Reviewerly/exHarmony huggingface dataset:
ANALYSIS OF THE SIGNAL TO NOISE RATIO IN USE OF 15% KVP RULE METHOD IN THE RADIOGRAPHY EXAMINATION SUPINE AP CHEST

The exposure factor is one of the important parameters in optimizing the radiographic examination. This study aimed to analyze the value of the Signal To Noise Ratio (SNR) against the use of the 15% kV rule method in the examination of Chest AP Supine. Descriptive quantitative research method conducted in the laboratory of the Department of diagnostic imaging and radiotherapy, Health Polytechnic of the Ministry of Health, Jakarta 2, using computer radiography, X-rays, piranha radiation detectors, and anthropomorphic phantoms, with statistical analysis of the Pearson test to determine the level of relationship between SNR and Exposure Index (EI). Against the 15% kV rule method, then the one-way ANOVA test to determine the effect of the 15% method on changes in value. The results of the Pearson test obtained a p-value of 0.820 with a strong relationship between SNR and EI against the 15% kV method. Therefore, using an exposure factor of 15% kV rule method makes it possible to control the SNR and EI values. The one way ANOVA test has a p-value of 0.943, so there is no significant difference in the SNR value to changes in the exposure factor with the 15% kV rule method so that the optimization of the exposure factor with the 15% kV rule method can reduce the radiation dose while maintaining the image quality radiographic
Out-of-Field Junior High School Music Teachers in the Online Teaching of Music Amidst COVID-19 Pandemic

This study is a transcendental phenomenology that explores the lived experiences of the out-of-field junior high school music teachers in the online teaching of music amidst the COVID-19 pandemic.The outof-field teaching phenomenon simply refers to teaching outside one's qualifications and expertise.Through purposive sampling, nine participants from public junior high schools in Tacloban City, Philippines with outof-field music teachers provided significant responses relative to their lived experience which was then treated with thematic analysis.The results suggest that the success in teaching music online based on the lived experiences of the out-of-field music teachers primarily depends on the issues of teacher qualification, support for adequate resources, and professional development training.Moreover, factors such as internet connectivity and the teacher's competence are directly affecting the students' interest to learn and the teachers' morale towards their profession.Efficiency in teaching music online, on the other hand, as experienced by the out-offield music teachers is attainable with their best practices in online music teaching.Therefore, out-of-field teaching must be alleviated since teaching music online entails a holistic approach to content mastery, support for online teaching, equipment, and training for professional development.
Real-Time Communication over Blockchain

Abstract: Blockchain Technology becoming popular with time giving rise to Web 3.0 and this technology will change the way we see the Internet. Blockchain is a decentralized, digitally dis- tributed immutable ledger that allows real-time communication to happen securely; this is the reason we need blockchain in a social networking websites as these websites keep the data on centralized servers that can be risky as the data can easily be stolen and can easily be distributed with third parties without the need of users consent. But with the help of Blockchain and DApps, we can create a reliable and efficient way to share messages and media on secured networks without any third party interference. In this paper, we are going to discuss how we make use of smart contracts and peer-to-peer networks like Ethereum to create such applications and allow users to share their messages and other forms of information without any fear of data getting lost or being shared without user consent, we also going to discuss how this method is different from the current method which social networking websites use to secure users data, and how Web 3.0 is going to be different from current Web 2.0 in terms of a social network. Index Terms: decentralization, blockchain, Apps(Decentralized applications), Ethereum
IDENTIFICATION OF SCAMS OF CHEQUES

Scams of cheque is being most common attacks done by the fraudsters against consumers. Currently, there is no effective solution to validate cheque and check fake ones instantly. The bank requires a lot of time or a day to detect and eliminate the scam. More effectively, our methodology helps the banks to send information about provided cheque and used ones,by securing user’s credential . Fake cheque come in many forms. They might look like business or personal cheque, cashier’s cheque, money orders, or a cheque delivered electronically. Charity trust have their Register login and approved by main branch and charity needed send to user and if user need to help charity they can help by give cheque to charity which passed to bank and amount is transaction to charity and the details about charity amount transaction will send to main branch and maintained by main branch.If response received from concern customer only, transaction will be happened. If the fake check was detected , then the details of customers which been accessed, will be encrypted using SHA -1 algorithm .So that The user’s credential will be safe . The theft user account will be removed by the Admin. Keywords : Charity , Bank, Public , login ,Admin,SHA -1,Encryption.
Housing Based on Communal Connectivity to Enhance Resilience in Response to Rob Flood

Rob flood is one of flood types caused by the increasing sea level rise submerging in area with lower level than the sea surface. With the hazard occurring regularly, this will be able to threaten the community’s vulnerability in responding to rob flood which includes social, economic, and physical impacts. With the existing housing precedents that lacks in providing a multifaceted aspect between users and its built environment, this paper aims to offer design concept based on communal connectivity to increase the resilience of community in responding rob flood. Communal connectivity focuses on the concept where communities are able to adapt and mitigate either pre-disaster, during disaster, and post-disaster. The study takes place in Semarang at Jl. Ngilir Timur that regularly has rob flood each year with 2050 as the time context. The typology offered in this design is a co-housing settlement with community resilience approach, where this approach focuses on ways to increase the communities‘adaptive capacity. Using force base framework, the main concept offered is a settlement with communal connectivity concept which focuses on several aspects in formal, spatial, material, construction, landscape, and utility. The main concept of this design mainly discusses on social connectivity and supported co-housing in formal and technical explorations which will be able to enhance community resilience in social, economy, and environment aspects.
Implementation of K-Means Clustering on Poverty Indicators in Indonesia

This study aims to cluster all districts/cities in Indonesia related to poverty indicators. The attributes used are poverty gap index and poverty severity index. The data used comes from BPS. The method used is K-Means clustering, and the results show that by using the elbow and silhouette index methods, the optimal number of clusters is 2, where for cluster 1, it can be defined as a cluster with an area with a high poverty gap index and poverty severity index compared to cluster 2. As a result, cluster 1 has 42 districts/cities, and 472 for cluster 2.
THE APPLICATION OF MARKOV CHAIN MODEL TO CALCULATE PREMIUM AND RESERVE OF ENDOWMENT INSURANCE

The calculation of premiums and reserves are two essential parts of insurance. The calculation of premiums and reserves in life insurance involves using mortality tables. This research constructed a mortality table for 20-year endowment insurance using the Markov chain model. Two reasons make the policy inactive, namely death or withdrawal. The initial age used in this research is 30 years. Meanwhile, the maximum age to join this life insurance is 40 years. The mortality table that has been obtained is used to calculate premiums and reserves. Furthermore, from the research done, it was found that the age of entry to become a member of endowment insurance affects the number of premiums that must be paid. Meanwhile, the number of reserves required will increase with the increase of customers and the period of calculation of reserves
Analysis of English Cultural Teaching Model Based on Machine Learning

According to the world population, nearly five billion people use mobile phones in their daily lives, and this has increased by 20% in the last twelve months compared to the previous report. An average survey conducted by researchers to find the amount of data consumed in a month by every mobile phone in the world has finally resulted in 45 exabytes of data being collected from a single user within a month. In today's world, data consumption and data analytics are being considered as one of the most important necessities for e-commerce companies. With the help of such collected data from a person, it is possible to predict the future signature or activity of the person. If 45 terabytes of data can be stored for a single user, determining the average calculation and amount of data to be collected for five billion users appears to be much more difficult. More than the human working concept, it looks like it would be difficult for a traditional computer system to handle this amount of data. To study and understand a concept from machine learning and artificial intelligence requires quite a collection of data to predict according to a person's activity. This article explains the roles of faculty and students, as well as the requirements for academic evaluation. Even before the pandemic, most people did not have any idea about the online teaching model. It is only after the disability of conducting direct (offline) classes that people are forced to get into the online world of teaching. Nearly 60% of countries are trying to convert their education systems to such online models, which improve communication between students and teachers and also enable different schemes for students. Big data can be considered as one of the technological revolutions in information technology companies that became popular after the crisis of cloud computing. A support vector machine (SVM) is proposed for analyzing English culture teaching and is compared with the traditional fuzzy logic. The results show the proposed model achieves an accuracy of 98%, which is 5% higher than the existing algorithm.
Perancangan Portable Continuous Passive Motion (CPM) sebagai Alat Bantu Rehabilitasi Fraktur Lutut Pasca Operasi Berbasis Internet of Things (IoT)

&lt;p&gt;&lt;em&gt;One of the steps needed in patients with fractures of the knee joint is therapeutic exercises guided by physiotherapists. Therapeutic exercise is a physiotherapy modality by moving the joints both actively and passively. Inspired by this, the Portable Continuous Passive Motion (CPM) tool was created which is a physiotherapy aid for patients after surgery or knee surgery. Portable Continuous Passive Motion (CPM) has been developed based on IoT. Portable Continuous Passive Motion (CPM) uses Arduino LoRa as a micro controller, a stepper motor as a driver and uses a software application as a controller. The form of this research is research and development. From the results of the development, it can be concluded that Portable Continuous Passive Motion (CPM) can be useful for postoperative fracture patients as a practical and flexible postoperative manual therapy tool.&lt;/em&gt;&lt;/p&gt;
Revisiting Paratone Prosodic Features with the EIIDA corpus

This paper discusses the prosodic properties of the paratone, the oral paragraph of speech.Using manually annotated paratones and automatic prosodic labels on the EIIDA corpus, we re-examine the claims proposed by Tench (1996).We show that rhythmic cues to signal paratone boundaries seem to be more reliable than absolute pitch values.
Third-party enabled auditing for uniqueness-based integrity and data sharing with information hiding

The majority data are now kept in the cloud. There are many Cloud storage applications used to exchange data that range from normal to highly sensitive. Among the most essential security measures in cloud is Cloud auditing. It is the process of validating the reliability of data stored in the cloud. As of the inevitability of hardware problems, system failures and errors by people these data may be corrupted or lost. An efficient auditing system to determine whether or not the data is corrupted is a challenging task among the recent research. This paper proposes a third-party enabled auditing methodology to ensure data integrity, privacy data sharing and protect against outside attackers in the public cloud. In this proposed method, the record / data owner generates signatures or add sanitizer before importing sensitive data blocks into the cloud. The record blocks that report sensitive data are sanitized, and the signatures of those records blocks are converted into legitimate ones for the sanitized report. As a result, the records saved in the cloud have the identical signature. Then a third-party auditor is implemented to confirm the cloud's storage accuracy by validating the reliability of the cloud records on the person's behalf.
Measured Composite Collision Models: Quantum Trajectory Purities and Channel Divisibility

We investigate a composite quantum collision model with measurements on the memory part, which effectively probe the system. The framework allows us to adjust the measurement strength, thereby tuning the dynamical map of the system. For a two-qubit setup with a symmetric and informationally complete measurement on the memory, we study the divisibility of the resulting dynamics in dependence of the measurement strength. The measurements give rise to quantum trajectories of the system and we show that the average asymptotic purity depends on the specific form of the measurement. With the help of numerical simulations, we demonstrate that the different performance of the measurements is generic and holds for almost all interaction gates between the system and the memory in the composite collision model. The discrete model is then extended to a time-continuous limit.
THE IMPLEMENTATION OF SCHOOL OPERATIONAL ASSISTANCE AT THE BORDER

The government has made various efforts to increase school participation rates such as through the provision of School Operational Assistance (BOS) which has been operating since 2005. However, in 2019 it was noted that many of the population of Suruh Tembawang Village were illiterate and did not graduate from Elementary School. Therefore, this study was conducted to describe the implementation of the BOS in two schools in Suruh Tembawang Village. This research used the descriptive method with a qualitative approach. The results showed that part of the BOS funds in the schools of Suruh Tembawang have been used in accordance with the provisions stipulated in Permendikbud Number 1 of 2018. However, expenditure of the BOS funds on infrastructure and maintenance had not been properly observed. In terms of teaching staff and administrations, many teachers, including the school principals were often unavailable on site. The community members interviewed expressed their disappointment in the implementation of the BOS funds, particularly on how the school administration used the funds for the operation of the schools. This was the result of a lack of community engagement, a lack of supervision, and a lack of transparency. In order to maximize the use of BOS funds in both schools, the schools must involve the school committee and its members, village officials, parents of students in planning, budgeting, and managing the BOS funds.
Covid-19 Face Mask Detection and People Count

Abstract: During this pandemic the problems faced was shortage of testing services, vaccines and poor medical care all these lead to lockdown for a long run which affected our daily lives. During this pandemic the problems faced were shortage of testing services, vaccine and poor medical care all these lead to lockdown for the long run which affected our daily lives. The prevention for this problem was to wear masks in public areas. Facemask detection had seen remarkable growth in the image processing and deep learning domain. Facemask detection is already an existing concept in which they had used different algorithms and techniques to show better results. The proposed system in this project is developed to avoid mask-less people from entering the desired places by detecting face-mask, and sending a signal to an Arduino device that connects to the sensors and counts the people while entering and exiting. This helps to maintain the social distancing inside those places and limit the Total number of persons. If the total number of people count increases, the Arduino microcontroller will give the buzzer alarm to notify the person. In This project, we use live detection and identify either the person wears a mask or not. Therefore, this proposed approach will make a significant change in the public healthcare system. Keywords: Deep Learning, Sensors, Computer Vision, Convolutional Neural Networks (CNNs), public Safety, face mask detection, OpenCV, COVID-19.
Computer Vision Based System for Mask Detection

Abstract: Coronavirus disease is the latest epidemic that forced an international health emergency. It spreads mainly from person to person through airborne transmission. Community transmission has raised the number of cases over the world. Reports indicate that wearing face masks while at work clearly reduces the risk of transmission. Many countries have imposed compulsory face mask policies in public areas as a preventive action. Manual observation of the face mask in crowded places is a tedious task. Thus, researchers have motivated for the automation of face mask detection system. An efficient and economic approach of using AI to create a safe environment in a manufacturing setup. A hybrid model using deep and classical machine learning for face mask detection will be presented. The face mask recognition is developed with a machine learning algorithm through the image classification method: MobileNetV2. A face mask detection dataset consists of with mask and without mask images, we are going to use MobileNetV2 to do real-time face detection from a live stream via our webcam. We introduce face mask detection that can be used by the authorities to make mitigation, evaluation, prevention, and action planning against COVID-19. The steps for building the model are collecting the data, pre-processing, split the data, testing the model, and implement the model. The built model can detect people who are wearing a face mask and not wearing it at an accuracy of 96 percent. This will help track safety violations, promote the use of face masks, and ensure a safe working environment
A Preliminary Study on Learners’ Perception on Out of Class Autonomous Vocabulary Learning Strategies

The current study tries to explore learners’ perception of out of class autonomous vocabulary learning strategies. The respondents were from one tertiary institution in Malaysia from the Diploma in Plantation and Industrial Management program. Questionnaires were distributed via the google classroom platform to 30 students because of the covid 19 pandemic where classes were conducted online. Data gathered were analysed using descriptive analysis based on percentages. Online distance learning (ODL) has taken place during this pandemic. Findings show the three most preferred ways to find meanings of the unknown words outside of class time are checking the meanings of the words, reviewing the new learnt words and encouraging themselves to speak in English using the words. On the other hand, the least preferred strategy is going to the access center or library or consulting online sources. As the findings show, it is vital for learners to be autonomous since some courses will still be conducted on-line even when the cases of covid 19 reduce later. By being autonomous learners will not depend a lot on lecturers and activities conducted in the classroom as time spent in the classroom is limited.
Canva and Collaborative Learning in Virtual Environments with Students from the Private Universities of Lima-Peru

The use of digital tools in the educational sector has generated great impacts in the development of virtual classes, since they provide the possibility of interaction between students to carry out work in groups, such is the case of Canva, which facilitates the creation of online infographic materials with creative designs, through the active contribution of each of the members, which can be evaluated in real time by the teacher. The general objective of the research was to determine the relationship between the use of Canva in collaborative learning in virtual environments with students from private universities in Lima. The study was of a basic or pure type, with a quantitative approach, correlational-causal level, transactional design and explanatory level. The sample was obtained by simple random probabilistic sampling and was made up of 217 participants; the technique applied was the survey, the instruments were two questionnaires validated by the judgment of four experts, with a Cronbach's Alpha (0.982 and 0.976), the Descriptive and inferential statistical analysis was performed using the IBM SPSS Statistics 25 program. According to the results obtained, they show that the variables studied have a positive and significant correlation, since 41.1% of the variability of collaborative learning depends on the use of Canva, in the same way, 37.4% of reciprocity, 33.6% of responsibility and 32.4% of affective and positive relationships depend on the use of Canva in students from private universities in Lima-Peru , which denotes the importance of this digital tool in the interaction of students to carry out collaborative work.
CODE SWITCHING AND CODE MIXING IN #NEBENG BOY

As a social creature, human beings need society to live in. There is always a power to survive in society including being survive to communicate. In exchanging the message to one another, people use language and some strategies in purpose of being successful to deliver meaning that they want. Among those strategies, there are code switching and code mixing, which is used when people communicate in multilingual society. Code switching is when a speaker uses strategy to switch from one language to another, whether code mixing is when a speaker mix the language and use it in an utterance. In this study, the object of the research is a Youtube channel called #nebengboy. This channel hosted by bilingual talented Indonesian host who usually speak fluent both in Indonesian and English. The finding shows that there are many types of code switching and code mixing use in the conversation of this Youtube channel, both by the host and the guest. From the findings, it can be concluded that the host, uses many code switching and code mixing for some reasons. This reasons can be one of the consideration for people to create a successful and meaningful communication in multilingual society.