Reviewerly/exHarmony huggingface dataset:
The effect of educational videos on the level of community knowledge and awareness of the importance of treatment in prosthodontics

In addition to chewing and speaking, teeth play an important role in a person's appearance. The concerns that are often experienced by patients are usually caused by the opinion of the patient who is not included in the planning of treatment in the field of prosthodontics, the patient's understanding and knowledge about treatment in the field of prosthodontics is minimal, and the patient's attitude towards treatment in prosthodontics. Counseling is one of the efforts to increase understanding and knowledge related to prosthodontic treatment. In this study, the patient's level of understanding and knowledge will be evaluated after and before watching the educational video of Prosthodontics, Faculty Dental Medicine, Universitas Airlangga. This research is an analytic observational study with a cross section-al approachand used used a questionnaire before and after being given an educational video. After watching the educational video, there was an increase in knowledge about follow-up care after tooth extraction from those who previously did not know to know as much as 42.5%. It was concluded that there is an increase in public knowledge and awareness about the impact of tooth loss and restoration options after watching educational videos.
SUPPORT VECTOR MACHINE (SVM) ALGORITHM FOR STUDENT SENTIMENT ANALYSIS OF ONLINE LECTURES

Covid-19 was first discovered in Wuhan City, Hubei Province, China at the end of December 2019. According to the WHO (World Health Organization) as of October 13 2020, the number of positive confirmed cases of Covid-19 reached 38,103,332 cases, while in Indonesia the number of cases exposed to Covid-19 reached 268.85 cases and is likely to increase every day (Covid-19 Handling Task Force, 2020). The formulation of the problem that will be raised from this research is to measure the level of accuracy obtained from the results of classifying sentiments of distance learning during the Covid-19 pandemic using the Support Vector Machine (SVM) method and measuring the impact of implementing online lectures during the Covid-19 pandemic. The data used in this research is in the form of public responses regarding distance learning policies implemented during the Covid-19 pandemic, taken from January to March 2022. The data obtained will then be divided into training data as much as 80% of the the total data and test data is 20% of the total data. Based on the results of testing the previous Support Vector Machine classification model, the accuracy value for the entire system can be calculated at 70.8%. Based on the results of testing the previous Support Vector Machine classification model, the accuracy value for the entire system can be calculated at 70.8%.
Analisis Photoplethysmography Jarak Jauh dalam berbagai Kondisi Pencahayaan

One of the limitations of photoplethysmography (PPG) using a contact sensor to estimate the heart rate is that the sensor must be attached directly to the patient's body. rPPG (remote-Photoplethysmography) can remotely monitor a patient's heart ratebased on an image. However, rPPG has limitations in instances where this technology is directly affected by the lighting conditions and direction of the observed subject. This study used rPPG based on the Green Channel and HSV (Hue, Saturation, and Value) color model to estimate heart rate under different lighting conditions. Analysis, computational methods,and image transformation functions are used for data selection, denoising, colormodel conversion, spectral analysis, and visualization to extract biomedical signals from inputs. The estimatedheart rate was then derivedusing spectral analysis on videostaken from an area of interest on the forehead. Compared to the ground truth, theaverage percentage error from the facial lighting tests conducted at 260 lux, 19 lux, and 11 lux for the Green Channel color modelis 0.038, 0.118, and 0.229, which is less than the HSV's error of 0.095, 0.212, and 0.247.
Eunomia: Enabling User-specified Fine-Grained Search in Symbolically Executing WebAssembly Binaries

Although existing techniques have proposed automated approaches to alleviate the path explosion problem of symbolic execution, users still need to optimize symbolic execution by applying various searching strategies carefully. As existing approaches mainly support only coarse-grained global searching strategies, they cannot efficiently traverse through complex code structures. In this paper, we propose Eunomia, a symbolic execution technique that allows users to specify local domain knowledge to enable fine-grained search. In Eunomia, we design an expressive DSL, Aes, that lets users precisely pinpoint local searching strategies to different parts of the target program. To further optimize local searching strategies, we design an interval-based algorithm that automatically isolates the context of variables for different local searching strategies, avoiding conflicts between local searching strategies for the same variable. We implement Eunomia as a symbolic execution platform targeting WebAssembly, which enables us to analyze applications written in various languages (like C and Go) but can be compiled into WebAssembly. To the best of our knowledge, Eunomia is the first symbolic execution engine that supports the full features of the WebAssembly runtime. We evaluate Eunomia with a dedicated microbenchmark suite for symbolic execution and six real-world applications. Our evaluation shows that Eunomia accelerates bug detection in real-world applications by up to three orders of magnitude. According to the results of a comprehensive user study, users can significantly improve the efficiency and effectiveness of symbolic execution by writing a simple and intuitive Aes script. Besides verifying six known real-world bugs, Eunomia also detected two new zero-day bugs in a popular open-source project, Collections-C.
Peter Manning 1948–2022

Peter Manning first established an international reputation with his book Electronic and Computer Music , originally published by Oxford University Press in 1985 and now in its fourth edition (Manning 2004). The book presents a detailed account of the technical and creative evolution of electronic music from its earliest days. Starting from Thaddeus Cahill’s 1897 patent application for the Dynamophone, it traces developments in North America and Europe and discusses a range of analogue techniques including tape manipulation and voltage-controlled synthesisers. Later chapters consider the digital revolution that followed, including developments in MIDI and digital workstations. In later editions, the sections on computer music were significantly revised and expanded to reflect the major and rapid transformation of the field. A distinctive feature of the book is the way it combines detailed historical information and thorough explanations of technical developments, often clarified by use of explanatory diagrams, with insightful accounts of the musical repertoire produced using this technology. The book was derived from Peter’s PhD thesis at Durham University in which he surveyed and analysed numerous contemporaneous texts documenting developments in minute detail.
Self-regulated Learning and Digital Literacy: Relationship with Conceptual Understanding of Excretory System

Biology learning in the 21st century makes students have to understand concepts, including in excretory system learning. Self-regulated learning is the way students manage learning on their own, with digital literacy skills which should be maintained as students must control their use of technology and information in learning. This research aimed to analyze the relationship between self-regulated learning with the conceptual understanding of the excretory system, digital literacy with the conceptual understanding of the excretory system, then also the relationship between self-regulated learning and digital literacy as a whole with the conceptual understanding of the excretory system in a high school with a post-pandemic learning situation. This research was held for two months duration from March until April 2022 in SMAN 6 Jakarta, involving 94 students of class XI Science as samples. A descriptive correlational study was chosen as the method, while questionnaires and tests are used as instruments. The hypothesis test shows a multiple linear regression model in Ŷ=-12.495+0.345X1+0.680X2 with the model significance of 0.000 and 0.062 as relationship linearity, then concludes that there is a positive relationship which is significant and linear between self-regulated learning and digital literacy simultaneously with excretory system conceptual understanding.
Presenting a Model for the Development of Public-Private Partnerships in the Health System through Electronic Word-of-Mouth

Background. This study aimed to design a model for developing health system partnerships by using electronic word-of-mouth communication. This issue has recently attracted the attention of researchers and managers of the country’s public and private sectors. Methods. In this qualitative study, the meta-composite method and Delphi technique were employed. The data collection tools included library studies and review of articles related to the research background. First, relevant information and findings were extracted from reliable national and international scientific databases using the meta-combination method, and then the opinions of the expert panel were recorded using a questionnaire. After two stages of opinion polling, the initial findings of refinement and unnecessary items were merged or deleted. Finally, the components and indicators affecting the development of health system partnerships were identified and categorized through word-of-mouth communication. Results. Out of 66 primary codes extracted by metacombination method, 36 final indicators were identified by the experts using Delphi method. The identified indicators were then divided into three categories and nine components including Creation Factors with "structural and contextual, economic and financial, communication, and interactive" components, Diffusion Factors with "organizational and institutional, legal and contractual, awareness, and trust building" components, as well as Impact Factors with "legal and regulatory, technical and specialized, and acceptability and effectiveness" components. Conclusion. A new model and perspective was presented for developing health system partnerships through electronic word-of-mouth communication, so that the enormous economic, social, and cultural potentials of the public, private, and charitable sectors may have been exploited for developing health and treatment through using new marketing tools and modern technologies.
MEMS-scanning-based image projection simulation

Abstract The absence of simulation tools to predict image quality significantly complicates the hardware and software development of MEMS scanning-based projection systems. In this work, we present a mathematical and simulational framework to accurately predict the quality of images projected by MEMS-based point-scanning projection systems. The described framework is applied to visualize different kinds of distortions limiting the image quality of scanning-based projection systems. The simulation of beam propagation through the system enables entirely correcting all distortions in the projected image. Finally, simulation results are compared to images projected using a custom-made MEMS scanning-based projection system. The presented results demonstrate the potential of adequate simulation tools for system hardware and software optimization. The presented simulation framework can lay the foundation for systematic studies of scanning-based image formation and the optimization of perceived image quality.
Ontology-based Complementary Breastfeeding Search Model

Children's nutritional requirements differ from those of adults. The health ministry's Indonesian data shows that in 2017, there were 17.8% of malnourished children under five years old (toddlers), one of which was related to complementary breastfeeding problems. Complementary breastfeeding is given to babies starting at 6–24 months of age. This research aims to build a complementary breastfeeding search model and be able to present it as a treatment for malnourished babies. A search model is built to understand natural language input given by a user. Also, it can do reasoning by applying a set of rules to obtain implicit knowledge about the complementary breastfeeding menu recommended for babies. The methods used in this research are data collection, designing a search model, building an ontology model, building SWRL, natural language processing, and usability testing by users and nutritionists. This research succeeded in building an ontology-based complementary breastfeeding search model in the form of a semantic web. The testing result shows that the web can provide an alternative complementary breastfeeding menu according to the baby’s nutritional needs and has a high usability capability of 4.01 on a scale of 1 to 5.
Business Model Using Design Thinking Concept for Pet Industry in Indonesia

The COVID-19 pandemic that has been present since 2019 has had a significant impact on many aspects of human life. One of the business sectors that has thrived even in the midst of a pandemic is pet industry. The aim of this research is to identify possibilities for business growth in the pet industry. This study attepmts to describe the consumer behavior of pet owners, the pain and gain associated with providing the needs of their pets, and the potential solutions to the challenges that experienced by the pet owners. The design thinking methodology and in-dept interviews with pet pwners as persona mere both used in this study. The stages of design thinking method applied in this study include; understand, define, ideate prototype, and test. Based on this research a quick-commerce platform online app, called Petway apps is being offered to pet owners as a solution. The Petway apps provide solution by addressing all of the pet needs, including providing original pet food brands, with fast delivery services to consumers’ homes at affordable pricing.
Design And Development of Car Sparepart Sales Information System For Web-Based Using RAD Method On UMKM Sinar Seroja

UMKM A business that deals in auto accessories and parts is called Sinar Seroja. UMKM Sinar Seroja wishes to create an integrated system because errors frequently occur in the data collection and processing of traditional sales transaction data, namely inventory data with sales transaction data in a traditional system that is not integrated. This makes it tough to record and process data regarding inventory and sales transactions. Rapid Application Development (RAD) is a technique used to create a web-based integrated sales information system. This was proven after the Black Box testing was carried out with an average result of 88.3% indicating that the web-based application had been successfully implemented.Customers may get around current issues so that it is simpler to save and handle sales and warehousing transaction data with an integrated web-based sales information system. Additionally, Sinar Seroja needs a system to be developed as a medium for transaction data storage because it.
3D Multimedia E-Book Based on Mobile Learning Basic Competency of Artistic Hair Coloring

The problem of research is the low understanding of students in the subject of hair trimming and coloring which has an impact on student learning outcomes. The purpose of this study was to develop an e-book-based learning media on the subject matter of double application hair coloring at SMK. This type of research is research and development using a 4-D model. The population of this research is the students of class XI KC II SMK totaling 32 people. The data collection technique used a validity and practicality questionnaire. The data analysis technique is by calculating the score of the e-book media assessment from the questionnaire given and categorized according to the interpretation obtained. The results of the media validation study were 0.89 (very valid category) and 0.82 material validation (very valid category). The results of the practicality of student responses were 86.07% (very practical category) and from the teacher's response of 87.2 (very practical category). E-book-based learning can be said to be valid and practical to be used as teaching materials in the classroom on hair trimming and coloring subjects to improve student learning outcomes.
Specification of Agents’ Activities in Past, Present and Future

The behaviour of a multi-agent system is driven by messaging.Usually, there is no central dispatcher and each autonomous agent, though resource-bounded, can make less or more rational decisions to meet its own and collective goals.To this end, however, agents must communicate with their fellow agents and account for the signals from their environment.Moreover, in the dynamic, permanently changing world, agents' behaviour, i.e. their activities, must also be dynamic.By communicating with other fellow agents and with their environment, agents should be able to learn new concepts and enrich their knowledge base.Processes and events that happened in the past may be irrelevant in the present or have a significant impact in the future, and vice versa.Therefore, the finegrained analysis of agents' activities as well as events within or beyond the system is very important so that the system can run smoothly without falling into inconsistencies.Moreover, as the system should communicate with its environment, the analysis should be as close to natural language as possible.The goal of this paper is a proposal for such an analysis.To this end, I apply Transparent Intensional Logic (TIL) because TIL is particularly apt for a finegrained analysis of processes and events specified in the present, past Organon F 30 (1) 2023: 66-101 or future tense with reference to the time when they happened, happen or will happen.
Odesa’s Libraries during the Martial Law of 2022

The article analyses the work of Odesa’s libraries during the martial law of 2022. The author aimed to collect information about librarians’ reactions to the beginning of the war, the overall state of the city’s libraries, and the extent of collection losses, and to assess changes and trends in library work over half a year of martial law. The study is based on the oral-historical and historical-comparative methods and represents the first attempt to analyze the ongoing state of the library industry in Odesa. The author conducted a survey (in the form of a questionnaire) of employees of 21 libraries in the city. As part of the survey, librarians were asked to answer a number of questions regarding their situation, functions, and actions at the beginning of the full-scale Russian aggression against Ukraine. On the basis of the received answers, the principal directions of library activities and innovation during the war of national defense of 2022 are outlined. The distinguishing features of the work of libraries in Odesa concern five aspects: reaction to the beginning of the war; security conditions; collection-related issues; innovation; and situation of employees. The author notes that the libraries of Odesa have suffered less damage than library institutions in many frontline cities of Ukraine. Martial law has created both a number of challenges, particularly in the areas of security, funding, and collection expansion, and some opportunities for innovation. Libraries fast-tracked the scanning of valuable collections and began to pay more attention to issues of security and to their role in the psychological health of the community. Success has been had with a number of volunteer initiatives. Libraries have been taking very active part in informational resistance against the Russian invasion and are demonstrating professionalism in preserving their collections and responding to various challenges.
Unsupervised Text Style Transfer for Authorship Obfuscation in Bahasa Indonesia

Authorship attribution is an NLP task to identify the author of a text based on stylometric analysis. On the other hand, authorship obfuscation aims to protect against authorship attribution by modifying a text’s style. The main challenge in authorship obfuscation is how to keep the content of the text despite the text modification. In this research, we are applying text style transfer methods for modifying the writing style while preserving the content of the input text. We implemented two unsupervised text style transfer: dictionary-based and back translation methods to change the formality level of the text. Experiment results shows that the back-translation method outperformed the dictionary-based method. The authorship attribution performance decreased up to 16.15% and 23.66% on F1-score for 3 and 10 authors respectively using back-translation. While for dictionary-based method the F1-score dropped up to 1.99% and 11.56% for 3 and 10 authors respectively. Evaluation on sensibleness and soundness factors show that the back-translation method can preserve the semantic of the obfuscated texts. Moreover, the modified texts are well-formed and inconspicuous.
Application of Neural Network in Risk Management

In recent years, with the intensification of project competition and the rapid increase of various risks, all the major companies are facing unprecedented challenges.The emergence of this phenomenon makes people pay more attention to the engineering risk management, so the project risk management system comes into being under this background.The key of risk management is to analyze various risk factors that may occur in the project.Firstly, quantify each risk factor and adopt different quantitative methods for different risk factors; Then, using the risk information in the historical project, the neural network is trained to establish a complete network model; Finally, BP algorithm is used to train the weight of the neural network.Through the verification of the proposed neural network, the effectiveness of project risk management using neural network is verified.On the basis of risk management, according to the improved risk identification method of risk identification, risk identification results input to neural network project risk analysis, then use the optimal neural network algorithm solution, finally the risk level and countermeasures displayed on the system page, to reduce the project risk, improve the success rate of the project, make risk management more accurate, standardized, scientific and convenient.
Synthetically Generating Human-like Data for Sequential Decision Making Tasks via Reward-Shaped Imitation Learning

We consider the problem of synthetically generating data that can closely resemble human decisions made in the context of an interactive human-AI system like a computer game. We propose a novel algorithm that can generate synthetic, human-like, decision making data while starting from a very small set of decision making data collected from humans. Our proposed algorithm integrates the concept of reward shaping with an imitation learning algorithm to generate the synthetic data. We have validated our synthetic data generation technique by using the synthetically generated data as a surrogate for human interaction data to solve three sequential decision making tasks of increasing complexity within a small computer game-like setup. Different empirical and statistical analyses of our results show that the synthetically generated data can substitute the human data and perform the game-playing tasks almost indistinguishably, with very low divergence, from a human performing the same tasks.