereas the high temperature events were influenced by the planets that are directly above the location (91 to 120 degrees azimuth) and the in between temperature events were influenced by both 61-90 and 241-270 degrees. The specific azimuth of the Sun, Mercury, Venus, Jupiter, Saturn, Uranus, and Neptune had a makeable influence on a particular temperature event, however all the azimuths of the Moon and Mars had only a mild effect on any temperature event. Based on the results, Astrometeorological rules for the temperature events could be defined and used for the development of hybrid forecasting by overlapping the astromet forecast output on the numerical forecast output. This will produce more accuracy than individual forecast, reduce missing forecast, falls alarms, and improve the usability of forecast.
Voice Chatbot for Hospitality

Chatbot is a machine with the ability to answer automatically through a conversational interface. A chatbot is considered as one of the most exceptional and promising expressions of human computer interaction. Voice-based chatbots or artificial intelligence (AI) devices transform human-computer bidirectional interactions that allow users to navigate an interactive voice response (IVR) system with their voice generally using natural language. In this paper, we focus on voice based chatbots for mediating interactions between hotels and guests from both the hospitality technology providers’ and guests’ perspectives. We developed a hotel web application with the capability to receive a voice input. The application was developed with Speech recognition and deep synthesis API for voice to text and text to voice conversion, a closed domain question answering (cdQA) NLP solution was used for query the answer.
Improving English Vocabulary Mastery through Audio Lingual and Drill Methods for Class VII-I in English Subjects at MTs “Wali Songo” Ngabar Ponorogo

This study was structured with the aim of knowing the effectiveness of the Audio Lingual and Drill learning method in improving vocabulary mastery of the VII-I grade students of MTs "Wali Songo" Ngabar Ponorogo. The subjects of this study were students of class VII-I, totaling 25 female students. This research is an action research classroom and was conducted in two cycles. Each cycle is carried out with the stages of planning, implementing, observing, and reflecting. This research was conducted in the even semester of the 2021/2022 academic year, namely in December. Data were analyzed descriptively and presented in the form of tables and graphs. The results showed an increase in students' vocabulary mastery in English, namely in the first cycle by 64% then in the second cycle, it increased to 80%. It is said that there is an increase of 16%, with the use of the Audio Lingual and Drill method in English subjects can improve the understanding and mastery of words of students in grades VII-I MTs “Wali Songo” Ngabar Ponorogo.