Reviewerly/exHarmony huggingface dataset:
Solving partial differential equations on near-term quantum computers

In this work, we obtain the numerical temperature field to a thermally developing fluid flow inside parallel plates problem with a quantum computing method. The physical problem deals with the heat transfer of a steady state, hydrodinamically developed and thermally developing fluid flow inside two parallel plates channel subjected to a prescribed constant heat flux. Its solution is formulated numerically with Finite Differences method, where a sequence of linear systems must be solved in order to determine the complete temperature field. Such linear systems are written as discrete unconstrained optimization problems with floating points being approximated using binary variables and solved using near-term quantum heuristics. Due to the exponential cost of simulating quantum algorithms, a reduced number of qubits had to be used in the simulations, causing a loss of precision in the results. However, this work advances the state of the art of solutions of differential equations with noisy quantum devices and could be used for useful applications when quantum computers with thousands of qubits become available.
Learning Based Joint Coding-Modulation for Digital Semantic Communication Systems

In learning-based semantic communications, neural networks have replaced different building blocks in traditional communication systems. However, the digital modulation still remains a challenge for neural networks. The intrinsic mechanism of neural network based digital modulation is mapping continuous output of the neural network encoder into discrete constellation symbols, which is a non-differentiable function that cannot be trained with existing gradient descend algorithms. To overcome this challenge, in this paper we develop a joint coding-modulation scheme for digital semantic communications with BPSK modulation. In our method, the neural network outputs the likelihood of each constellation point, instead of having a concrete mapping. A random code rather than a deterministic code is hence used, which preserves more information for the symbols with a close likelihood on each constellation point. The joint coding-modulation design can match the modulation process with channel states, and hence improve the performance of digital semantic communications. Experiment results show that our method outperforms existing digital modulation methods in semantic communications over a wide range of SNR, and outperforms neural network based analog modulation method in low SNR regime.
A unified interpretation of the Gaussian mechanism for differential privacy through the sensitivity index

The Gaussian mechanism (GM) represents a universally employed tool for achieving differential privacy (DP), and a large body of work has been devoted to its analysis. We argue that the three prevailing interpretations of the GM, namely $(\varepsilon, \delta)$-DP, f-DP and R\'enyi DP can be expressed by using a single parameter $\psi$, which we term the sensitivity index. $\psi$ uniquely characterises the GM and its properties by encapsulating its two fundamental quantities: the sensitivity of the query and the magnitude of the noise perturbation. With strong links to the ROC curve and the hypothesis-testing interpretation of DP, $\psi$ offers the practitioner a powerful method for interpreting, comparing and communicating the privacy guarantees of Gaussian mechanisms.
Improving Nevergrad’s Algorithm Selection Wizard NGOpt Through Automated Algorithm Configuration

Algorithm selection wizards are effective and versatile tools that automatically select an optimization algorithm given high-level information about the problem and available computational resources, such as number and type of decision variables, maximal number of evaluations, possibility to parallelize evaluations, etc. State-of-the-art algorithm selection wizards are complex and difficult to improve. We propose in this work the use of automated configuration methods for improving their performance by finding better configurations of the algorithms that compose them. In particular, we use elitist iterated racing (irace) to find CMA configurations for specific artificial benchmarks that replace the hand-crafted CMA configurations currently used in the NGOpt wizard provided by the Nevergrad platform. We discuss in detail the setup of irace for the purpose of generating configurations that work well over the diverse set of problem instances within each benchmark. Our approach improves the performance of the NGOpt wizard, even on benchmark suites that were not part of the tuning by irace.
In-Materio Extreme Learning Machines

Nanomaterial networks have been presented as a building block for unconventional in-Materio processors. Evolution in-Materio (EiM) has previously presented a way to configure and exploit physical materials for computation, but their ability to scale as datasets get larger and more complex remains unclear. Extreme Learning Machines (ELMs) seek to exploit a randomly initialised single layer feed forward neural network by training the output layer only. An analogy for a physical ELM is pro0duced by exploiting nanomaterial networks as material neurons within the hidden layer. Circuit simulations are used to efficiently investigate diode-resistor networks which act as our material neurons. These in-Materio ELMs (iM-ELMs) outperform common classification methods and traditional artificial ELMs of a similar hidden layer size. For iM-ELMs using the same number of hidden layer neurons, leveraging larger more complex material neuron topologies (with more nodes/electrodes) leads to better performance, showing that these larger materials have a better capability to process data. Finally, iM-ELMs using virtual material neurons, where a single material is re-used as several virtual neurons, were found to achieve comparable results to iM-ELMs which exploited several different materials. However, while these Virtual iM-ELMs provide significant flexibility, they sacrifice the highly parallelised nature of physically implemented iM-ELMs.
Study on Digital Painting Art Based on Computer Virtual Technology

To improve the comprehensive level of artificial intelligence robot painting art creation, the software and hardware of the robot are designed from the perspective of robot copying painting. In this study, a more refined 6-axis robot is used to cooperate with the 2-axis slider connecting rod platform for performing painting operation. Its hardware uses a 6-axis robot system grafted on the 2-axis screw slider platform, and its software uses machine learning artificial intelligence algorithms. These algorithms include multi-layer spatial convolution neural network and multi-column fuzzy neural network. It is found that the subjective evaluation results and market transaction value of the robot copying paintings completed by the system are equivalent to the creative level of senior undergraduate and graduate students majoring in fine arts. It is far higher than the high-precision inkjet system that has completed market transformation. Finally, it is considered that the robot copying painting system has basically met the requirements of the robot art creation system and is separated from the technical category of the picture printer.
Preface: Education and Society

Publishing articles in scholarly journals is an unavoidable activity for academics. Some courses require postgraduate students to publish in a journal in order to pass their classes. Some Indonesian institutions require students to publish articles in a journal before graduation and journal publication has become one of the requirements for lecturers to be promoted into a higher-ranked job. Out of these obligations, there are many benefits of publishing articles in a journal. One of these is that our thoughts and expertise will be conveyed to the public. This will attract further benefits such as being invited to be the speaker on the topic about which we have written or being invited to collaborate on further research and publications.
Homography Decomposition Networks for Planar Object Tracking

Planar object tracking plays an important role in AI applications, such as robotics, visual servoing, and visual SLAM. Although the previous planar trackers work well in most scenarios, it is still a challenging task due to the rapid motion and large transformation between two consecutive frames. The essential reason behind this problem is that the condition number of such a non-linear system changes unstably when the searching range of the homography parameter space becomes larger. To this end, we propose a novel Homography Decomposition Networks(HDN) approach that drastically reduces and stabilizes the condition number by decomposing the homography transformation into two groups. Specifically, a similarity transformation estimator is designed to predict the first group robustly by a deep convolution equivariant network. By taking advantage of the scale and rotation estimation with high confidence, a residual transformation is estimated by a simple regression model. Furthermore, the proposed end-to-end network is trained in a semi-supervised fashion. Extensive experiments show that our proposed approach outperforms the state-of-the-art planar tracking methods at a large margin on the challenging POT, UCSB and POIC datasets.
a Prototype Design of Smart Quranic Garden System using ATmega328 and ESP8266 Microcontrollers

Medicinal plants are one of the leading plants cultivated by farmers in Parongpong District, West Bandung Regency. There are so many benefits of medicinal plants, especially the bidara plant which is the main commodity of a farmer group called the Quran Garden Foundation. The vision of this bidara cultivation is in addition to a health function, as well as an effort to implement the sunnah in Islam. Therefore, the authors initiated the Smart Quranic Garden System prototype which is based on green house system automation technology and Internet of Things (IoT) based security using the ATmega328 and ESP8266 microcontrollers. This research was conducted using experimental methods, namely design and testing. The system built on this prototype includes watering, weather and security. Based on the test results, the pump on the watering system works when the soil moisture sensor detects soil moisture at an ADC value of more than or equal to 700. Whereas in the weather system, the heater will work when DHT11 detects a temperature below 25oC and the blower will work when a temperature is detected above 30oC. . The security system also responds according to the program that is set, namely the relay for the solenoid lock door will open only when the password is correct and the virtual button on Blynk is pressed. It is hoped that the system in this prototype can be implemented so that the growth height of the bidara plant in Parongpong district can be optimized.
Cryptocurrency and the Future of the World Currency

Cryptocurrencies and blockchain technology are increasingly loved, especially the COVID-19 pandemic sweeping the world. Some people choose to trade, invest, or mine using cryptocurrency because it is considered practical and able to generate fantastic profits. This article was written to analyze the prospects and implications of using cryptocurrency as a currency. To explore and describe the prospects and implications of cryptocurrency as a currency, a study was conducted with a literature review approach from secondary sources regarding the reasons for the prohibition of cryptocurrencies, the instability of crypto values, and without a clear underlaying of assets. Furthermore, the study in this article is expected to be able to explain the advantages and disadvantages of cryptocurrencies as well as alternative efforts in creating a stable and fair world currency
Effects of collaboration on students’ learning using Intelligent Tutoring System

Computer-based learning tools called Intelligent Tutoring Systems (ITS) assist students to become better learners by simulating human tutors using Artificial Intelligence (AI) approaches. Students can interact using collaborative ITSs from various locations to study, discuss, and articulate concepts relevant to a certain problem. This paper presents a collaborative ITS to teach UML that is built to enable students to effectively communicate and share each other's mistakes. The ITS is capable of detecting and identifying student errors and offers students suggestions during the problem-solving stage, giving them guidance on how to proceed. The ITS also determines a student's current level of thinking and intellect in order to assign them activities that need more attention. The evaluations conducted for this study revealed that the experimental group had considerably more learning gains (81% scores on the posttest) than the control group, where students only showed a very low significant change in their learning with posttest scores of 46%
Application of Basic Knowledge of Physical Chemistry in Chemical Engineering Thermodynamics Teaching

As one of the core courses for students majoring in chemical engineering and technology, chemical thermodynamics is closely related to physical chemistry, and the latter is the basis for learning the former.In teaching students new knowledge about chemical thermodynamics, the relevant knowledge from physical chemistry can be reviewed and explained, emphasizing the mutual penetration of physical chemistry and chemical thermodynamics.This can improve not only student understanding and mastery of chemical thermodynamics knowledge, but also the quality of teaching, thereby acquiring greater learning efficiency.In this paper, based on teaching practices in chemical thermodynamics and physical chemistry, some examples and opinions regarding the application of physical chemistry knowledge in the teaching of chemical thermodynamics are elucidated.
A Systematic Study for the Effects of PCA on Hyperspectral Imagery Denoising

In this paper, we conduct a study for the effects of principal component analysis (PCA) on hyperspectral imagery denoising. Our previous works combined PCA with wavelet shrinkage, block matching and 3D filtering (BM3D), and block matching and 4D filtering (BM4D), respectively, and very good denoising results have been obtained for hyperspectral imagery with very little noise. To demonstrate if these methods are the best for other noise scenarios, we combine PCA with video BM3D (VBM3D) and video BM4D (VBM4D), and non-local means (NL-Means) as well. Experimental results show that the PCA+VBM3D is the best denoising method for moderate and high noise levels, and PCA+BM4D is preferred for very low noise levels.
The Effect of Media Literacy on Social Health with the Mediating Role of Moral Literacy: A Case Study

The Effect of Media Literacy on Social Health with the Mediating Role of Moral Literacy: A Case Study
PENENTUAN JARAK OBJEK PENGHALANG MENGGUNAKAN METODE PERHITUNGAN JARAK PIKSEL DARI HISTOGRAM PROYEKSI BERPANDUAN LASER GARIS

The rapid advancement of digital image processing technology is expected to facilitate human life in various aspects of life. This study aims to detect and determine the distance of a barrier object based on the detection of lines emitted by a line laser light beam using the Matlab programming language with the pixel distance calculation method. The pixel distance calculation method is used to detect lines in an image that is processed by looking at the consistency of the laser lines. This study uses a box as an object to determine the presence of obstructions from an image captured by a camera. In this study, the parameters of distance, camera angle, and line laser angle are used. Research data collection was carried out in the afternoon in a closed room with a light intensity of 10 lux. An object can be said to be a barrier if in an image there is a laser line that is broken or not at the same pixel position. However, if in an image there are consistent lines or no line changes, then the image can be said to have no barriers. Based on the evaluation of the distance accuracy calculation with data collection, it can actually be concluded that the distance accuracy when taking data is above 85%.
Creating and Evolution Centralized Scientific Journals Remote Access System for Information Support of Russian Scientific Research

The article considers the system of information support of Russian scientific research in the field of natural sciences process. It’s gradual creating and development based on the creation of hybrid scientific library, using both the local (located directly in the library) traditional collection, and collections of electronic full-text media available remotely to the library patron and being a virtual part of the whole library collection. The article deals with the use of scientific journals (mainly foreign) as the most important part of the scientific resources required by Russian scientists’ access. The analysis is based on the Library for Natural Sciences of the Russian Academy of Sciences (one of the leading scientific libraries in Russia) example. The mentioned process started in the last centuries 1990s, and, as shown in the article, passes through several stages. From the very beginning, the process required for the libraries to unite into associations for the electronic resources joint use. These associations took, in accordance with international experience, the form of library consortia. At the first stage, consortia were created to bring together several libraries to access the electronic resources of a single foreign library. This system turned out to be viable, but rather cumbersome for a library (for effective work a library has to be a member of several consortia, which turned out to be non-technological). At the next stage, a single consortium was created with the support of the Russian Foundation for Basic Research — Scientific Electronic Library RFBR. Further development required the direct state on the one of the Ministry of Higher Education and Science projects basis support. This process went through several development stages (using as a project operator consortium NEICON, the RNPLS&amp;T and again RFBR — at another level of organization and funding). As a result, by 2020 the providing mainly information support for the work of the main mass of scientific and educational institutions in the specified field system was created and debugged on the practical level. By the early 2020s, the work had entered a more or less stable working mode. The issues requiring an urgent solution are the lack of an insurance copy of resources purchased abroad, which creates an uncertain situation in the event of the relationship with the resource owner termination, and the absence, in full, of a similar access to Russian scientific resources system, if their publication rights, in part, have been transferred to foreign publishers.
A Visual Analytics Approach for Hardware System Monitoring with Streaming Functional Data Analysis

Many real-world applications involve analyzing time-dependent phenomena, which are intrinsically functional, consisting of curves varying over a continuum (e.g., time). When analyzing continuous data, functional data analysis (FDA) provides substantial benefits, such as the ability to study the derivatives and to restrict the ordering of data. However, continuous data inherently has infinite dimensions, and for a long time series, FDA methods often suffer from high computational costs. The analysis problem becomes even more challenging when updating the FDA results for continuously arriving data. In this paper, we present a visual analytics approach for monitoring and reviewing time series data streamed from a hardware system with a focus on identifying outliers by using FDA. To perform FDA while addressing the computational problem, we introduce new incremental and progressive algorithms that promptly generate the magnitude-shape (MS) plot, which conveys both the functional magnitude and shape outlyingness of time series data. In addition, by using an MS plot in conjunction with an FDA version of principal component analysis, we enhance the analyst's ability to investigate the visually-identified outliers. We illustrate the effectiveness of our approach with two use scenarios using real-world datasets. The resulting tool is evaluated by industry experts using real-world streaming datasets.
SPECIFICS OF WASTEWATER PARAMETERS CALCULATION, WHICH SHOULD BE DETERMINED WHEN DRAWING UP RULES FOR RECEIVING WASTEWATER INTO THE CITY SEWERAGE SYSTEM

The article analyzed the problems of environmental monitoring and the level of automation for predicting the state of the environment and the level of use of computer information and analytical systems for environmental expertise. It is established that in order to improve the environmental safety management system and automate the processes of assessing the impact of economic activity on the environment, it is necessary to create software packages aimed at solving various environmental problems, namely receiving wastewater from enterprises to the urban sewerage systems. It is known that the relationship between consumers and water utilities is governed by the Rules of sewage. According to these Rules, the permissible concentrations of pollutants contained in the wastewater of enterprises are determined. But such calculations are characterized by a large number of parameters and a large amount of input data. The authors of the article developed a software package for calculations and rationing of wastewater quality indicators of enterprises that discharge their wastewater into the sewerage network of cities and may disrupt the operation of treatment facilities. In general, the developed software package will reduce the time and perform calculations to determine the permissible concentrations of pollutants in the wastewater of enterprises (consumers), and at the same time analyze large data sets. Automation of the main components of environmental procedures will increase the efficiency and reliability of urban sewerage systems and more effectively assess the impact on the environment. Also, the created software complex will determine the concentration of heavy metals in the sewage sludge and ensure its use as a fertilizer containing more phosphorus and calcium. It should be noted that the created software package allows you to perform such calculations that are difficult to perform in Excel. You can export data from any source - WEB, Excel, OpenOffice. Data and calculation algorithms are separated, which minimizes error. The software package was created using Node.js technology.