Reviewerly/exHarmony huggingface dataset:
A Secure Unmanned Aerial Vehicle Service for Medical System to Improve Smart City Facilities

The use of drone technology and drones are currently widespread due to their increasing applications.However, there are some specific security-based challenges in the authentication process.In most drone-based applications, there are many authentication approaches, which are subject to handover delay issues with security complexities for an attack.To end these issues, the presented research has focused on developing a novel Optimized deep learning model known as Fruit Fly based UNet Drone Assisted Security (FFUDAS) to remove the malicious attacks.Moreover, the user requests are stored in the cloud, and the stored data are trained to the drones.Hereafter, the drones can deliver medicine to the requestor's location; in that, the malicious attacks were changes the location of drones.Once the attack is identified, then the attack removal process is done.Finally, the new path location to the requested user was identified with the help of fruit fly fitness; then the medicines are delivered to the requested user's location.Furthermore, the designed procedure is executed in an NS2 platform with required nodes.The robustness of the presented model was verified by evaluating the metrics like confidential data rate, execution time, handover delay, pack perception and data delivery rate, and energy consumption.Furthermore, to identify the effectiveness of the presented work, the presented model is compared with other existing schemes.The comparison results show that the presented model has higher throughput, less execution time and handover delay.
Correction to: Multimedia Cloud Computing Systems

The book was inadvertently published with an incorrect affiliation for one of the author Xiangbo Li as “Brightcove, Scottsdale AZ, USA”. It has been updated as “Twitch Interactive Inc., San Francisco, CA, USA”
A New Method in Feature Selection based on Deep Reinforcement Learning in Domain Adaptation

In data mining and machine learning methods, it is traditionally assumed that training data, test data, and the data that will be processed in the future, should have the same feature space distribution. This is a condition that will not happen in the real world. In order to overcome this challenge, domain adaptation-based methods are used. One of the existing challenges in domain adaptation-based methods is to select the most efficient features so that they can also show the most efficiency in the destination database. In this paper, a new feature selection method based on deep reinforcement learning is proposed. In the proposed method, in order to select the best and most appropriate features, the essential policies in deep reinforcement learning are defined, and then the selection features are applied for training random forest, k-nearest neighborhood and support vector machine classifiers. The trained classifiers with the considered features are evaluated on the target database. The results are evaluated with the criteria of accuracy, sensitivity, positive and negative predictive rates in the classifiers. The achieved results show the superiority of the proposed method of feature selection when used in domain adaptation. By implementing the RF classifier on the VisDA-2018 database and the Syn2Real database, the classification accuracy in the feature selection of the proposed deep learning reinforcement has increased compared to the two-feature selection of Laplace monitoring and feature selection states. The classification sensitivity with the help of SVM classifier on the Syn2Real databases had the highest values in the feature selection state of the proposed deep learning reinforcement. The obtained number 100 is a positive predictive rate in the Syn2Real database with the help of SVM classifier and in the case of selecting the proposed feature, it indicates its superiority. The negative predictive rate in the Syn2Real database in the state of feature selection of the proposed deep reinforcement learning was 100%, which showed its superiority in comparison with 90.1% in the state of selecting the Laplace monitoring feature. Gmean in KNN classifier on the Syn2Real database has improved in the feature selection state of the proposed deep learning reinforcement in comparison to without feature selection state.
Implementasi Pemanfaatan Web Service Pada Layanan Puskesmas Kabupaten Musi Banyuasin

Information technology is currently developing very rapidly and affects various aspects of life and the profession, one of which is in the field of health services, in various places, be it health centers, clinics or hospitals. The party will definitely record in detail the medical results of someone who is receiving treatment, that is what is called a medical record. Some of the puskesmas in the Musi Banyuasin district, especially the Tanah Abang puskesmas, are located in the district. Batanghari leko still doesn't have a decentralized database which means it doesn't have centralized storage. Web service itself is a liaison that allows various systems to communicate without being affected by platform differences. Web services also provide existing services on the old system to be able to communicate with the new system without making changes to both. This study was simulated at Tanah Abang Public Health Center and Bukit Selabu Public Health Center in the Musi Banyuasin Regency with the aim of making it easier for doctors and health centers to obtain patient medical records in the shortest time.
DETEKSI EVENT PADA HASHTAG TWITTER MENGGUNAKAN DF-IDF DAN ENTROPI WAVELET

This study aims to detect event from a collection of tweets having same hashtag. Discrete Wavelet Transform (DWT) and Document Frequency-Inverse Document Frequency (DF-IDF) techniques were utilised in this research to develop and analyse the signal. Signals are developed using DF-IDF during a certain period while DWT is applied to capture the sudden change in the DF-IDF signal and display it in the form of entropy. Words that have a sudden change in signal value at the same period of time might represent an event related to the topic of the hashtag. Knowing the words will assist users to discover the event associated to the hashtag. Using 3473 tweets collected on the RIPLKY hashtag with the 20 most frequently occurring words, the results showed that DWT managed to capture the sudden change in df-idf signal related to a spike occured in the wavelet entropi. The spike was shown by three words, namely proud, sophialimx, and goals. We also found that the three words were under the same tweet, and it describes an event about the funeral of Singaporean prime minister.
Development Rime Syar'i Business &amp; Administration Management System with Rapid Application Development Method

This research aims to produce an administrative information system design to increase accuracy in data processing and the ability to provide faster information for a business and increase the accuracy of service to consumers. This study also aims to identify information system problems on the system running on Rime Syar'i business and produce a Web-based administrative information application program that includes administrative transactions to produce transaction reports and reports that are needed to facilitate business management. Rime Syar'i. The conclusion obtained from this research is that using a web-based information system, can minimize errors in data processing, increase the effectiveness and efficiency of Rime Syar'i's business work in a better direction, and ease in making reports.
Behavior Analysis and Prediction of Civil Services Staff in Occupational Functional Positions Using C4.5 Algorithm

Functional positions are not positions that can be filled by every state civil apparatus, their filling is only based on certain expertise and skills as evidenced by certain certifications and/or assessments such as passing a competency test and for promotion to functional positions it is determined by credit numbers. In carrying out their professional duties, functional positions are also independent. The high interest of state civil servants in occupying functional positions, it is necessary to make rules to avoid subjectivity in choosing functional positions, as one solution is to use data mining techniques. Data mining has an important function or method to help get valuable information and increase knowledge for its users. Data mining can be used in various disciplines, such as education, health, agriculture and government. The C4.5 algorithm has the ability to resolve incomplete attribute values ​​and produce rules that are easy to understand, this is evidenced in determining the predictions of state civil apparatus occupying functional positions as evidenced by the test results using the confusion matrix, obtaining an accuracy of 92.54% with a ratio of 80% training data and 20 test data. The information gain value obtained from the education name attribute is the main factor in determining the position in functional positions.
English-Indonesian Translation Method of Book’s Glossary

Translation is an adjustment idea of one language to a different language equitably. In doing a translation, a translator needs to apply some methods to produce an acceptable translation. Plenty of researches on translation method have been administered. However, translation method research on a book's glossary is ostensibly still under-researched in translation studies. So that, to fill in this gap, this research aimed at figuring out and describing the methods of English-Indonesian translation used in the book's glossary “An Introduction: Theories of Learning 7th Edition Book”. This research exerted a qualitative method. The objects of this research were An Introduction: Theories of Learning 7th Edition Book and its Indonesian version Theories of Learning: Teori Pembelajaran Edisi ke-7 based on Newmark’s translation methods. The data was geared by documentation. Afterward, the researchers classified the data suited to the determined table of instrument as researchers' tools in data collection. Furthermore, after elaborating the data, researchers analyzed it descriptively. The result showed that there were five out of eight translation methods applied by the translator. Three of them are concentrated on source text comprising semantic translation, literal translation, and faithful translation. While two of those are concentrated on target text, namely free translation and communicative translation.
Capsule Ambulance

Abstract: We know that multi specialist, multi talented hospitals and doctors are mostly situated in metro cities or at district level. In emergency situation, it is mandatory that a patient reached at destination in less time to save their life. While travelling inside through metro cities, there are major problem of traffic. Because of traffic ambulance will have more time to reach destination or hospital. In emergency situation millisecond time is very important. So to increase patient’s life here introduce a capsule ambulance concept. Keywords: Pillars, Start-End Station, Rope Way, Ambualnce car, Control Software, Emergency Medical Service, GPS
Aplikasi Virtual Tour Sekolah Menengah Pertama (SMP) Negeri 3 Kota Pagar Alam Berbasis Android

Technological developments are increasingly rapid, giving rise to many new innovations from technology such as virtual tours. Virtual tour is one of the information media that displays 360? panoramic images in visual form. However, the use of virtual tour applications as a promotional medium and introduction to the school environment is still very little. In this study, the author makes a virtual tour application to help parties from SMP Negeri 3 Kota Pagar Alam in promoting and introducing the virtual school environment. The application development method used in this study is the Multimedia Development Life Cycle (MDLC) which consists of six stages of multimedia development, namely Concept, Design, Material Collecting, Assembly, Tasting, and Destribution. The tools used in this research are Unity 3D, Google Street View Application. The tools used in the development are Use Case Diagrams, and Activity Diagrams. With the formation of this virtual tour application, it can make it easier for all students, teachers and the wider community to see the environment of SMP Negeri 3 Pagar Alam City virtually.
Detection and Contact Tracing of COVID-19 in Indonesia through a Red Cross Community Based Surveillance System

Purpose: As of June 30, 2021, WHO reported 181,344,224 confirmed cases worldwide and 3,934,252 deaths due to SARS CoV-2.India accounts almost 10% of the total mortality.The mutated Variants of Concern (VoC) and Variants of Interest (VoI) has acquired non-synonymous amino acid substitutions in Spike (S), ORF1a, ORF1b, Nucleocapsid (N), Membrane (M), Envelope (E), ORF6, ORF7a, ORF3a and ORF8 regions exhibiting more virulence and higher transmission rate.The S gene displaying nucleotide polymorphisms are studied for identification of major SARS CoV-2 variants circulating in India using in silico PCR-RFLP analysis.Methods & Materials: DNA sequences of major SARS beta (B.1.351),delta (B.1.617.2),epsilon (B.1.429+ B.1.427),eta (B.1.525)and zeta (P.2)] prevailing in India retrieved from GISAID database were annotated using VIPR-VIGOR4 genome annotator tool.The S gene of variants were aligned using CLUSTALW algorithm in MEGA-X with default parameters and analyzed for sequence identity using Geneious Prime v2019.2.1.Primers were designed using Primer-BLAST tool, proof-read using FastPCR v6.7.46 and PCR-amplified using Snapgene v.3.2.1.Unique restriction sites in S amplicons of each variant were subjected to online Restriction Analyzer tool.The S amplicons were digested with restriction endonucleases and the band profile of each variant were visualized in the gel simulation tool using Snapgene v.3.2.1.Results: The percentage of identical sites present in S region among SARS CoV-2 variants was found to be 98.6%.The amplified products were in the length of 3,689 and 3,698 bp.Out of 400 restriction endonucleases identified, 14 buffer-com patible enzymes were selected for single-step restriction digestion to generate unique RFLP profiles for each variant.The Bsa XI-Xcm I-Acu I triple digest showed unique banding pattern identifiers on 2% agarose gel for individual variants including alpha, eta, delta and zeta.The Apa LI-Bsa I double digest produced distinct band profiles for beta and epsilon variants. Conclusion:Our study strongly suggests PCR-RFLP analysis of Spike region can differentiate major SARS CoV-2 variants that are circulating in India.Further, quadruple digestion based wet lab experiments are underway to explore the possibility of surveillance of the major variants using a single-tube reaction followed by agarose gel-based profiling.
Impact of Online Learning of Economics in Lebanon on Acquiring Essential Skills in Light of the COVID-19 Pandemic

The sudden and recent outbreak of the Covid-19 had its impact on the way of life around the entire world; it challenged the education systems around the globe and forced schools and universities to switch to online education overnight. Several schools and universities that were formerly hesitant to change their traditional pedagogical approach had no choice but to entirely switch to online education. This study examines the impact of online learning of Economics on acquiring essential skills in light of the Coronavirus outbreak. The researchers used a descriptive-analytical approach and constructed a five-point Likert style questionnaire as a study tool. The questionnaire was distributed to a sample chosen from the population of Economics teachers in Lebanese schools. The sample consisted of 153 teachers all of which responded and their responses were valid for testing and analysis. The study reached some important findings mainly that through online learning of Economics, learners are not acquiring all of the 21st-Century skills, and the researchers had some recommendations as a result.
The Enlightenment of Children’s Language Learning Mechanism on Adult Foreign Language Learning

Children learn their mother language very quickly and effortless, while foreign language learning is extremely difficult for adults, spending more time, but very effective.This paper analyzed the same and different points between them by comparison.Hopefully, some inspiration to help adults learn foreign languages.
INVESTIGATING YOUNG LEARNERS PERCEPTION AND MORAL VALUES ON LISTENING SKILL THROUGH WATCHING MOVIE “DORA: THE LOST CITY OF GOLD”

The aim of the research was to investigate young learners perceptions and moral values on listening while English language teaching for young learner by having "Dora: The Lost Gold City" Movie at SMP Daarul Yaqiin. Method of research used descriptive analysis to explore young learner’s perception and moral values. Instrument used were observation, questionnaires and interviews. Interviews and questionnaires were conducted in the seventh grades of SMP Daarul Yaqiin. It was followed by 50 young learners who join listening class. The results of this study indicate; (1) Young learners give a good perception about the use of the movie "Dora: The lost city of gold" (2) Young learners give positive feedback to attract listening skills by using the movie "Dora: The lost city of gold" in learning, and (3) young learners get moral values by watching the movie "Dora: The lost city of gold". The advantages of using the movie "Dora: The lost city of gold" in learning listening are; it helps young learners understanding the subject easily, young learners were happy, gave them motivation to learn English for young learner. From these finding the conclusion was the used of the movie "Dora: The lost city of gold" in English listening easy understanding material has positive response from young learners and also provided several benefits for them especially moral values for young learners.
08 - Configuring Non-Image-Based Clinical Data to Support Application of Computer Vision Techniques: Application to Non-invasive Discrimination of PHTN

Logistic Regression? ConvolutionalNeural Network? Both?Can we create an accurate model to discriminate between PAH and PVH using non-invasive echocardiographic and patient characteristics?
Utilization of Library Resources Among Graduate Students of Leyte Normal University (LNU)

&#x0D; &#x0D; &#x0D; &#x0D; This study assessed the utilization of the resources of the Leyte Normal University Learning Resource Center by the graduate students enrolled in various graduate curricular program offerings for the AY 2018, 2019, and 2020. The assessment concentrated on the subject area, borrowers per program, professional journals and magazines, and databases, e-books, and internet connectivity during the academic years 2018, 2019, and 2020. In this context, utilization was focused. Utilizing the survey design, statistically treated data showed that books are commonly borrowed resources and that borrowing frequency is dependent on the enrollment of a curricular program offering. Bulk of borrowers were recorded for AY 2018 and 2019. Taking things holistically, the general circulation of the library is deemed helpful to its immediate users. An intervention plan was prepared further to promote the richness of the resources in the library and consequently attract more users.&#x0D; &#x0D; &#x0D; &#x0D; &#x0D;
Real Time Profile Analysis and Fake Detection Model for Improved Profile Security in Online Social Networks

The problem of social network security has been well studied.Numbers of approaches are identified towards securing the profile of social network users and identifying the fake profiles.Still the methods suffer to produce efficient results on detecting fake profiles.To improve the performance, an efficient profile analysis and fake detection model is presented in this article.The proposed Real Time Profile Analysis and Fake Detection Model (RTPAFDM) works on three phases: first the Post Level Trust Analysis (PLTA) is performed, which monitors the post updated on every day and share the posts internally with other users to claim the trustworthy of the post which computes the value of User Post Trust Weight (UPTW); second the method performs Profile Level Trust Analysis (PrLTA) which extracts the profile information like user name, personal details, contact details and friends list.According to the information extracted, the method searches on the entire social network to measure the Profile Match Similarity (PSM).Based on the PSM value, the method would identify the originality of the profile; finally, the method performs Profile Historic Trust Analysis (PHTA) which works on the earlier posts made and their truth values.It computes the value of Historical Trusted Post Weight (HTPW).Using the result of all these trust analysis values, the profile security and fake detection is performed.The method is evaluated with Twitter data set and achieved fake detection accuracy up to 97% and supports the improvement profile security efficiently.
PENGAMANAN MIKROTIK ROUTERBOARD DARI SERANGAN KEAMANAN DENGAN NOTIFIKASI BOT TELEGRAM

The task of the network administrator is also not easy, this is because an admin must secure his network from an attack that can cause the network router to go down until it is damaged. There are so many ways to prevent a person/company from being able to provide optimal service, one of which is to attack the router using a DDoS attack type. Therefore, network security is needed with the Intrusion Detection System (IDS) method. An intrusion Detection System (IDS) is a method used to detect suspicious activity in a system or network. In this study, IDS is used as a deterrent and sends notifications of DDoS attacks on Mikrotik routers via Telegram bots. The process of testing DDoS attacks in the form of ping flood, SYN Flood and UDP Flood, telegram bot notifications were successfully implemented quite well, where IDS sent notifications via network admin telegram bots.
E-learning Platforms Used by the EFL Teacher during Distance Learning

Due to the Covid-19 outbreak, learning activities had to be changed from face-to-face activities in class to distance learning. The e-learning platform has been essential to use since the covid-19 outbreak. However, online learning has several obstacles, such as the lack of facilities owned by students. Some parents and students face a problem during distance learning because they do not have a computer or android device. This study aims to analyze the bold learning platform used by EFL teachers during the covid-19 outbreak and analyze the use during distance learning. This research uses a descriptive qualitative approach. Observations and interviews were used as methods in this study. The subject of this research is an EFL teacher. This study indicates that EFL teachers entirely use WhatsApp as an e-learning platform to carry out teaching activities during distance learning using several steps. First, the teacher sends a greeting, reviewing the previous material and information on today's material. Second, the teacher provides additional material in e-modules and learning videos. Third, the teacher gives some assignments to students. Fourth, the teacher collects the collection of assignments. This research can be used as a reflection on how the implementation of classroom language used by the EFL teacher during distance learning.