Reviewerly/exHarmony huggingface dataset:
Using intelligent technologies for knowledge formation in research on the impact of power industry on ecology and quality of life

The article discusses the possibilities of using intelligent technologies, namely, ontological and cognitive modeling to represent knowledge in studies of the impact of energy facilities on the environment and the quality of life of the population. The relevance of this work is due to the need to improve research methods. An intelligent information system and an ontological space of knowledge are being developed, integrating tools and an information base to carry out research. It is proposed to use ontologies to identify and organize the basic concepts of different subject areas related to joint research, establish relationships between them, as well as for the structural representation of knowledge. The cognitive modeling methodology is designed to analyze and model situations and make coordinated decisions in the energy industry, taking into account its impact on the environment and quality of life. Cognitive modeling is used to identify causal relationships between concepts, visualize them, describe possible situations and support to decision-making.
Proposal of Navigation by Scenarios Using Topological Map

We discuss a data format of topological maps and a generation method of the route guidance (scenario). Recent most autonomous mobile robots use a geometrically detailed map for the navigation. On the other hand, humans can move to a destination without such a detailed map. When a human teaches a way to a destination, he/she probably uses the information of landmarks and their connections. We focused on the information that human uses, we discuss the data format of the topological map. Furthermore. We propose a scenario generation method based on the experimental results. We obtained the text of route guidance by a questionnaire and analyze their structures and the most frequent words. And, based on the results, we propose the data format and generation method of the scenario. For verifying the effectiveness of the proposed method, we checked whether the subjects reach the goal based on the generated scenario.
The Challenges of Studying during the SARS-Cov-2 Pandemic

The subject of digitization of universities, online classes and courses, as well as studying via the Internet, has become very urgent and popular due to the SARS-CoV-2 coronavirus pandemic. This forced the implementation or development of appropriate remote learning systems at all universities. There are many doubts and questions concerning not only the organisation of distance learning, but also the quality of verification of learning outcomes; availability of teaching materials; technical skills of students and teachers using ICT tools; access to training and equipment; financial, mental and psychological difficulties, etc. The aim of the article is to analyse the challenges faced by universities that have gone remote during pandemic. The article in its main part consists of three elements: theoretical insight into the problems of distance education, difficulties and challenges concerning the organization of remote studying in universities and the evaluation of students of distance classes. This is the empirical part of the work. The research covered the issues of education using the methods and techniques of distance learning during the coronavirus pandemic. The research was conducted using the diagnostic survey method, survey technique, using a questionnaire. In the second part of the analysis the data found were used.
Few-shot Thangka image classification based on improved DenseNet

Abstract Thangka is an important part of Tibetan culture, and the classification of Thangka image is one of the basic works of Thangka research. DenseNet(Densely connected convolutional networks) has achieved a very good effect in the field of image classification. Considering that the DenseNet adopts ReLU function which loses the negative feature of the image in the feature propagation process, this paper proposed an improved DenseNet, called L-DenseNet that Leaky ReLU replaces ReLU function to increase the negative feature of propagation. In order to solve the problem of insufficient Thangka image sample, we adopted the method of based fine-tuned network. Experimental results show that L-DenseNet obtains an outstanding performance, which improves 1.1% performance compared with DenseNet. Compared with other CNNs, such as VGG16, ResNet50 and InceptionV3, L-DenseNet obtains state-of-the-art performance in the classification of Thangka image.
Analysis of Backpropagation Algorithm Using the Traingda Function for Export Prediction in East Java

Exports are significant for a country's economic development, especially in regions that carry out export activities because not all countries and regions have the same natural and human resources. Therefore this study aims to predict the level export of oil, gas, and others in the province of East Java and understand the forecast for the number of exports in the coming year. This is important to provide information to the East Java provincial government so that it can make policies so that the export value can be increased, at least so that the export value remains stable. The prediction algorithm used is the Backpropagation Neural Network algorithm using the Gradient Descent training function with Adaptive Learning rate. The research data is data on the Export of oil, gas, and others in East Java Province from 2008 to 2019. The prediction process analysis uses 3 network architecture models, namely: 5-10-1, 5-15-1, and 5-20-1. Based on the analysis results, the 5-10-1 model is the best compared to the other two models with an accuracy rate of more than 90% and MSE testing 0.0012454304, which means that this model is good for predicting the export of oil, gas, and others.
Chaos-Based Cryptography

Chaos-based cryptography is the applicability of the chaos theory and its mathematical background to create new and unique cryptography algorithms. In 1989, it was investigated for the first time by Robert Matthews in [1] and it attracted significant interest.
Systematic searching: Practical ideas for improving results

"Systematic searching: Practical ideas for improving results." Journal of Electronic Resources Librarianship, 32(4), pp. 341–342
Use of object shape priors for fractographic image segmentation

Approach to efficient level-set model with shape priors for images segmentation is considered. The use of edge based level-set model in combination with principal component analysis (PCA) based shape priors for image segmentation is investigated. Shape priors considered as a tool to cope with proper segmentation of overlapping or partially visible objects on input image. It is argued that in some cases consequent optimization of different groups of parameters can be advantageous in comparison to simultaneous optimization of all parameters. The approach was applied for segmentation of fractographic images obtained by scanning electron microscope (SEM). Experimental results for image segmentation using level-set model with shape priors are presented.
Spatial Privacy Pricing: The Interplay between Privacy, Utility and Price in Geo-Marketplaces

A geo-marketplace allows users to be paid for their location data. Users concerned about privacy may want to charge more for data that pinpoints their location accurately, but may charge less for data that is more vague. A buyer would prefer to minimize data costs, but may have to spend more to get the necessary level of accuracy. We call this interplay between privacy, utility, and price spatial privacy pricing. We formalize the issues mathematically with an example problem of a buyer deciding whether or not to open a restaurant by purchasing location data to determine if the potential number of customers is sufficient to open. The problem is expressed as a sequential decision making problem, where the buyer first makes a series of decisions about which data to buy and concludes with a decision about opening the restaurant or not. We present two algorithms to solve this problem, including experiments that show they perform better than baselines.
Using of Viola and Jones Method to Localize Objects in Multispectral Aerospace Images based on Multichannel Features

A new algorithm for localizing engineering objects on multispectral images based on the Viola and Jones method has been developed. The proposed algorithm uses multichannel features allowing to construct classifiers that are sensitive to features of joint brightness distribution and the brightness distribution in different channels. The algorithm described in the paper provides a precision value of 0.96 and a recall value of 0.99 in the problem of localizing oil storage tank images in a set of aerospace images. The proposed algorithm can be used for visual analytics and automatic detection of various critical objects in aerospace images.
Quantum State Estimation from Partial Tomography Data Using a Stack of Machine Learning Models and Imputation

Reconstruction of two-qubit systems typically performed using 36 coincidence measurements. We trained an ensemble of CNN &amp; XGBoost ML models, employed imputation to demonstrate high-fidelity state estimation when multiple measurements are missing.
Analisis Kontrol Optimal Pada Model Matematika Penyebaran Pengguna Narkoba Dengan Faktor Edukasi

ABSTRACT&#x0D; This paper discusses the mathematical model of drug users with education. Optimal control theory was used on this model with education as a control to achieve the goal of minimizing the number of drug users. The optimal control problem was analyzed using Pontryagin’s minimum principle and performed numerical simulation by using a 4th-order Runge-Kutta method. Based on the numerical simulation, there was a change in the number in each population which caused the population with education to increase, and control with education resulted in the reduced number of drug users.&#x0D; Keywords: Optimal control; mathematical model; drug users; education&#x0D; &#x0D; ABSTRAK&#x0D; Artikel ini membahas tentang model matematika penyebaran pengguna narkoba dengan faktor edukasi. Teori kontrol optimal diterapkan pada model ini dengan pemberian kontrol berupa edukasi dengan tujuan untuk meminimumkan jumlah pengguna narkoba. Kontrol optimal dianalisis menggunakan Prinsip Minimum Pontryagin dan dilakukan simulasi numerik dengan menggunakan metode Runge-Kutta orde 4. Berdasarkan simulasi diperoleh bahwa terjadi perubahan jumlah di tiap populasi dan mengakibatkan jumlah populasi dengan edukasi bertambah, serta pemberian kontrol dengan edukasi mengakibatkan jumlah pengguna narkoba berkurang.&#x0D; Kata kunci : Kontrol optimal; model matematika; pengguna narkoba; edukasi
Introducing DevOps Techniques in a Software Construction Class

As more companies adopt techniques related to DevOps and continuous deployment, it is critical for students in software engineering courses to gain hands-on experience with these techniques. In this paper, we describe a collection of assignments given in a graduate software construction class that guides students through the process of creating Docker containers, configuring continuous integration services, constructing a build pipeline, and automating deployment of new versions of a software system when changes are committed to the code repository. We also briefly analyze the performance of students on these hands-on exercises, identifying areas where additional support is needed to ensure student success.
El Proyecto UNA Educación de Calidad en el contexto de la COVID-19

This reflection presents the reorganization in the dynamics of the UNA Quality Education Project in the context of COVID-9, in order to provide support to students with disabilities in university training.
Maximum absolute determinant of the confusion matrix

Most accuracy measures for finding optimal thresholds on the ROC curve, surface and manifold make use of only misclassification rates or correct classification rates in the confusion matrix. The MADET (maximum absolute determinant) was proposed to use all elements of the confusion matrix. The power of MADET was compared with those of the generalized Youden index and the volume under the ROC surface. In this paper, two and three dimensional MADETs are implemented geometrically. And for the three dimensional confusion matrix, MADET is compared with some accuracy measures defined only as the correct classification rates or misclassification rates. When the standard deviation of one distribution is greater than other two, MADET might be conclude to be as good accurate measure as Youden index, and better than any other measures, based on the sum of correct classification rates which is the trace of the confusion matrix.
Sharing Secured Data on Peer-to-Peer Applications Using Attribute-Based Encryption

The strong growth of communication and storage gives rise to the significantly increasing demand for storing and sharing big data on networks. Research studies and industry applications can apply analytic techniques for exploiting data, or Internet users can exchange data on social networks or peer-to-peer networks. However, securing this shared data is a challenging problem that attracts much attention to researchers. Sharing data with a group of users on peer-to-peer faces the unavailability problem of peer-to-peer nodes, so that users cannot download the shared data. This affects an application class of sharing and storing online services. In this paper, we propose a solution for sharing secured data on peer-to-peer applications using blockchain and attribute-based encryption. The attribute-based encryption guarantees sharing keys among a group of users, while blockchain guarantees keys distribution. We implement the solution on the mobile peer-to-peer network that provides services for sharing and storing data securely.
Fusion of inertial and optical data for monitoring the geometry of the rail track

Abstract Methods and means of monitoring the state of the rail track by a number of key geometric parameters are analyzed. The concept of joint use of inertial and optical technologies as an accurate and cost-effective solution in this area is proposed. An assessment of the influence of errors of individual measuring modules of an optical-inertial diagnostic system on the accuracy of determining the geometric parameters of a rail track has been carried out. Questions related to the recognition of the rail image in the readings of optical sensors against the background of stray lighting and sun glares are touched upon. Attention is paid to the methods of obtaining a priori data on the position of the rail head profile on the matrix of the scanner camera. The results of experimental testing of the proposed solutions are presented. The current approach to the indirect assessment of the dynamical behavior of a railway mobile unit’s bogie in a track is analyzed. An approach is proposed for direct control of this dynamics without introducing an intermediate parameter of equivalent conicity.
Sentence Compression as Deletion with Contextual Embeddings

Sentence compression is the task of creating a shorter version of an input sentence while keeping important information. In this paper, we extend the task of compression by deletion with the use of contextual embeddings. Different from prior work usually using non-contextual embeddings (Glove or Word2Vec), we exploit contextual embeddings that enable our model capturing the context of inputs. More precisely, we utilize contextual embeddings stacked by bidirectional Long-short Term Memory and Conditional Random Fields for dealing with sequence labeling. Experimental results on a benchmark Google dataset show that by utilizing contextual embeddings, our model achieves a new state-of-the-art F-score compared to strong methods reported on the leader board.
Unsupervised Data Mining with K-Medoids Method in Mapping Areas of Student and Teacher Ratio in Indonesia

The purpose of this study was to analyze the k-medoids method in conducting cluster mapping in the ratio of the number of students and teachers in Indonesia by region, especially at the elementary school level. The data source is secondary obtained from the Ministry of Education and Culture which is processed by the Central Statistics Agency (abbreviated as BPS) in the BPS Catalog: 4301008 concerning the Portrait of Indonesian Education. The analysis process uses the help of Rapid Miner software by using parameters of the Davies Bouldin Index (DBI) and Performance (Classification). By using three cluster labels, namely the high cluster (K1), normal cluster (K2) and poor cluster (K3), it was found that 3 provinces were in the high cluster, 9 provinces were in the normal cluster and 22 provinces were in the fewer clusters. By testing the cluster results (k = 3) through the DBI parameter the value = 0.587 was obtained. This shows that the results of the cluster formed are optimal (the smaller the better). The test results with the parameter Performance (Classification) show the results of classification error = 2.50%. The results of the research can be used as information to determine the ratio of students and teachers because the higher the value of this ratio means that the level of teacher supervision and attention to students is reduced so that the quality of teaching tends to be lower.
A Reversible Data Hiding Method for AMBTC Compressed Image without Expansion inside Stego Format

This paper proposes a new framework of reversible data hiding scheme for absolute moment truncation coding (AMBTC) compressed images.AMBTC-based RDH can be applied to optical remote sensing (ORS) image transmission, which achieves target region preservation and image compression simultaneously.Existing methods can be concluded as two types.In type I schemes, stego codes mimic the original AMBTC format where no file bloat occurs, yet the carried secret data is limited.Type II schemes utilize predication errors to recode quantity levels of AMBTC codes which achieves significant increase in embedding capacity.However, such recoding causes bloat inside stego format, which is not appropriate in mentioned ORS transmission.The proposed method is a novel type I RDH method which prevents bloat inside AMBTC stego codes with significant improvement in embedding capacity.The AMBTC compressed trios are grouped into two categories according to a given threshold.In smooth trio, the modified low quantity level is constructed by concatenating Huffman codes and secret bits.The reversible contrast mapping (RCM) is performed to complex trios for data embedment.Experiments show that the proposed scheme provides highest payload compared with existing type I methods.Meanwhile, no expansion inside stego codes is caused.
Implementation of Combination Vigenere Cipher and RSA in Hybrid Cryptosystem for Text Security

According to the key used, cryptography can be divided into two, namely: symmetric cryptography and asymmetric cryptography, each of which has advantages and disadvantages. The selection of asymmetric cryptographic algorithm can perform the encryption process in a short time, but the key security is less secure, so it must be changed frequently. While asymmetric cryptography is the opposite, the security of key distribution can be overcome, but the data encryption process is slower. The coding process in this study uses two cryptographic algorithms, namely the Vigenere Cipher algorithm as an example of the symmetric algorithm and the RSA (Rivest Shamir Adleman) algorithm which is an example of an asymmetric algorithm. The purpose of this research is to calculate and implement so that it can be applied to overcome the weaknesses that occur from the two types of cryptography. The hybrid cryptosystem coding method is always used to overcome the weaknesses of the two cryptographs. The results show that there is an increase in security in encryption because there will be two encodings, namely message encoding with the Vigenere Cipher cryptographic algorithm and key coding with the RSA cryptographic algorithm. Besides, there is an increase in the time in the encryption and decryption process. From the results of the research, it takes 424 milliseconds in the encryption process and 335 milliseconds for the decryption process with 59,400 characters. A hybrid cryptosystem coding method using a combination of Vigenere Cipher and RSA can be implemented to increase text security and increase speed in the encryption process.
Evaluating the Seasonal Weather Influence on the Electrical Power Generation From Solar Cells

The renewable energy sources were considered as a potentially promising and far less harmful alternative to traditional methods of electrical production. The main aim of this paper is to evaluate the seasonal weather influence on the electrical power generation from solar cells. Experimental and quantitative methodologies were used to analysis the data were collected from two sources the primary data were collected from PhotoVoltaic (PV) system of capacity 1200W for one year. The second source of data were collected from the Kuwait Directorate General of Civil Aviation. The key findings of the results showed that the daily sunlight hours are considered an important factor for electrical power generation; the temperature had reverse impact when it raised to more than 30oC, and the relative humidity had reverse impact when it raised to more than 49%. The CO2 avoided by this system was 1.325tonnes per year. The recommendation of this study is to depend on PV cells to reduce dependence on fossil fuels.
SISTEM INFORMASI MANAJEMEN TAMAN KANAK-KANAK (STUDI KASUS : TAMAN KANAK-KANAK (TK) MEKAR SARI DESA AMBAWANG)

Current technological developments can be done to facilitate work. One of them can be applied to support management information system that focus on management TK Mekar Sari. The problems that exist in the process of acceptance of new students are still conventional (manual) and the class division process is still shared conventionally (manually) using Microsoft Excel. So it can take much time for class and student division in each semester. Based on the problem, the system is called "Kindergarten Management Information System (case study: Kindergarten (TK) Mekar Sari village Ambawang)". The system is built using the PHP programming language with a native framework. While the database development uses MySQL that works for the database server. Design of the display interface that author builds are created using Adobe XD CC 2019. As well as the draft database using Entity Relationship Diagram, Data Flow Diagram and Flowchart. This system can facilitate admins, principals and prospective registrants in the registration process, class division and Administration data collection to make it easier, faster and efficient both in terms of time, place, cost and energy at kindergarten (TK) Mekar Sari in Ambawang village.&#x0D;
Prototyping Sensors and Actuators for Robot Swarms in Mixed Reality

Swarm robotics is an approach to the coordination of large numbers of relatively simple robots with limited physical capabilities. Extending the capabilities of these robots usually requires either purchasing or prototyping new sensors or actuators (a costly and time-consuming process), often before even knowing whether these new sensors or actuators will be able to perform the necessary task effectively. This paper presents a software platform that enables researchers to prototype new sensors and actuators in the virtual world, eliminating the time and resources necessary to prototype physical hardware, and allows for experiments to be run in as many configurations as required in order to determine the efficacy of the proposed sensor/actuator.