Reviewerly/exHarmony huggingface dataset:
ANALISIS PERBEDAAN BIAYA RILL DENGAN TARIF INA CBG’S RUMAH SAKIT PADA PASIEN ASMA PESERTA JKN DI INSTALASI GAWAT DARURAT RUMAH SAKIT UMUM XYZ JEMBER

Abstract: The cost of treating an asthma attack at the XYZ General Hospital, which previously had asthma patients receiving treatment at the emergency room. This study is different from other studies because in addition to describing the direct medical costs, it also recognizes the discrepancy between the real costs of INA-BGS’S rates for asthma in hospitals. The INA-CBG system, the casemix system is a grouping of diagnoses and procedures with reference to similar clinical features and similar treatment costs, grouping is done using a grouper. The research design used in this study is a non-experimental research design with a retrospective method. Retrospective studies are used by following patient medical record data. The sampling technique used in this study was purposive sampling. In this study with a minimum total sample size of 97 people. Based on the results of research related to the real cost analysis compared with the cost of INA CBG'S in asthma patients hospitalized at the Hospital is 1) The average total direct medical costs in grade 1 mild asthma patients is Rp 3,711,753 / patient, grade 2 mild asthma patients in the amount of Rp. 3,451,968/ patient, grade 3 mild asthma patients in the amount of Rp.4,961,418 / patient; 2) The average total direct medical costs for moderate grade 1 asthma patients is Rp 1,912,000 / patient, moderate grade 2 asthma patients are Rp 1,942,512 / patient and no data is found in grade 3 moderate asthma patients; 3) The average total direct medical costs in grade 1 severe asthma patients is Rp 2,100,000 / patient and no data is found in grade 2 and 3 severe asthma patients; 4) The results of data processing from the help of SPSS for Windows version 25 with the independent t-test obtained data that the P value of 0.002 is smaller than the alpha value of 0.05 (P value <Value α). It can be concluded that there are significant differences in the total direct medical costs between the Real cost group and the INA CBG's Cost.
UTILIZING SENTANI FOLKTALES TO TEACH SPEAKING FOR CHILDREN OF COMMUNAL AGENTS IN JAYAPURA REGENCY, PAPUA

Folktale is one of Sentani people’s cultural heritages that is rarely told anymore. As social products that teach knowledge, history and moral values, folktales have to be preserved. In Jayapura Regency, there are some communal agents for children that have various programs and one of them is teaching English. To keep motivating them learning, it needs more interesting and challenging materials. From the research on revitalization of Sentani language for children through folktales in Jayapura Regency in 2017-2018, it was found that children like to listen and read Sentani folktales. Accordingly, this paper aims at utilizing folktales to teach English for children focusing on speaking in some children communal agents in Jayapura Regency by exploring two main questions, i.e. (1) why teaching speaking using Sentani folktales and (2) how to teach speaking using Sentani folktales. This is a qualitative-descriptive study utilizing data of folktales that were obtained via observation, interview, and FGD from some informants, namely tribal chiefs and Sentani elders in East, Central, and West Sentani in 2017. This writing adopts theory of literature and language teaching (Lazar, 2002) and Vigotsky’s scaffolding learning (Omrod, 2020). This study concludes that (1) children are more active and enthusiastic to speak in English, (2) children are able to learn their ancestor’s heritages, (3) it is an alternative way of both revitalizing Sentani folktales and disseminating the socio-cultural values embedded in them.
HYDROCHEMISTRY AND GEOCHEMICAL FACIES OF\r\nGROUNDWATER FOR THE TLEMCEN REGION: STATISTICAL AND\r\nGEOCHEMICAL APPROACH (EXTREME WEST OF ALGERIA)

Ponte Academic JournalAug 2020, Volume 76, Issue 8 HYDROCHEMISTRY AND GEOCHEMICAL FACIES OF\r\nGROUNDWATER FOR THE TLEMCEN REGION: STATISTICAL AND\r\nGEOCHEMICAL APPROACH (EXTREME WEST OF ALGERIA)Author(s): Guettaia Sabrine ,A. BOUDJEMAJ. Ponte - Aug 2020 - Volume 76 - Issue 8 doi: 10.21506/j.ponte.2020.8.12 Abstract:The study area is located in the northern part of the Tlemcen Mountains. It contains very important underground hydraulic potentialities represented by the very karstified dolomitic formations of the Upper Jurassic and the sandstones of the Upper Miocene and Quaternary. The hydrogeochemical study allowed us to conclude that the water points that are saturated in carbonate formations undergo basic exchanges between calcium and sodium in the clay fraction of the aquifer, which led to the presence of a deficit of Ca2+ compared to either SO42-, or bicarbonates. On the other hand, water points which are undersaturated in carbonate formations have induced either an inverse base exchange between Na+ and Ca2+ or the dissolution of the carbonate formations, which has led to the predominance of Ca2+ or Mg2+ over sulphates or even a deficit of Na+ over chlorides. Analysis by Main Component and by the Ascending Hierarchical Component revealed the existence of a close correlation between the chemical elements (Cl-, SO42-, Na+, Mg2+, NO3-,K+ and SO42-), indicating the presence of pollution by irrigation water. A second correlation is initiated between Ca2+ and HCO3- indicating the dissolution of carbonate formations. Keywords: Tlemcen aquifers, Multi-variate statistical analysis, Hydrogeochemistry, Pollution. Download full text:Check if you have access through your login credentials or your institution Username Password
A Novel Approach for Hiding Information into Mathematical Expression

Information hiding has received a lot of attention recently. Various methods have been developed for steganography, and at the same time, proper steganalysis has been designed to detect hidden data. However, an approach that is introduced in a new type of cover can be less doubtful due to the lack of attention to steganalysis analyses. This paper proposes a method that can convert a message into a mathematical expression. The generated mathematical expression can be used as a cover to transmit the message along with a highly secure text. The proposed method, using a suitable stochastic grammar, has the ability to create a mathematical expression based on a given text. Probability of grammar rules can be determined in accordance with the carrier text and based on the type of mathematical expressions.
Medical Diagnosis using Verbal Description to Classify the Category of the Ailment

A huge amount of unstructured text data that contains valuable information over the online. This text is more volatile and changing rapidly making hard to process, read, extract and process. Natural language Processing (NLP) may be a subfield of linguistics which is worried with interactions with text data accustomed extract the key information. NLP helps to beat the challenges which is related to text data vulnerability. There are numerous publicly available unstructured text data. Among those we chose medical text data which is comprised of description of patients within the text and voice format. Basically, doctors follow an explicit procedure of collecting data of assorted symptoms or anomalies that a patient experiences so as to research true and treat the condition. Often the patient has vague memory of what and when these anomalies have occurred. we aim to form accurate records of those ailments together with when it occurred to assist doctors better understand the circumstance in as little time as possible. We used different machine and deep learning model to extract the summary from the statement text data to classify the ailments.
Sentiment Based Movie Rating System

Opinion Mining (also referred as Sentiment Analysis) refers to the use of natural language processing, text analysis and computational linguistics to identify and extract subjective information in source materials. For any type of information gathering, we always see what the opinions of people about that product are or any service provided. With the growing availability and popularity of opinion-rich resources such as online review sites and personal blogs, new opportunities and challenges are now available for people. Opinion Mining is such a field that helps user know the reviews about any product or service he / she is interested in. OpinionMining is a task of extracting from a set of documents expressed by a source on a specified target.
Gaussian Process Surrogate Methods for Sample-Efficient Approximate Bayesian Computation

In many application fields such as ecology, epidemiology and astronomy, simulation models are used to study complex phenomena that occur in nature. Often the analytical form of the likelihood function of these models is either unavailable or too costly to evaluate which complicates statistical inference. Likelihood-free inference (LFI) methods such as approximate Bayesian computation (ABC), based on replacing the evaluations of the intractable likelihood with forward simulations of the model, have become a popular approach to conduct inference for simulation models. Nevertheless, current LFI methods feature several computational and statistical challenges. Especially, standard ABC algorithms require a huge number of simulations which makes them infeasible when the forward simulations are expensive. This thesis deals with likelihood-free inference for computationally costly models. The main contribution is a coherent framework for LFI based on Gaussian process (GP) surrogate models. GP models allow to encode smoothness assumptions of the simulation model output to reduce the amount of simulations needed. Additionally, the uncertainty in the resulting model-based posterior approximations due to the limited simulation budget can be quantified. We develop Bayesian experimental design strategies to select the evaluation locations as to minimise the computational cost. Both sequential designs, where simulations are chosen one-at-a-time basis, and batch strategies, which allow to take advantage of parallel computing, are derived. In addition to the LFI scenario, the proposed methods also apply when the likelihood can be evaluated but is expensive. In essence, the proposed framework can be viewed as an LFI counterpart of probabilistic numerical methods such as Bayesian optimisation, developed for optimising expensive objective functions, and Bayesian quadrature, developed for computing integrals of expensive functions. We demonstrate the advantages of the proposed LFI methods using extensive empirical simulations. Some theoretical analysis of the proposed algorithms is also provided and their relation to some other GP surrogate methods are discussed. In addition to the contributions to statistical methodology, applications in population genomics are also considered. In particular, we use the GP-based ABC methodology to obtain an approximate posterior of a simulation model describing horizontal gene transfer in bacteria. We also develop a probabilistic model and an inference algorithm using a novel combination of ABC and Metropolis-within-Gibbs sampling to facilitate better understanding of bacterial colonisation.; Monilla sovellusaloilla, kuten ekologia, epidemiologia ja tahtitiede, monimutkaisia luonnonilmiota tutkitaan simulaatiomallien avulla. Usein tallaisiin malleihin liittyva uskottavuusfunktio ei ole analyyttisesti kasiteltavissa tai se on laskennallisesti liian raskas evaluoida, mika hankaloittaa tilastollista paattelya. Uskottavuusvapaasta paattelysta (likelihood-free inference, LFI), kuten likimaarainen…
Characteristics of the Most Popular Video Lessons from Chemistry Channels on YouTube Edu

There has been an increase in the use of video lessons in education since the 1990s.Currently, video platforms on the Internet facilitate the access and publication of video lessons from various disciplines.In this paper, we aimed to identify Chemistry channels on YouTube Edu and analyze the characteristics of their most popular video lessons by evaluating some technical and pedagogical aspects.We identified 15 Chemistry channels on YouTube Edu, of which his most popular video lessons have diversified characteristics, but which generally have long durations and the teacher speaking when using a blackboard to expose content directed for high school level.We conclude that the characteristics related to the teaching resources and strategies of the video classes analyzed are similar to those of traditional classroom lectures.
The Influence of Internet Search on College Students Independent Thinking Against the Background of Big Data

Against the background of big data, the convenience of Internet search expands the knowledge of college students, and stimulates the activity and creativity of thinking to some extent.However, overreliance on search engine will weaken the independent thinking ability of college students.Starting from the current situation of college students using the Internet, this paper discusses the mechanism of the influence of Internet search on college students' independent thinking, and then puts forward how college students use Internet search properly in the context of big data, and maintain their independence of thinking.
Penggunaan Sensor TCS3200 dan NodeMCU untuk Mendeteksi Warna Daun Padi dalam Menentukan Jumlah Pupuk Urea Bebasis IoT

Technological developments encourage changes in the way decisions are made. In terms of stopping the application of urea fertilizer, farmers still rely on BWD observations. In this study, using the RnD method by directly observing the research location in the farmer group Gapoktan, in the village of Tosari, Kendan district and analyzing the problem then making a prototype which will be tested by experts. In this study, a tool was made using NodeMCU with TCS3200 sensor to detect color, which was then sent via the internet to the database using IoT technology. In this study, using several trials with different parameters of urea fertilizer use and the results of the TCS3200 sensor can detect colors according to what is on the BWD and send data to the database via the internet. In this system, farmers can recommend the use of suitable urea fertilizers outside a certain area so as to minimize errors in the observation on BWD, this will make the use of urea fertilizer to be the right dose.&#x0D;
Advanced Oversampling for Improved Detection of Software Anomalies in a Robot

Anomaly detection has been a challenging topic for decades and it still is open to new contributions nowadays. More specifically, the detection of anomalies (not only hardware ones but also those affecting the software) suffers from many problems when monitoring cyber-physical systems. One such usual problem is the much fewer data samples of anomalies than those available for the normal functioning of systems. This class-imbalance problem is addressed in the present paper and a novel strategy for oversampling the minority class is applied to an open dataset containing information about the performance of a component-based robot. The proposed strategy mainly consists on selecting the instances to be oversampled according to different criteria instead of randomly oversampling. Obtained results demonstrate that the proposed strategy improves predictive performance, especially when the SVM (Support Vector Machine) is used as classifier.
On codes in the projective linear group $PGL(2,q)$

In this paper, we resolve a conjecture of Green and Liebeck [Disc. Math., 343 (8):117119, 2019] on codes in $PGL(2,q)$. To be specific, we show that: if $D$ is a dihedral subgroup of order $2(q+1)$ in $G=PGL(2,q)$, and $A=\{g\in G: g^{q+1}= 1,\, g^2\ne 1 \}$, then $\lambda G=A\cdot D$, where $\lambda=q$ or $q-1$ according as $q$ is even or odd.
Privacy-Preserving Distributed Processing: Metrics, Bounds, and Algorithms

Privacy-preserving distributed processing has recently attracted considerable attention. It aims to design solutions for conducting signal processing tasks over networks in a decentralized fashion without violating privacy. Many algorithms can be adopted to solve this problem such as differential privacy, secure multiparty computation, and the recently proposed distributed optimization based subspace perturbation. However, how these algorithms relate to each other is not fully explored yet. In this paper, we therefore first propose information-theoretic metrics based on mutual information. Using the proposed metrics, we are able to compare and relate a number of existing well-known algorithms. We then derive a lower bound on individual privacy that gives insights on the nature of the problem. To validate the above claims, we investigate a concrete example and compare a number of state-of-the-art approaches in terms of different aspects such as output utility, individual privacy and algorithm robustness against the number of corrupted parties, using not only theoretical analysis but also numerical validation. Finally, we discuss and provide principles for designing appropriate algorithms for different applications.
ANALYSIS OF STUDENT RESPONSE TO KWLA (WHAT I ALREADY KNOW, WHAT I WANT TO KNOW, WHAT I LEARNED, AND THE AFFECT OF THE STORY) STRATEGY IN THE LEARNING READING COMPREHENSION

This study aims to determine students' responses to learning to read narrative text comprehension using the KWLA strategy (What I Already Know, What I Want to Know, What I Learned, and The Affect of the Story). A collecting data in this study used a questionnaire in the form Unstructured questionnaires and interviews The results of the data were obtained and analyzed quantitatively qualitatively The data generated in the form of numbers were then described Based on the results of the study, it was found that aspects 1 to 5 that contained responses of students' interest in learning thus obtained by 90.4% included in the category very good.In aspects 6 to 10 which contain student responses to ease in understanding and learning the material obtained a percentage of 89.1% included in the very good category.In aspects 11 to 13 which contain student responses in the activity and courage to express opinions in the learning process a percentage of 87 is obtained , 9% in the category of very good, and aspects 14 to 15 which contain responses to the ease of students in concluding learning activities get an average percentage of 90.2% included in the very good category. This shows that the KWLA strategy is able to increase student interest in efforts to improve reading comprehension skills.
An Analysis of the Relationship between Coastal Economic Belt Environment and University Students' Entrepreneurship

Duan, Y.F., 2020. An analysis of the relationship between coastal economic belt environment and university students' entrepreneurship. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 262-264. Coconut Creek (Florida), ISSN 0749-0208.In recent years, with the number of new graduates remaining high and the jobs that society can provide can no longer fully meet the severe situation of college graduates, China has put forward the development strategy of “entrepreneurship drives employment”, which effectively solves Employment issues. This article makes an in-depth study and analysis of the relationship between the development of the coastal economic zone and the employment and entrepreneurship of college students, and puts forward some reasonable suggestions according to the actual situation, which is helpful for the development and construction of the coastal economic zone. Solve the employment problem of college students..
Gemini: A Grammar and Recommender System for AnimatedTransitions in Statistical Graphics

Animated transitions help viewers follow changes between related visualizations. Specifying effective animations demands significant effort: authors must select the elements and properties to animate, provide transition parameters, and coordinate the timing of stages. To facilitate this process, we present Gemini, a declarative grammar and recommendation system for animated transitions between single-view statistical graphics. Gemini specifications define transition "steps" in terms of high-level visual components (marks, axes, legends) and composition rules to synchronize and concatenate steps. With this grammar, Gemini can recommend animation designs to augment and accelerate designers' work. Gemini enumerates staged animation designs for given start and end states, and ranks those designs using a cost function informed by prior perceptual studies. To evaluate Gemini, we conduct both a formative study on Mechanical Turk to assess and tune our ranking function, and a summative study in which 8 experienced visualization developers implement animations in D3 that we then compare to Gemini's suggestions. We find that most designs (9/11) are exactly replicable in Gemini, with many (8/11) achievable via edits to suggestions, and that Gemini suggestions avoid multiple participant errors.
THE DIVINE UNITY IN AND BEYOND NATURE: A COMPARATIVE STUDY IN WALT WHITMAN’S AND JALAL AD-DIN MUHAMMAD RUMI’S ECSTATIC POEMS

As of today, the teachings of Rumi, Ibn al-Arabi and other Sufi mystics are enjoying a considerable revival in the United States. Especially ecstatic poems of Jalal ad-Din Muhammad Rumi have sold hundreds of thousands of copies recently, making him a best-selling poet not only in the United States but also in other many countries. The roots of American fascination for Sufism, however, reach as deep as the nineteenth century when American transcendentalism appeared as an expression within Romanticism as a literary movement. This paper aims to compare the concept of the Divine Unity in both seemingly unrelated philosophical movements in terms of how the ecstatic poems of Walt Whitman and Jalal ad-Din Muhammad Rumi transcend physical existence in nature to see the truth of the universe, which means, for all of them, the unity with God. Some studies, albeit clear differences between two traditions, show evidence to commentate that their mystical and transcendental tenets share a basic understanding of human desire leading to the Divine Unity. Two religious and philosophical movements argue about omnipresence and omnipotence of God and in this point nature plays a crucial role as God’s perfect manifestation. The ascetic poems of Rumi, the thirteenth-century Sufi Muslim philosopher born in today’s Afghanistan, and the transcendental poems of Whitman, the nineteenth-century Christian transcendentalist from New York, are bedecked with similar natural elements to see what lays beyond form in compossible nature.
Generalized Zero-Shot Learning via VAE-Conditioned Generative Flow

Generalized zero-shot learning (GZSL) aims to recognize both seen and unseen classes by transferring knowledge from semantic descriptions to visual representations. Recent generative methods formulate GZSL as a missing data problem, which mainly adopts GANs or VAEs to generate visual features for unseen classes. However, GANs often suffer from instability, and VAEs can only optimize the lower bound on the log-likelihood of observed data. To overcome the above limitations, we resort to generative flows, a family of generative models with the advantage of accurate likelihood estimation. More specifically, we propose a conditional version of generative flows for GZSL, i.e., VAE-Conditioned Generative Flow (VAE-cFlow). By using VAE, the semantic descriptions are firstly encoded into tractable latent distributions, conditioned on that the generative flow optimizes the exact log-likelihood of the observed visual features. We ensure the conditional latent distribution to be both semantic meaningful and inter-class discriminative by i) adopting the VAE reconstruction objective, ii) releasing the zero-mean constraint in VAE posterior regularization, and iii) adding a classification regularization on the latent variables. Our method achieves state-of-the-art GZSL results on five well-known benchmark datasets, especially for the significant improvement in the large-scale setting. Code is released at https://github.com/guyuchao/VAE-cFlow-ZSL.