A supervised hierarchical segmentation of remote-sensing images using a committee of multi-scale convolutional neural networks

This paper presents a supervised, hierarchical remote-sensing image segmentation technique using a committee of multi-scale convolutional neural networks. With existing techniques, segmentation is achieved through fine-tuning a set of predefined feature detectors. However, such a solution is not robust since the introduction of new sensors or applications would require novel features and techniques to be developed. Conversely, the proposed method achieves segmentation through a set of learnt feature detectors. In order to learn feature detectors, the proposed method exploits a committee of convolutional neural networks that perform multi-scale analysis on each band in order to derive individual confidence maps on region boundaries. Confidence maps are then inter-fused in order to produce a fused confidence map. Furthermore, the fused map is intra-fused using a morphological scheme into a hierarchical segmentation map. The proposed method is quantitatively compared to baseline techniques on a publicly available data set. The results presented in this paper highlight the improved accuracy of the proposed method.     

Tunable Volatility of Ge2Sb2Te5 in Integrated Photonics

The operation of a single class of optical materials in both a volatile and nonvolatile manner is becoming increasingly important in many applications. This is particularly true in the newly emerging field of photonic neuromorphic computing, where it is desirable to have both volatile (short‐term transient) and nonvolatile (long‐term static) memory operation, for instance, to mimic the behavior of biological neurons and synapses. The search for such materials thus far have focused on phase change materials where typically two different types are required for the two different operational regimes. In this paper, a tunable volatile/nonvolatile response is demonstrated in a photonic phase‐change memory cell based on the commonly employed nonvolatile material Ge₂Sb₂Te₅ (GST). A time‐dependent, multiphysics simulation framework is developed to corroborate the experimental results, allowing us to spatially resolve the recrystallization dynamics within the memory cell. It is then demonstrated that this unique approach to photonic memory enables both data storage with tunable volatility and detection of coincident events between two pulse trains on an integrated chip. Finally, improved efficiency and all‐optical routing with controlled volatility are demonstrated in a ring resonator. These crucial results show that volatility is intrinsically tunable in normally nonvolatile GST which can be used in both regimes interchangeably.     

A wideband polarization reconfigurable isosceles trapezoidal monopole antenna

In this article, a polarization reconfigurable isosceles trapezoidal monopole antenna for the circular polarization (CP) is presented. A trapezoidal monopole and the ground plane are on the same side of the dielectric substrate. The monopole is excited by a reconfigurable T‐shaped 50 Ω microstrip feed line and reconfigurable vertical slots are incorporated in the ground plane to realize switchable wideband CP. For the different switching states of the p‐i‐n diodes, linear polarization, left‐handed and right handed CP can be achieved in the boresight direction (+z direction). The antenna prototype is fabricated and tested. The measured reflection coefficient bandwidth (|S11| < ?10 dB) is 31.2% (2.13 ‐ 2.91 GHz) and axial ratio bandwidth (axial ratio < 3 dB) is 22% (2.18 ‐ 2.72 GHz) for the CP. The measured reflection coefficient bandwidth is 18.56% (2.15 ‐ 2.59 GHz) for linear polarization.     

Golden angle‐inspired design of massive MIMO tapered slot array with less correlation for 5G lower band applications

In this article, for the first time, we come up with a nature‐inspired MIMO antenna configuration that could provide less correlated wireless channels for 5G lower band (3000‐4200 MHz). Essentially, the cross‐correlation among the antenna elements is reduced by incorporating the concept of golden angle into a cylindrical configuration of tapered slot antenna array. The golden angle helps in arranging the end‐fire radiating tapered slot antennas (TSAs) in such a way that there will not be any spatial overlap among the radiation fields of the individual antenna elements. The idea is validated with 24 TSA elements placed in a cylindrical fashion. The envelope correlation coefficient (ECC) is calculated from the simulations in ANSYS HFSS and verified with measurements. The ECC value is found to be less than 0.01 in the range of 3 GHz to 4.25 GHz. The impedance matching and mutual coupling between the elements are found to be very good in the above‐mentioned frequency range from the simulations and measurements. It is believed that the application of golden angle concept to MIMO antennas would open up the windows for implementation of dense massive MIMO.     

Exploring Traffic Dynamics in Urban Environments Using Vector‐Valued Functions

The traffic infrastructure greatly impacts the quality of life in urban environments. To optimize this infrastructure, engineers and decision makers need to explore traffic data. In doing so, they face two important challenges: the sparseness of speed sensors that cover only a limited number of road segments, and the complexity of traffic patterns they need to analyze. In this paper we take a first step at addressing these challenges. We use New York City (NYC) taxi trips as sensors to capture traffic information. While taxis provide substantial coverage of the city, the data captured about taxi trips contain neither the location of taxis at frequent intervals nor their routes. We propose an efficient traffic model to derive speed and direction information from these data, and show that it provides reliable estimates. Using these estimates, we define a time‐varying vector‐valued function on a directed graph representing the road network, and adapt techniques used for vector fields to visualize the traffic dynamics. We demonstrate the utility of our technique in several case studies that reveal interesting mobility patterns in NYC's traffic. These patterns were validated by experts from NYC's Department of Transportation and the NYC Taxi & Limousine Commission, who also provided interesting insights into these results.     

Turbulence structure and bank erosion process in a dredged channel

Riverbank erosion has significant geomorphological as well as anthropogenic consequences. The geomorphological impacts include form changes such as lateral channel migration, meanders, channel expansion, etc. The anthropogenic effects include the threat to floodplain human habitation, agricultural land, and stability of instream hydraulic structures and buried pipelines. Channel dredging for the extraction of sand and gravel has seen a multi-fold rise in the last few decades. Therefore, riverbank erosion response to channel mining gains importance in river basin management. Sandpits dredged in the riverbeds can significantly impact the downstream riverbank stability. In order to assess these impacts, we conducted a series of experiments at a laboratory scale in a recirculating water flume. Three riverbank slopes, 25° (gentle), 31° (equal to the angle of repose of the bank sediments), and 40° (steeper than the angle of repose), were tested along with a sandpit. Remarkable changes in the turbulence structure of riverbank flow were found due to the channel pit. Pit excavation directly impacts the fluvial erosion characteristics of the riverbank. Pit action increases the Reynolds shear stress fields in the near-bank flow, which causes progressive fluvial erosion of the berm at the bank toe. The erosivity of the main channel flow in the riverbank also leads to channel degradation, which increases the exposed height of the bank slope. Pit dredging leads to the generation of stronger ejection bursts which provide a mechanism for berm sediment mobility and erosion. The hydro morphological response of the riverbank due to sand mining was analysed, and process understandings are presented in the paper.     

A rigorous targeting algorithm for resource allocation networks

Techniques of process integration can be applied to conserve resources such as energy, freshwater, cooling water, hydrogen, solvent, etc. Process integration methodologies are broadly classified into two categories: methodologies based on the mathematical optimization techniques and methodologies based on the conceptual approaches of pinch analysis. In this paper, a mathematically rigorous methodology is proposed to minimize the requirement of a natural resource in a chemical process industry. The proposed methodology combines the simplicity of the pinch analysis with the mathematical rigor of mathematical optimization techniques. Conservation of resource in a chemical process industry is posed as a network flow optimization problem and a simple algebraic methodology is proposed to solve the optimization problem. The proposed algebraic methodology is mathematically proved in this paper. The proposed algorithm is numerically faster than the general mathematical optimization methods used for solving optimal resource allocation problems.     

Device‐Level Photonic Memories and Logic Applications Using Phase‐Change Materials

Inspired by the great success of fiber optics in ultrafast data transmission, photonic computing is being extensively studied as an alternative to replace or hybridize electronic computers, which are reaching speed and bandwidth limitations. Mimicking and implementing basic computing elements on photonic devices is a first and essential step toward all‐optical computers. Here, an optical pulse‐width modulation (PWM) switching of phase‐change materials on an integrated waveguide is developed, which allows practical implementation of photonic memories and logic devices. It is established that PWM with low peak power is very effective for recrystallization of phase‐change materials, in terms of both energy efficiency and process control. Using this understanding, multilevel photonic memories with complete random accessibility are then implemented. Finally, programmable optical logic devices are demonstrated conceptually and experimentally, with logic “OR” and “NAND” achieved on just a single integrated photonic phase‐change cell. This study provides a practical and elegant technique to optically program photonic phase‐change devices for computing applications.     

Localization of region of interest in surveillance scene

Multimedia Tools and Applications - In this paper, we present a method for autonomously detecting and extracting region(s)-of-interest (ROI) from surveillance videos using trajectory-based...