Correction to: Comparative analysis of limit equilibrium and numerical methods for prediction of a landslide

Bulletin of Engineering Geology and the Environment - Landslides that occur due to the rapid motion of a rock-mass are a primary risk in mountainous terrains and are a danger to human life and...     

Experimental investigation of tool wear and machining rate in rotary ultrasonic machining of nickel alloy

Nickel alloys possess the excellent potential at high temperature and resistance to oxidation/corrosion owing to its high nickel content. These materials necessitate non-traditional machining methods. The rotary ultrasonic machining (RUM) process comes into existence as a superior alternative to the conventional machining of nickel alloys. The processing of these alloys using RUM needs attention. This article details the multi-response optimization in RUM of nickel alloy using the desirability concept. The present work is carried out with two shapes of the tool: (i) Plain tool and (ii) lateral slotted tool. During RUM, the process parameters—power rating tool rotation, abrasive diamond grit size and feed rate are varied. Compared with the plain tool, the lateral slotted tool shows the more efficient machining rate (MR) with less tool wear (TW). The micro-graphs disclose the mechanism of MR and TW during RUM.     

Case study of safe lowering of an in service gas pipeline

This paper describes an experimental investigation carried out involving instrumentation, measurement and monitoring of stresses in a large diameter gas pipeline during its lowering operations. It also highlights the ingenious techniques developed and adopted to overcome the difficulties pertaining to long leadwires, measurement of existing strains on the curved surface of a pipeline and protection of strain gauge installations. These novel methods were used to ensure smooth and proper functioning of strain gauge instrumentation even under the severe field conditions at site for more than two weeks, till the lowering operations and pipeline monitoring was successfully completed.     

Software‐defined network‐enabled opportunistic offloading and charging scheme in multi‐unmanned aerial vehicle ecosystem

Unmanned aerial vehicles (UAVs) are autonomous fliers, which can play different roles in modern day applications. In one of the important role, UAVs can act as aerial data forwarding nodes for communication range enhancement in remote areas. UAVs form a web of drones, which can be geo‐distributed across a large area to serve various applications. However, the two major contradicting challenges with respect to multi‐UAV networks are channel congestion and flight time enhancement. The use of effective data transmission techniques to handle congestion can lead to higher battery dissipation, which in turn end up in the reduction in flight time. However, it is utmost necessity to provide an effective framework, which can provide a viable solution for handling congestion in multi‐UAV networks while enhancing the flight time of UAVs. To handle these issues, software‐defined network (SDN)–enabled opportunistic offloading and charging scheme (SOOCS) in multi‐UAV ecosystem is designed in this paper. In this scheme, an opportunistic offloading scheme is proposed, which uses an SDN‐based control model to handle congestion issues. Apart from this, an opportunistic energy‐charging scheme is designed, wherein the UAVS can either replenish their batteries using solar plates or they can wirelessly charge energy from charging points deployed at various geo‐distributed locations. The proposed scheme is evaluated using a simulation‐based study over the realistic deployment of charging points in Chandigarh City, India. The results obtained show the superiority of SOOCS over other variants of its category in terms of end‐to‐end delay, throughput, and hand‐over latency.     

Curvelet Transform Based on Edge Preserving Filter for Retinal Blood Vessel Segmentation

Segmentation of vessel in retinal fundus images is a primary step for the clinical identification for specific eye diseases. Effective diagnosis of vascular pathologies from angiographic images is thus a vital aspect and generally depends on segmentation of vascular structure. Although various approaches for retinal vessel segmentation are extensively utilized, however, the responses are lower at vessel's edges. The curvelet transform signifies edges better than wavelets, and hence convenient for multiscale edge enhancement. The bilateral filter is a nonlinear filter that is capable of providing effective smoothing while preserving strong edges. Fast bilateral filter is an advanced version of bilateral filter that regulates the contrast while preserving the edges. Therefore, in this paper a fusion algorithm is recommended by fusing fast bilateral filter that can effectively preserve the edge details and curvelet transform that has better capability to detect the edge direction feature and better investigation and tracking of significant characteristics of the image. Afterwards C mean thresholding is used for the extraction of vessel. The recommended fusion approach is assessed on DRIVE dataset. Experimental results illustrate that the fusion algorithm preserved the advantages of the both and provides better result. The results demonstrate that the recommended method outperforms the traditional approaches.     

Hyperspectral imaging of nanoparticles in biological samples: Simultaneous visualization and elemental identification

While engineered nanomaterials (ENMs) are increasingly incorporated into industrial processes and consumer products, the potential biological effects and health outcomes of exposure remain unknown. Novel advanced direct visualization techniques that require less time, cost, and resource investment than electron microscopy (EM) are needed for identifying and locating ENMs in biological samples. Hyperspectral imaging (HSI) combines spectrophotometry and imaging, using advanced optics and algorithms to capture a spectrum from 400 to 1000 nm at each pixel in an enhanced dark‐field microscopic (EDFM) image. HSI‐EDFM can be used to confirm the identity of the materials of interest in a sample and generate an image “mapping” their presence and location in a sample. Hyperspectral mapping is particularly important for biological samples, where ENM morphology is visually indistinct from surrounding tissue structures. While use of HSI (without mapping) is increasing, no studies to date have compared results from hyperspectral mapping with conventional methods. Thus, the objective of this study was to utilize EDFM‐HSI to locate, identify, and map metal oxide ENMs in ex vivo histological porcine skin tissues, a toxicological model of cutaneous exposure, and compare findings with those of Raman spectroscopy (RS), energy‐dispersive X‐ray spectroscopy (EDS), and scanning electron microscopy (SEM). Results demonstrate that EDFM‐HSI mapping is capable of locating and identifying ENMs in tissue, as confirmed by conventional methods. This study serves as initial confirmation of EDFM‐HSI mapping as a novel and higher throughput technique for ENM identification in biological samples, and serves as the basis for further protocol development utilizing EDFM‐HSI for semiquantitation of ENMs. Microsc. Res. Tech. 79:349–358, 2016. © 2016 Wiley Periodicals, Inc.