Hydrological studies in the north-eastern part of the Barents Sea in 2019 and 2020

The article presents the results of hydrological studies of the north-eastern part of the Barents Sea. The observations were made in the oceanographic expeditions R/W “Dalnie Zelentsy” of the MMBI RAS in October–November 2019 and 2020. The analysis of a series of hydrological sections is carried out, which details the vision of the structure of the waters and currents of the studied area. In the water structure, two streams of Atlantic waters are distinguished. The flows are directed opposite to each other and are located in different deep layers. The Atlantic stream emerging from the Barents Sea is identified as a branch of the warm New Earth current. At the beginning of the winter,the current spreads in a layer from the surface to 50–75 m. The Atlantic waters flowing into the Barents Sea are identified as a branch of the deep current of the St. Anna trench. They come from the Polar Basin and pass into the sea from east to west up to 62–60o E.

Extracting Related Images from E-commerce Utilizing Supervised Learning

In this article for the sequence to catch the concept of ocular affinity, we suggest a deep convolutional neural network to know the embedding of images. We show the deep architecture of Siamese that learns embedding which correctly resembles objects' classification in visual similarity while trained on positive and negative picture combinations. We often introduce a novel system of loss calculation employing angular loss metrics based on the problem's requirements. The combined description of the low or top-level embeddings was its final embedding of the image. We also used the fractional distance matrix to calculate the distance in the n-dimensional space between the studied embeddings. Finally, we compare our architecture with many other deep current architectures and continue to prove our approach's superiority in terms of image recovery by image recovery. Architecture research on four datasets. We often illustrate how our proposed network is stronger than other conventional deep CNNs used by learning optimal embedding to capture fine-grained picture comparisons.

Flow of Antarctic Bottom Water from the Vema Channel

We analyze measurements of bottom currents and thermohaline properties of water north of the Vema Channel with the goal to find pathway continuations of the Antarctic Bottom Water flow from the Vema Channel into the Brazil Basin. The analysis is based on the CTD/LADCP casts north of the Vema Channel. The flow in the deep-water Vema Channel consists of two branches. The deep current flows along the bottom of the channel and the other branch flows above the western wall of the channel. We found two smaller channels of the continuation of the bottom flow. These flows become weak and cease at a latitude of 26°S. The upper current that flows at a depth of 4100-4200 m along the continental slope is balanced by the gravity and Coriolis forces. We traced this current up to 24°S over a distance exceeding 250 km. This branch transports bottom water that eventually fills the deep basins of the North Atlantic.

The energy spectrum of the current velocity in deep layers of the Black Sea

In 2016-2017, for the first time, nearly year-long measurements of the current velocities were carried out below the thermocline at a depth of 100 m and at a depth of 1700 m that was about 100 m above the seabed by using the mooring station in the deep central part of the Black Sea. Analysis of the new data set allowed us to uncover the followings. In the near-bottom layer, the significant flow velocities were recorded, reaching a peak magnitude of 0.13 m/s. Near the frequency of 110-6 Hz, in the transition region of the energy spectrum, the spectral energy of the deep current was close to that observed in the same range in the subthermocline layer of the sea. In the range of balanced geostrophic motions, the energy spectrum had a slope of -2,8 that should be compared to a spectrum slope of -1,8 obtained for current below the thermocline. The regular strong horizontal currents were observed near the local inertial frequency fI. There was a blue shift of the inertial maximum up to 5% with respect to fI in the energy spectrum.

Recurrent neural networks with controlled elements in restoring frame flows

Introduction: Various interfering influences raise pressing problems of promptly restoring the flow of distorted frames,remembering about the background and dynamics of the event measurement laws. The traditional methods of recovering flows ofdistorted frames do not fully take into account the peculiarities of this process. Purpose: Exploring the possibilities of recurrent neuralnetworks with controlled elements for restoring frame flows. Results: It is proposed to evaluate the potential of a recurrent neuralnetwork with controlled elements by the number of successful options for restoring a distorted sequence of frames. Evaluation of thecapabilities of such neural networks according to the introduced indicator showed their strong dependence on the type of networkstructure and settings. Recurrent neural networks with spiral structures of layers work better. As the number of the turns in the helixgrows, the network capabilities also grow. Enhancing the capacity of a network to restore distorted frame flows is feasible if we replaceunipolar functions of the synapse weights by bipolar ones. A significant increase in the capabilities of the neural networks under studyis possible by controlling the neuron excitation thresholds in order to provide sequential rather than parallel elimination of variouserrors. In contrast to the conventional neural networks, recurrent neural networks with controlled elements can adapt to changes in№ 5, 2019 ИНФОРМАЦИОННОУПРАВЛЯЮЩИЕ СИСТЕМЫ 17ОБРАБОТКА ИНФОРМАЦИИ И УПРАВЛЕНИЕthe laws inherent in frame flows, and implement controlled associative signal processing. Experiments have shown that these neuralnetworks can use associative connections for taking into account deep current experience in signal processing, and be successfully usedfor restoring distorted frame flows.

Trump’s National Security Strategy: “America First” meets the establishment

Donald Trump’s 2017 National Security Strategy (NSS) promises to put “America first.” However, it is only a partial break from convention, and evinces a deep current of incoherence in Trump’s foreign policy. The NSS attempts to combine two incompatible worldviews into a single doctrine: the president’s “America First” nationalism and the seventy-year-old internationalist consensus among the US foreign policy establishment. Not only does it betray strategic dissonance, it portends an impossible working relationship between Trump’s insurgent nationalism and the traditionalism of the US foreign policy bureaucracy.

Development of a High-Performance 3,300V Silicon Carbide MOSFET

To address stringent performance and reliability requirements of industrial and traction power conversion systems we have developed planar 3,300V MOSFETs at a 6-inch SiC-compatible silicon CMOS foundry. By optimizing the unit cell structure and using a deep current-spreading layer we demonstrated a low MOSFET specific on-resistance RDSA=11.2 mΩ·cm2(ID=5A, VGS=15V) and fast switching for the baseline design. Robust short-circuit handling (7.5μs at Vds=1500V and 5.0μs at Vds=2200V) was demonstrated with an alternative unit cell design with RDSA=14.8 mΩ·cm2(ID=5A, VGS=15V).