Reviewerly/exHarmony huggingface dataset:
Meta-mass systems: A harbinger for a vibration energy harvesting technology

For a limited class of fuzzy structures, the “master” structure is a grounded Newtonian mass wherein are distributed the “fuzzies,” modeled as nearly equal magnitude sprung masses with resonances densely filling a frequency band. We term said system a grounded “meta-mass,” showing a properly designed “meta-mass vibration energy harvester” addresses a fundamental technical obstacle to the harvesting of waste mechanical energy, the so-called “aperture” problem; thereby making meta-mass systems a harbinger for a vibration energy harvesting technology. Shown is the oscillators’ resonances provide ``bounds’’ on the system resonances, the relative “locations” of the system resonances within its bound-pair being determinative of system behavior. Then shown is the value of a certain combination of non-dimensional system measures—twice the fractional bandwidth squared divided by the product of the mass ratio and the natural log of N—is determinative of said relative locations. Finally shown is virtually all the energy inputted impulsively to the Newtonian mass is transferred to the encapsulated oscillators in a time of the order of the inverse of the band of oscillators, for a narrow system subclass wherefore each system resonance is near the center of its bound-pair.
Intelligent throughput stabilizer for UDP-based rate-control communication system

In view of the successful application of deep learning, mainly in the field of image recognition, deep learning applications are now being explored in the fields of communication and computer networks. In these fields, systems have been developed by use of proper theoretical calculations and procedures. However, due to the large amount of data to be processed, proper processing takes time and deviations from the theory sometimes occur due to the inclusion of uncertain disturbances. Therefore, deep learning or nonlinear approximation by neural networks may be useful in some cases. We have studied a user datagram protocol (UDP) based rate-control communication system called the simultaneous multipath communication system (SMPC), which measures throughput by a group of packets at the destination node and feeds it back to the source node continuously. By comparing the throughput with the recorded transmission rate, the source node detects congestion on the transmission route and adjusts the packet transmission interval. However, the throughput fluctuates as packets pass through the route, and if it is fed back directly, the transmission rate fluctuates greatly, causing the fluctuation of the throughput to become even larger. In addition, the average throughput becomes even lower. In this study, we tried to stabilize the transmission rate by incorporating prediction and learning performed by a neural network. The prediction is performed using the throughput measured by the destination node, and the result is learned so as to generate a stabilizer. A simple moving average method and a stabilizer using three types of neural networks, namely multilayer perceptrons, recurrent neural networks, and long short-term memory, were built into the transmission controller of the SMPC. The results showed that not only fluctuation reduced but also the average throughput improved. Together, the results demonstrated that deep learning can be used to predict and output stable values from data with complicated time fluctuations that are difficultly analyzed.
Peningkatan Hasil Belajar Peserta Didik dengan Menggunakan Model Pembelajaran Discovery learning pada Kelas XI MA As’adiyah Putri Sengkang

This research is classroom action research. Teachers who are delivering learning materials do not use varied methods and always use the lecture method, so that most students do not understand and are not active in the learning process which results in unsatisfactory student learning outcomes. The purpose of this study was to determine the increase in student learning outcomes through the Discovery Learning cooperative learning model in biology class XI IPA MA As'adiyah Putri Sengkang. The subjects of this study were students of class XI MA As'adiyah Putri Sengkang, totaling 22 students. It was carried out in two cycles. Each cycle was carried out 3 meetings. At the end of cycles I and II, data was collected using a learning outcome evaluation test. The instruments used in this research are learning outcomes test questions and student activity observation sheets. The results showed that the application of the Discovery Learning learning model could improve student learning outcomes in biology class XI IPA 5 MA As'adiyah Putri Sengkang.
Background Speech Synchronous Recognition Method of E-commerce Platform Based on Hidden Markov Model

In order to improve the effect of e-commerce platform background speech synchronous recognition and solve the problem that traditional methods are vulnerable to sudden noise, resulting in poor recognition effect, this paper proposes a background speech synchronous recognition method based on Hidden Markov model. Combined with the principle of speech recognition, the speech feature is collected. Hidden Markov model is used to input and recognize high fidelity speech filter to ensure the effectiveness of signal processing results. Through the de-noising of e-commerce platform background voice, and the language signal cache and storage recognition, using vector graph buffer audio, through the Ethernet interface transplant related speech recognition sequence, thus realizing background speech synchronization, so as to realize the language recognition, improve the recognition accuracy. Finally, the experimental results show that the background speech synchronous recognition method based on Hidden Markov model is better than the traditional methods.
Uso de redes sociales en la educación por los profesores en la Facultad de Odontología de la Universidad de Los Andes

Social networks inprove communication and learning, becoming a resource in health education. A better understanding of these tools can help to redefine teaching. The aim is to describe the use of social networks by teachers of the Faculty of Dentistry-ULA as digital tools in dental education. This is a descriptive and cross-sectional investigation, applying a mixed and self-administered questionnaire to 110 teachers. There is a good receptivity for the use of social networks; However, there are still barriers to its integration into teaching methodologies. It is concluded that they are very useful tools, but it is still necessary to develop effective strategies for their inclusion, as well as policies for use and guidance for teachers and students. Recibido: 22/09/2021  Aceptado: 07/10/2021
Learning Through Social Networks: How Foreign Workers Optimize the Use of Fintech to Send Remittances

We use data from a leading fintech firm in Korea, including transaction-level data on international remittance payments to developing Asia and referral data among users, to study the role of social networks in helping low-income workers optimize their use of a new technology. Our study shows how experience using a desirable fintech feature--an order cancellation option--helps workers optimize the timing of the exchange rate applied to their transactions. Overall, we find that workers' personal experience using the fintech, and the experience of the worker's social network, increase the frequency and efficiency of workers' use of the feature.
Using SAPR Model for Solution of Social Poverty Problem Due to Covid-19 in Makassar City

This study aims to build an SAPR model on the problem of poverty, analyze the model, predict the number of poverty rates in the city of Makassar, and determine the parameters that affect the decrease in the number of poverty rates due to Covid-19 in the city of Makassar. This research is quantitative. The population of this study is the number of people in Makassar City who are affected by the spread of COVID-19, while the sample of this study is 400 people. The research stages are: Building the SAPR model on the level of social poverty, determining and analyzing the stability of the equilibrium point, determining the value of the basic reproduction number (R0), conducting model simulations using Maple. The results shown that the mathematical model of SAPR which is a non-linear system of differential equations can be a reference model for the problem of poverty; The results also shown that the analysis of the social poverty level of the population finds two equilibrium points, namely the free equilibrium point for the poor and the poor; the stability of the equilibrium point is free-poor and poor; The basic reproduction number R0 = 0.426 indicates that the poverty level of the social population can be controlled even though it has increased. Based on the model simulation, it was found that the parameter in the form of business funding assistance from the government could reduce the poverty rate due to the Covid-19 pandemic in Makassar city.
Gapped indexing for consecutive occurrences

The classic string indexing problem is to preprocess a string S into a compact data structure that supports efficient pattern matching queries. Typical queries include existential queries (decide if the pattern occurs in S), reporting queries (return all positions where the pattern occurs), and counting queries (return the number of occurrences of the pattern). In this paper we consider a variant of string indexing, where the goal is to compactly represent the string such that given two patterns P1 and P2 and a gap range [\alpha,\beta] we can quickly find the consecutive occurrences of P1 and P2 with distance in [\alpha,\beta], i.e., pairs of occurrences immediately following each other and with distance within the range. We present data structures that use O(n) space and query time O(|P1|+|P2|+n^(2/3)) for existence and counting and O(|P1|+|P2|+n^(2/3)*occ^(1/3)) for reporting. We complement this with a conditional lower bound based on the set intersection problem showing that any solution using O(n) space must use \tilde{\Omega}}(|P1|+|P2|+\sqrt{n}) query time. To obtain our results we develop new techniques and ideas of independent interest including a new suffix tree decomposition and hardness of a variant of the set intersection problem.
초등학교에서 동물복지교육 실태 분석 및 활성화 방안 연구

Societal concerns regarding animal rights and welfare are rising. In response to this social phenomenon, educators should consider incorporating animal welfare education into public education. To explore new educational approaches to animal welfare, topics related to animal welfare in the 2015 revised curriculum were carefully analyzed. Teachers’ awareness on this issue was also evaluated in order to apply appropriate methods of animal welfare education in elementary education. The study found some contents of the 2015 revised curriculum that presented specific examples of animal welfare. Science units including Life Cycle of Animals, The World of Animals, Ecosystem and Environment introduced animal welfare. Other subjects of the curriculum also implemented the concepts of animal welfare. On the other hand, current teachers were aware of the need of animal welfare education, however the lack of systematic training prevents them from producing maximum effect of the current education. Therefore, a systematic training for teachers must be established, and an innovative approach to the new curriculum must be taken.
CODE MIXING OF SIPITUHUTA LANGUAGE IN MEREK WEDDING CEREMONY

The research is aimed at discussing code mixing in Merek wedding ceremony. The theories in this thesis is about code mixing. The method used in this thesis is descriptive qualitative design. The objectives of this research are to find out the types of code mixing used by the speakers of Merek wedding ceremony and describe the function of the reasons why the speakers using code mixing on Merek wedding ceremony and also to explain why the speakers using code mixing on the utterances. The result of the research applied Muysken(2000) showed there are 3 types of code mixing consisted in the utterances on the wedding namely : Insertion, Alternation, Congruent lexicalization, then the function of code mixing supported by Hoffman (1991) namely : Talking about particular topic , Being emphatic about something, Quoting somebody else, and Intention of clarifiying the speech content interculator from the 17 utterances. The findings are expacted to contribute a better understanding of code mixing.
Devanagari Handwritten Marathi Compound Character Recognition System

Handwritten character recognition a field of research in AI, computer vision, and pattern recognition. Devanagari handwritten Marathi compound character recognition is most tedious tasks because of its complexity as compared to other languages. As compound character is combination of two or more characters it becomes challenging task to recognize it. However, the researchers used various methods like Neural Network, SVM, KNN, Wavelet transformation to classify the features of compound Marathi characters and tried to give the accuracy in the recognition of it. But the problem of feature extraction, and time required is large. In this paper I am proposing the Offline handwritten Marathi compound character recognition using deep convolution neural network which reduces the computational time and increases the accuracy.
유아교사의 교사행복감과 교수효능감 및 직무스트레스가 교사-유아상호작용에 미치는 영향

In its most positive context, the purposes of the study are two-fold. One aspect of the study was to examine the relations between early childhood teacher’s job stress, happiness, teaching efficacy, and teacher-child interactions. The other intention of the study was to investigate the effects of early childhood teacher’s job stress, happiness, and teaching efficacy on the teacher in relation to teacher-child interactions in the classroom learning environment. The subjects of the study were 390 early childhood teachers working at kindergartens or child-care centers located in the Seoul, Korea Metropolitan area. The study utilized survey questionnaires, which were distributed and were used to measure major variables; teacher-child interaction inventory developed by Lee (2003), job stress inventory developed by Shin (2004), happiness inventory developed by Argyle (2001), and teaching efficacy inventory developed by Enochs and Riggs (1990). The collected data were analyzed using a SPSS 23.0 program. In the study, the descriptive statistics and Cronbach’s α coefficient were yielded to produce accurate results. For testing research questions, a Pearson’s correlation analyses and hierarchical regression analyses were performed. As the results show, the incidence of early childhood teacher’s job stress had a significant negative correlation with teacher-child interactions, but happiness and teaching efficacy had significant positive correlations. The effects of early childhood teacher’s job stress, happiness, and teaching efficacy had significant effects on the teachers and their corresponding teacher-child interactions. As for the relative impact, teaching efficacy had the strongest impact, followed by happiness and job stress. The study results suggest the importance of the teacher’s internal psychological factors such as teaching efficacy and happiness.
Pengembangan Aplikasi Unggah Mandiri Repositori Karya Ilmiah Perpustakaan

The management of documentation for the publication of student writings at the IBI Darmajaya library has several problems. These problems include: the accumulation of files that must be inputted within a certain period of time, slow processing, and frequent data inconsistencies. Meanwhile, the publication of student scientific works is a valuable asset of the University and the academic community. So that scientific work that is managed and well documented is very much needed in a university.This study aims to build an independent upload repository for student scientific work publications. The research was conducted in several stages, namely: planning and needs analysis, design, system development and testing. The research produces outputs that facilitate the process of independent uploading of student papers. The independent upload process is carried out in several stages, starting from creating an account, uploading papers and validation from the editor.
Poster: PyGMT: Accessing the Generic Mapping Tools from Python

Poster presented at the AGU 2019 Fall Meeting.AbstractFor almost 30 years, the Generic Mapping Tools (GMT) have provided the Earth,Ocean, and Planetary Sciences with an open-source toolbox for processing andvisualizing spatial data (bathymetry, gravity, magnetic, earthquake focalmechanisms, and more). In many fields, GMT is the de facto standard forcreating high-resolution publication quality maps, figures, and animations.Since version 5, GMT has provided a C language Application ProgrammingInterface (API) that allows other programs to access its core functionality. Weare using this bridge to develop PyGMT (www.pygmt.org;formerly GMT/Python), an open-source library that allows users of the Pythonprogramming language to leverage the almost thirty years of continuous GMTdevelopment. PyGMT is designed to integrate with the existing scientific Pythonecosystem, including popular packages such as numpy, pandas, and xarray. PyGMTintegrates seamlessly with the Jupyter notebook, allowing high-quality figuresto be generated interactively both in a personal computer and in cloudcomputing environments compatible with Jupyter. We will present the design andusage of the software package, latest developments and updates, and lessonslearned during its implementation.NotesThe poster was made entirely on Inkscape. The fonts are Noto Sans and Source Code Pro.The development of PyGMT was funded byNSF grant OCE-1558403.
Anti-corruption training of public officials: practice-oriented view of the problem

The article describes the features of the formation of an anti-corruption system aimed at training public officials. This system takes into account the international obligations of Russia, as well as the needs of the authorities in the professional training of officials, the creation of an efficient apparatus, and increased efficiency in the fight against corruption. The author presents an approach to developing the training for anti-corruption officials, engaged in countering corruption and other offenses, as well as other employees or persons filling state (municipal) posts through the use of interactive technologies. Special attention is paid to the use of interactive teaching methods, such as brainstorming, case work, group work, analysis and working with documents, modeling, demonstration, guided discussion, debate, creative assignments, business games, expert meeting, Socrates method, use of video recordings and visual guidances. Government bodies, working to prevent corruption and other offenses, together with educational organizations are actively developing curricula and training materials for anti-corruption classes. All materials of the article can be used for organizing anti-corruption education for civil servants and public officials.
Ontology Based Recommender System for Diabetic Patients

Chronic diseases are a persistent and long-lasting human health conditions that lasts for more than three months.Today the prevalence of chronic non-communicable diseases in Ethiopia increases rapidly because of different reasons like poor nutrition habit, lack of physical activities, drinking alcohols, smoking and life style issues.To overcome this problem different technological applications are developed globally to support both the health professional in diagnosis process and the patients for their self-treatment activities.Ontology helps to create common understanding between human and computers, enable reusability of information, and allows sharing of concepts.Ontology based personalized recommendation model is for diabetic patient in Ethiopian context.We have used design science research methodology in our proposed study.In the development of the proposed model, first we have developed the patient and domain or disease ontology and then the two ontologies needs to integrate in order to develop the required recommendation model.We have used Protégé ontology development tool for the development of the proposed domain or disease and patient ontology.This research discusses how to develop patient and domain or disease ontology and then it also describes how two ontologies need to integrate in order to develop the required recommendation model.
해방 후 1950년대까지 중등교사 자격제도의 수립과 한계

This study set out to analyze the characteristics of the review process for the authorization of history textbooks during the period of the ‘Course of Study’. The main findings of this study are as follows:This study dealt with the establishment of teacher qualification standards and the problem of unqualified teachers in the expansion of secondary school teachers in Korea from the 1940s to the 1950s.As qualification certification was implemented in step with an increase of secondary education teachers after liberation, teacher qualification standards had to be made.Teacher qualification standards were established, starting with Elementary and Secondary School Teacher Qualification Standards (1948) and going through the legislation processes of Educational Civil Service Qualification Standards (1953) and Enforcement Regulations (1954). Accordingly, educational background, experience, and retraining standards needed for the provision of teacher certifications such as for regular teachers and assistant teachers were prepared.The establishment of standards led to the occurrence of unqualified teachers. While opportunities for qualification through retraining were provided, acquisition was difficult due to the Korean War. As unqualified people were on the verge of being expelled under the laws of 1945, educational authorities relieved them through simple screenings.Consequentially, policies to maintain teacher standards by establishing teacher qualification standards and certification expiration dates were not carried out and were refracted. This became a precedent and afterwards, it led to teacher policies busy with supply and demand during a period of secondary education expansion.
Heat Consumption Technique of Cloud Data Center and Produce Distilled Water

Cloud computing is a recent and emerging technology of computer science and engineering. In cloud data center runs more than thousands of server and host runs for process and store the data. Due to this reason, the cloud data center produces a lot of carbon and heat which exhalation into the air thus the environment pollution occurs due to the cloud data center. That is why researches in energy consumption, saving energy, cooling renewable energy, environmental pollution control are a new researches area of cloud computing. In this research, we mainly concentrate on the heating problem of the cloud data center and produce distilled water by using the heat of the cloud data center. We transfer the heat from the cloud data center to the water tank through the channel and by using this heat we produce the distilled water. For produce, the distill water huge heat and cost required. In our research proposal for producing the distilled water, the main source of the heating energy is cloud data center so we can reduce the heating cost for producing the distilled water. By using this proposed model we not only reuse the heat of the data center but also we can control the heating problem of the cloud data center which is harmful to the environment.