THE STYLE OF THINKING ACTIVITY OF MODERN YOUTH AS A SCIENTIFIC AND PRACTICAL PROBLEM

The statistic is based on the state of the art of scientific advancement in the style of misinformation of the modern student youth. The style of the target is to be seen as a system of intellectual strategies, priyom, a quick reference to the operation of a specialty, how to be victorious with it in a target performance. To respect the links to the style of the targeting from the cognitive style as the way of receiving and processing information. It is to be determined that the effectiveness of the educational performance of students is significant because of the fact that the methodology of victoriousness will be the same because of the dominant style characteristics of their thinking acyivity. Respect for class is characteristic of the specialty of the style of thinking of the current student youth. It is emphasized that the tendency to reproduce heterogeneous objects, without coherent elements between them, which are characterized by illogicality, heterogeneity and high speed of switching between pieces of information, leads to difficulties in forming the desired quality of students' thinking – criticality as the ability to assess reliability, accuracy or values of something, the ability to search for and find causes and alternative points of view, to perceive the situation as a whole or to change one's position on the basis of facts and arguments. It is noted that in order to optimize the educational process in university it is necessary to select such teaching methods that would ensure the effectiveness of the thinking process of students.

COMPOSITIONAL PROCESS OF MOBILE APPLICATION DEVELOPMENT BASED ON HETEROGENEOUS SOFTWARE OBJECTS

Несмотря на множество доступных мобильных приложений с различными формами реализации (например, компонент, услуга или приложение), потребности пользователя отличаются от одного к другому. Кроме того, мобильные устройства характеризуются разнородными программными и аппаратными конфигурациями. Таким образом, важной проблемой при разработке мобильных приложений является их развертывание на доступных разнородных устройствах. Для решения этих проблем необходим процесс композиции, позволяющий повторно использовать существующие разнородные объекты для разработки мобильных приложений в соответствии с требованиями пользователя, и чтобы поведение желаемых приложений можно было настраивать в соответствии с их различной контекстной информацией. В статье эта проблема решается на основе процесса создания мобильных приложений с учетом контекста на основе существующих гетерогенных программных объектов. Despite the many mobile applications available with different forms of implementation (for example, a component, service or application), the user's needs differ from one to another. In addition, mobile devices are characterized by heterogeneous software and hardware configurations. Thus, an important problem in the development of mobile applications is their deployment on available heterogeneous devices. To solve these problems, we need a composition process that allows us to reuse existing heterogeneous objects for developing mobile applications in accordance with the user's requirements, and so that the behavior of the desired applications can be customized according to their different contextual information. In the article, this problem is solved on the basis of the process of creating mobile applications taking into account the context on the basis of existing heterogeneous program objects.

Learning hidden elasticity with deep neural networks

Elastography is an imaging technique to reconstruct elasticity distributions of heterogeneous objects. Since cancerous tissues are stiffer than healthy ones, for decades, elastography has been applied to medical imaging for noninvasive cancer diagnosis. Although the conventional strain-based elastography has been deployed on ultrasound diagnostic-imaging devices, the results are prone to inaccuracies. Model-based elastography, which reconstructs elasticity distributions by solving an inverse problem in elasticity, may provide more accurate results but is often unreliable in practice due to the ill-posed nature of the inverse problem. We introduce ElastNet, a de novo elastography method combining the theory of elasticity with a deep-learning approach. With prior knowledge from the laws of physics, ElastNet can escape the performance ceiling imposed by labeled data. ElastNet uses backpropagation to learn the hidden elasticity of objects, resulting in rapid and accurate predictions. We show that ElastNet is robust when dealing with noisy or missing measurements. Moreover, it can learn probable elasticity distributions for areas even without measurements and generate elasticity images of arbitrary resolution. When both strain and elasticity distributions are given, the hidden physics in elasticity—the conditions for equilibrium—can be learned by ElastNet.

Deductive Synthesis of Networks Hierarchical Knowledge Graphs

The article focuses on developing of a deductive synthesis method for building telecommunications networks (TN) hierarchical knowledge graphs (KG). Synthesized KGs can be used to solve search, analytical, and recommendation (forecast) problems. TNs are complex heterogeneous objects. The synthesis of knowledge graphs of such objects requires much computational resources. The proposed method provides a low complexity of the synthesis of KG of TN by taking into account their hierarchical structure. The authors propose to do synthesis by direct downward multilevel inference and reverse multilevel inference. The article analyses existing graph models of TNs and methods for their building. Detailed description of the proposed method of networks hierarchical KGs synthesis is given. In order to evaluate the deductive synthesis method, a prototype of the system is developed. The provided real-world example shows how telecommunications networks hierarchical knowledge graphs are synthesized and used in practice. Finally, conclusions are formulated, and the areas of further research are identified.

A Novel Approach for Protecting RPL Routing Protocol against Blackhole Attacks in IoT Networks

Nowadays, we are witnessing an increasing trend towards interconnected devices. This process of connecting devices instead of people is called the Internet of Things (IoT). The main concept of IoT is to connect heterogeneous objects separately and centrally in different places using standard protocols. The general idea is to create an independent world using intelligent objects that have the ability to exchange information and make decisions. Connected objects allow users to monitor and track remotely and in real-time. IoT relies on the development of a low-power, high-throughput network to support communication between objects and their connection to the Internet. These networks are characterized by limited resources in terms of energy, memory, and processing. In the true sense of the Internet of Things, networks called 6LoWPAN were created, and a new routing protocol compatible with these networks, called RPL, was introduced. Due to the limited nature of RPL-based networks, they may be exposed to a variety of internal attacks. Neighbor attacks and DIS are specific attacks in this protocol. This study proposes a trust-based RPL routing protocol which deals with blackhole threats. Besides, it is shown that while our recommended system is secure against blackhole attacks, it doesn’t incur any unwanted expenses in terms of network traffic.

Modelling of Power-Law Fluid Flow Inside a Piezoelectric Inkjet Printhead

Piezoelectric three-dimensional inkjet printing has been used to manufacture heterogeneous objects due to its high level of flexibility. The materials used are non-Newtonian inks with complex rheological properties, and their behavior in the context of inkjet printing has not been fully understood: for example, the fact that the shear-thinning viscosity affects the droplet generation. Therefore, a control strategy coping with shear-thinning behaviors is needed to ensure printing consistency. In this paper, a novel model-based approach is presented to describe the shear-thinning ink dynamics inside the piezoelectric inkjet printhead, which provides the basis to design the excitation parameters in a systematic way. The dynamic equation is simplified into a quasi-one-dimensional equation through the combination of the boundary layer theory and the constitutive equation of the power-law fluid, of which the viscosity is shear-thinning. Based on this, a nonlinear time-varying equivalent circuit model is presented to simulate the power-law fluid flow rate inside the tube. The feasibility and effectiveness of this model can be evaluated by comparing the results of computational fluid dynamics and the experimental results.

Dynamics of the Dual Relationships

Nature creates its systems in the form of a sequence of hierarchy levels that unite many heterogeneous objects, based on dual relationships. The article discusses the general principles of work and the manifestation of dual relations, as well as a measuring instrument for their functioning.

Methodological research of T.A. Guriev in ossetian studies

Профессор Т.А. Гуриев – один из немногих ученых-осетиноведов, сумевших сформировать стройную, целостную концепцию осетинской духовной и художественной культуры, свою собственную научную картину национального мира. Ученый поставил целью исследовать содержательные формы взаимодействия осетин и их предков с объективным миром в исторической перспективе; взаимодействия, при котором выявляются многогранные аспекты этно-национального духовно-нравственного космоса, культурно-философского кода народа, во-первых. Во-вторых, в процессе традиционного осмысления и познания объекта своего изучения профессор умело и творчески использует уже устоявшиеся, апробированные правила, нормативы, принципы познания, которые помогают ему решить свои творческие задачи. При этом Т.А. Гуриев стремится выстроить в своих исследованиях структуру созидаемого научного знания таким образом, чтобы установить преемственную линию связи с уже существующей научной теорией. Активно используя сравнительно-исторический метод, Т.А. Гуриев стремится выявить общее и особенное в скифо-сарматско-алано-осетинском мире, достичь глубокого познания различных исторических этапов данных объектов, выяснить и сопоставить разные уровни в их эволюции, тенденции становления и развития. Прибегая к сравнительно-сопоставительному методу, ученый пытается проанализировать природу и своеобразие разнородных объектов. А сравнительно-типологический метод позволяет ему объяснить сходство явлений, которые не связаны по генетике. Творчески использует профессор такие философские категории, как историческое и логическое. Причем с помощью исторического ученый прослеживает процесс становления и развития скифо-сармато-алано-осетинского мира, а с помощью логического – его развитие в системе важнейших связей и отношений. Professor T.A. Guriev is one of the few Ossetian scholars who have managed to form a coherent, integral concept of the Ossetian spiritual and artistic culture, his own scientific picture of the national world. The scientist set a goal to investigate the meaningful forms of interaction of Ossetians and their ancestors with the objective world in a historical perspective; interaction, which reveals the multifaceted aspects of the ethno-national spiritual and moral space, the cultural and philosophical code of the people, firstly. Secondly, in the process of traditional comprehension and cognition of the object of his study, the professor skillfully and creatively uses already established, approved rules, standards, principles of cognition that help him to solve his creative problems. At the same time, T.A. Guriev seeks to build in his research the structure of the scientific knowledge being created in such a way as to establish a successive line of communication with the already existing scientific theory. Actively using the comparative-historical method, T.A. Guriev seeks to identify typicality and specificity in the Scythian-Sarmatian-Alanian-Ossetian world, to achieve deep knowledge of the various historical stages, to find out and compare different levels in their evolution, tendencies of formation and development. Using the comparative-contrastive method, the scientist tries to analyze the nature and originality of heterogeneous objects. And the comparative-typological method allows him to explain the similarity of phenomena that are not related in genetics. The scientist creatively uses such philosophical categories as historical and logical. Moreover, with the help of the historical category the scientis reconstructs the process of the formation and development of the Scythian-Sarmatian-Alanoian-Ossetian world, and with the help of the logical categpry analyses its development in the system of the most important connections and relations.

Do we really need sub-micron resolution to analyse single cell molecular features through vibrational spectroscopy? A pilot study using Plasmodium falciparum-infected Human Erythrocytes

Malaria is one of the major life-threatening diseases to afflict humanity with an estimated 228 million cases worldwide in 2018. There exists no approved Malaria vaccine on the market yet, partly due to the complexity of the parasite life cycle and the vast repertoire of polymorphic proteins they express during different stages of development. In this work, we have tested two emerging spectroscopic approaches: Optical Photothermal Infrared (O-PTIR) spectroscopy and Atomic Force Microscopy combined with infrared spectroscopy (AFM-IR) in contrast to the more traditional Fourier Transform InfraRed (FTIR) microspectroscopy which has emerged recently as a new promising tool to provide label-free analysis of cell and tissue sections. Examples of chemical spatial distributions of selected bands and spectra for Plasmodium falciparum infected RBCs collected with the three modalities are presented and compared together with advantages and limitations of each method. Based on these results, it appears that O-PTIR and AFM-IR techniques can be explored as powerful tools for the analysis of cells and ipso facto, these methods can help in better understanding complex processes occurring within heterogeneous objects such as infected RBC due to their superior spatial resolution in comparison with traditional approaches for infrared spectroscopic characterization.

Spatiotemporal tomography based on scattered multiangular signals and its use for resolving evolving clouds using moving platforms

<p>The climate is strongly affected by interaction with clouds. To reduce major errors in climate predictions, this interaction requires a much finer understanding of cloud physics than current knowledge. Current knowledge is based on empirical remote sensing data that is analyzed under the assumption that the atmosphere and clouds are made of very broad and uniform layers. To help to overcome this problem, 3D scattering computed tomography (CT) has been suggested as a way to study clouds. </p><p>CT is a powerful way to recover the inner structure of three dimensional (3D) volumetric heterogeneous objects. CT has extensive use in many research and operational domains. Aside from its common usage in medicine, CT is used for sensing geophysical terrestrial structures, atmospheric pollution and fluid dynamics. CT requires imaging from multiple directions and in nearly all CT approaches, the object is considered static during image acquisition. However, in many cases, the object changes while multi-view images are acquired sequentially. Thus, an effort has been invested to expand 3D CT to four-dimensional (4D) spatiotemporal CT. This effort has been directed at linear CT modalities. Since linear CT is computationally easier to handle, it has been a popular method for medical imaging. However, these linear CT modalities do not apply to clouds: clouds constitute a scattering medium, and therefore radiative transfer is non-linear in the clouds’ content.</p><p>This work focuses on the challenge of 4D scattering CT of clouds. Scattering CT of clouds requires high-resolution multi-view images from space. There are spaceborne and high-altitude systems that may provide such data, for example AirMSPI, MAIA, HARP and AirHARP. An additional planned system is the CloudCT formation, funded by the ERC. However, these systems are costly. Deploying them in large numbers to simultaneously acquire images of the same clouds from many angles can be impractical. Therefore, the platforms are planned to move above the clouds: a sequence of images is taken, in order to span and sample a wide angular breadth. However, the clouds evolve while the angular span is sampled.</p><p>We pose conditions under which this task can be performed. These regard temporal sampling and angular breadth, in relation to the correlation time of the evolving cloud. Then, we generalize scattering CT. The generalization seeks spatiotemporal recovery of the cloud extinction field in high resolution (10m), using data taken by a small number of moving cameras. We present an optimization-based method to reach this, and then demonstrate the method both in rigorous simulations and on real data.</p>