Reviewerly/exHarmony huggingface dataset:
Hubungan Kepercayaan Diri dengan Kemampuan Berbicara Siswa Pada Pembelajaran Tematik SDN Bakalan Krajan 1 Malang Kelas IV

The purpose of this study was to examine the relationship between self-confidence and speaking ability of students at SDN Bakalan Krajan 1 Malang. This research uses a quantitative approach to this type of research. The population of the research was 77 students of grade IV SDN Bakalan Krajan 1 Malang with a total of 77 students and a sample of 42 students. The data technique was carried out by observation, tests, questionnaires, documentation. The results showed that the level of self-confidence of the fourth grade students of SDN Bakalan Krajan 1 Malang was in the high category with a percentage of 69% of 29 students with a total of 42 students and the level of speaking ability of the fourth grade students of SDN Bakalan Krajan 1 Malang was in the good category with a percentage of 67% of 28 students with a total of 42 students. It is realized that there is a significant relationship between self-confidence and speaking ability of fourth grade students of SDN Bakalan Krajan 1 Malang.
Hybrid Elliptic Curve Based Bio-Hash Function Sign-Cryption for Big Data Privacy and Security in Wireless Sensor Networks

Increasing numbers of people, sensors and computers link digital networks that share data, view, transfer and interpret data. The phenomenon of heterogeneous data production is known as broad data. Although the additional comfort of Big Data is advantageous, people often face direct challenges to data privacy and security. Big data is immense and hence you need an appropriate system for defence. In order to provide an efficient single stage, signcryption technology blends encryption with signature. The chosen encryption protection and message security are two essential features when grappling with data security risks. This means that an appropriate mechanism to solve these issues is incredibly necessary. Here we give signature based on the cryptography and the biohash feature of hyperelliptic curves. The protection of the scheme proposed is tested using the logic of Burrows-Abadi-Needham. Furthermore, considering big data protection in Wireless Sensor Networks as a topic, it should not only be taken into consideration when designing and integrating an environment for big data, but over the entirety of its life cycle, including activities and in particular when coping with and reacting to accidents. This article offers a case report focused on a response mechanism sponsored by a private blockchain wireless sensor networks in the big data ecosystem. To this end, this paper provides a case study. The use of blockchain helps to improve the data privacy, immutability and traceability of stored data.
Recognition of handwritten mathematical expressions using machine learning

Handwritten digits, symbols and handwritten mathematical expressions recognition is ademanding or inspiring mission owing to variation in writing style its , overwriting in symbols, characters ,digits also complex semantics and two dimensional structure. It is an area of research from last threedecades, but not a single method fulfills all the requirement viz. execution time and identification rate. Thedatabase collected or generated from various writers considering the style of writing, stroke movements,overwriting and all that also the statistical and complex features have been detached and neural networkclassifier has been used for the recognition. The automatic recognition of math symbol and expressions arenecessary to recognize math symbols, expression, digits, characters in students answer sheet, Postal address,handwritten notes etc. The success rate of the system can be determined with throughput, efficiency andidentification rate.
Designing Augmented Reality Surah Al-Fatihah Application in Assisting Learning for Children

The development of the world of technology which is getting more advanced every day has helped people to facilitate human activities such as military activities, government, offices, entertainment and others. One of them is education, with the application of sophisticated technology, of course, it can help activities in the teaching and learning system, one of which is the use of smartphones. Smartphones have now become a lifestyle and necessity among various people even among children who mostly depend on smartphones to fill their time every day, but this not only produces a positive side for the child but also gives negative impact on their life patterns. At this time many children use the smartphone only for games and entertainment, wasting a lot of time in vain and leaving the Qoran activities. This condition requires us to make smartphone use even more positive. So a learning application of the Al-Fatihah surah was designed using Android-based Augmented Reality which was designed and programmed using Unity 3D and Vuforia. In order to make children more interested in learning Surah Al-Fatihah.
Massively Distributed Clustering via Dirichlet Process Mixture

Dirichlet Process Mixture (DPM) is a model used for multivariate clustering with the advantage of discovering the number of clusters automatically and offering favorable characteristics, but with prohibitive response times, which makes centralized DPM approaches inefficient. We propose a demonstration of two parallel clustering solutions : i) DC-DPM that gracefully scales to millions of data points while remaining DPM compliant, which is the challenge of distributing this process, ii) HD4C that addresses the curse of dimensionality by performing a distributed DPM clustering of high dimensional data such as time series or hyperspectral data.
초등학교 신규교사의 교직 생애 첫 교원능력개발평가 경험기

The purpose of this study was to explore the experiences of elementary school novice teachers, and to examine their honest thoughts and feelings about the teacher ability development evaluation system. As it was the teachers first time experiencing this system, novice teachers in elementary school can easily recall and compare their thoughts before and after entering into teaching. After listening to their stories, we explored the points noted in order to discuss and improve this system. For this study, ten novice teachers in elementary school participated in the in-depth interviews. Prior to their involvement in the teacher ability development evaluation, few teachers had prior knowledge of the system. However, although there was little prior knowledge regarding evaluation, they knew about the purpose of the system: professional growth. Also, the novice teachers had both expectations and worries about the evaluation. Based on the answers received in the survey and interviews, it was suggested that universities of Education, and training sessions for novice teachers should add course materials related to this system. It was also suggested that it is necessary to expand upon the evaluation of students, not of fellow teachers. Moreover, it was also pointed out that it is necessary to clarify the questions and improve the introduction data of educational activities and the ability development plan. Moreover, there is a need to develop the positive function of the teacher ability development evaluation and reduce the negative atmosphere of schools.
A Visuospatial Dataset for Naturalistic Verb Learning.

We introduce a new dataset for training and evaluating grounded language models. Our data is collected within a virtual reality environment and is designed to emulate the quality of language data to which a pre-verbal child is likely to have access: That is, naturalistic, spontaneous speech paired with richly grounded visuospatial context. We use the collected data to compare several distributional semantics models for verb learning. We evaluate neural models based on 2D (pixel) features as well as feature-engineered models based on 3D (symbolic, spatial) features, and show that neither modeling approach achieves satisfactory performance. Our results are consistent with evidence from child language acquisition that emphasizes the difficulty of learning verbs from naive distributional data. We discuss avenues for future work on cognitively-inspired grounded language learning, and release our corpus with the intent of facilitating research on the topic.
Online Voting System - Powered by Blockchain

Electronic voting or e-voting has been used in varying forms since the 1970s with fundamental benefits over paper based systems such as increased efficiency and reduced errors. However, there remain challenges to achieve widespread adoption of such systems especially with respect to improving their resilience against potential faults. Blockchain is a disruptive technology of the current era and promises to improve the overall resilience of e-voting systems. This paper presents an effort to leverage benefits of blockchain such as cryptographic foundations and transparency to achieve an effective scheme for e voting. The proposed scheme conforms to the fundamental requirements for e-voting schemes and achieves end-to-end verifiability. The paper presents details of the proposed e-voting scheme along with its implementation using the Multichain platform. The paper presents in-depth evaluation of the scheme which successfully demonstrates its effectiveness to achieve an end-to-end verifiable e-voting scheme.
Penerapan Soft System Methodology dalam Ekstraksi Pengetahuan Tentang Akreditasi Universitas XYZ

As a university, accreditation is a benchmark and recognition of quality standards and definitions of an educational institution (higher education) by parties outside an independent institution. Accreditation is also interpreted as an effort by the government to standardize and guarantee the quality of higher education alumni in order to ensure that quality among universities is not too varied and according to work needs. Management of Higher Education needs to improve quality and be an input for stakeholders who continue to improve the university. Using Soft System Methodology, researchers map and conceptualize models and plans to help XYZ University develop its accreditation values. In this case the Faculty of Science and Technology at XYZ University. From this research it was found that the XYZ University's Faculty of Science and Technology can provide alternative funding and development from all parties and grants as well as cooperation in outside universities that will help this faculty to add facilities, improve the quality of supervisors by using technology at the University's Faculty of Science and Technology XYZ. Recommendations given by researchers are faculties can make a web-based DSS (Decision Support System) accessed by intranet to help download traces of faculty development and can be used as a basis for decision making.
HUMAN RESOURCES MANAGEMENT IN SCHOOL

The article discusses the main aspects of human resource management in secondary schools. Emphasis is placed on the differences between school management and business. The essential factors influencing the management of human resources in secondary schools are pointed out. The strong connection between the ability of principals to create a positive environment and attitudes for full-fledged work in school was studied. The article promotes the idea that good human resource management is important for the image of a school, not only from the point of view of the principal, but also of each teacher managing his class and communication with parents. Unfortunately, there is a lack of competence in this area, which leads to negatives in the management of schools.
A Communication Efficient Federated Kernel k-Means

A federated kernel k-means algorithm is developed in this paper. This algorithm resolves two challenging issues: 1) how to distributedly solve the optimization problem of kernel k-means under federated settings; 2) how to maintain communication efficiency in the algorithm. To tackle the first challenge, a distributed stochastic proximal gradient descent (DSPGD) algorithm is developed to determine an approximated solution to the optimization problem of kernel k-means. To tackle the second challenge, a communication efficient mechanism (CEM) is designed to reduce the communication cost. Besides, the federated kernel k-means provides two levels of privacy preservation: 1) users’ local data are not exposed to the cloud server; 2) the cloud server cannot recover users’ local data from the local computational results via matrix operations. Theoretical analysis shows: 1) DSPGD with CEM converges with an O(1/T) rate, where T is the number of iterations; 2) the communication cost of DSPGD with CEM is unrelated to the number of data samples; 3) the clustering quality of the federated kernel k-means approaches that of the standard kernel k-means, with a (1+ϵ) approximate ratio. The experimental results show that the federated kernel k-means achieves the highest clustering quality with the communication cost reduced by more than 60% in most cases.
Pemanfaatan Berkelanjutan Gas Suar Bertekanan dan Bertemperatur Rendah Untuk Mengurangi Emisi Gas Rumah Kaca

Gas Flaring serves to protect gas processing equipment from excess pressure. Usually also used in precarious conditions, the flare system will burn the entire process gas. In oil exploration, refineries and chemical plants, the main purpose of using flares is as a safety equipment to protect vessels or pipes from over-pressure. Flaring gas usually comes from the upstream oil and gas business (Upstream Industry) and from downstream business (Downstream Industry). Basically, flare installation is a safety system for a gas produced from the processing and production process by burning the gas. Aside from being a safeguard, flare gas combustion aims to minimize environmental pollution because if the gas is discharged into the air without being burned first, it certainly has a negative impact on the surrounding environment, because it can trigger fire, explosion and poisoning. But with the burning of this gas, it also has another negative impact that is increasing gas emissions which can have an impact on the greenhouse effect. Therefore, being burned or not burned will both have a negative impact, the best solution is to be utilized, so that it is not only beneficial to the user, but also friendly to the surrounding environment. Not all flaring gases can be utilized, there are several conditions where flaring gases are difficult to use, especially flaring gases which have low pressure will be difficult to distribute, as well as low temperature gases which trigger freezing so that it is difficult to be channeled. Then a unit of equipment called a mini gas compressor is needed to increase the existing pressure, and a double pipe heat exchanger to increase the existing temperature, so that the flare gas can be flowed and utilized. Low pressure gas which ranges below 50 psig will flow to the mini gas compressor, resulting in an increase in pressure to almost 200 psig. With this pressure, the gas can be channeled to the Gas Collection Station (GCS) and subsequently used as gas injection to increase production or flow to PLN as a selling gas. At low temperatures the gas will freeze when it flows into the Gas Collection Station, so that the freezing does not occur, the gas will pass the double pipe heat exchanger which has been flowed with hot temperatures, so that the gas can melt, and gas can continue to flow from the gas well to the Collecting Station Gas for further utilization
Global Video Stabilization with Truncated Motion Estimation Model and Motion Smoothening

Extensive use of low-cost handheld cameras triggers handshakes and camera gestures to the majority of captured images. Methods to eliminate undesired camera movements from Video sequences have been developed for Video Stabilization (VS). Movement of camera-related artifacts may also affect the efficiency of most 2D video stabilization processes. By improving the motion estimation or motion fluidity process, the performance of the VS procedure can be improved. This article therefore proposes a global approach for video stabilization, which combines an efficient motion smoothing algorithm with a truncating motion calculation. Smoothing up of the high-frequency movements within frames achieves the stabilization. During the first step, the global movement estimate is selecting global motion vectors with the truncated Taylor series expansion. An FIR philter is used in this article to smooth global movement vectors by estimated motion vectors to stabilize shaky images. The proposed method eliminates undesirable movements efficiently and also conserves video information. Motion smoothening eliminates the loss of frame areas after stabilization. The method's efficiency is also compared with the latest global video stability results.
Portfolio Optimization based on Synthetic Fish Congestion Algorithm and Artificial Intelligence: In the Condition of Uncertainty and Half-Variance Risk

The issue of stock portfolio optimization is the most well-known issue in the area of optimization. The purpose of this issue is to create a portfolio among different stocks in such a way that it has the highest returns and the least risk. The problem of optimal selection of stock portfolio is one of the Non-deterministic polynomial hardproblems (NP-hard). For this reason, this article introduces a new hybrid algorithm based on artificial immunity algorithm and swarm of fish algorithm. The computational results show that the proposed combination method has the ability to find the best investment boundary in comparison to other proposed methods.
Knowledge management of research data: an initial analysis of Institute of Radiation Protection and Dosimetry

It can be said that scientific community produces research data, as well as uses research data to validate its work. Thus, research data cease to be research products to become informational resources. In this context, digital data repositories play an extremely important role in the scientific research process, since they can be used to share, access, reuse and validate data. In this sense, the informational recognition of research data, in recent years, transformed the view that characterized them as simple by-products of research processes, to the point that researchers, academic institutions and research development agencies begin to understand that these data contribute as a source of informational resources for scientific research and science teaching. Based on this, the objective of this work is to make a preliminary survey of the type of research data generated at the Institute of Radiation Protection and Dosimetry (IRD). For this, an analysis was made of the papers published by the permanent professors of the Post-graduation Program in Radiation Protection and Dosimetry in the last year (2019). It was then generated a table relating the Concentration Areas versus some technical information, regarding the generation of research data. In this sense, the analysis of the data of the IRD consists of a initial stage to assist the creation of the Institute's Digital data repository, which aims to provide the research data in order to be used in other researches.
In search of lost edges: a case study on reconstructing ﬁnancial networks

In this paper, we review the different methods designed to estimate matrixes from their marginals and potentially exogenous information. This includes a general discussion of the available methodology, which provides edge probabilities and models that are focused on the reconstruction of edge values. Besides summarizing their advantages and shortfalls, we conduct a competitive comparison of the approaches using Society for Worldwide Interbank Financial Telecommunication (SWIFT) MT 103 single customer credit transfers. The comparison concerning the binary reconstruction is divided into an evaluation of the edge probabilities and of the accuracy of the predicted edge values. To test the methods on different topologies, the application is split into two parts. The first part considers the full MT 103 network, providing an illustration of the reconstruction of large, sparse financial networks. The second part is concerned with reconstructing a subset of the full network, representing a dense medium-sized network. Regarding substantial outcomes, it is found that there are some methods that do work well in many respects. However, that does not imply that a certain method is generally superior. In general, the preferred model choice highly depends on the goal of the analysis, the presumed network structure and the availability of exogenous information.
Verification module for 3D reconstructions of historical and cultural heritage objects in virtual and augmented reality. The problem of combining 2D and 3D materials

The issues of preparation and selection of historical sources for their integration into the verification module are considered. Examples of using the module for different types of sources are presented. The features of the development of a virtual interface for such tasks are described using the example of pictorial historical sources of the 19th century. The issues of integration of narrative sources into virtual space were also touched upon.
Black-Gray-White Barcode Based on Error Correction Data Encoding

The paper presents an approach based on using barcodes with three color gradations (white, gray, and black) instead of traditional black and white barcodes. Such three-color barcodes can be produced and read by using the same equipment as usual black and white barcodes, but due to the third color they have a higher information density.It is shown in the paper that in order to ensure high reliability and accuracy of barcoded information reading, it is necessary to encode the data with a Reed-Solomon correction code which is capable of correcting multiple errors.The method of data encoding and decoding in the Galois field GF(3m), where m is the degree of an irreducible polynomial, is proposed. The noise immunity of the black-gray-white barcode capable of multiple errors correction based on Reed-Solomon code is analyzed and discussed as well.
Factors in the development of the education system in Russia

The paper aims to uncover the substance and content of the factors exerting a profound effect on the functioning of the higher education market in Russia. The research highlights the relevance of studying the needs of the job market for personnel training in conjunction with determining the prospects for the development of the educational services market. The authors perform econometric analysis and construct the demand and supply models. The empirical basis of the study includes the statistical data for the 1993-2018 time period. The results indicate that throughout the entire period there was a steady decrease in the number of school graduates in Russia which exacerbated in 2005 due to the decline in the birth rate in the early 1990s. The analysis found no significant correlation between the number of school graduates and the number of entrants admitted to higher education institutions. On the other hand, the number of students enrolled at universities was decreasing at a much slower rate than the number of school graduates. The study clarifies that the faculty number has a principal influence on the demand for higher education services in Russia, whereas the volume of investment in education affects a supply of graduates in the job market.