Reviewerly/exHarmony huggingface dataset:
Challenges In Telemedicine Implementation For Pregnancy Care During The Covid-19 Pandemic

Background: COVID-19 pandemic condition made the consultation shifted from face to face consultation to telemedicine for mild, stable, and follow up cases. In stabile condition of pregnant patients, telemedicine implementation will be beneficial to reduce the COVID-19 transmission risk. The problems are not all patients can implement telemedicine and the reimbursement procedure was hard. The aim of this paper is to describe about challenges in telemedicine implementation for pregnancy care during the COVID-19 pandemic. Methods: this paper is a literature review, Literature was identified from the archives of PubMed, Scopus, and Elsevier. All the literature was published in 2020. The inclusion criteria were the literature should be peer-reviewed and related to the topic of the paper. Keywords were challenges, COVID-19, opportunities, pregnancy, and telemedicine. Results: from 18 articles in this literature review, it was found that challenges in telemedicine are reimbursement, infrastructure, confidentiality, and unfamiliarity for the pregnant patients. Conclusion: Telemedicine can be used for pregnant patient control consultation during the stable condition to minimize the risk of COVID-19 transmission. The implication of this paper is to give insight that telemedicine can be done for stable pregnancy condition to reduce the risk of COVID-19 transmission during the pandemic. The benefits of reducing COVID-19 risk transmission for baby and mother outweigh the challenges and problems such as reimbursement, confidentiality, and technical issues.
Serverless Event-driven Applications Development Tools and Techniques

Serverless, a new cloud-based architecture, brings development and deployment flexibility to a new level by significantly decreasing the size of the deployment units. Nevertheless, it still hasn’t been clearly defined for which applications it should be employed and how to use it most effectively, and this is the focus of this research.The study uses Microsoft Azure Functions – one of the popular mature tools – because of its stateful orchestrators – Durable Functions. The tool is used to present and describe four flexible serverless patterns with code examples.The first pattern is HTTP nanoservices. The example demonstrates how flexible can be the Function-as-a-Service model, which uses relatively small functions as deployment units.The second usage scenario described is a small logic layer between a few other cloud services. Thanks to its event-driver nature, serverless is well-suited for such tasks as making an action in one service after a specific event from another one. New functions easily integrate with the API from the first example.The third scenario – distributed computing – relies on the ability of Durable Functions to launch a myriad of functions in parallel and then aggregate their results. and distributed computing. A custom MapReduce implementation is presented in this section.The last pattern described in this research significantly simplifies concurrent working with mutable data by implementing the actor model. Durable Entities guarantee that messages are delivered reliably and in order, and also the absence of deadlocks.The results of this work can be used as a practical guide to serverless main concepts and usage scenarios. Main topic of future research was chosen to be the development of a full-fledged serverless application using typical patterns to study the architecture in more depth.Manuscript received 08.06.2020
TueMix at SemEval-2020 Task 9: Logistic Regression with Linguistic Feature Set

Commonly occurring in settings such as social media platforms, code-mixed content makes the task of identifying sentiment notably more challenging and complex due to the lack of structure and noise present in the data.SemEval-2020 Task 9, SentiMix, was organized with the purpose of detecting the sentiment of a given code-mixed tweet comprising Hindi and English.We tackled this task by comparing the performance of a system, TueMix -a logistic regression algorithm trained with three feature components: TF-IDF n-grams, monolingual sentiment lexicons, and surface features -with a neural network approach.Our results showed that TueMix outperformed the neural network systems and the addition of the linguistic features beyond TF-IDF n-grams enhanced our performance, yielding a weighted F1-score of 0.685.
Smartphone usage patterns in public universities in Malawi: student perspectives

This study was motivated by the shortage of qualitative studies on student uses and gratifications of smartphone technology. Most research studies on mobile device uses and gratifications are quantitative and focus on mobile phones. Further, these studies are quite general, with insufficient information on how participants in those studies appropriate and engage with the technology. The purpose of this study was to investigate motives for use and usage patterns of smartphones among public university students. The study employed qualitative methods in the form of face-to-face interviews, focus group discussions, questionnaires and document analysis. Uses and Gratifications Theory was employed as a theoretical framework to form the basis of this study as well as to interpret the findings. The study found that students were motivated to use smartphones for internet access, social media and communication. As for patterns of use, it was found that the pattern was dominated by social networking. This paper contributes to the body of knowledge by providing a rich understanding of smartphone uses and gratifications which has insufficiently been described in previous similar studies. The paper further added the concept of policy to the main categories of the uses and gratifications framework.
Image Encryption based on a New Generation of Key from Rubik's Cube Principle of AES Algorithm

Encryption is the most secure way to save data, whether text, images, video, or any other type of multimedia, as in recent years, a lot of encryption algorithms have been suggested to protect this digital data from all kinds of attacks, and the protection process was carried out through encryption and the use of many algorithms.Through the proposed method, this research was focused on an important aspect, which is protecting the key by creating a new method for the algorithm key, as the more difficult it is to know the key, the more difficult it is to break the algorithm, as Rubik's Cube method was used to create the key of the AES algorithm, where it performs just throw the cube to generate the key, then the improved algorithm was used to encrypt the images and then restore the original image without problems and the process was of a high quality as the key configuration time was reduced and a good level of security was provided.The proposed method has been programmed in Visual Basic.Net 2015 language.
Secure Software Engineering: A Knowledge Modeling based Approach for Inferring Association between Source Code and Design Artifacts

Secure software engineering has emerged in recent decades by encouraging the idea of software security has to be an integral part of all the phases of the software development lifecycle.As a result, each phase of the lifecycle is associated with security-specific best practices such as threat modeling and static code analysis.It was observed that various artifacts (i.e., security requirements, architectural flaws, bug reports, security test cases) generated as a result of security best practices tend to be segregated.This creates a significant barrier to resolve the security issues at the implementation phase since most of them are originated in the design phase.In order to address this issue, this paper presents a knowledge-modeling based approach to semantically infer the associations between architectural level security flaws and code-level security bugs, which is manually tedious.Threat modeling and static analysis are used to identify security flaws and security bugs, respectively.The case study based experimental results revealed that the architectural level security flaws have a significant impact on originating security bugs in the code level.Besides, the evaluation results confirmed the scalability of the proposed approach to large-scale industrial software products.
Peningkatan Hasil Belajar Bangun Ruang Melalui Metode Duti Duta (Two Stay Two Stray) Siswa Kelas IV SDN Buncitan Kecamatan Sedati Kabupaten Sidoarjo

This research is motivated by the fact that the learning outcomes of students. The purpose of this research is to improve the learning outcomes of students through methods Two Stay Two Stray the subject matter of waking up space on the fourth grade students of SD Negeri Buncitan Sedati Sidoarjo. This study uses learning methods Two Stay Two Stray is applied so that students can be motivated to learn The general procedural theories more appropriate if taught with cooperative learning methods, one where students work together with other students in thinking independently to solve existing problems. The results of research on the application of cooperative learning Two Stay Two Stray in wake classroom materials IV SDN Buncitan on preliminary observations with a percentage of 43,8% mastery learning. Around 1 shows that the average grade 71,8 with a percentage of 68,8% mastery learning, then increasing in around 2 the average value of 76,1 students into a class with a percentage of 78,1% completeness. The conclusion of this study that the use of cooperative learning methods Two Stay Two Stray can improve the learning outcomes of student grade fourth of State Elementary school Buncitan Sedati Sidoarjo.
Detecting, Counting Objects to Form Color Image Features

Color image features are very important victor of values.Which is used as an image identifier or primary key which can be used easily in a color image retrieval system, the features victor can be used also as an image signature to compute image classifier in a color image recognition system.In this paper research we will introduce a texture method to create color image features.This method will have based on using crossing number to detect some objects in the image, the detected objects where isolated, ending, connected and crossing points.The idea of the proposed method is to find the count of each objects, these counts will form the image features.The proposed method will be implemented and the experimental results will be analyzed to prove the efficiency, accuracy, and stability of the proposed method.
THE EFFECT OF EDUCATION WITH THE LEAFLET MEDIA ON MOTIVATION IN CARING BABY WITH DIARRHEA

Diarrhea is the highest cause of death in infants due to infectious disease characterized by increasing frequency of defecation more than three times per day with changes in the consistency of watery stool. The purpose of this study will to determine if health influence education with leaflet. The motivation of mother in caring for toddler diarrhea. The research is a quasy-experimental study with non randomized design without control group, pretest-posttest design with 27 taken then the respondents are divided group leaflet. Changes in motivation of the mother in caring toddler with diarrhea measured using questionnaires motivation with likert scale. There are difference of motivation of mother in caring for children with diarrhea before and after being given education with value ? value &lt;0.05. Change in leaflet (motivation: 9.8, attitude: 10.2). It is expected that educators to apply audiovisual media in health education activities.
Implementation of the E-Pocket Book to Improve Learning Outcomes in Economics at Madrasah Aliyah Madinatussalam, Bandar Khalifah Regency, Indonesia

Teaching materials playing a vital role in supporting the learning process in a classroom. The right teaching materials will make the learning process more effective. The problem that is often faced by students is the teaching materials that are not appropriate, so that it lowers student learning outcomes. This causes the low learning outcomes of students in class XI economics MA Madinatusallam. For this reason, researchers try to investigate the effectiveness of e-pocketbook teaching materials. Field test results showed that the experimental class obtained higher learning outcomes than the control class, with a significant difference (p = &lt;.05).
Uncertainty of Optimal Rain Gauge Coastal Region: Case Study Makassar

The quality of rainfall data is very important in disaster or hazard analysis and water resource management. However, the accuracy and density of rainfall gauges are increasing, especially if related to the increasing amount of rainfall due to extreme events, such as floods that occurred in Makassar City in 2019. The purpose of this study is to analyze the scenario of optimal rainfall measurement measures in Makassar City. Determination number of the optimal rainfall equipment acquired by calculation of the coefficient of variation or relative standard deviation and error level based on the latest rainfall data in several locations in Makassar City. The results showed that the change of the number of optimal rain gauges varies with the level of error schemes. If the rainfall measurement wants to be improved, the number of rain gauges must be added. Moreover, increasing rainfall accumulation requires an additional rain gauge. By comparing the monthly rainfall data obtained from the rain station in Makassar, it takes 10 rain stations so that the error level is 5%. Nevertheless, using a longer rainfall duration causes the number of the optimal rain gauge to increase. The optimal rain gauge for annual rainfall data at an error level of 5% is 55 units, while if the error level is increased to 10% then 14 units and 6 units for error levels of 15%. Based on the calculation of the relative standard deviation (RSD) from 5 locations that measuring rainfall in Makassar, the biggest city in west coast Sulawesi Island obtained the level of error level is 10%. The scenario with combined among the five existing rain gauges showed that needs to be added to the rainfall gauge between Panaikang or Biring Romang and Sudiang. It is also important to add equipment on-site between Paotere and Barombong.
Pengembangan Sistem Informasi Perpustakaan Sekolah Berbasis Web

The school library is a means for teachers and students to find information. The school library provides books or reading materials that can support the learning process. The focus of this research is to develop the information system contained in the school library. Many school libraries still collect data in the conventional way, such as handwritten using a ledger or using excel. The development of this school library system will use the website as a means to process data. The data that has been created will be entered into the data storage using the MySQL application as the database. This research planning uses the SDLC method with the waterfall model. The waterfall model is used because it is considered more efficient in developing school libraries. There are two entities that can use this website, namely library officers and members. Library officers can use the web to process data on book procurement, book borrowing transactions and viewing library reports. Meanwhile, members can fill in the guest book every time they visit the school library and also do book searches. Thus, the school library information system can facilitate the data processing. Book lending and borrowing transactions will also be more efficient and errors in data processing can be reduced.
Emotional Identity in the Process of Evaluation in Primary School Children. School and Family Expectations

School years have an important role in defining a person for the world he will live in. The influence that the school environment has on defining a person for the future is something that teachers and policy makers take into consideration when developing strategies for learning and equally important in the evaluation process. The evaluation process is an integral part of the education process and the connections between evaluation, assessment of learning and learning constitute a focal part of the educators. School performance is not solely a function of student’s aptitude set, but also covers the optimal cognitive and affective-motivational recourses in relation to certain tasks. Emotional competence, along with the social competence is important in the development of positive relationships and emotionally feelings of security in creating a positive self image for young people. Young people with a positive self image will have a greater disposition to learning. For children learning about themselves happens within the context of their families and community and it includes all the type of relationships they forge with their peers, places and things in relation to the actions and responses from others. Experience is the one that shapes the emotional responses that children have in regards to all the things happening around them and inside them, at a self-understanding level. This paper aims to understand the way emotional identity of children helps them focus on the evaluation task in various contexts of every day school life.
Crowdsourcing Framework for QoE-Aware SD-WAN

Quality of experience (QoE) is an important measure of users’ satisfaction regarding their network-based services, and it is widely employed today to provide a real assessment of the service quality as perceived by the end users. QoE measures can be used to improve application performance, as well as to optimize network resources and reallocate them as needed when the service quality degrades. While quantitative QoE assessments based on network parameters may provide insights into users’ experience, subjective assessments through direct feedback from the users have also gathered interest recently due to their accuracy and interactive nature. In this paper, we propose a framework that can be used to collect real-time QoE feedback through crowdsourcing and forward it to network controllers to enhance streaming routes. We analyze how QoE can be affected by different network conditions, and how different streaming protocols compare against each other when the network parameters change dynamically. We also compare the real-time user feedback to predefined network changes to measure if participants will be able to identify all degradation events, as well as to examine which combination of degradation events are noticeable to the participants. Our aim is to demonstrate that real-time QoE feedback can enhance cloud-based services and can adjust service quality on the basis of real-time, active participants’ interactions.
Privacy-Preserving Edge Video Analytics

Edge video analytics (EVA) emerges as a promising paradigm to decentralize video analytics tasks to the edge of the network and thus improve user experience by enabling faster task execution for users. However, it is challenging to enable edge-based model training while still satisfying the requirement of user privacy. A faster model training process is commonly at the cost of more disclosure of user privacy. We propose a federated learning driven privacy-preserving model training framework called FedEVA for edge video analytics, which can protect user privacy and ensure a fast convergence rate. Instead of directly sending gradients to the parameter server, users conduct a local perturbation operation on users’ update information, and then send the perturbed gradients to the parameter server. The parameter server at the edge can update the neural network model directly over the perturbed gradients. We carefully design the perturbation function to conceal partial information about data while efficiently performing computation over the gradients from multiple users. Different from crypto-based methods, our perturbation process is a light-weight operation. We conduct extensive evaluations using large-scale real-world datasets to verify the effectiveness of our FedEVA framework and compare with other baseline algorithms. The results show that our FedEVA framework can improve the degree of privacy preservation, and still maintain the same level of convergence rate.
DebateSum: A large-scale argument mining and summarization dataset.

Prior work in Argument Mining frequently alludes to its potential applications in automatic debating systems. Despite this focus, almost no datasets or models exist which apply natural language processing techniques to problems found within competitive formal debate. To remedy this, we present the DebateSum dataset. DebateSum consists of 187,386 unique pieces of evidence with corresponding argument and extractive summaries. DebateSum was made using data compiled by competitors within the National Speech and Debate Association over a 7year period. We train several transformer summarization models to benchmark summarization performance on DebateSum. We also introduce a set of fasttext word-vectors trained on DebateSum called debate2vec. Finally, we present a search engine for this dataset which is utilized extensively by members of the National Speech and Debate Association today. The DebateSum search engine is available to the public here: http://www.debate.cards
Digital model of a pseudo-random number generator based on a continuous chaotic system

It is shown that the choice of the time sampling parameter of the digital model of a continuous dynamic system with chaotic modes based on its dynamics makes it possible to control the characteristics of the output sequence, including avoiding short cycles and periodic behavior modes. On the example of the Lorentz system, the analysis of the law of motion of a chaotic system, linearized in the vicinity of points of stable and unstable equilibrium, is carried out, on the basis of which the parameters of the mathematical model of the generator of pseudo-random numbers are selected. The output sequence of numbers generated in proposed way is subjected to statistical and correlation analysis. Based on the results of the tests carried out, we can say that the obtained pseudo-random sequences based on continuous chaotic systems have statistically random properties and can be used in steganographic and cryptographic systems.
Rancang Bangun Aplikasi Mobile Pengenalan Huruf Jawa (Aksara Jawa) Berbasis Android

Technological developments, especially smart phones, have been widely applied in the education sector. One example is the number of mobile-based learning media. Javanese language, especially Javanese script, has begun to erode because it is very rare nowadays to learn Javanese. The many forms of writing and also terms in Javanese script sometimes make us lazy and reluctant to learn them. In this study, the authors made an application as an Android-based learning media for learning Javanese characters. The application is equipped with a voice reading character so that users can easily understand the material. In addition, the application is equipped with a quiz to review the user's ability to learn Javanese script. Android based was chosen because the smart phone owned in addition to communication media can also be used for learning media. This research uses the waterfall system method. The stages used are analysis, design, coding and testing. The results of the black box testing on this application show that the application is running well according to its function.&#x0D;