A survey of sensory data boundary estimation,covering and tracking techniques using collaborating sensors

Boundary estimation and tracking have important applications in the areas of environmental monitoring and disaster management. A boundary separates two regions of interest in a phenomenon. It can be visualized as an edge if there is a sharp change in the field value between the two regions or alternatively, as a contour with a field value $f=\tau$ separating two regions with field values $f>\tau$ and $f<\tau$. Examples include contours/boundaries of hazardous concentration in a pollutant spill, frontal boundary of a forest fire, isotherms, isohalines etc. Recent advances in the area of embedded sensor devices and robotics have led to deployments of networks of sensors capable of sensing, computing, communication and mobility. They are used to estimate the boundaries of interest in physical phenomena, monitor or track them over time and also in some cases, mitigate the spatial spread of the phenomena. Since these sensors work autonomously in the environment, minimizing the energy consumed while maximizing the accuracy of estimation or tracking is the main challenge for algorithms for boundary estimation and tracking. Several algorithms with these objectives have been proposed in the literature. In this work, we focus on the algorithms that estimate and cover boundaries found in the sensory data in a field and not the topological boundary of the sensor network per se, which is beyond the scope of this paper.Here, our objective is to provide a comprehensive survey of the algorithms for boundary estimation and tracking by providing a taxonomy based on two broad categories — (i) Boundary estimation and tracking, where the sensors estimate the boundary without physically covering the boundary and (ii) Boundary covering — where the sensors not only predict the location and estimate the entire boundary but also physically cover the boundary by surrounding and bounding it. We further classify the techniques based on (a) sensing capabilities —in situ, range or remote sensing (b) movement capabilities — static or mobile sensors and (c) boundary type — static or dynamic and (d) type of estimation — field estimation where the entire field is sampled to search for contours and localized estimation where sampling is done near the boundary and (e) different types of mobility models in the case of mobile sensors. We believe that such a survey has not been performed before. By capturing and classifying the current state-of-the-art and identifying open research problems, we hope to ignite interest and stimulate efforts towards promising solutions for real-world boundary estimation and tracking problems.     

Exergy analysis of a coal‐based 210 MW thermal power plant

In the present work, exergy analysis of a coal‐based thermal power plant is done using the design data from a 210 MW thermal power plant under operation in India. The entire plant cycle is split up into three zones for the analysis: (1) only the turbo‐generator with its inlets and outlets, (2) turbo‐generator, condenser, feed pumps and the regenerative heaters, (3) the entire cycle with boiler, turbo‐generator, condenser, feed pumps, regenerative heaters and the plant auxiliaries. It helps to find out the contributions of different parts of the plant towards exergy destruction. The exergy efficiency is calculated using the operating data from the plant at different conditions, viz. at different loads, different condenser pressures, with and without regenerative heaters and with different settings of the turbine governing. The load variation is studied with the data at 100, 75, 60 and 40% of full load. Effects of two different condenser pressures, i.e. 76 and 89 mmHg (abs.), are studied. Effect of regeneration on exergy efficiency is studied by successively removing the high pressure regenerative heaters out of operation. The turbine governing system has been kept at constant pressure and sliding pressure modes to study their effects. It is observed that the major source of irreversibility in the power cycle is the boiler, which contributes to an exergy destruction of the order of 60%. Part load operation increases the irreversibilities in the cycle and the effect is more pronounced with the reduction of the load. Increase in the condenser back pressure decreases the exergy efficiency. Successive withdrawal of the high pressure heaters show a gradual increment in the exergy efficiency for the control volume excluding the boiler, while a decrease in exergy efficiency when the whole plant including the boiler is considered. Keeping the main steam pressure before the turbine control valves in sliding mode improves the exergy efficiencies in case of part load operation. Copyright © 2006 John Wiley & Sons, Ltd.     

Application of associative memories in designing assemblers

A method for implementing the assembler of a system by hardware is described. The implementation is based on using the associative memories for storing various tables that are maintained by the assembler during different phases of assembling. The assembling is done in two passes. This hardware implementation results in less assembling time and main storage requirements than its software counterpart. Also the method offers a good amount of design flexibility to fit into different systems.     

Effect of Co Doping in Tuning the Band Gap of LaFeO3

Abstract

Herein, we reported the effect of cobalt (Co) doping on the optical band gap of LaFeO₃ (LFO). The Co doped nanoparticles were prepared by a simple sol-gel technique with composition LaFe_1–xCo_xO₃by varying content ratio of x?=?0, 0.4, 0.5 and 0.6. Structure of the LFO and Co doped LFO nanoparticles have been investigated by X-ray diffraction (XRD) pattern. Whereas, surface morphology of LFO and Co doped LFO has been ascertained by scanning electron microscopy (SEM). The observed optical properties investigated by UV-Vis spectroscopy suggest decrease in band gap with Co doping in LFO, which can be useful for optoelectronic applications.     

Light-emitting porous silicon: materials science, properties, anddevice applications

Silicon-based, light-emitting devices (LED's) should find numerous uses in optoelectronics. For example, the integration of silicon LED's with silicon microelectronics could lead to reliable and inexpensive optical displays and optical interconnects. Until recently, however, it had not been possible to obtain efficient room-temperature luminescence from silicon. The demonstration in 1990 that a form of silicon called “porous” can emit bright photoluminescence in the red region of the spectrum triggered worldwide research efforts aimed at establishing the mechanisms for the unexpected luminescence and at fabricating efficient and durable LED's. In less than five years, significant progress has been achieved on both fronts, LED's emitting throughout the visible spectrum have been demonstrated, and the best measured external electroluminescence efficiency has risen from 10^-5% to ~0.01% at room temperature. The photoluminescence efficiency of the best samples is near 10% at room temperature, and light-emitting porous silicon (LEPSi) that luminesces from the blue part of the spectrum to the infrared beyond 1.5 μm has been produced. In this article, we first review why silicon is a poor light emitter and then define porous silicon and its main properties. We then focus on the properties of the three luminescence bands (“red,” “blue,” and “infrared”) and present the results of femtosecond time-resolved optical measurements. Next, we report progress toward the fabrication of LED's and discuss some specific device structures. Finally, we outline what is necessary for commercial LEPSi LED's to become a reality and report on experimental results that suggest the possible integration of LEPSI with standard microelectronic devices     

A low‐cost high‐gain dual polarized antenna design from cuboids and shorting strips for base stations

This article presents a novel low‐cost high‐gain dual‐polarized antenna using suspended cuboid and ground connected cuboid geometry. The design structure of the antenna is simple and it's all components are fabricated by a copper sheet of thickness 0.5 mm. The prototype is fabricated and measured and has ?15 dB impedance bandwidths of 33.33%(2.5‐3.5 GHz) with broadside gain of 9.2 ± 0.3 dBi and 32.25%(2.6‐3.6 GHz) with broadside gain 9 ± 0.3 dBi over bandwidths when measured from port 1 and port 2, respectively. The isolation between the ports is enhanced by shorting suspended cuboid from the ground plane and measured one more than 17 dB from 2.45 to 3.7 GHz. The proposed dual polarized antenna can be used for base stations such as Wireless Local Area Network (WLAN), Long Term Evolution (LTE), and Worldwide Interoperability for Microwave Access (WiMAX) applications. The antenna is designed and simulated and there are good agreements between simulated and measured results are obtained.     

Sediment distribution and its impacts on Hirakud Reservoir (India) storage capacity

Construction of dams causes reduced flow velocities, inducing gradual deposition of sediments carried by the inflowing stream, and resulting in sedimentation and ultimately diminishing reservoir storage capacity. This study focuses on sedimentation of Hirakud Reservoir in Odisha, India, using available reservoir capacity and numerical simulation data. Reduced trap efficiency, observed and projected capacity curves, rising reservoir bed level and the capacities of the different storage zones for various projected years are analysed. The area‐reduction method indicates the loss in the live, gross and dead storage will be 58%, 63% and 100%, respectively, of their original capacities by 2057, which represents 100 years of impounding of water in the reservoir. If the present sediment inflow rate continues without regular flushing of the deposited sediment, it is predicted the reservoir bed level will rise to the full reservoir level of 192.02 m by the year 2110. Brune's trap efficiency and step method indicate the gross storage zone of Hirakud Reservoir will be completely depleted by the end of 2110, with the trap efficiency reduced to zero. The empirical area‐reduction method is found to be more suitable for determining the storage capacities of Hirakud Reservoir in the absence of sedimentation survey data. An attempt was also made to solve the combined hydrodynamic and sediment transport equations numerically to predict morphological changes in Hirakud Reservoir. The finite‐element code TELEMAC‐2D and finite‐volume code for SISYPHE, respectively, were applied to solve the above set of equations in order to predict the bed profiles at different reservoir cross sections for the period of 1958–2008. Analysis of the simulated results demonstrates that, considering the model inputs, the model performs well in simulating the morphology and dynamic characteristics of a reservoir. Projection of the numerical results indicates a complete loss of reservoir operational life due to sedimentation by around 2150.     

SDN/NFV security framework for fog-to-things computing infrastructure

Currently, core networking architectures are facing disruptive developments, due to emergence of paradigms such as Software-Defined-Networking (SDN) for control, Network Function Virtualization (NFV) for services, and so on. These are the key enabling technologies for future applications in 5G and locality-based Internet of things (IoT)/wireless sensor network services. The proliferation of IoT devices at the Edge networks is driving the growth of all-connected world of Internet traffic. In the Cloud-to-Things continuum, processing of information and data at the Edge mandates development of security best practices to arise within a fog computing environment. Service providers are transforming their business using NFV-based services and SDN-enabled networks. The SDN paradigm offers an easily programmable model, global view, and control for modern networks, which demand faster response to security incidents and dynamically enforce countermeasures to intrusions and cyberattacks. This article proposes an autonomic multilayer security framework called Distributed Threat Analytics and Response System (DTARS) for a converged architecture of Fog/Edge computing and SDN infrastructures, for emerging applications in IoT and 5G networks. The major detection scheme is deployed within the data plane, consisting of a coarse-grained behavioral, anti-spoofing, flow monitoring and fine-grained traffic multi-feature entropy-based algorithms. We developed exemplary defense applications under DTARS framework, on a malware testbed imitating the real-life DDoS/botnets such as Mirai. The experiments and analysis show that DTARS is capable of detecting attacks in real-time with accuracy more than 95% under attack intensities up to 50 000 packets/s. The benign traffic forwarding rate remains unaffected with DTARS, while it drops down to 65% with traditional NIDS for advanced DDoS attacks. Further, DTARS achieves this performance without incurring additional latency due to data plane overhead.