bluuebunny/crossref_metadata_2025 huggingface dataset:
Visualization of the Stress-Strain State of Shell Structures Using Virtual and Augmented Reality Technologies
Authors: Semenov Alexey , Zgoda Iurii
Published: December 2020

The paper describes a mathematical model of changes in the geometry of thin-shell structures for visualization of the analysis data on their stress-strain state (SSS). Based on this mathematical model, a visualization module for shell SSS visualization using VR and AR technologies was developed. The interactive visualization environment Unity 2019.3 and C# programming language were used. The interactive visualization module makes a 3D image of a shell structure and visualizes the SSS either through heat maps over the shell or through the changes in the shell geometry on the basis of the shell type, its geometric characteristics, and SSS analysis data (transferred to the visualization module by means of a JSON file). While working on the visualization module, the authors developed a system of components that makes it possible to visualize any 3D surface with coordinate axes (including numbers with a pitch determined automatically), visualize heat maps with a graduated scale, visualize a mesh over the graph to improve the perception of the surface deformations. The middle surface can also be deformed on the basis of SSS analysis data. This solution increases the efficiency of the work of specialists in civil engineering and architecture and can be used when training specialists in courses on thin-shell structures and procedural geometry.
Image-based System for 3D Visualization of Flow in Hydrodynamic Tunnel
Authors: Knyaz Vladimir , Novikov Michail , Kniaz Vladimir , Mizginov Vladimir , Ippolitov Eugeny
Published: December 2020

Aircraft safety depends on wing flow process, so the study of air flow in different flight conditions is one of the most important parts of aircraft design and exploiting. The effective method of aerodynamic processes modeling is experiment in wind (aerodynamic) tunnel or water (hydrodynamic) tunnel. They allow to perform experiments with a scaled model of an aircraft affected by icing and to visualize the wing flow process and changes caused by icing. A visualization and video registration of the wing flow yields useful qualitative information about flow, but it is more important to retrieve quantitative 3D data of flow for 3D visualization and analysis. The presented study addresses to creating an image-based system for accurate 3D flow acquisition for further diverse 3D visualization and quantitate evaluation of 3D flow parameters in a hydrodynamic tunnel for aircraft icing influence exploration. Being an initial part of a long- term research project, this study is aimed at developing stereolithography (SLA) modeling technique for flow visualization in hydrodynamic tunnel and a photogrammetric system for accurate flow 3D caption. The results of first experiments of the system calibration and application are given along with preliminary results of flow jets 3D reconstruction.
Edge Detection and Machine Learning Approach to Identify Flow Structures on Schlieren and Shadowgraph Images
Authors: Znamenskaya Irina , Doroshchenko Igor , Tatarenkova Daria
Published: December 2020

Schlieren, shadowgraph and other types of refraction-based techniques have been often used to study gas flow structures. They can capture strong density gradients, such as shock waves. Shock wave detection is a very important task in analyzing unsteady gas flows. High-speed imaging systems, including high-speed cameras, are widely used to record large arrays of shadowgraph images. To process large datasets of the high-speed shadowgraph images and automatically detect shock waves, convective plumes and other gas flow structures, two computer software systems based on the edge detection and machine learning with convolutional neural networks (CNN) were developed. The edge-detection software utilizes image filtering, noise removing, background image subtraction in the frequency domain and edge detection based on the Canny algorithm. The machine learning software is based on CNN. We developed two neural networks working together. The first one classifies the image dataset and finds images with shock waves. The other CNN solves the regression task and defines shock wave position (single number) based on image pixels tensor (3-D array of numbers) for each image. The supervised learning code based on example input-output pairs was developed to train models. It was shown, that the machine learning approach gives better results in shock wave detection accuracy, especially for low-quality images with a strong noise level. Software system for automated shadowgraph images processing and x-t curves of the shock wave and convective plume movement plotting was developed.
Evaluation of Vector Transformations for Russian Word2Vec and FastText Embeddings
Authors: Korogodina Olga , Karpik Olesya , Klyshinsky Eduard
Published: December 2020

Authors of Word2Vec claimed that their technology could solve the word analogy problem using the vector transformation in the introduced vector space. However, the practice demonstrates that it is not always true. In this paper, we investigate several Word2Vec and FastText model trained for the Russian language and find out reasons of such inconsistency. We found out that different types of words are demonstrating different behavior in the semantic space. FastText vectors are tending to find phonological analogies, while Word2Vec vectors are better in finding relations in geographical proper names. However, we found out that just four out of fifteen selected domains are demonstrating accuracy more that 0.8. We also draw a conclusion that in a common case, the task of word analogies could not be solved using a random word pair taken from two investigated categories. Our experiments have demonstrated that in some cases the length of the vectors could differ more than twice. Calculation of an average vector leads to a better solution here since it closer to more vectors.
On Applying of Generalized Computational Experiment to Numerical Methods Verification
Authors: Alekseev Aleksey , Bondarev Alexander , Galaktionov Vladimir , Kuvshinnikov Artem , Shapiro Lev
Published: December 2020

This work is devoted to the application of a generalized computational experiment for a comparative assessment of numerical methods accuracy. A generalized computational experiment allows one to obtain a numerical solution for a class of problems determined by the ranges of defining parameters variation. The approaches to the application of a generalized computational experiment in the presence of a reference solution and in its absence are dis-cussed. An example of constructing error surfaces is given when the solvers of the OpenFOAM software package are compared. The classic inviscid problem of oblique shock wave is used as a basic task. Variations of the key parameters of the problem — the Mach number and angle of attack — are considered. An example of the problem of flow around a cone at an angle of attack with varying Mach number, cone angle and angle of attack is also considered. The concept of an error index is introduced as an integral characteristic of deviations from the exact solution for each solver in the class of problems under consideration.
Visual Analysis of Textual Information on the Frequencies of Joint Use of Nouns and Adjectives
Authors: Bondarev Alexander , Bondarenko Alexander , Galaktionov Vladimir , Shapiro Lev
Published: December 2020

This paper presents the results of numerical experiments on the study of data volumes consisting of frequencies of joint use of adjectives and nouns. The volumes of data were obtained from samples from text collections in Rus-sian. The aim of the research is to analyze the cluster structure of the studied volume and semantic proximity of words in clusters and subclusters. The hypothesis was used that words with similar meaning should occur in approximately the same context. In this regard, in the space of features, they will be at a relatively close distance from each other, while differing words will be at a more distant distance from each other. Research is carried out using elastic maps, which are effective tools for visual analysis of multidimensional data. The construction of elastic maps and their extensions in the space of the first three principal components makes it possible to determine the cluster structure of the studied multidimensional data volumes. The analysis of the cluster structure for the considered volume of multidimensional data is carried out. The influence of transposition of the initial data array is considered.
Optical Diagnostics of Temperature and Structural Parameters of an Axisymmetric Flame
Authors: Arbuzov Vitaly , Arbuzov Edward , Dubnishchev Yuri , Zolotukhina Olga , Lukashov Vladimir
Published: December 2020

In this paper a method for restoring the parameters of multicomponent media for optical diagnostics of jet using the example of a hydrogen-air flame study is considered. Hilbert visualization and numerical modeling of phase perturbations induced by the studied medium in the probing light field are used. The study of the burning jet was carried out using the methods of Hilbert op-tics and Abel transformation in the model of axial symmetry of the torch. A software package has been developed that implements a direct solution to the problem: calculation of the spatial optical phase structure of the flame and its corresponding hilbertograms based on the temperature and molar concentrations of the combustion products of the mixture. The reliability of the obtained results is confirmed by comparing the Hilbert structures obtained in the experiment and the reconstructed optical density field of the phase using the Abel transform. The results of the comparison are used as a quality criterion for modeling the phase structure and temperature field in the study of the combustion process. The developed method can be used to solve the in-verse problem of restoring the temperature field from the Hilbert image of the phase structure of a hydrogen-air flame in the approximation of axial symmetry. The research is motivated by the scientific and practical significance of the problem, which consists in finding methods for controlling the structural and thermodynamic parameters of reacting jets and flames.
Non-Empirical Metrics for Ontology Visualizations Evaluation and Comparing
Authors: Baimuratov Ildar , Nguyen Than
Published: December 2020

There are numerous ontology visualization systems, however, the choice of a visualization system is non-trivial, as there is no method for evaluation and comparing them, except for empirical experiments, that are subjective and costly. In this research, we aim to develop non- empirical metrics for ontology visualizations evaluation and comparing. First, we propose several half-formal metrics that require expert evaluation. These metrics are completeness, semanticity, and conservativeness. We apply the proposed metrics to evaluate and compare VOWL and Logic Graphs visualization systems. And second, we develop a com- pletely computable measure for the complexity of ontology visualizations, based on graph theory and information theory. In particular, ontology visualizations are considered as hypergraphs and the information mea- sure is derived from the Hartley function. The usage of the proposed information measure is exemplified by the evaluation of visualizations of the sample of axioms from the DoCO ontology in Logic Graphs and Graphol. These results can be practically applied for choosing ontology visualization systems in general and regarding a particular ontology.
A Distributed Tracking Algorithm for Counting People in Video by Head Detection
Authors: Kuplyakov Denis , Geraskin Yaroslav , Mamedov Timur , Konushin Anton
Published: December 2020

We consider the problem of people counting in video surveillance. This is one of the most popular tasks in video analysis because this data can be used for predictive analytics and improvement of customer services, traffic control, etc. Our method is based on the object tracking in video with low framerate. We use the algorithm from [1] as a baseline and propose several modifications that improve the quality of people counting. One of the main modifications is to use a head detector instead of a body detector in the tracking pipeline. Head tracking is proved to be more robust and accurate as the heads are less susceptible to occlusions. To find the intersection of a person with a signal line, we either raise the signal lines to the level of the heads or perform a regression of bodies based on the available head detections. Our experimental evaluation has demonstrated that the modified algorithm surpasses the original in both ac- curacy and computational efficiency, showing a lower counting error on a lower detection frequency.
Pen Trace Reconstruction with Skeleton Representation of a Handwritten Text Image
Authors: Kryzhanovskaya Svetlana , Arseev Sergey , Mestetskiy Leonid
Published: December 2020

This paper presents a new approach for the pen trace reconstruction task in handwritten text images. The proposed approach is based on the skeleton representation of a binary image which provides sufficient information about the pen movement trajectory during the writing. As such, the initial problem can be viewed as a problem of constructing a specific walk in the skeleton graph covering all its edges. The proposed approach consists of splitting the graph into structural elements and estimating the pen movement direction in each of them with the resulting trace being composed of the traces of these elements.
Improving the Neural Network Algorithm for Assessing the Quality of Facial Images
Authors: Lisin Nikita , Gromov Alexander , Konushin Vadim , Konushin Anton
Published: December 2020

The paper considers the task of obtaining a quality assessment of facial images for usage in various video surveillance systems, video analytics, and biometric identification. The accuracy of person recognition and classification depends on the quality of the input images. We consider an approach to obtaining single face image quality assessment using a neural network model, which is trained on pairs of images that are split into two possible classes: the quality of the first image is better or worse than the quality of the second one. Two modifications of the selected baseline algorithm are proposed. A face recognition system is applied to change the loss function and image and face quality attributes are used when training the model. Experimental studies of the proposed modifications show their effectiveness. The accuracy of selecting the best and worst frame is increased by 1.3% and 1.9%, respectively.
Dataset Expansion by Generative Adversarial Networks for Detectors Quality Improvement
Authors: Kostin Alexander , Gorbachev Vadim
Published: December 2020

Modern neural network algorithms for object detection tasks require a large la-belled dataset for training. In a number of practical applications creation and an-notation of large data, collections requires considerable resources which are not always available. One of the solutions to this problem is creation of artificial images containing the object of interest. In this work the use of generative adversarial networks (GAN) for generation of images of target objects is proposed. It is demonstrated experimentally that GAN’s allows to create new images on the basis of the initial collection of real images on background images (not containing objects), which simulate real images accurately enough. Due to this, it is possible to create a new training collection containing a greater variety of training examples, which allows to achieve higher precision for detection algorithm. In our setting, GAN training does not require more data than is required for direct detector training. The proposed method has been tested to teach a network for detecting unmanned aerial vehicles (UAVs).
Pairwise Ranking Distillation for Deep Face Recognition
Authors: Nikitin Mikhail , Konushin Vadim , Konushin Anton
Published: December 2020

This work addresses the problem of knowledge distillation for deep face recognition task. Knowledge distillation technique is known to be an effective way of model compression, which implies transferring of the knowledge from high-capacity teacher to a lightweight student. The knowledge and the way how it is distilled can be defined in different ways depending on the problem where the technique is applied. Considering the fact that face recognition is a typical metric learning task, we propose to perform knowledge distillation on a score-level. Specifically, for any pair of matching scores computed by teacher, our method forces student to have the same order for the corresponding matching scores. We evaluate proposed pairwise ranking distillation (PWR) approach using several face recognition benchmarks for both face verification and face identification scenarios. Experimental results show that PWR not only can improve over the baseline method by a large margin, but also outperforms other score-level distillation approaches.
Facial Expression Recognition using Distance Importance Scores Between Facial Landmarks
Authors: Ryumina Elena , Karpov Alexey
Published: December 2020

In this paper, we present a feature extraction approach for facial expressions recognition based on distance importance scores between the coordinates of facial landmarks. Two audio-visual speech databases (CREMA-D and RAVDESS) were used in the research. We conducted experiments using the Long Short-Term Memory Recurrent Neural Network model in a single corpus and cross-corpus setup with different length sequences. Experiments were carried out using different sets and types of visual features. An accuracy of facial expression recognition was 79.1% and 98.9% for the CREMA-D and RAVDESS databases, respectively. The extracted features provide a better recognition result compared to other methods based on the analysis of facial graphical regions.
Data Distillation for Traffic Sign Detection
Authors: Popov Alexey , Shakhuro Vlad , Konushin Anton
Published: December 2020

This work is devoted to the traffic sign detection on images using deep learning methods. We focus on the problem of detector transfer to new datasets with different road signs. We present an algorithm for distilling a set of unlabelled data to select the most informative images to be labeled. This method allows to significantly reduce the amount of data labeling with a small decline of detector performance.
Graph-Based Visual Analytics Tools for Digital Humanities Research
Authors: Ryabinin Konstantin , Belousov Konstantin , Chuprina Svetlana
Published: December 2020

This paper is devoted to the development of the Web application for the visual analytics of the interconnected data within digital humanities research highly adaptable to the specifics of application domain and personal analytics preferences. The circular graph is proposed as a visual model to depict the interconnected data in a comprehensive way. The graph rendering software is organized according to the model-driven architecture utilizing ontology engineering methods and means, which ensure configuration flexibility and modification ease. The functioning scenarios of the application’s visualization component can be changed without its source code modifications, just by editing the under- lying ontology that describes data processing and rendering mechanisms. Extraction, transformation, loading and rendering of the data are con- figured in the intuitive way by data flow diagrams with the help of a high-level graphical editor. The described features are demonstrated on the real-world examples from the digital humanities application domain.
Visualization of the Process of Static Buckling of a Micropolar Meshed Cylindrical Panel
Authors: Krylova Ekaterina , Papkova Irina , Krysko Vadim
Published: December 2020

Process visualization of static stability loss in mechanics is shown by the micropolar meshed cylindrical panel example with two families of mutually perpendicular ribs. The mathematical model of the panel's behavior is based on the Kirchhoff-Love hypotheses. The micropolar theory is applied to ac-count for scale effects. Geometric nonlinearity is taken into account according to the theory of Theodor von Karman. The mesh structure is taken into account based on the Pshenichnov I. G. continuum model. Visualization of numerical results using Autodesk 3ds Max software made it possible to more clearly assess the phenomenon of static buckling of the shell in question. Visualization of the results using 3D made it possible to establish that an in-crease in the distance between the edges of the mesh panel and an increase in the parameter depending on the size does not change the bending shape of the panel, as well as the diagrams of moments and forces at subcritical and supercritical loads.
Chaotic Oscillations Type of Flexible Closed Cylindrical Nanoshells Under the Strip Loads Action
Authors: Yakovleva Tatiana , Stasuk Michael , Krysko Anton
Published: December 2020

The theory and data visualization of flexible closed cylindrical nanoshells nonlinear dynamics under the strip loads action are constructed. The theory is based on hypotheses: Kirchhoff-Love, modified couple stress theory, geometric non-linearity adopted in the T. von Karman form. To obtain the de-sired differential equations, the Hamilton-Ostrogradsky principle was used, which makes it possible to obtain the desired differential equations in mixed form describing nano effects. For reduction to the Cauchy problem in spatial coordinates, the Bubnov-Galerkin method in higher approximations is ap-plied. Further, the Cauchy problem is solved by methods such as Runge-Kutta and Newmark. The convergence of the Bubnov-Galerkin method is studied depending on the number of terms in the original functions expansion in spatial coordinates. The oscillations transition scenario from harmonic to chaotic depending on the number of series members in the Bubnov-Garekin method, as well as depending on the type of load, geometric and size-dependent parameters, is investigated. The numerical experiment results were visualized by nonlinear dynamics methods and using wavelet analysis. It was revealed that the oscillations type substantially depends on these parameters; two types of chaos are observed: chaos and hyperchaos. This was revealed according to the chaos criterion given by Gulik, and the Lyapunov exponents study by the methods of Rosenstein, Kantz, and Wolf. A chaos type analysis was carried out based on the signs of Lyapunov exponents spectrum calculated by the Sano-Sawada method.
Synthesis and Visualization of Photorealistic Textures for 3D Face Reconstruction of Prehistoric Human
Authors: Kniaz Vladimir , Knyaz Vladimir , Mizginov Vladimir
Published: December 2020

Reconstruction of face 3D shape and its texture is a challenging task in the modern anthropology. While a skilled anthropologist could reconstruct an appearance of a prehistoric human from its skull, there are no automated methods to date for automatic anthropological face 3D reconstruction and texturing. We propose a deep learning framework for synthesis and visualization of photorealistic textures for 3D face reconstruction of prehistoric human. Our framework leverages a joint face-skull model based on generative adversarial networks. Specifically, we train two image-to-image translation models to separate 3D face reconstruction and texturing. The first model translates an input depth map of a human skull to a possible depth map of its face and its semantic parts labeling. The second model, performs a multimodal translation of the generated semantic labeling to multiple photorealistic textures. We generate a dataset consisting of 3D models of human faces and skulls to train our 3D reconstruction model. The dataset includes paired samples obtained from computed tomography and unpaired samples representing 3D models of skulls of prehistoric human. We train our texture synthesis model on the CelebAMask-HQ dataset. We evaluate our model qualitatively and quantitatively to demonstrate that it provides robust 3D face reconstruction of prehistoric human with multimodal photorealistic texturing.
Adversarial Learning for Effective Detector Training via Synthetic Data
Authors: Gorbachev Vadim , Nikitin Andrey , Basharov Ilya
Published: December 2020

Current neural network-based algorithms for object detection require a huge amount of training data. Creation and annotation of specific datasets for real-life applications require significant human and time resources that are not always available. This issue substantially prevents the successful deployment of AI algorithms in industrial tasks. One possible solutions is a synthesis of train images by rendering 3D models of target objects, which allows effortless automatic annotation. However, direct use of synthetic training datasets does not usually result in an increase of the algorithms’ quality on test data due to differences in data domains. In this paper, we propose the adversarial architecture and training method for a CNN-based detector, which allows the effective use of synthesized images in case of a lack of labeled real-world data. The method was successfully tested on real data and applied for the development of unmanned aerial vehicle (UAV) detection and localization system.
Neural Network Model for Face Recognition from Dynamic Vision Sensor
Authors: Shvetsov Fedor , Konushin Anton , Sokolova Anna
Published: December 2020

In this work, we consider the applicability of the face recognition algorithms to the data obtained from a dynamic vision sensor. A basic method using a neural network model comprised of reconstruction, detection, and recognition is proposed that solves this problem. Various modifications of this algorithm and their influence on the quality of the model are considered. A small test dataset recorded on a DVS sensor is collected. The relevance of using simulated data and different approaches for its creation for training a model was investigated. The portability of the algorithm trained on synthetic data to the data obtained from the sensor with the help of fine-tuning was considered. All mentioned variations are compared to one another and also compared with conventional face recognition from RGB images on different datasets. The results showed that it is possible to use DVS data to perform face recognition with quality similar to that of RGB data.
Deep Two-Stage High-Resolution Image Inpainting
Authors: Moskalenko Andrey , Erofeev Mikhail , Vatolin Dmitriy
Published: December 2020

In recent years, the field of image inpainting has developed rapidly, learning-based approaches show impressive results in the task of filling missing parts in an image. But most deep methods are strongly tied to the resolution of the images on which they were trained. A slight resolution increase leads to serious artifacts and unsatisfactory filling quality. These methods are therefore unsuitable for interactive image processing. In this article, we propose a method that solves the problem of inpainting arbitrary-size images. We also describe a way to better restore texture fragments in the filled area. For this, we propose to use information from neighboring pixels by shifting the original image in four directions. Moreover, this approach can work with existing inpainting models, making them almost resolution-independent without the need for retraining. We also created a GIMP plugin that implements our technique. The plugin, code, and model weights are available at https://github.com/a-mos/High Resolution Image Inpainting.
Research Methods in the Field of Computer Visualization Based on Virtual Reality
Authors: Averbukh Natalya , Averbukh Vladimir
Published: December 2020

The paper examines research methods in the field of computer visualization based on virtual reality. Virtual reality environments were initially used for training simulation, but as far back as in the late 1980s scientific visualization systems based on virtual reality occurred. Those were the pilot versions of virtual test stands that were used in developing reusable space shuttles. Currently, virtual reality environments have been actively used in scientific visualization and software visualization systems. Developing such systems involves not only the issues of software implementation, modelling or adequate equipment choice, but also the tasks connected with cognitive processes occurring in both users and developers of visualization systems. Featured is a brief review of papers dealing with research in human interaction with virtual reality. The scope of tasks in developing visualization systems based on virtual reality is determined. The conclusion discusses several research issues, the solutions to which will increase the efficiency of interaction of users with virtual environments.
Scientific Visualization of the Results of a Numerical Experiment of the Nonlinear Dynamics of a Nanoscale Beam Structure
Authors: Saltykova Olga
Published: December 2020

The paper presents the results of scientific visualization of the nonlinear dynamics of contact interaction of a nanoscale beam structure under the action of an external harmonic load. The beam structure consists of two beams obeying the kinematic hypotheses of Euler-Bernoulli and S.P. Timoshenko. The constructed mathematical model takes into account geometric and constructive nonlinearities. The size-dependent behavior of the structure is implemented on the basis of the modified moment theory of elasticity. The resulting system of partial differential equations is reduced to a system of ordinary differential equations by the second order finite difference method. The Cauchy problem is solved by the fourth order Runge-Kutta method. In this work, using the methods of scientific visualization of the results of applying the methods of nonlinear dynamics, the influence of the size-dependent parameter and external load on the vibrations of the beam structure is investigated. As methods for studying nonlinear dynamics, the work uses wavelet spectra based on the mother Morlet, Fourier power spectra, signals. The use of scientific visualization methods makes it possible to develop specific recommendations for the operating conditions of the beam structure. This, in turn, makes it possible to avoid unwanted vibration modes of beam nanostructures, which are widely used as sensitive elements of sensors of micro and nano electromechanical systems.
Graph Visualization of the Characteristics of Complex Objects on the Example of the Analysis of Politicians
Authors: Ulizko Mikhail , Antonov Evgeniy , Artamonov Alexey , Tukumbetova Rufina
Published: December 2020

The paper considers the task of analyzing complex interconnected objects using graph construction. There is no unified tool for constructing graphs. Some solutions can build graphs limited by the number of nodes, while others do not visually display data. The Gephi application was used to construct graphs for the research. Gephi has great functionality for building and analyzing graphs. The subject of research is a politician with a certain set of characteristics. In the paper an algorithm that enables to automate data collection on politicians was developed. One of the main methods of data collecting on the Internet is web scraping. Web scraping software may access the World Wide Web directly using the HTTP, or through a web browser. While web scraping can be done manually by a software user, the term typically refers to automated processes implemented using a software agent. The data was necessary for constructing graphs and their analysis. The use of graphs enables to see various types of relationships, including mediate. This methodology enables to change the attitude towards the analysis of multidi-mensional objects.
The Variational Iterations Method for the Three-dimensional Equations Analysis of Mathematical Physics and the Solution Visualization with its Help
Authors: Tebyakin Aleksey , Papkova Irina , Krysko Vadim
Published: December 2020

The aim of the work is to use the variational iterations method to study the three-dimensional equations of mathematical physics and visualize the solutions obtained on its basis and the 3DsMAX software package. An analytical solution of the three-dimensional Poisson equations is obtained for the first time. The method is based on the Fourier idea of variables separation with the subsequent application of the Bubnov-Galerkin method for reducing partial differential equations to ordinary differential equations, which in the Western scientific literature has become known as the generalized Kantorovich method, and in the Eastern European literature has known as the variational iterations method. This solution is compared with the numerical solution of the three-dimensional Poisson equation by the finite differences method of the second accuracy order and the finite element method for two finite element types: tetrahedra and cubic elements, which is a generalized Kantorovich method, based on the solution of the three-dimensional stationary differential heat equation. As the method study, a set of numerical methods was used. For the results reliability, the convergence of the solutions by the partition step is checked. The results comparison with a change in the geometric parameters of the heat equation is made and a conclusion is drawn on the solutions reliability obtained. Solutions visualization using the 3Ds max program is also implemented.
Pemberdayaan Usaha Mikro Hasil Olahan Laut
Authors: Santoso Djoko , Indarto Indarto , Saddewisasi Wyati , Santoso Aprih
Published: December 2020

Kampung Tambak Lorok dan Tambak Rejo adalah kampung nelayan terbesar dan menjadi Kawasan Minapolitan Wisata Bahari di kota Semarang, Jawa Tengah. Masyarakatnya bergantung pada laut tempat mencari ikan.Hal ini telah menyatu dengan kondisi sosial ekonomi dan kehidupan kebudayaan masyarakat serta telah berlangsung secara turun menurun sehingga pemukiman ini lebih dikenal sebagai Pemukiman Nelayan. Penggerak utama ekonomi  kampung Tambak Lorok dan kampung Tambak Rejo berupa perdagangan sentra produksi serta pengolahan ikan, perikanan tangkap, perikanan budidaya, pengolahan ikan, atau kombinasi disamping usaha lain seperti produksi kue kering, produksi kerajinan kain perca dan kerajinan dari sampah organik. Untuk itu perlu diberdayakan usaha mikro olahan hasil laut dan potensi yang lain untuk mendukung kemajuan wisata Bahari. Namun usaha mikro masih banyak memiliki kelemahan dari aspek strategi pengembangan usaha, aspek permodalan dan pembiayaan, aspek pemasaran kususnya kemasan produk. Diharapkan dengan pemberdayaan yang dilakukan Tim pengabdian masyarakat dapat menstimulasi kapabilitas usaha pelaku usaha mikro di Kampung Tambak Lorok dan Tambak Rejo mampu mendukung pengembangan wisata Bahari kota Semarang. Kata kunci: Pemberdayaan, Usaha, Olahan,
HAMBATAN BELAJAR SISWA PADA MASA PANDEMI COVID-19 DI MA MA’ARIF 06 PASIR SAKTI LAMPUNG TIMUR
Authors: Janah Siti Roikatul
Published: December 2020

This article aims to describe the barriers to student learning during the Covid-19 pandemic at MA Maarif 06 Pasir Sakti, East Lampung. The research used a qualitative descriptive method with data sources of teachers, homeroom teachers, students and parents. The result of this determination is that there are several obstacles faced by students, teachers and parents in teaching and learning activities in the Covid-19 Pandemic Era, namely the addition of internet quota costs, communication and socialization between students, teachers and parents is reduced and working hours which becomes unlimited for teachers because they have to communicate and coordinate with parents, other teachers, and principals. The positive contribution of the results of this study is the spread of information regarding the urgency of mastery of technology to support every activity carried out by humans, one of which is in the realm of education to be able to compete globally.
Polyethylene microplastics are ingested and induce biochemical changes in Culex quinquefasciatus (Diptera: Culicidae) freshwater insect larvae
Authors: Malafaia Guilherme , Da Luz Thiarlen Marinho , Guimarães Abraão Tiago Batista , Araújo Amanda Pereira da Costa
Published: December 2020

Although microplastics’ (MPs) toxicity has been reported in several aquatic and terrestrial organisms, the knowledge about how these pollutants can affect insects at the early developmental stage remains incipient. Thus, the aim of this study was to use Culex quinquefasciatus larvae as a model system to test the hypothesis that, besides accumulating in animals, polyethylene microplastics (PE MPs) lead to biochemical changes predictive of nutritional impacts, as well as induce oxidative stress, redox state imbalance, and neurotoxicity in them. Our results have indicated that short exposure to PE MPs (5 days) at the environmental concentration of 4.24 x 106 particles m-3 induced changes suggesting damage to energy metabolism such as reduced total proteins, total soluble carbohydrates, and triglycerides levels. In addition, increased thiobarbituric acid reactive species, in association with reduced total glutathione and DPPH radical scavenging activity (%) have suggested an imbalance between oxide-reducing agents and antioxidant defense system, induced by pollutant. On the other hand, increased acetylcholinesterase activity has suggested the neurotoxic effect of PE MPs. Finally, PE MPs have accumulated in the larvae, and it may have been a triggering factor for the observed changes. Thus, our study has confirmed the potential of C. quinquefasciatus larvae to act as vector of MPs in different ecosystems and helped improving the knowledge about how PE MPs can affect their development and lead to losses in different ecological functions of this species.
Determinants of Inflation in Palestine
Authors: Alareeni Bahaaeddin , Qdeh Nariman , Lulu Mohammed
Published: December 2020

This study aimed at identifing the most important determinants and economic factors affecting inflation rates in the Palestine during the period (2000-2014), in order to help in reducing its effects on the Palestinian economy. The descriptive and analytical approach was used, by selecting a set of variables that were expected to have an impact on the inflation rates in the Palestinian economy, as these factors were such as economic growth rate, interest rate, exchange rate, unemployment rate, money supply, wages, inflation rate in Israel, and the global inflation rate. Two statistical models were developed for West Bank and Gaza Strip separately, based on quarter time series data for determinants of inflation in the Palestinian economy for the period from 2000-2014. The results showed the significatnt impact of: (the exchange rate, the Israeli inflation rate, the economic growth rate) on the inflation rate in the West Bank. In addition, it showed the significant effect of: (global inflation rate, unemployment rate, the economic growth rate) on the inflation rate in Gaza Strip. The other variables: credit facility, wage rate and interest rate were statistically insignificant. In light of this, the study recommended the necessity of issuing a national currency to reduce the losses of the Palestinian economy due to the absence of the national currency, as well as the pressure of imports and trying to find local alternatives by supporting the national product, as well as the need to review trade and economic policies between the Palestinian Authority and Israel to serve the development of the Palestinian economy.
The Role of Management Information Systems in Strengthening the Adminstrative Governance in Minstry of Education and Higher Education in Gaza
Authors: Alzaneen Ramiz , Mahmoud Ahmed
Published: December 2020

The study aims at identifying the role of management information systems in sustaining the administrative governance of the Ministry of Education and Higher Education in Gaza. To achieve this purpose, the researcher used the "descriptive analytical approach", and adopted the questionnaire as a tool for the study, using a "stratified random sample" to poll the sample opinions, which amounted to (289) male and female employees of the staff of the Ministry of Education and Higher Education in Gaza, and the number of questionnaires recovered was (254) recovery rate (87.9%). The study finds that the targeted individuals of the study sample showed a high degree of the availability of management information systems infrastructure in the Ministry of Education and Higher Education, reached to a relative weight of (73.2%). In addition, the results showed a rise in the application of management information systems at the Ministry of Education and Higher ?Education resulted in a relative weight of (70.5%). The high quality of the ?information resulting from management information systems at the Ministry of Education and Higher Education in a relative weight of (68.6%). The application of administrative governance in the Ministry of Education and Higher Education Standards reached a relative weight of (64.82%), and received the standard response at the highest relative weight of (67.64%).
Belleğin Ontolojik Statüsü Nedir: Bergson’da Zihnin Metafiziği
Authors: DURAK Burak K.
Published: December 2020

Günümüzden yaklaşık bir asır önce, henüz zihin felsefesi farklı bir disiplin olarak ayrışmış olmaktan çok uzaktayken, kendi felsefesini “zihin felsefesi” olarak tanımlayan ve gelecekte kaçınılmaz olarak bu disiplinin kurulacağını öngören Bergson, Kartezyen düalizmin ruh ve madde yaklaşımının yarattığı sorunlar üzerinden felsefesini şekillendirerek bu iki etkenin bir sentezini oluşturmaya çalışır. Zihinsel süreçler yorumlanırken algı şu anki gerçeklikte ve maddi karşılığı olan bir fenomen olarak karşımıza çıkar. Eski deneyimlerimize dayanan anı ise geçmiş zamanlıdır ve maddi karşılığı yoktur. Diğer yandan, zihinsel süreçler içinde aktif bir role sahip geçmiş zamanlı anının birikimli olarak bellekte yer aldığı düşünülür. Bu noktada Bergson şu sıra dışı soruyu problem olarak ortaya koyar: Maddi karşılığı olmayan anıların birikimiyle oluştuğu düşünülen belleğin maddi bir karşılığı var mıdır? Ya da daha açık bir ifade ile: Belleğin ontolojik statüsü nedir? Bu makale Bergson metafiziğini, güncel zihin felsefesi problemleri perspektifinden yorumlayarak bu problemlerin metafiziksel altyapısını analiz etmeyi amaçlamaktadır.
Correlation Between Tolerance for Disagreement and Postsecondary Enrollment Among African American Men
Authors: Miller Michael T. , Tolliver, III David V. , Gearhart G. David
Published: December 2020

The study explored the concept of disagreement within family and societal structures, hypothesizing that for certain individuals to dramatically break with family and social traditions, they must have a high level of disagreement. Using McCroskey’s Tolerance for Disagreement scale, the findings indicated that those African American men who were included in the study had significantly higher levels of Tolerance for Disagreement than African American men who did not pursue postsecondary education.
Hepatic carcinosarcoma with rhabdomyosarcoma: A case report and review of literature
Authors: Liang Gongbo , Yan Guangning , Lai Xuwen , Lai Huangwen , Qian Yunfeng , Wang Zhuocai
Published: December 2020

Objective To analyze the clinical and pathological manifestations of a hepatic carcinosarcoma case with rhabdomyosarcoma components (HCSR).Methods A case of HCSR was observed by macroscopy, microscopy, immunohistochemistry and electron microscopy, along with thorough review of correlated literatures.Results The tumor tends to occur in elder patients without differences on gender. Epigarstric sicknesses, AFP rising in serum, and a mass on the right liver shown in radiography are commonly initial signs. It was composed of both hepatic carcinoma and variously differentiated sarcoma components, with identifiable rhabdomyosarcoma. Immunohistochemistry showed that the hepatic carcinosarcoma was positive of epithelial markers and mesenchymatous component was diffuse positive of Vimentin, and mosaic positive of SDHB, CD117, while rhabdomyosarcoma was positive of muscular markers. Transmission electron microscopy showed the tumor had both epithelial and rhabdomyosarcoma ultra-microstructure.Conclusion HCSR is a very rare type and highly malignant tumor with a dismal prognosis, hardly demonstrating unique clinical manifestations. Diagnosis and differential diagnosis rely on combination of histomorphology, immunohistochemistry and ultra-microstructure observation.
Breast tall cell carcinoma with reversed polarity with an unusual molecular profile
Authors: Nielson Kaitlyn J , Fischer Edgar G. , Jacklyn Nemunaitis Jacklyn , Prabhakaran Sangeetha , Falk Nadja K.
Published: December 2020

Breast tall cell carcinoma with reversed polarity (TCCRP) is rare and previously referred to as solid papillary carcinoma with reverse polarity.  This low grade tumor commonly exhibits IDH2 p.Arg172 mutation, however is not completely understood at the molecular level.  We present a case of TCCRP in a 55 year old woman with a 0.7 cm left breast mass.  A core biopsy was performed with immunohistochemistry.  Lumpectomy and sentinel lymph node biopsy were completed two months later.  MammaPrint$^{\textregistered}$ and BluePrint$^{\textregistered}$ gene expression profilers were performed on an excision block.  Microscopically, the tumor was composed of circumscribed nests of columnar cells, with focal papillary architecture.  Tumor cells had apically located nuclei with grooves and rare inclusions. Tumor cells were positive for CK5, IDH1/2, and calretinin, and myoepithelial cells were absent.  BluePrint$^{\textregistered}$ subtyped the tumor as basaloid.  MammaPrint$^{\textregistered}$ classified the tumor as high risk for metastasis.  TCCRP presents a diagnostic challenge.  Although these rare breast carcinomas are generally reported to have an indolent clinical course, molecular analysis by gene expression profiling classified this tumor as high risk of recurrence with a basaloid type.  Therefore, molecular analysis of this tumor may lead to conflicting data regarding prognosis and treatment considerations.  Clinicians and patients should weigh published data and individual prognostic information for treatment planning.  Our patient and clinical team opted for radiation without chemotherapy.  More cases of TCCRP need to be studied to better understand its molecular profile.
Response of ductile reinforced concrete frames located in Zone C
Authors: Paulay T. , Carr A. J. , Tompkins D. N.
Published: December 2020

The results of theoretical prediction of the inelastic seismic response to selected severe earthquake motions of f our prototype ductile frames are reported. The structures  were proportioned in accordance with capacity design principles for loads corresponding with the loading requirements for seismic Zone C of New Zealand. The effects of P-delta secondary moments on seismic response are briefly reported. A three  storey frame, in which factored gravity loads rather than specified lateral earthquake loads governed the proportioning  of members, has been examined in detail. It was found that  in all frames the intended hierarchy of the energy dissipating mechanisms could be maintained during the full El Centro excitation. The analysis predicted very satisfactory performance for all frames, with a few exceptions, with frames where members were provided with a minimum amount of reinforcement.