Evaluation methods basis of strategy development effectiveness of the enterprise

The urgency to study the problem is caused by the necessity to make management decisions in terms of reducing goods life cycle, reducing profitability of production, increasing speed of technological progress. In this context, this article aims to identify and elaborate the tools for integrated diagnostic of strategy efficiency, taking into account the relationship of parameters which characterize various spheres of enterprise activity, and to formulate integral indicator of strategic effectiveness, which can be accepted as the criterion for evaluating the effectiveness of strategic development. The leading approach to the study of this problem was the systems approach, used in the development of methods for efficiency evaluation of strategic development, it allows to identify priority factors of the strategic development of the company. The article substantiates the use of value approach to management as a methodical bases of diagnostics of the effectiveness of the strategic development of the industrial enterprises; the matrix tool was developed, supplementing the information-analytical foundation of management. The results of the research work may be useful for effectiveness evaluation of the strategic development of industrial enterprise and for identifying priority strategic development factors and making recommendations to improve the value of business. © 2016 Zotova et al

Hyperspectral images neural network analysis of unstained micropreparations

The article presents the results of a study of hyperspectral imaging in microscopy to assess pathological changes in unstained medical micropreparations.Hyperspectral imaging was carried out using a system of synchronous shooting and movement of a movable table combined with a stepper motor. To improve the quality of theobtained images, software correction of the illumination of the spectral channels was used. The classification was carried out by a convolutional neural network. This method may be promising for assessing pathological changes in clinical practice. Experimental studies were carried out on histological preparations with different types of tissues without staining with contrasting medical dyes. To assess the reliability of the classification method, a comparison was made with thestandard method using staining of the studied samples

Neural network analysis of hyperspectral images of soil

The article approaches to the classification of high-resolution hyperspectral images in the problem of classification of soil species is proposed. A spectral-spatial convolutional neural network with compensation for lighting variations is used as a classifier. The effectiveness of the proposed approach in the problem of classification of hyperspectral images of soils obtained by a scanning hyperspectral camera is shown. The essence of the developed method is to use binary classification together with multiclass, thereby improving the result of the latter

Narrow-jet plasma technology – the way to new standards on welding production

Показана возможность изменения отраслевых стандартов на производство сварных соединений, так как качество сварных швов, полученных после плазменной резки по технологии узкоструйной плазмы без удаления зон термического влияния не уступает показателям, достигаемым после механической разделки.The possibility of changing the industry standards for the production of welded joints is shown, since the quality of welds obtained after plasma cutting using the technology of narrow-jet plasma without removing the zones of thermal influence is not inferior to the indicators achieved after mechanical cutting

Three-Dimensional Endoscopy-Assisted Excision and Reconstruction for Metastatic Disease of the Dorsal and Lumbar Spine: Early Results

BACKGROUND: The aim of this study was to explore the role of three-dimensional (3D) endoscopy in surgical management of metastatic disease of the dorsal and lumbar spine. METHODS: This is a prospective study on 33 patients (15 men and 18 women, mean age of 61.6 ± 8.9 years) with biopsy-proven metastatic disease of the spine managed by sequential/staged posterior decompression-stabilization, followed by 3D endoscopy-assisted anterior corpectomy and stabilization with a mesh cage. All patients had significant extradural compression or spinal instability or both. Sixteen patients had neurological deficits. Visual analog scale (VAS), Frenkel grade (neurological deficits), Karnofsky performance status scale, and the 36-item short-form health survey (SF-36) were used for assessment preoperatively and at 3, 6, and 12 months from surgery. RESULTS: At a mean follow-up of 1.7 ± 0.7 years from surgery, 18 patients were alive. VAS showed significant improvement at the latest follow-up compared to preoperative levels (4.39 vs. 6.61, p = 0.001). Karnofsky status did not show any significant improvement. Frenkel grade improved in 5 patients, deteriorated in 4 patients, and remained unchanged in 24 patients. Regarding SF-36 parameters, general health showed deterioration, but role functioning—physical, role functioning—emotional, social functioning, and body pain showed statistically significant improvement. There was no change in physical health, viability, and mental health. Subjectively the surgeons felt better depth perception and smoother surgical experience with the 3D optics technology. The only complication was delayed wound healing in three patients who had a previous history of radiotherapy to the surgical site. CONCLUSIONS: 3D endoscopy is a valuable tool in the management of metastatic spinal disease requiring excision and reconstruction using the combined posterior and anterior approaches. These early results warrant confirmation with more data and longer follow-ups

МОДЕЛИРОВАНИЕ ДЖОУЛЕВА НАГРЕВА В СРЕДЕ COMSOL MULTIPHYSICS

Using the example of thermal processes in a resistor, an algorithm for simulating the Joule heating in a COMSOL Multiphysics environment is shown. The choice of materials and the assignment of their properties for electronic products are considered. The process of creating two-dimensional models of temperature distribution in electronic components of medical electronics is shown.На примере тепловых процессов в резисторе показан алгоритм моделирования Джоулева нагрева в среде COMSOL Multiphysics. Рассмотрен выбор материалов и задание их свойств для изделий электронной техники. Показан процесс создания двухмерных моделей распределения температуры в электронных компонентах средств медицинской электроники

The Energetics of Li Off-Centering in K1−x_{1-x}Lix_xTaO3_3; First Principles Calculations

K$_{1-x}$Li$_{x}$TaO$_3$ (KLT) solid solutions exhibit a variety of interesting physical phenomena related to large displacements of Li-ions from ideal perovskite A-site positions. First-principles calculations for KLT supercells were used to investigate these phenomena. Lattice dynamics calculations for KLT exhibit a Li off-centering instability. The energetics of Li-displacements for isolated Li-ions and for Li-Li pairs up to 4th neighbors were calculated. Interactions between nearest neighbor Li-ions, in a Li-Li pair, strongly favor ferroelectric alignment along the pair axis. Such Li-Li pairs can be considered "seeds" for polar nanoclusters in KLT. Electrostriction, local oxygen relaxation, coupling to the KT soft-mode, and interactions with neighboring Li-ions all enhance the polarization from Li off-centering. Calculated hopping barriers for isolated Li-ions and for nearest neighbor Li-Li pairs are in good agreement with Arrhenius fits to experimental dielectric data.Comment: 14 pages including 10 figures. To Physical Review B. Replaced after corrections due to referees' remark

MultiMSOAR 2.0: An Accurate Tool to Identify Ortholog Groups among Multiple Genomes

The identification of orthologous genes shared by multiple genomes plays an important role in evolutionary studies and gene functional analyses. Based on a recently developed accurate tool, called MSOAR 2.0, for ortholog assignment between a pair of closely related genomes based on genome rearrangement, we present a new system MultiMSOAR 2.0, to identify ortholog groups among multiple genomes in this paper. In the system, we construct gene families for all the genomes using sequence similarity search and clustering, run MSOAR 2.0 for all pairs of genomes to obtain the pairwise orthology relationship, and partition each gene family into a set of disjoint sets of orthologous genes (called super ortholog groups or SOGs) such that each SOG contains at most one gene from each genome. For each such SOG, we label the leaves of the species tree using 1 or 0 to indicate if the SOG contains a gene from the corresponding species or not. The resulting tree is called a tree of ortholog groups (or TOGs). We then label the internal nodes of each TOG based on the parsimony principle and some biological constraints. Ortholog groups are finally identified from each fully labeled TOG. In comparison with a popular tool MultiParanoid on simulated data, MultiMSOAR 2.0 shows significantly higher prediction accuracy. It also outperforms MultiParanoid, the Roundup multi-ortholog repository and the Ensembl ortholog database in real data experiments using gene symbols as a validation tool. In addition to ortholog group identification, MultiMSOAR 2.0 also provides information about gene births, duplications and losses in evolution, which may be of independent biological interest. Our experiments on simulated data demonstrate that MultiMSOAR 2.0 is able to infer these evolutionary events much more accurately than a well-known software tool Notung. The software MultiMSOAR 2.0 is available to the public for free

Актуальные вопросы построения вихретоковой аппаратуры неразрушающего контроля

Светличный, В. А. Актуальные вопросы построения вихретоковой аппаратуры неразрушающего контроля / В. А. Светличный, А. А Ивлев, М. А. Чумаченко //Актуальні проблеми автоматики та приладобудування :матеріали Міжнарод. наук.-техн. конфер. (м. Харків, 06-07 груд. 2018 р.) / Є. І. Сокол (голова оргком.). – Харків : ФОП Панов А.М., 2018. – С. 141-142.Рассмотрены вопросы аппаратной разработки конструкции вихретоковых преобразователей для приборов определяющих параметры качества плоских, тонких покрытий или пленок. Показаны особенности создания таких устройств.The problems of hardware design of eddy-current transducers for devices determining the quality parameters of flat, thin coatings or films are considered. The features of creating such devices are shown.Розглянуто питання апаратної розробки конструкції вихорострумових перетворювачів для приладів, що визначають параметри якості плоских, тонких покриттів або плівок. Показано особливості створення таких пристроїв

Deep learning-based video stream reconstruction in mass-production diffractive optical systems

Возможность существенно снизить массу и стоимость систем технического зрения привела к появлению большого числа работ, посвященных разработке новых оптических схем на основе дифракционной оптики и новых подходов к реконструкции получаемых изображений. Получаемые системы демонстрируют достаточное для прикладных систем технического зрения качество изображений. Однако при создании таких прикладных систем возможны источники дополнительных потерь качества получаемого видеопотока. В настоящей работе исследовано влияние на итоговое качество реконструируемого видеопотока таких факторов, как ограничения технологии массового производства дифракционной оптики, артефактов сжатия видеопотока с потерями, а также особенностей нейросетевого подхода к реконструкции. Предложена сквозная нейросетевая технология реконструкции изображений, позволяющая компенсировать дополнительные факторы потери качества и получить итоговый видеопоток с качеством, достаточным для решения прикладных задач технического зрения. Many recent studies have focused on developing image reconstruction algorithms in optical systems based on flat optics. These studies demonstrate the feasibility of applying a combination of flat optics and the reconstruction algorithms in real vision systems. However, additional causes of quality loss have been encountered in the development of such systems. This study investigates the influence on the reconstructed image quality of such factors as limitations of mass production technology for diffractive optics, lossy video stream compression artifacts, and specificities of a neural network approach to image reconstruction. The paper offers an end-to-end deep learning-based image reconstruction framework to compensate for the additional factors of quality losing. It provides the image reconstruction quality sufficient for applied vision systems.Теоретическая часть работы и разработка нейросетевых моделей выполнена при поддержке гранта РНФ 20-69-47110, экспериментальная часть выполнена при поддержке грантов РФФИ № 18-07-01390-А, а также в рамках государственного задания ИСОИ РАН – филиала Федерального научно-исследовательского центра «Кристаллография и фотоника» РАН (соглашение № 007-ГЗ/Ч3363/26)