Reviewerly/exHarmony huggingface dataset:
EANet: Depth Estimation Based on EPI of Light Field

The light field is an important way to record the spatial information of the target scene. The purpose of this paper is to obtain depth information through the processing of light field information and provide a basis for intelligent medical treatment. In this paper, we first design an attention module to extract the features of light field images and connect all the features as a feature map to generate an attention image. Then, the attention map is integrated with the convolution layer in the neural network in the form of weights to enhance the weight of the subaperture viewpoint, which is more meaningful for depth estimation. Finally, the obtained initial depth results were optimized. The experimental results show that the MSE, PSNR, and SSIM of the depth map obtained by this method are increased by about 13%, 10 dB, and 4%, respectively, in some scenarios with good performance.
Neuronal Homotopy Regressors

In this work, a neural model is proposed, which solves two limitations of artificial neural networks. The first refers to the ability to extrapolate outside the domain of the training data. The second arises when only a small sample is available for training. On the other hand, there is a need to characterize a complex system, and the dynamics of its components is partially known. The proposed model is based on the construction of a regressor from a feasible space, using Homotopy Analysis. In this way, a functional neural network is obtained.
A Dual-Mode 2-bit Uniform Scalar Quantizer for Data with Laplacian Distribution

In this paper, a novel dual-mode 2-bit scalar quantizer based on uniform quantization of data with Laplacian distribution is proposed. It is composed of two uniform quantizers with different step size, whereby the rule for quantizer selection is determined in order to provide the highest signal to quantization noise ratio in the given range of data variance. The proposed dual-mode scalar quantizer also performs frame-by-frame processing. It is shown that in terms of signal to quantization noise ratio our proposal is able to outperform single uniform quantizer in a wide dynamic range of input data variances. To verify benefits achieved with the proposed dual-mode quantizer the experiment is performed with the Multi-Layer Perceptron (MLP) weights.
Personally Oriented Model of the Educational Process: Subjectively Essense Focus

The article proves that globalization, informatization, openness and standardization of the education quality have radically changed not only the scheme of knowledge transfer, teaching methods, but also have actualized the problem of understanding the deep essence of knowledge itself, its levels. The emphasis is placed on the priorities of cultural and personal knowledge, which are an integral part of the personality and provide with the expansion of his/ her social experience. It is substantiated a significance of the educational knowledge formation as a synthesized set of philosophical principles, humanitarian knowledge, pedagogical experience, which are designed to overcome the inconsistency and diversity of two types of «products»: «production of a cultural person» in education and «production of knowledge» about the structure and basic processes of education. It is stated that the positions of a synergetic approach allow to analyze the development and functioning of the educational system both in the short and long perspective, to create favorable conditions in the educational environment for choosing and giving each subject a chance to move individually, to stimulate independence of choice and making a responsible decision, to provide personal development and educational knowledge, the formation of skills of knowledge self-management of as the basis of professional competence.
Performance Comparison with Hierarchical and Partitional Clustering Methods

In data mining, one of the commonly-used techniques is the clustering. Clustering can be done by the different algorithms such as hierarchical, partitioning, grid, density and graph based algorithms. In this study first of all the concept of data mining explained, then giving information the aims of using data mining and the areas of using and then clustering and clustering algorithms that used in data mining are explained theoretically. Ultimately within the scope of this study, "Mall Customers" data set that taken from Kaggle database, based partitioned clustering and hierarchical clustering algorithms aimed at the separation of clusters according to their costumers features. In the clusters obtained by the partitional clustering algorithms, the similarity within the cluster is maximum and the similarity between the clusters is minimum. The hierarchical clustering algorithms is based on the gathering of similar features or vice versa. The partitional clustering algorithms used; k-means and PAM, hierarchical clustering algorithms used; AGNES and DIANA are algorithms. In this study, R statistical programming language was used in the application of algorithms. At the end of the study, the data set was run with clustering algorithms and the obtained analysis results were interpreted.
Urge for Novel and Secure Software Framework for Extraction and Decoding of Mobile Artifacts

Mobile Forensics is now days, increasingly becoming more challenging as it is the field of science that is continuously evolving with respect to the rapidly developing technologies and techniques for the extraction of the mobile data and its decoding. Majority of the crimes are getting committed digitally and especially the criminals are preferring mobile handsets than a laptop or desktop machines, leaving the footprints behind which could be evidence against them. The mobile handsets along with their software applications are getting more advanced and sophisticated mainly due to advances in Cloud computing where clouds are used to store data, Anti-forensics where efforts are made to defeat forensic procedures and Encryption which is used to secure the data during transit. But when compared with the pace of development in mobile hardware and software, the forensic tools and techniques are growing very slowly. Hence the contemporary forensic tools and methodologies are becoming increasingly obsolete and hence urges for the advanced forensic tools, methods which could comply with the need of today’s mobile forensics. Hence, this work presents a detailed survey of the contemporary challenges faced by the forensic experts with the current forensic tools and its methodologies and also the need, scope and opportunities associated with the novel and secure software framework that can address the majority of issues occurring while extraction and decoding of mobile artifacts.
VIII-th International Young Scientists Conference on Information Technologies, Telecommunications and Control Systems

The VIII-th International Young Scientists Conference on Information Technologies, Telecommunications and Control Systems (ITTCS) will be held from 16th to 17th of December, 2021, at the Innopolis University. The Conference agenda will work as a competence platform, providing facilities for efficient communication to boost the IT science and engineering knowledge of young scientists and help them in their professional development. Young scientists will be given a unique chance not only to improve their presentation skills and public speaking abilities but to gain an experience of scientific publication. The importance of the project lies in the need to create conditions for the growth of recognition of a young scientist in world scientific circles and an increase in interest in his work, an increase in the level of scientific publications of students, postgraduate students and young scientists, and an increase in their quality. The exchange of experience in the field of professional interests with colleagues from foreign and Russian universities and scientific organizations will improve the qualifications of researchers and establish promising scientific contacts among young scientists. List of Programm Committee, General Chair are available in this pdf.
Research Progress of User Portrait Technology in Medical Field

In recent years, due to the rise of big data mining and intelligent recommendation, user portrait technology has gradually become a hot topic. As a new data analysis method, user portrait technology aims to mine user characteristics from a large number of user behavior data, and complete the user information panorama of the monomer or group through information mining, so as to prepare for the realization of precision service and personalized recommendation in various industries. It has been widely used in personalized recommendation and precision recommendation, personalized service and intelligent service, group characteristics analysis, prediction analysis and auxiliary decision-making. User portrait technology in the domestic research started late, currently in e-commerce, commercial precision marketing, book recommendation management, network personalized search, video entertainment and other fields of application is relatively mature. However, the application of user portrait technology in the field of medical and health is still in the preliminary exploration stage, and the combination of medical big data and user portrait technology can vividly depict the portraits of patients, doctors, residents and other different groups in promoting health and disease prevention. According to the different characteristics extracted, it can provide reference for meeting the needs of patients and achieving precision medicine. Therefore, this study reviews the concept, elements, implementation process and application of user portrait technology in the medical field, and provides reference for the subsequent application research of user portrait technology in the medical field
Historical aspects of monologue stage speech

The purpose of the article is to explore the historical aspects of monologue stage speech as the most difficult type of psychophysical action of the actor. The research methodology involves the use of an integrated approach with the use of analytical, systematic methods, comparative, which allows to distinguish the features of monologue stage speech in the work of the actor. The scientific novelty of the work is to deepen the study of individual acting in the context of the development of monologue speech and analysis of historical aspects of its formation and development in acting. Conclusions. It is emphasized that the masterful performance of monologues from a classical or modern play is a manifestation of the professional creative growth of the actor. Historical digression and research of methods of work on the monologue is an extremely important and useful source of obtaining the right techniques, principles, skills, a way to acquire professional knowledge of monologue stage speech. Text notes of extended monologue speech (if such are sometimes permissible) should be made carefully, carefully, together with the director-producer. It is noted that to master verbal action, its expressive possibilities is the main task, which is always faced by actors and directors of professional and amateur theaters.
A New IOT Image Encryption Algorithm based on Chaotic Map

IOT information is always subjected to attacks, because component of the IOT system always unsupervised for most of time, also due to simplicity of wireless communication media, so there is high chance for attack, lastly, IOT is constraint device in terms of energy and computation complexity. So, different research and study are proposed to provide cryptographic algorithm. In this paper, a new image encryption is proposed based on anew chaotic map used to generate the binary key. The proposed map is three dimensional map, which is more sensitive to initial condition, each dimension of the 3-D chaotic map is depended on the others dimension, which may increase the randomness of the behavior trajectory for the next values and this gives the algorithm the ability to resist any attacks. At first, 3-D chaotic map is proposed, which is very sensitive for initial condition, the three dimension is depended on each other, which make the system more randomness, then the produced sequences is converted on binary key by using mod operation. The original image is scrambled based on mod operation to exchange the row and interleaving them, the same operations are repeated for column of the image. Later, the image is divided into blocks of size (8*8) and scrambled by using negative diagonal scan, the final pixels are converted into binary sequences, which are XORed with the generated key to produce the encrypted image. The experiment is performed on different images with different properties and tested with different metrics such as entropy, correlation, key sensitivity, number of pixel change rate (NPCR) and histogram of the original and encrypted images. T results shows that the proposed encryption algorithm is more efficient and outperform other methods.
Informal Provability, First-Order BAT Logic and First Steps Towards a Formal Theory of Informal Provability

BAT is a logic built to capture the inferential behavior of informal provability. Ultimately, the logic is meant to be used in an arithmetical setting. To reach this stage it has to be extended to a first-order version. In this paper we provide such an extension. We do so by constructing non-deterministic three-valued models that interpret quantifiers as some sorts of infinite disjunctions and conjunctions. We also elaborate on the semantical properties of the first-order system and consider a couple of its strengthenings. It turns out that obtaining a sensible strengthening is not straightforward. We prove that most strategies commonly used for strengthening non-deterministic logics fail in our case. Nevertheless, we identify one method of extending the system which does not.
Automatic verification method of ATC command repetition based on Siamese network

In order to ensure the safety of ATC (Air Traffic Control), air traffic controllers need to artificially compare the ATC instructions between the original ones and repetitions from the pilot, which may bring errors and flight conflicts. Hence, an automatic verification method of ATC command repetition based on the Siamese network is proposed in this paper. Firstly, the instruction texts of the original ones and repetitions are converted into word vector sequences, respectively. The attention mechanism is introduced to generate word vectors containing interactive information. Secondly, the two generated word vectors are input into BiGRU for semantic extraction. Finally, the text similarity between the two generated word vectors is measured by Manhattan distance. The experiment results show that the method is effective in the automatic verification task of ATC instruction repetition, and its average test accuracy reaches 94.81%.
Robust Complaint Processing in Portuguese

The Natural Language Processing (NLP) community has witnessed huge improvements in the last years. However, most achievements are evaluated on benchmarked curated corpora, with little attention devoted to user-generated content and less-resourced languages. Despite the fact that recent approaches target the development of multi-lingual tools and models, they still underperform in languages such as Portuguese, for which linguistic resources do not abound. This paper exposes a set of challenges encountered when dealing with a real-world complex NLP problem, based on user-generated complaint data in Portuguese. This case study meets the needs of a country-wide governmental institution responsible for food safety and economic surveillance, and its responsibilities in handling a high number of citizen complaints. Beyond looking at the problem from an exclusively academic point of view, we adopt application-level concerns when analyzing the progress obtained through different techniques, including the need to obtain explainable decision support. We discuss modeling choices and provide useful insights for researchers working on similar problems or data.
EFEKTIFITAS PENGAJARAN DARING MENGGUNAKAN MEDIA DIGITAL TERHADAP KEMAMPUAN MEMBACA PERMULAAN SISWA KELAS I SEKOLAH DASAR

The impact of COVID19 has crippled not only the economic field but also the field of education. Indonesia is one of the countries affected by COVID19 since March 2020. The education process must continue as the government changes the learning activities conducted face-to-face now conducted online. Online learning makes education workers have to be creative and innovative in delivering lessons, especially in grade 1 students. Early reading skills in students are an important concern for teachers and parents who the author chooses to use digital media (YouTube) in the online learning process. The purpose of this research is to find out the influence of digital media (YouTube) on students' early reading ability; to find out the difference in students' initial reading ability using digital media (YouTube) with students without digital media (YouTube). This research uses quantitative methods with quasi-experimental approach. The results of this study showed that the normality test of Shapiro wilk value &gt; 0.05 which means normal distribution. Next Test Paired simple T test with pretest value and posttest experimental group obtained Sig score. (2-tailed) of 0.000 &lt; 0.05 and for control classes of 0.002 &lt; 0.05 in conclusion there is an average difference in students' initial reading ability; and independent sample T test results obtained by Sig (2-tailed) data of 0.045 &lt; 0.05 this score shows that there is a significant difference in students' initial reading ability by using digital media (YouTube) with students without using digital media (YouTube). Based on the results obtained online learning using digital media (YouTube) is very effective to improve the ability to read the beginnings of grade 1 elementary school students.
Digital Image Analysis Tools Developed by the Indiana O’Brien Center

The scale and complexity of images collected in biological microscopy have grown enormously over the past 30 years. The development and commercialization of multiphoton microscopy has promoted a renaissance of intravital microscopy, providing a window into cell biology in vivo. New methods of optical sectioning and tissue clearing now enable biologists to characterize entire organs at subcellular resolution. New methods of multiplexed imaging support simultaneous localization of forty or more probes at a time. Exploiting these exciting new techniques has increasingly required biomedical researchers to master procedures of image analysis that were once the specialized province of imaging experts. A primary goal of the Indiana O'Brien Center has been to develop robust and accessible image analysis tools for biomedical researchers. Here we describe biomedical image analysis software developed by the Indiana O'Brien Center over the past 25 years.
Geoelectric heterogeneities of the Kerch iron ore basin

The three-dimensional geoelectric model of the Earth’s crust and upper mantle of the Kerch Peninsula has been built for the first time based on the results of experimental observations of the Earth’s low-frequency electromagnetic field, carried out in 2007—2013 by the Institutes of the National Academy of Sciences of Ukraine. Its physical and geological interpretation and detailing of the near-surface part were carried out according to the data of the audiomagnetotelluric sounding method to study the deep structure of the Kerch iron ore basin. To the east of the Korsak-Feodosiya fault along the southern part of the Indolo-Kuban trough (in the north of the South Kerch and almost under the entire North Kerch zones), a low-resistance anomaly (ρ=1 Ohm∙m) was found at depths from 2.5 km to 12 km about 20 km wide. Its eastern part is located in the consolidated Earth’s crust and is galvanically connected with surface sedimentary strata, while the western part is completely in sedimentary deposits. The anomaly covers the territory of the Kerch iron ore basin and occurrences of mud volcanism. The characteristics of the upper part of the layered section of the Kerch Peninsula in the interval of the first hundreds of meters were obtained from the results of one-dimensional inversion of the audiomagnetotelluric sounding data (frequency range 8—4000 Hz). It is shown that the first 15 m of the section, corresponding to Quaternary deposits, have resistivity values up to 1 Ohm∙m. Below, in the Neogene sediments, the electrical resistance increases to values of 5 Ohm∙m and more. Both horizontally and vertically, the distribution of resistivity values has a variable character, manifesting as a thin-layered structure with low resistivity values. Possibly, such areas have a direct connection with the channel for transporting hummock material and gases. A connection is assumed between the low-resistivity thin-layered near-surface areas, a deep anomaly of electrical conductivity in the upper part of the Earth’s crust, and the likely high electrical conductivity of rocks at the depths of the upper mantle with iron ore deposits, as well as the manifestation of mud volcanism. The heterogeneity of the crustal and mantle highly conductive layers may indicate a high permeability of the contact zones for deep fluids.
“The Impact of Health Informatics on Public Health Emergency Response During the COVID-19 Pandemic in Developing Countries – Systematic Review”

<strong>Introduction: </strong>The world grapples with the unprecedented challenges of the Covid-19 pandemic with devastating economic and social impacts. The healthcare systems across developed and developing countries are laid a huge responsibility with immense pressure to combat this contemporary global crisis. With modern technological improvements health informatics (HI) plays a vital role in the public health emergency response (PHER). However, there is little empirical evidence to show the impact of HI in developing countries during this pandemic. <strong> </strong> <strong>Objective: </strong>To determine how HI impacted the PHER during Covid-19 pandemic in developing countries. <strong> </strong> <strong>Methodology: </strong>This study deployed a systemic review of published quality academic journals that emphasize and evaluate the HI role and impact during PHER in developing countries. <strong> </strong> <strong>Results: </strong>The synthesized evidence in developed countries found that the technological advances in telemedicine, e-health and mobile devices have proven to possess huge potentials in controlling the pandemic spread with enormous rapid transformations of service delivery patterns, with high patient satisfaction. HI impact on developing countries reported a high positivity towards PHER during Covid-19 pandemic. The adoption rates were low in developing countries with the key determinants; digital technology, efficient health governance, partnership, collaboration in national &amp; international, infrastructure, stakeholder skills and acceptance. The empirical research findings clearly showed the fundamental need to establish suitable HI initiative framework in developing countries in align with the countries national policies with medium to long-term plans and collaborative international partnerships. The level of maturity of HI needed to be deployed within health systems at pace and scale ready enough to save the world in most needed.