cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
ОСОБЕННОСТИ РАЗВИТИЯ СТРУКТУРЫ ПРОФЕССИОНАЛИЗМА БУДУЩЕГО ОФИЦЕРА
Creators: name: В.А. Чебатарев
Publisher: name: Мир науки, культуры, образования
Year: 2020
Subjects: структура профессионализма
профессиональное становление
профессиональная компетентность
образовательный процесс военного вуза.

description: В данной статье рассматриваются особенности развития структуры профессионализма будущего офицера в процессе обучения в военном вузе. Профессионализм офицера характеризуется как высшая способность субъекта военно-профессиональной деятельности выполнить свой воинский долг, проявляющаяся в условиях военного социума и признаваемая другими его членами. В определении общей структуры и содержания профессионализма является многоплановое понимание самого явления профессионализма и его полиструктурное представление. В основу исследования положены теоретико-методологические исследования профессионального становления (Э.Ф. Зеер, Е.К. Климов, А.К. Маркова), психолого-педагогические концепции профессионализма (А.С. Белкина, А.А. Вербицкий, С.А. Дружилов, М.Д. Ильязова, В.А. Цвык, В.А. Митрохович), военно-профессиональной направленности личности (А.Ю. Асриев, А.Ф. Иониди, И.Б. Нагаева, В.В. Усманова); дедуктивный анализ и оформление материала, связанного со структурой развития профессионализма будущего офицера. В статье дана характеристика структуры профессионализма со стороны целостной функционально-смысловой системы, которая включает компоненты: ценностно-смысловой, мотивационный, индивидуально-психологический, инструментальный, когнитивный. Также рассматривается структура профессионализма через призму социально-философского анализа и формируется в двух планах: культурно-личностном и социально-функциональном. Комплексный подход к пониманию профессионализма находит свое отражение в различных концепциях и подходах к этому явлению. Как системное качество, профессионализм рассматривается в единстве трех подсистем, каждая из которых обладает собственной структурой: подсистема профессиональной продуктивности, подсистема профессиональной идентичности, подсистема профессиональной зрелости. Автор выделяет в структуре профессионализма будущего офицера наиболее значимые компоненты: деятельностный, идентификационный, адаптационный, интеграционный, которые охватывают профессиональное становление военного специалиста в условиях образовательного процесса военного вуза. Определены компоненты, входящие в структуру профессионализма будущего офицера, которые на наш взгляд, являются наиболее важными и доступными для развития профессионализма будущего офицера в условиях образовательного процесса высшего военного учебного заведения, а также которыми должен обладать офицер для успешного выполнения военно-профессиональных задач по должностному предназначению.
ИЗУЧЕНИЕ ВЛИЯНИЯ ДИСТАНЦИОННОЙ ФОРМЫ ОБУЧЕНИЯ ВО ВРЕМЯ ПАНДЕМИИ НА РЕЗУЛЬТАТЫ ОБУЧЕНИЯ
Creators: name: Л.И. Якобюк
Publisher: name: Мир науки, культуры, образования
Year: 2020
Subjects: дистанционное обучение
пандемия
балл ЕГЭ
абитуриент
репетитор
школа
выпускник

description: В данной статье приведен анализ результатов ЕГЭ по профильной математике путем сравнения ожидаемых и фактических баллов. Автор приходит к выводу, что дистанционная форма обучения в период пандемии коронавируса отрицательно сказалась на результатах ЕГЭ. Об этом также свидетельствует оценка уровня подготовки по математике в дистанционной форме, для определения которой обучаемым было предложено выставить баллы по шкале от 0 до 10. Среднее значение уровня подготовки по математике в дистанционной форме составило 4,9 баллов, при этом 62% опрошенных оценили данный показатель от 0 до 5 баллов. Низкий уровень подготовки к ЕГЭ в школе привел к необходимости прибегнуть за помощью к репетитору, 48% опрошенных указали, что при подготовке к единому государственному экзамену по математике они обращались за дополнительной помощью.
Data mining techniques on astronomical spectra data. II : Classification Analysis
Creators: name: Yang, Haifeng
name: Zhou, Lichan
name: Cai, Jianghui
name: Shi, Chenhui
name: Yang, Yuqing
name: Zhao, Xujun
name: Duan, Juncheng
name: Yin, Xiaona
Publisher: name: arXiv
Year: 2022
Subjects: subject: Instrumentation and Methods for Astrophysics (astro-ph.IM)
subject: FOS: Physical sciences

description: Classification is valuable and necessary in spectral analysis, especially for data-driven mining. Along with the rapid development of spectral surveys, a variety of classification techniques have been successfully applied to astronomical data processing. However, it is difficult to select an appropriate classification method in practical scenarios due to the different algorithmic ideas and data characteristics. Here, we present the second work in the data mining series - a review of spectral classification techniques. This work also consists of three parts: a systematic overview of current literature, experimental analyses of commonly used classification algorithms and source codes used in this paper. Firstly, we carefully investigate the current classification methods in astronomical literature and organize these methods into ten types based on their algorithmic ideas. For each type of algorithm, the analysis is organized from the following three perspectives. (1) their current applications and usage frequencies in spectral classification are summarized; (2) their basic ideas are introduced and preliminarily analysed; (3) the advantages and caveats of each type of algorithm are discussed. Secondly, the classification performance of different algorithms on the unified data sets is analysed. Experimental data are selected from the LAMOST survey and SDSS survey. Six groups of spectral data sets are designed from data characteristics, data qualities and data volumes to examine the performance of these algorithms. Then the scores of nine basic algorithms are shown and discussed in the experimental analysis. Finally, nine basic algorithms source codes written in python and manuals for usage and improvement are provided.
description: 25 pages, 41 figures
A Reliable and Low Latency Synchronizing Middleware for Co-simulation of a Heterogeneous Multi-Robot Systems
Creators: name: Dey, Emon
name: Walczak, Mikolaj
name: Anwar, Mohammad Saeid
name: Roy, Nirmalya
Publisher: name: arXiv
Year: 2022
Subjects: subject: Robotics (cs.RO)
subject: Multiagent Systems (cs.MA)
subject: Networking and Internet Architecture (cs.NI)
subject: FOS: Computer and information sciences

description: Search and rescue, wildfire monitoring, and flood/hurricane impact assessment are mission-critical services for recent IoT networks. Communication synchronization, dependability, and minimal communication jitter are major simulation and system issues for the time-based physics-based ROS simulator, event-based network-based wireless simulator, and complex dynamics of mobile and heterogeneous IoT devices deployed in actual environments. Simulating a heterogeneous multi-robot system before deployment is difficult due to synchronizing physics (robotics) and network simulators. Due to its master-based architecture, most TCP/IP-based synchronization middlewares use ROS1. A real-time ROS2 architecture with masterless packet discovery synchronizes robotics and wireless network simulations. A velocity-aware Transmission Control Protocol (TCP) technique for ground and aerial robots using Data Distribution Service (DDS) publish-subscribe transport minimizes packet loss, synchronization, transmission, and communication jitters. Gazebo and NS-3 simulate and test. Simulator-agnostic middleware. LOS/NLOS and TCP/UDP protocols tested our ROS2-based synchronization middleware for packet loss probability and average latency. A thorough ablation research replaced NS-3 with EMANE, a real-time wireless network simulator, and masterless ROS2 with master-based ROS1. Finally, we tested network synchronization and jitter using one aerial drone (Duckiedrone) and two ground vehicles (TurtleBot3 Burger) on different terrains in masterless (ROS2) and master-enabled (ROS1) clusters. Our middleware shows that a large-scale IoT infrastructure with a diverse set of stationary and robotic devices can achieve low-latency communications (12% and 11% reduction in simulation and real) while meeting mission-critical application reliability (10% and 15% packet loss reduction) and high-fidelity requirements.
Zeta functions, Grothendieck groups, and the Witt ring
Creators: name: Ramachandran, Niranjan
Publisher: name: arXiv
Year: 2014
Subjects: subject: Number Theory (math.NT)
subject: Algebraic Geometry (math.AG)
subject: K-Theory and Homology (math.KT)
subject: FOS: Mathematics
subject: 11Mxx 14G15

description: We prove some results connecting the zeta functions of varieties over finite fields with the big Witt ring over $\mathbb Z$. We explore relations with motivic measures and a classical formula of Macdonald on invariants of symmetric products of a variety.
description: 23 pages, submitted for publication. Added reference to Niko Naumann's work. Comments welcome
XEngine: Optimal Tensor Rematerialization for Neural Networks in Heterogeneous Environments
Creators: name: Schuler, Manuela
name: Membarth, Richard
name: Slusallek, Philipp
Publisher: name: arXiv
Year: 2022
Subjects: subject: Machine Learning (cs.LG)
subject: Programming Languages (cs.PL)
subject: FOS: Computer and information sciences

description: Memory efficiency is crucial in training deep learning networks on resource-restricted devices. During backpropagation, forward tensors are used to calculate gradients. Despite the option of keeping those dependencies in memory until they are reused in backpropagation, some forward tensors can be discarded and recomputed later from saved tensors, so-called checkpoints. This allows, in particular, for resource-constrained heterogeneous environments to make use of all available compute devices. Unfortunately, the definition of these checkpoints is a non-trivial problem and poses a challenge to the programmer - improper or excessive recomputations negate the benefit of checkpointing. In this article, we present XEngine, an approach that schedules network operators to heterogeneous devices in low memory environments by determining checkpoints and recomputations of tensors. Our approach selects suitable resources per timestep and operator and optimizes the end-to-end time for neural networks taking the memory limitation of each device into account. For this, we formulate a mixed-integer quadratic program (MIQP) to schedule operators of deep learning networks on heterogeneous systems. We compare our MIQP solver XEngine against Checkmate, a mixed-integer linear programming (MILP) approach that solves recomputation on a single device. Our solver finds solutions that are up to 22.5 % faster than the fastest Checkmate schedule in which the network is computed exclusively on a single device. We also find valid schedules for networks making use of both central processing units and graphics processing units if memory limitations do not allow scheduling exclusively to the graphics processing unit.
Pemetaan Topik Penelitian Seputar Cash Ratio pada Perbankan Syariah dan Konvensional: Studi Bibliometrik VOSviewer dan Literature Review
Creators: name: Budianto, Eka Wahyu Hestya
name: Dewi, Nindi Dwi Tetria
Publisher: name: Zenodo
Year: 2023
Subjects: Cash Ratio
Perbankan Syariah dan Konvensional
Bibliometrik
VOSviewer
Literature Review

description: This study aims to determine the mapping of research topics around Cash Ratio in Islamic and Conventional Banking with a mix-method approach, namely the VOSviewer bibliometric study and literature review. Data analysis techniques include: (1) mapping the distribution of journal publications around the Cash Ratio; (2) map the results of the VOSviewer bibliometric visualization around the Cash Ratio based on the number of clusters and their items; and (3) mapping research topics around the Cash Ratio using a literature review study. The results of the study show that: (1) based on the mapping of the distribution of journal publications, there are 26 journal publications regarding the Cash Ratio; (2) based on the mapping of the VOSviewer bibliometric study, the network visualization results regarding the Cash Ratio are divided into 8 clusters and 106 topic items; (3) based on the mapping of the literature review study, there are 15 influences caused by the Cash Ratio and 7 factors that influence the Cash Ratio. The difference between this research and previous research is that this research explains and maps all research topics around cash ratios, so that future researchers can find out research gaps about cash ratios. The implication and contribution of this research is that there is a mapping of research topics around cash ratios that are often or rarely researched by researchers, so that they can be a reference for further researchers.
Hierarchy of modes in an interacting system
Creators: name: Tsyplyatyev, O.
name: Schofield, A. J.
name: Jin, Y.
name: Moreno, M.
name: Tan, W. K.
name: Ford, C. J. B.
name: Griffiths, J. P.
name: Farrer, I.
name: Jones, G. A. C.
name: Ritchie, D. A.
Publisher: name: arXiv
Year: 2014
Subjects: subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: FOS: Physical sciences

description: Studying interacting fermions in 1D at high energy, we find a hierarchy in the spectral weights of the excitations theoretically and we observe evidence for second-level excitations experimentally. Diagonalising a model of fermions (without spin), we show that levels of the hierarchy are separated by powers of $\mathcal{R}^{2}/L^{2}$, where $\mathcal{R}$ is a length-scale related to interactions and $L$ is the system length. The first-level (strongest) excitations form a mode with parabolic dispersion, like that of a renormalised single particle. The second-level excitations produce a singular power-law line shape to the first-level mode and multiple power-laws at the spectral edge. We measure momentum-resolved tunnelling of electrons (fermions with spin) from/to a wire formed within a GaAs heterostructure, which shows parabolic dispersion of the first-level mode and well-resolved spin-charge separation at low energy with appreciable interaction strength. We find structure resembling the second-level excitations, which dies away quite rapidly at high momentum.
description: 5 pages, 3 figures, 1 table
КОМПЛЕКСНАЯ ПРОГРАММА КАК ИННОВАЦИОННАЯ ОПЫТНО-ЭКСПЕРИМЕНТАЛЬНАЯ ДЕЯТЕЛЬНОСТЬ: ОПЫТ ПЕДАГОГИЧЕСКОЙ РАЗРАБОТКИ
Creators: name: Н.Н. Дацюк
name: О.А. Бокова
Publisher: name: Мир науки, культуры, образования
Year: 2020
Subjects: комплексная программа
особенности разработки и реализации
инновационная деятельность

description: Авторами отмечается, что к инновационной опытно-экспериментальной деятельности в области образования можно отнести разработку и реализацию комплексной программы психолого-педагогического сопровождения семей, воспитывающих молодых инвалидов в условиях Комплексного центра социального обслуживания населения, в рамках которой осуществляется реализация групповых и индивидуальных форм психолого-педагогического сопровождения как родителей, воспитывающих молодых инвалидов, так и самих взрослых детей. Социально-психолого-педагогическими условиями психолого-педагогического сопровождения семей, воспитывающих детей с ограниченными возможностями здоровья, в деятельности специалистов Комплексного центра социального обслуживания населения являются повышение уровня психолого-педагогической грамотности родителей и степени вовлеченности в коррекционно-развивающий процесс, формирование принимающего отношения к взрослому ребенку.
Associated production of Higgs and single top at the LHC in presence of the SMEFT operators
Creators: name: Bhattacharya, Subhaditya
name: Biswas, Sanjoy
name: Pal, Kuntal
name: Wudka, Jose
Publisher: name: arXiv
Year: 2022
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: FOS: Physical sciences

description: We analyse the single top production in association with the Higgs at the Large Hadron Collider (LHC) using Standard Model (SM) effective operators upto dimension six. We show that the presence of effective operators can significantly alter the existing bound on the top-Higgs Yukawa coupling. We analyse events at the LHC with 35.9 and 137(140) fb$^{-1}$ integrated luminosities using both cut-based and machine learning techniques to probe new physics (NP) scale and operator coefficients addressing relevant SM background reduction. The four fermi effective operator(s) that contributes to the signal, turns out to be crucial and a bound on the operator coefficient is obtained from the present data and for future sensitivities.
description: Version published in JHEP
Projected changes of rainfall seasonality and dry spells in a high concentration pathway 21st century scenario
Creators: name: Pascale, Salvatore
name: Lucarini, Valerio
name: Feng, Xue
name: Porporato, Amilcare
name: Hasson, Shabeh ul
Publisher: name: arXiv
Year: 2014
Subjects: subject: Atmospheric and Oceanic Physics (physics.ao-ph)
subject: Geophysics (physics.geo-ph)
subject: FOS: Physical sciences

description: In this diagnostic study we analyze changes of rainfall seasonality and dry spells by the end of the twenty-first century under the most extreme IPCC5 emission scenario (RCP8.5) as projected by twenty-four coupled climate models participating to Coupled Model Intercomparison Project 5. We use estimates of the centroid of the monthly rainfall distribution as an index of the rainfall timing and a threshold-independent, information theory-based quantity such as relative entropy (RE) to quantify the concentration of annual rainfall and the number of dry months and to build a monsoon dimensionless seasonality index (DSI). The RE is projected to increase, with high inter-model agreement over Mediterranean-type regions (southern Europe, northern Africa and southern Australia) and areas of South and Central America, implying an increase in the number of dry days up to one month by the end of the twenty-first century. Positive RE changes are also projected over the monsoon regions of southern Africa and North America, South America. These trends are consistent with a shortening of the wet season associated with a more prolonged pre-monsoonal dry period. The extent of the global monsoon region, characterized by large DSI, is projected to remain substantially unaltered. Centroid analysis shows that most of CMIP5 projections suggest that the monsoonal annual rainfall distribution is expected to change from early to late in the course of the hydrological year by the end of the twenty-first century and particularly after year 2050. This trend is particularly evident over Northern Africa, Southern Africa and western Mexico, where more than 90 % of the models project a delay of the rainfall centroid from a few days up to two weeks. Over the remaining monsoonal regions, there is little inter-model agreement in terms of centroid changes.
АНАЛИЗ ПОТРЕБНОСТЕЙ БУДУЩИХ ПЕДАГОГОВ В ОБЛАСТИ ИСПОЛЬЗОВАНИЯ ТЕХНОЛОГИЙ ЭЛЕКТРОННОГО ОБУЧЕНИЯ
Creators: name: Е.В. Москаленко
Publisher: name: Мир науки, культуры, образования
Year: 2020
Subjects: электронное обучение
профессиональная подготовка будущего педагога
дистанционные образовательные технологии
информационно-коммуникационные технологии
информатизация образования

description: Основное содержание исследования составляет анализ потребностей будущих педагогов в освоении навыков проектирования и использования технологий электронного обучения и дистанционных образовательных технологий в процессе вузовской подготовки. В статье приводятся результаты анкетирования будущих педагогов, касающегося влияния перехода образовательных учреждений на электронное обучение с использованием дистанционных образовательных технологий на процесс профессиональной подготовки будущих педагогов, на примере Алтайского государственного педагогического университета. В статье акцентируется внимание на том, что в условиях глобального процесса информатизации образования современный педагог должен соответствовать запросам общества, новым быстроизменяющимся условиям, в частности обладать навыками реализации электронного обучения, в том числе и опосредованно, с применением дистанционных образовательных технологий, а также использовать технологии электронного обучения и в рамках своей профессиональной деятельности.
title: Johann Caspar Hirzel, der ältere (1725-1803)
title: seine Werdejahre und seine Freundschaft mit Gleim
titleType: Subtitle
Creators: name: Hirzel, Bruno
Publisher: name: Kommissionsverlag von Beer & Cie.
Year: 1916
Subjects: subject: 836 Deutsche Briefe
subject: 920 Biografien, Genealogie, Insignien
subject: Zürich
subject: Hirzel, Hans Caspar
subject: Gleim, Johann Wilhelm Ludwig
subject: Brief
subject: Familienarchiv

description: Mit unbekannten Briefen von Johann Wilhelm Ludwig Gleim an Hans Caspar Hirzel
Optimal pricing for carbon dioxide removal under inter-regional leakage
Creators: name: Franks, Max
name: Kalkuhl, Matthias
name: Lessmann, Kai
Publisher: name: arXiv
Year: 2022
Subjects: subject: General Economics (econ.GN)
subject: FOS: Economics and business

description: Carbon dioxide removal (CDR) moves atmospheric carbon to geological or land-based sinks. In a first-best setting, the optimal use of CDR is achieved by a removal subsidy that equals the optimal carbon tax and marginal damages. We derive second-best policy rules for CDR subsidies and carbon taxes when no global carbon price exists but a national government implements a unilateral climate policy. We find that the optimal carbon tax differs from an optimal CDR subsidy because of carbon leakage and a balance of resource trade effect. First, the optimal removal subsidy tends to be larger than the carbon tax because of lower supply-side leakage on fossil resource markets. Second, net carbon exporters exacerbate this wedge to increase producer surplus of their carbon resource producers, implying even larger removal subsidies. Third, net carbon importers may set their removal subsidy even below their carbon tax when marginal environmental damages are small, to appropriate producer surplus from carbon exporters.
ТРАНСДИСЦИПЛИНАРНЫЙ ПОДХОД ПРИ ФОРМИРОВАНИИ НАВЫКОВ САМОРЕАЛИЗАЦИИ В ПРОЦЕССЕ ПОДГОТОВКИ МАГИСТРОВ
Creators: name: И.А. Звонарева
name: А.А. Баранова
name: Б.Н. Гузанов
Publisher: name: Мир науки, культуры, образования
Year: 2020
Subjects: трансдисциплинарность
системный подход
магистратура
навыки самореализации
методология
системное мышление
научно-исследовательская работа
непрерывное образование
биоинженерия

description: В современной педагогической практике применение трансдисциплинарного подхода в профессиональном образовании рассматривается как один из важнейших способов повышения качества и фундаментальности подготовки студентов технических вузов, особенно при освоении магистерских программ. Отмечается, что в отличие от междисциплинарного обучения трансдисциплинарность как более глубокий и транспарентный уровень интеграции различных по содержанию, но профессионально равнонаправленных базовых дисциплин позволяет магистрам сформировать необходимые навыки самосовершенствования и последующей самореализации при выборе собственного карьерного пути. В статье с целью обеспечения подготовки кадров высокой квалификации в контексте специализации, направленной на овладения методами смежных наук, соответствующих потребностям современного производства, научно обоснована и спроектирована на принципах трансдисциплинарности основная образовательная программа по профилизации “Биомедицинской инженерии” на основе СУОС УрФУ для направления подготовки 12.04.04 Биотехнические системы и технологии.
Towards Privacy-Aware Causal Structure Learning in Federated Setting
Creators: name: Huang, Jianli
name: Guo, Xianjie
name: Yu, Kui
name: Cao, Fuyuan
name: Liang, Jiye
Publisher: name: arXiv
Year: 2022
Subjects: subject: Machine Learning (cs.LG)
subject: Artificial Intelligence (cs.AI)
subject: Cryptography and Security (cs.CR)
subject: FOS: Computer and information sciences

description: Causal structure learning has been extensively studied and widely used in machine learning and various applications. To achieve an ideal performance, existing causal structure learning algorithms often need to centralize a large amount of data from multiple data sources. However, in the privacy-preserving setting, it is impossible to centralize data from all sources and put them together as a single dataset. To preserve data privacy, federated learning as a new learning paradigm has attracted much attention in machine learning in recent years. In this paper, we study a privacy-aware causal structure learning problem in the federated setting and propose a novel Federated PC (FedPC) algorithm with two new strategies for preserving data privacy without centralizing data. Specifically, we first propose a novel layer-wise aggregation strategy for a seamless adaptation of the PC algorithm into the federated learning paradigm for federated skeleton learning, then we design an effective strategy for learning consistent separation sets for federated edge orientation. The extensive experiments validate that FedPC is effective for causal structure learning in a federated learning setting.
description: This paper has been accepted by the journal IEEE Transactions on Big Data, and it contains 21 pages, 9 figures and 15 tables
The structure of groups with all proper quotients virtually nilpotent
Creators: name: Klopsch, Benjamin
name: Quick, Martyn
Publisher: name: arXiv
Year: 2022
Subjects: subject: Group Theory (math.GR)
subject: FOS: Mathematics
subject: 20E18 20F19 20E26

description: Just infinite groups play a significant role in profinite group theory. For each $c \geq 0$, we consider more generally JNN$_c$F profinite (or, in places, discrete) groups that are Fitting-free; these are the groups $G$ such that every proper quotient of $G$ is virtually class-$c$ nilpotent whereas $G$ itself is not, and additionally $G$ does not have any non-trivial abelian normal subgroup. When $c = 1$, we obtain the just non-(virtually abelian) groups without non-trivial abelian normal subgroups. Our first result is that a finitely generated profinite group is virtually class\nbd$c$ nilpotent if and only if there are only finitely many subgroups arising as the lower central series terms $γ_{c+1}(K)$ of open normal subgroups $K$ of $G$. Based on this we prove several structure theorems. For instance, we characterize the JNN$_c$F profinite groups in terms of subgroups of the above form $γ_{c+1}(K)$. We also give a description of JNN$_c$F profinite groups as suitable inverse limits of virtually nilpotent profinite groups. Analogous results are established for the family of hereditarily JNN$_c$F groups and, for instance, we show that a Fitting-free JNN$_c$F profinite (or discrete) group is hereditarily JNN$_cF$ if and only if every maximal subgroup of finite index is JNN$_c$F. Finally, we give a construction of hereditarily JNN$_c$F groups, which uses as an input known families of hereditarily just infinite groups.
description: Minor typos corrected. Accepted to appear Pacific J Math
Reduced description of exact coherent states in parallel shear flows
Creators: name: Beaume, Cedric
name: Chini, Gregory P.
name: Julien, Keith
name: Knobloch, Edgar
Publisher: name: arXiv
Year: 2014
Subjects: subject: Fluid Dynamics (physics.flu-dyn)
subject: FOS: Physical sciences

description: Exact coherent states of a linearly stable, plane parallel shear flow confined between stationary stress-free walls and driven by a sinusoidal body force (a flow first introduced by F. Waleffe, Phys. Fluids 9, 883 (1997)) are computed using equations obtained from a large Reynolds-number asymptotic reduction of the Navier-Stokes equations. The reduced equations employ a decomposition into streamwise-averaged (mean) and streamwise-varying (fluctuation) components and are characterized by an effective order one Reynolds number in the mean equations along with a formally higher-order diffusive regularization of the fluctuation equations. A robust numerical algorithm for computing exact coherent states is introduced. Numerical continuation of the lower branch states to lower Reynolds numbers reveals the presence of a saddle-node; the saddle-node allows access to upper branch states that, like the lower branch states, appear to be self-consistently described by the reduced equations. Both lower and upper branch states are characterized in detail.
Theoretical investigation of the electronic and magnetic properties of the orthorhombic phase of Ba(Fe$_{1-x}$Co$_x$)$_2$As$_2$
Creators: name: Derondeau, Gerald
name: Polesya, Svitlana
name: Mankovsky, Sergiy
name: Ebert, Hubert
name: Minár, Ján
Publisher: name: arXiv
Year: 2014
Subjects: subject: Superconductivity (cond-mat.supr-con)
subject: FOS: Physical sciences

description: We present a comprehensive study on the low-temperature orthorhombic phase of Ba(Fe$_{1-x}$Co$_x$)$_2$As$_2$ based on the Korringa-Kohn-Rostoker-Green function approach. Using this bandstructure method in combination with the coherent potential approximation alloy theory we are able to investigate the evolution of the magnetic and electronic properties of this prototype iron pnictide for arbitrary concentrations $x$, while dealing with the chemical disorder without uncontrolled simplifications by using solely a rigid band shift or the virtual crystal approximation. We discuss the development of the site resolved magnetic moments for the experimentally observed stripe antiferromagnetic order together with the strong electronic anisotropy of the Fermi surface and compare it with angle-resolved photoemission spectroscopy measurements of detwinned crystals. We furthermore calculate magnetic exchange coupling parameters $J_{ij}$ and use them for Monte-Carlo simulations on the basis of the classical Heisenberg model to get an insight on the temperature dependence of the magnetic ordering on the cobalt concentration.
СМЫСЛОВЫЕ ДЕТЕРМИНАНТЫ СТАНОВЛЕНИЯ И РАЗВИТИЯ САМОАКТУАЛИЗИРУЮЩЕЙСЯ ЛИЧНОСТИ В ОБРАЗОВАТЕЛЬНОМ ПРОЦЕССЕ
Creators: name: В.С. Цилицкий
name: В.В. Баркова
Publisher: name: Мир науки, культуры, образования
Year: 2020
Subjects: личность
образование
образовательный процесс
развитие
самоактуализация
саморазвитие
ценности

description: В данной статье раскрывается проблема становления самоактуализирующейся личности в образовательном процессе. Основное содержание исследования составляет анализ философско-педагогических концепций и теорий, на основе которых авторами статьи была раскрыта взаимосвязь и влияние процессов в диаде «образование – самоактуализация» на формирование личности индивида. В статье исследуются характерные признаки феномена самоактуализации, охарактеризованы факторы, оказывающие влияние на формирование мотивации и установок на самоактуализацию обучающегося. В работе охарактеризовано значение педагогического механизма формирования способности и готовности к самоактуализации через организацию образовательного процесса. Представленный материал позволяет сделать вывод, что ориентация образовательного процесса на поддержку самоактуализации у обучающихся привносит качественные изменения, в том числе и в их отношение к учебной деятельности, развивает жизненный опыт, даёт возможность для обучения и решения различных задач.
Forecasting Future Instance Segmentation with Learned Optical Flow and Warping
Creators: name: Ciamarra, Andrea
name: Becattini, Federico
name: Seidenari, Lorenzo
name: Del Bimbo, Alberto
Publisher: name: arXiv
Year: 2022
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: For an autonomous vehicle it is essential to observe the ongoing dynamics of a scene and consequently predict imminent future scenarios to ensure safety to itself and others. This can be done using different sensors and modalities. In this paper we investigate the usage of optical flow for predicting future semantic segmentations. To do so we propose a model that forecasts flow fields autoregressively. Such predictions are then used to guide the inference of a learned warping function that moves instance segmentations on to future frames. Results on the Cityscapes dataset demonstrate the effectiveness of optical-flow methods.
description: Paper published as Poster at ICIAP21
Terahertz Frequency-Domain Sensing Combined with Quantitative Multivariate Analysis for Pharmaceutical Tablet Inspection
Creators: name: Moradikouchi, Anis
name: Sparén, Anders
name: Svensson, Olof
name: Folestad, Staffan
name: Stake, Jan
name: Rodilla, Helena
Publisher: name: arXiv
Year: 2022
Subjects: subject: Applied Physics (physics.app-ph)
subject: FOS: Physical sciences

description: Near infrared (NIR) and Raman spectroscopy combined with multivariate analysis are established techniques for the identification and quantification of chemical properties of pharmaceutical tablets like the concentration of active pharmaceutical ingredients (API). However, these techniques suffer from a high sensitivity to particle size variations and are not ideal for the characterization of physical properties of tablets such as tablet density. In this work, we have explored the feasibility of terahertz frequency-domain spectroscopy, with the advantage of low scattering effects, combined with multivariate analysis to quantify API concentration and tablet density. We studied 33 tablets, consisting of Ibuprofen, Mannitol, and a lubricant with API concentration and filler particle size as the design factors. The terahertz signal was measured in transmission mode across the frequency range 750 GHz to 1.5 THz using a vector network analyzer, frequency extenders, horn antennas, and four off-axis parabolic mirrors. The attenuation spectral data were pre-processed and orthogonal partial least square (OPLS) regression was applied to the spectral data to obtain quantitative prediction models for API concentration and tablet density. The performance of the models was assessed using test sets. While a fair model was obtained for API concentration, a high-quality model was demonstrated for tablet density. The coefficient of determination for the calibration set was 0.97 for tablet density and 0.98 for API concentration, while the relative prediction errors for the test set were 0.7% and 6%for tablet density and API concentration models, respectively.
МУЗЫКАЛЬНОЕ ПРОИЗВЕДЕНИЕ КАК ОБЪЕКТ ОСВОЕНИЯ В КЛАССАХ ИНСТРУМЕНТАЛИСТОВ: ГЕРМЕНЕВТИЧЕСКИЙ ПОДХОД
Creators: name: О.А. Блок
Publisher: name: Мир науки, культуры, образования
Year: 2020
Subjects: музыкальное произведение
исполнитель-инструменталист
нотный текст
подтекст
надтекст
контекст
класс инструменталистов
педагогическая парадигма «4D»

description: В статье обосновывается актуальность применения герменевтического подхода в теории и практике музыкального исполнительства. Выявляется необходимость повышения качества музыкально-образовательного процесса в классах инструменталистов. В рамках рассматриваемой проблематики предлагается педагогическая парадигма, определяющая систему освоения музыкального произведения в пространстве «4D» (на уровне текста, подтекста, надтекста и контекста). Каждый отдельно взятый уровень включается в аналитический спектр, классифицируется, получает свою характеристику. Обращается внимание на детерминантность двух мегасистем, заявленных в предлагаемой педагогической парадигме: музыкальное произведение (текст, подтекст, надтекст, контекст) и сознание, подсознание, сверхсознание личности исполнителя, общественное сознание. Заостряется угол зрения на перспективности изучения векторов: сознание исполнителя, соединяющееся с сознанием педагога и общественным сознанием; бессознательное инструменталиста, которое делится на подсознание и сверхсознание, взаимодействующее с бессознательным педагога, зрителя, общества в целом. Как предполагает автор, педагогическая парадигма «4D» и позиционируемый научно-теоретический подход могут олицетворять инновационную технологию, позволяющую питать соответствующую исследовательскую платформу, обеспечивать эффективную реализацию реформирования и модернизации современного музыкального образования в классах инструменталистов.
Real-Time Rendering of Arbitrary Surface Geometries using Learnt Transfer
Creators: name: Dhawal, Sirikonda
name: KT, Aakash
name: Narayanan, P. J.
Publisher: name: arXiv
Year: 2022
Subjects: subject: Graphics (cs.GR)
subject: FOS: Computer and information sciences

description: Precomputed Radiance Transfer (PRT) is widely used for real-time photorealistic effects. PRT disentangles the rendering equation into transfer and lighting, enabling their precomputation. Transfer accounts for the cosine-weighted visibility of points in the scene while lighting for emitted radiance from the environment. Prior art stored precomputed transfer in a tabulated manner, either in vertex or texture space. These values are fetched with interpolation at each point for shading. Vertex space methods require densely tessellated mesh vertices for high quality images. Texture space methods require non-overlapping and area-preserving UV mapping to be available. They also require a high-resolution texture to avoid rendering artifacts. In this paper, we propose a compact transfer representation that is learnt directly on scene geometry points. Specifically, we train a small multi-layer perceptron (MLP) to predict the transfer at sampled surface points. Our approach is most beneficial where inherent mesh storage structure and natural UV mapping are not available, such as Implicit Surfaces as it learns the transfer values directly on the surface. We demonstrate real-time, photorealistic renderings of diffuse and glossy materials on SDF geometries with PRT using our approach.
description: Accepted at ICVGIP 2022
Significance Mode Analysis (SigMA) for hierarchical structures. An application to the Sco-Cen OB association
Creators: name: Ratzenböck, Sebastian
name: Großschedl, Josefa E.
name: Möller, Torsten
name: Alves, João
name: Bomze, Immanuel
name: Meingast, Stefan
Publisher: name: arXiv
Year: 2022
Subjects: subject: Astrophysics of Galaxies (astro-ph.GA)
subject: FOS: Physical sciences

description: We present a new clustering method, Significance Mode Analysis (SigMA), to extract co-spatial and co-moving stellar populations from large-scale surveys such as ESA Gaia. The method studies the topological properties of the density field in the multidimensional phase space. We validate SigMA on simulated clusters and find that it outperforms competing methods, especially in cases where many clusters are closely spaced. We apply the new method to Gaia DR3 data of the closest OB association to Earth, Scorpio-Centaurus (Sco-Cen), and find more than 13,000 co-moving young objects, with about 19% of these having a sub-stellar mass. SigMA finds 37 co-moving clusters in Sco-Cen. These clusters are independently validated by their narrow HRD sequences and, to a certain extent, by their association with massive stars too bright for Gaia, hence unknown to SigMA. We compare our results with similar recent work and find that the SigMA algorithm recovers richer populations, is able to distinguish clusters with velocity differences down to about 0.5 km s$^{-1}$, and reaches cluster volume densities as low as 0.01 sources/pc$^3$. The 3D distribution of these 37 coeval clusters implies a larger extent and volume for the Sco-Cen OB association than typically assumed in the literature. Additionally, we find the association to be more actively star-forming and dynamically more complex than previously thought. We confirm that the star-forming molecular clouds in the Sco-Cen region, namely, Ophiuchus, L134/L183, Pipe Nebula, Corona Australis, Lupus, and Chamaeleon, are part of the Sco-Cen The application of SigMA to Sco-Cen demonstrates that advanced machine learning tools applied to the superb Gaia data allows to construct an accurate census of the young populations, to quantify their dynamics, and to reconstruct the recent star formation history of the local Milky Way.
description: Submitted after first revision to A&A
Quantum algorithms for optimal effective theory of many-body systems
Creators: name: Yang, Yongdan
name: Zhang, Zongkang
name: Xu, Xiaosi
name: Lu, Bing-Nan
name: Li, Ying
Publisher: name: arXiv
Year: 2022
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: A common situation in quantum many-body physics is that the underlying theories are known but too complicated to solve efficiently. In such cases one usually builds simpler effective theories as low-energy or large-scale alternatives to the original theories. Here the central tasks are finding the optimal effective theories and proving their equivalence to the original theories. Recently quantum computing has shown the potential of solving quantum many-body systems by exploiting its inherent parallelism. It is thus an interesting topic to discuss the emergence of effective theories and design efficient tools for finding them based on the results from quantum computing. As the first step towards this direction, in this paper, we propose two approaches that apply quantum computing to find the optimal effective theory of a quantum many-body system given its full Hamiltonian. The first algorithm searches the space of effective Hamiltonians by quantum phase estimation and amplitude amplification. The second algorithm is based on a variational approach that is promising for near-future applications.
description: 10 pages, 7 figures
ДВОЙНАЯ ПОДСТАНОВКА В ИРРАЦИОНАЛЬНЫХ УРАВНЕНИЯХ
Creators: name: Г.М. Гузаиров
Publisher: name: Мир науки, культуры, образования
Year: 2020
Subjects: методы решений уравнений
разложение на множители
подстановка
двойная подстановка
иррациональные уравнения и неравенства.

description: Двойная подстановка – метод решения задач с параметрами, содержащими уравнения и неравенства. Этот метод почти не представлен в школьных учебниках математики, задачниках и справочниках по элементарной математике, но иногда оказывается проще, чем более традиционные методы решения таких задач, обычно применяемых в школе, – возведение в степень, разложение на множители и обычная подстановка. В настоящей работе будет показано применение двойной подстановки к иррациональным уравнениям. Этот метод позволяет обойтись без возведения уравнения в степень, что в случае четных степеней является неравносильным преобразованием уравнения. Еще более удобным приемом является двойная подстановка в неравенствах и задачах с параметрами, примеры которых мы приведем в следующих работах.
An Efficient Bit Plane X-OR Algorithm for Irreversible Image Steganography
Creators: name: Chakraborty, Soumendu
name: Jalal, Anand Singh
name: Bhatnagar, Charul
Publisher: name: arXiv
Year: 2014
Subjects: subject: Multimedia (cs.MM)
subject: FOS: Computer and information sciences

description: The science of hiding secret information in another message is known as Steganography; hence the presence of secret information is concealed. It is the method of hiding cognitive content in same or another media to avoid recognition by the intruders. This paper introduces new method wherein irreversible steganography is used to hide an image in the same medium so that the secret data is masked. The secret image is known as payload and the carrier is known as cover image. X-OR operation is used amongst mid level bit planes of carrier image and high level bit planes of data image to generate new low level bit planes of the stego image. Recovery process includes the X-ORing of low level bit planes and mid level bit planes of the stego image. Based on the result of the recovery, subsequent data image is generated. A RGB color image is used as carrier and the data image is a grayscale image of dimensions less than or equal to the dimensions of the carrier image. The proposed method greatly increases the embedding capacity without significantly decreasing the PSNR value.
Mass spectra of bottom-charm baryons
Creators: name: Li, Zhen-Yu
name: Yu, Guo-Liang
name: Wang, Zhi-Gang
name: Gu, Jian-Zhong
name: Shen, Hong-Tao
Publisher: name: arXiv
Year: 2022
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: FOS: Physical sciences

description: In this paper, we investigate the mass spectra of bottom-charm baryons systematically, where the relativistic quark model and the infinitesimally shifted Gaussian basis function method are employed. Our calculation shows that the $ρ$-mode appears lower in energy than the other excited modes. According to this feature, the allowed quantum states are selected and a systematic study of the mass spectra for $Ξ_{bc}^{'}$ ($Ξ_{bc}$) and $Ω_{bc}^{'}$ ($Ω_{bc}$) families is performed. The root mean square radii and quark radial probability density distributions of these baryons are analyzed as well. Next, the Regge trajectories in the $(J,M^{2})$ plane are successfully constructed based on the mass spectra. At last, we present the structures of the mass spectra, and analyze the difficulty and opportunity in searching for the ground states of bottom-charm baryons in experiment.
description: 19 pages, 9 figures, 6 tables. arXiv admin note: text overlap with arXiv:2210.13085
БИЗНЕС-ТЕМАТИКА НА ТЕЛЕВИДЕНИИ ТАТАРСТАНА
Creators: name: К.Р. Каримова
Publisher: name: Мир науки, культуры, образования
Year: 2020
Subjects: деловые СМИ
деловые СМИ Татарстана
телевидение Татарстана
предпринимательство

description: В данной статье мы рассмотрим специфику освещения бизнес-тематики на телеканалах Татарстана, вещающих из Казани. Выбор предмета исследования обусловлен необходимостью научного осмысления телевизионных практик региона в работе с деловой тематикой на фоне высокого уровня телесмотрения в республике и незначительного уровня изученности данного явления. В регионе наблюдается высокий спрос на СМИ деловой направленности, что отражается в лидирующих позициях деловых интернет-СМИ в рейтингах цитируемости СМИ в регионе. Соответственно, деловые интернет-СМИ уделяют деловой повестке значительное внимание. В этой связи важно рассмотреть особенности освещения бизнес-тематики местными телеканалами, уступающими по уровню цитируемости интернет-изданиям.
Multidimensional analysis using sensor arrays with deep learning for high-precision and high-accuracy diagnosis
Creators: name: Payette, Julie
name: Cloutier, Sylvain G.
name: Vaussenat, Fabrice
Publisher: name: arXiv
Year: 2022
Subjects: subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: In the upcoming years, artificial intelligence (AI) is going to transform the practice of medicine in most of its specialties. Deep learning can help achieve better and earlier problem detection, while reducing errors on diagnosis. By feeding a deep neural network (DNN) with the data from a low-cost and low-accuracy sensor array, we demonstrate that it becomes possible to significantly improve the measurements' precision and accuracy. The data collection is done with an array composed of 32 temperature sensors, including 16 analog and 16 digital sensors. All sensors have accuracies between 0.5-2.0$^\circ$C. 800 vectors are extracted, covering a range from to 30 to 45$^\circ$C. In order to improve the temperature readings, we use machine learning to perform a linear regression analysis through a DNN. In an attempt to minimize the model's complexity in order to eventually run inferences locally, the network with the best results involves only three layers using the hyperbolic tangent activation function and the Adam Stochastic Gradient Descent (SGD) optimizer. The model is trained with a randomly-selected dataset using 640 vectors (80% of the data) and tested with 160 vectors (20%). Using the mean squared error as a loss function between the data and the model's prediction, we achieve a loss of only 1.47x10$^{-4}$ on the training set and 1.22x10$^{-4}$ on the test set. As such, we believe this appealing approach offers a new pathway towards significantly better datasets using readily-available ultra low-cost sensors.
description: Corrected typo