Reviewerly/exHarmony huggingface dataset:
KNOWLEDGE WITH DENTAL AND ORAL HYGIENE IN DEAF CHILDREN

Background: Knowledge of dental and oral health is one of the efforts to prevent and overcome dental health problems through the approach of dental and oral health education. Hearing loss is one of the causes of the lack of knowledge of deaf people to maintain dental and oral hygiene and affect their attitudes and behavior in maintaining dental and oral hygiene. The purpose: from this study is to find out the relationship with dental and oral hygiene in deaf people at SLB Yayasan Bahagia Tasikmalaya City. Method: This type of research is quantitative analytics with cross sectional design. Samples taken by puposive sampling technique, the number of samples as many as 20 samples. Data collection uses questionnaires on dental hygiene knowledge and OHI-S examinations of deaf people. Results: research shows that there is a relationship between knowledge and dental and oral hygiene in deaf people at SLB Yayasan Bahagia Tasikmalaya City with the results of statistical tests of significance of 0.030 (&lt;0.05) with corelation coeffition (0.486%) sufficient, it can be concluded that there is a relationship between knowledge and dental hygiene and mouth on deaf presenters at SLB Yayasan Bahagia Tasikmalaya City. Conclusion: There is a knowledge relationship with dental hygiene in deaf people at SLB Yayasan Bahagia Tasikmalaya City.
A System to Support Memory Recall by Creating Tag Clouds from Calendars, Twitter, and Photos

Human memory is crucial for many daily activities. However, human memory is unreliable.Since existing memory aids such as diaries and notebooks need some effort for writing and accessing, we present an approach to capture and display memory cues from the user’s daily activities, such as writing schedules, posting SNS messages, and taking photos. We developed a system that supports memory recall by creating tag clouds from the user’s calendars and Twitter posts. The main feature of this research is using the number of photos taken by users to weight the tags to recall impressive events. This is based on the hypothesis that impressive events are found on the days when users took many photos. We evaluated out tag cloud generation algorithms and our implemented prototype system and obtained the following results for user memory recall: (1) Our tag cloud (using our weighting method with calendar and Twitter data) is superior to other tag clouds. (2) Sorting by time in the tag cloud outperforms other sorting methods. (3) Our implemented prototype system is useful.
SENTENCE PREDICTION USING NLP TECHNIQUES

In Today’s world automation has been playing a significant role. A language model is a set of rules for evaluating the likelihood of sequences of text. Language models have many uses, including generating text by repeatedly answering the question like what word would come next. Sentence Prediction is a technique in which it predicts the possible outcomes of next words. Sentence Prediction using LSTM and BERT technique is an efficient way to predict the word also with web scraping it is easier to look for doubts without switching tabs. The main aim of our project is to predict 5 or more words as quick as possible using BERT and LSTM model.
ANALISA ALUR KERJA INSPIRASI DAN EKSPIRASI PADA ALAT VENTILATOR

Research has been carried out on the Hamilton C2 ventilator which aims to find out how the of inspiration and expiration are in accordance with what has been set on the ventilator by the operator or user. Installation of a ventilator is meant for patients who have excess or lack of oxygen within the lungs and who experience respiratory failure. Where the ventilator is a breathing apparatus that can help maintain ventilation and oxygen delivery for quite a long time.This research method is disbursed using qualitative and quantitative methods in order to collect data. Research on this ventilator was applied in several stages, namely setting and taking data that the ventilator on Volume Tidal (VT) must be in accordance with the Volume Tidal Expiratory (VTE) so there's no collapse within the patient and damage to the device itself. The results of this study are to determine the way of inspiration and expiration consistent with what has been set by observing the worth displayed on the Volume Tidal Expiratory (VTE) which is the same because the value that has been inputted within the Volume Tidal (VT. If the value displayed on the display or screen is &lt;10% then there's a possibility of harm to the ventilator flow sensor or flow sensor within the patient, and the other way around if the value displayed on the display or screen is &gt;10% then there's a possibility of injury to the flow sensors, both ventilator flow sensors and flow sensors within the patient.
HUBUNGAN KECERDASAN EMOSIONAL DENGAN KUALITAS INTERAKSI SOSIAL SISWA DI SMK PANCA ABDI BANGSAKU (PABAKU), STABAT-LANGKAT

This research is motivated by some examples of cases that occurred in SMK Panca Abdi Bangsaku (PABAKU) which there are students / I in SMK PABAKU who do cases from 2012-2016 school year case examples are Fight Teachers, fights between students, smoking in school environment, watching porn and absent movies are on the rise. This suggests that students / I have not been able to improve their emotional intelligence that can impede the process of social interaction with their friends. This study aims to determine the relationship of emotional intelligence with the quality of social interaction of students, know the emotional intelligence of students, and to know the quality of social interaction of students in SMK PABAKU. This research uses quantitative research approach. The population in this research is 265 with sampling technique is Random Sampling 72. The result of rxy correlation test is 0.612, where the hypothesis test r shows that the price of r count 0.612&gt; r table (df = n-2; 72-2) 0.195. It means Ha is accepted and Ho is rejected or there is a relationship of Emotional Intelligence with Social Interaction of students in SMK Panca Abdi Bangsaku Stabat-Langkat. The conclusion of the result of this research is there is correlation of emotional intelligence with quality of social interaction of student. It is suggested to students / I to be more active in activities that are inside school and outside school, for further researcher can add insight, and for institution able to develop and support activity at student / I SMK PABAKU.
FAKTOR – FAKTOR YANG MEMPENGARUHI TERLAMBATNYA PENYELESAIAN STUDI PADA MAHASISWA FARMASI UNIVERSITAS SARI MUTIARA INDONESIA

This research was conducted by the number of students who could not graduate on time, the researchers were interested in finding the factors that caused the decline in student interest in completing the final assignment. This study aims to determine the factors behind the completion of the study for students of the Sari Mutiara Indonesia Pharmacy Study Program. Comparative causal research is a type of research in which research is conducted to determine the causes or reasons of differences in group behavior or individual status. The population in this study were students of the Medan USM-Indonesia pharmacy student study program, who were completing a final assignment or totaling 275 people. In this study the sampling was 15% of the population as follows: 15% x 275 = 41.6 rounded up to 42 people. Data collection techniques use indirect communication techniques, namely by distributing questionnaires. The data analysis technique uses statistical analysis. From the results of the study, the average pharmaceutical study student has the motivation to graduate on time, which is as many as 4 respondents or 9.5% availability of less available sources as many as 25 respondents or 59.5% poor quality as many as 30 respondents or 71.4% of peer groups do not support as many as 10 respondents or 23.8% so it can be concluded that motivation to graduate on time, ability to write scientific papers, availability of resources, thesis guidance quality and peer environment are factors that can influence the late completion of studies for students of the Pharmacy Study Program at Sari Mutiara Indonesia.&#x0D;
Neighborhood-Based Loss Functions for Explainability of Autoencoders

In e-Commerce, products are searched for directly or found via recommendations. Recommender Systems (RS) use Machine Learning (ML) methods to recommend items to users. This can be achieved by predicting their ratings and there are various approaches how to do so. In Collaborative Filtering (CF), Autoencoders (AE) have been used to fill missing values in a rating matrix. Typically, training and testing are based on a squared error metric. The evaluation of success is thus only measured by quantifying the reconstruction of given ratings and does not necessarily incorporate the relationships between similar users. Explainability is an important aspect of RS since it yields trustworthiness for the recommendations. However, it is hard to quantify and achieve. We seek to improve explainability without losing too much predictive power. We, therefore, inspect some optimization strategies and quality metrics. In this article, we propose two weighted loss functions to push the AE to learn explainability automatically. In experiments, we show this indeed yields an improvement of up to 45% compared to the unweighted loss function.
Correction to: Application of Ensemble Techniques Based Sentiment Analysis to Assess the Adoption Rate of E-Learning During Covid-19 Among the Spectrum of Learners

In the originally published version of chapter 14 the affiliation of the first author was incorrect. The affiliation has been corrected as “Lincoln University College, Petaling Jaya, Malaysia”.
The connection of emotional intelligence with the success of educational and professional activities of students of the Music Academy.

The subject of the research of this article is the connection of emotional intelligence with the success of educational and professional activities of students of the Music Academy. A study was conducted on 60 respondents of the Krasnoyarsk State Academy of Music and Theater. The following methods were used in the study: the scale of self-assessment of one's success (D. Laikert), the scale of assessment of the level of situational (concert) anxiety (C.D. Spielberg, Y.L. Khanin), the method of assessing "emotional intelligence" (N.Hall), mathematical methods of data processing. In the course of the study, a positive relationship was established between emotional intelligence, educational and performance success, and self-esteem of students in the general sample. Students manage their emotions better and are therefore better able to control anxiety and focus on the learning process, which in general has a positive effect on their success. Emotional intelligence affects the success of the educational and professional activities of students of the Music Academy and confirms our hypothesis. Indeed, the higher the emotional intelligence, the more successful the educational and professional activities of students and the lower the concert anxiety. Students with a higher level of emotional intelligence not only have high scores in musical performance, but are also more adequate in self-assessment of their abilities. We believe that in the conditions of musical performance, emotional intelligence receives a specific refraction determined by the peculiarities of musical and artistic activity. This is manifested in the development of such qualities as managing your emotions, self-motivation, empathy.
ICANN mechanisms: Extra remedies evaluation

At incorporation with World intellectual property organization, ICANN has created administrative mechanisms to solve contested domain names and other rights related to the use of trademarks in Cyberspace. In this context, this mechanism called UDRP was limited to general top-level domain names because at the early beginning of the world wide web, the conflicts were basically surrounded by domain names chains such as .com, .org.net with high trade value. On top of that, and because the increasing demand in the domain names industry was huge, ICANN seeks to pump new domain names chains into the market to encounter such an increasing demand for domain names. Accordingly, this step has increased the conflict while the UDRP mechanism was limited to solving the conflicts over top-level domain names. In this connection, ACANN had to find another mechanism to solve other conflict-related with the new gTLD. This article tries to shed light on these remedies and their effectiveness in solving such conflicts.
Perancangan Sistem Pengelolaan Data Untuk Mendukung Kinerja Kemahasiswaan Pada Universitas Atma Jaya Makassar

BKAM had difficulty in reporting to SIMKATMAWA, in finding data on achievements and student activities that had been carried out. The purpose of this study is to design a student activity management system to support the performance of the UAJM student bureau and design the UAJM student data structure to fit the SIMKATMAWA. The author understands the scope of the ranking, some data from SIMKATMAWA will be used as needed in UAJM student activities that have not been well recorded. Student performance data management system designed for data management that helps collect data, manage and present useful data for SIMKATMAWA, in support of student data needs within the UAJM student body. The results of the research make it easy for student affairs bureaus to get information on student activities, so that the data can be used for SIMKATMAWA reporting purposes.
Omnisemantics: Smooth Handling of Nondeterminism

This article gives an in-depth presentation of the omni-big-step and omni-small-step styles of semantic judgments. These styles describe operational semantics by relating starting states to sets of outcomes rather than to individual outcomes. A single derivation of these semantics for a particular starting state and program describes all possible nondeterministic executions (hence the name omni ), whereas in traditional small-step and big-step semantics, each derivation only talks about one single execution. This restructuring allows for straightforward modeling of both nondeterminism and undefined behavior as commonly encountered in sequential functional and imperative programs. Specifically, omnisemantics inherently assert safety (i.e., they guarantee that none of the execution branches gets stuck), while traditional semantics need either a separate judgment or additional error markers to specify safety in the presence of nondeterminism. Omnisemantics can be understood as an inductively defined weakest-precondition semantics (or more generally, predicate-transformer semantics) that does not involve invariants for loops and recursion but instead uses unrolling rules like in traditional small-step and big-step semantics. Omnisemantics were previously described in association with several projects, but we believe the technique has been underappreciated and deserves a well-motivated, extensive, and pedagogical presentation of its benefits. We also explore several novel aspects associated with these semantics, in particular, their use in type-safety proofs for lambda calculi, partial-correctness reasoning, and forward proofs of compiler correctness for terminating but potentially nondeterministic programs being compiled to nondeterministic target languages. All results in this article are formalized in Coq.
Sistem Deteksi Intrusi pada Server secara Realtime Menggunakan Seleksi Fitur dan Firebase Cloud Messaging

Intrusion detection is one of the fundamental parts of a security tool, such as adaptive security tools, intrusion detection systems, intrusion prevention systems and firewalls. There are various kinds of intrusion detection techniques used, the main problem of this intrusion technique is the performance problem. The accuracy of the intrusion detection technique greatly affects its performance, which needs to be improved to reduce the false alarm rate and increase the detection rate. In solving performance problems, multilayer perceptron, support vector machine (SVM), and other techniques have been used recently. This technique shows limitations and is inefficient for use in large data sets, such as system and network data. Intrusion detection systems are used in analyzing a very large data traffic; thus, an efficient classification technique is needed to overcome these problems. This issue is considered in this paper. The well-known machine learning techniques, namely, SVM, random forest, and extreme machine learning will be applied. These techniques are well known for their ability to classify. NSL knowledge discovery and data mining datasets were used, which were considered as benchmarks in the evaluation of intrusion detection mechanisms. The results show that ELM outperforms other approaches. Utilization of Firebase Cloud Messaging because it can work with multiple platforms in addition to the availability of a file store that can store all logs created by the JALA application.
Science Teachers’ Perceptions of Integration of M-Learning into Class Instructions in Kwara State, Nigeria

The mandate of the education system is for the advancement of knowledge, socioeconomic transformation, employment generation, and so forth. Literature is awash with arguments in favour of M-learning in the realization of the core mandate of the education system. This study, therefore, examines the perceptions of the science teachers on integration of M-Learning into science class instructions in Kwara State, Nigeria. One hundred and twenty-nine science teachers from 34 public and 27 private senior secondary schools participated in the study. Stratified and purposive sampling techniques were used to select the schools and the teachers, respectively. A researcher-designed questionnaire titled, “Teachers’ Perceptions of M-learning” (TPML) with a reliability coefficient of 0.85, was used for gathering data. Data were analyzed using the t-test statistical tool, and findings from the study revealed that the participating teachers had high perceptions of M-learning and were at the preparation stage of integrating it into class lessons. It was concluded that teachers had favorable perceptions of M-learning and were in vantage position to use M-learning to leverage students’ achievement. It is, therefore, recommended that science teachers should progress from the preparation stage to the action stage of integrating M-learning into science teaching.
Improvement of Services through Digital Documents Filing with The Template Matching Correlation Method

Scanning printed documents into digital documents has become a necessity in universities.Each document has a unique number as an identity with a certain code structure.The purpose of this research was to determine the effectiveness of document scanning results by utilizing an optical character recognition technique known as OCR (Optical Character Recognition) on this unique number.The method used in this optical character recognition process was to use template matching correlation,a technique to get the highest value in the comparison of characters in the input image.The image with the highest value is determined as the image that best fits the template.The technology developed in this study was Template Matching Correlation so that it can produce applications using MATLAB that can detect unique numbers in documents as a reference in file filing in the form of naming new files and placing the files in the desired folder.
Streaming Analytics with Adaptive Near-data Processing

Streaming analytics applications need to process massive volumes of data in a timely manner, in domains ranging from datacenter telemetry and geo-distributed log analytics to Internet-of-Things systems. Such applications suffer from significant network transfer costs to transport the data to a stream processor and compute costs to analyze the data in a timely manner. Pushing the computation closer to the data source by partitioning the analytics query is an effective strategy to reduce resource costs for the stream processor. However, the partitioning strategy depends on the nature of resource bottleneck and resource variability that is encountered at the compute resources near the data source. In this paper, we investigate different issues which affect query partitioning strategies. We first study new partitioning techniques within cloud datacenters which operate under constrained compute conditions varying widely across data sources and different time slots. With insights obtained from the study, we suggest several different ways to improve the performance of stream analytics applications operating in different resource environments, by making effective partitioning decisions for a variety of use cases such as geo-distributed streaming analytics.
Quantum Speedups of Optimizing Approximately Convex Functions with Applications to Logarithmic Regret Stochastic Convex Bandits

We initiate the study of quantum algorithms for optimizing approximately convex functions. Given a convex set ${\cal K}\subseteq\mathbb{R}^{n}$ and a function $F\colon\mathbb{R}^{n}\to\mathbb{R}$ such that there exists a convex function $f\colon\mathcal{K}\to\mathbb{R}$ satisfying $\sup_{x\in{\cal K}}|F(x)-f(x)|\leq \epsilon/n$, our quantum algorithm finds an $x^{*}\in{\cal K}$ such that $F(x^{*})-\min_{x\in{\cal K}} F(x)\leq\epsilon$ using $\tilde{O}(n^{3})$ quantum evaluation queries to $F$. This achieves a polynomial quantum speedup compared to the best-known classical algorithms. As an application, we give a quantum algorithm for zeroth-order stochastic convex bandits with $\tilde{O}(n^{5}\log^{2} T)$ regret, an exponential speedup in $T$ compared to the classical $\Omega(\sqrt{T})$ lower bound. Technically, we achieve quantum speedup in $n$ by exploiting a quantum framework of simulated annealing and adopting a quantum version of the hit-and-run walk. Our speedup in $T$ for zeroth-order stochastic convex bandits is due to a quadratic quantum speedup in multiplicative error of mean estimation.
Integrals detecting degree 3 string cobordism classes

The third string bordism group $\mathrm{Bord}_3^{\mathrm{String}}$ is known to be $\mathbb{Z}/24\mathbb{Z}$. Using Waldorf's notion of a geometric string structure on a manifold, Bunke--Naumann and Redden have exhibited integral formulas involving the Chern-Weil form representative of the first Pontryagin class and the canonical 3-form of a geometric string structure that realize the isomorphism $\mathrm{Bord}_3^{\mathrm{String}} \to \mathbb{Z}/24\mathbb{Z}$. We will show how these formulas naturally emerge when one considers certain natural $\mathrm{U}(1)$-valued and $\mathbb{R}$-valued 3d TQFT associated with the classifying stacks of Spin bundles with connection and of String bundles with geometric structure, respectively.