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Item Spatiotemporal Analysis(Springer Science and Business Media B.V., 2020) Bhattacharjee, S.; Madl, J.; Chen, J.; Kshirsagar, V.Several aspects of spatiotemporal analysis of trace gases have been discussed, including visualization, validation, and different spatiotemporal analysis methods, such as missing data handling, atmospheric transport modeling, inverse modeling, machine learning methods, etc. Each one of them explores the characteristics of atmospheric trace gases like CO2,CH4, NO2, etc., in different application domains and help to under-stand the global and local atmospheric processes worldwide. Satellite-borne trace gas data, combined with various ground-based monitoring networks, are the foundation that enables a broad spectrum of their spatiotemporal analysis. Different investigations around the globe have been mentioned here in order to show traditional methods for the spatiotemporal analysis of trace gases and investigate the recent extensions created with data fusion approaches in the future. Though the discussion is not exhaustive, it gives the initial pointers for further exploration. © Springer Nature Switzerland AG 2022.Item Spatiotemporal Modeling(Springer Science and Business Media B.V., 2020) Bhattacharjee, S.; Madl, J.; Chen, J.; Kshirsagar, V.Spatiotemporal dataset has three components in general, attributes, space, and time. Modeling approaches of spatiotemporal data have covered a broad spectrum of applications in many fields, including environmental applications, crime hotspot analysis, healthcare informatics, transportation modeling, social media, and many others. Clustering, predictive learning, frequent pattern mining, anomaly detection, change detection, and relationship mining are the few broad categories of the modeling approaches irrespective of the applications (Atluri et al. 2018). This chapter discusses some modeling approaches used for environmental applications in general. Further, one spatiotemporal modeling approach of outlier detection is chosen and presented here. Outlier detection within the application data is an essential preprocessing step for most of the spatiotemporal applications. Some important literature on spatiotemporal outlier detection methods is also discussed. Though the applications and methods presented here are not exhaustive, this chapter gives the initial pointers for further exploration of the spatiotemporal models. © Springer Nature Switzerland AG 2022.Item A Firefly Optimization Algorithm for Maximizing the Connectivity in Mobile Wireless Sensor Network(Springer, 2020) Mamatha, M.; Manjappa, K.For the effective functioning of a Mobile Wireless Sensor Networks (MWSN), the connectivity maintenance of the sensor nodes is of significant concern. Otherwise, it may result in an independent node or nodes wholly get detached from the network. Though such detached sensor nodes are functioning correctly and have good energy backup, its service cannot be utilized for the purpose it is intended for as it is isolated from the core network. These sensor nodes are sophisticated tiny devices and costlier depending on the application; therefore, proper care should be taken to keep them connected to the network. Hence, a firefly based algorithm, a Swarm Intelligence technique, referred to as Firefly Algorithm for Connectivity in Mobile WSN (FACM) has been proposed in this article in order to establish proper connectivity among the sensor nodes in MWSN. FACM is based on the insect fireflies, which have a unique feature of producing light, a result of chemical reaction, at different intervals to escape from the predators and most of the time to attract prey. The inevitable feature of insect firefly, attracting the prey, is exploited in the proposed FACM where a brighter sensor node (in terms of energy and distance) will attract the less bright neighboring sensor nodes. Thus, the less bright sensor node can depend on the brighter sensor node for the data transfer, thereby saving its energy. A fitness function has been designed based on the combination of two parameters energy and the distance, which decides the brightness of the sensor node. The effectiveness of the proposed FACM has been theoretically analyzed and verified by simulation through MATLAB. The results obtained are compared with classical FA and are found to be inspiring. © 2020, Springer Nature Switzerland AG.Item Surface Soil Moisture Retrieval Using C-Band Synthetic Aperture Radar (SAR) over Yanco Study Site, Australia—A Preliminary Study(Springer, 2020) Gururaj, G.; Umesh, U.; Shetty, A.The motto of this work is to evaluate retrieval of surface soil moisture (5 cm) using Sentinel-1a C-band data Synthetic Aperture Radar (SAR). Data for this study is collected from Yanco Study site, Australia. Yanco study site consists of 37 soil moisture measuring stations at every 20 min interval for various soil depths and it also provides other Hydro-Meteorological information. SAR backscattered energy is a function of soil roughness and soil moisture. Surface roughness is eliminated using change detection approach. The R2 performance statistics revealed that between Backscattered energy and NDVI there is no relation. Volumetric soil moisture and backscattered energy showed a positive correlation with R2 = 0.57 and 0.43 for VH and VV polarization. Dielectric constant also showed a positive correlation with backscattered energy having R2 = 0.62 and 0.38 for VH and VV polarization respectively. By taking into account of all these affecting parameters, a regional Semi-empirical model is developed to retrieve surface Soil moisture over the study area. © Springer Nature Singapore Pte Ltd. 2020.Item Women Empowerment Through Social Media: Insights from India(Springer, 2020) Pai, R.R.; Alathur, S.In recent times, social media has been used by people to participate in a particular event and has resulted in the generation of a large amount of data online. These data can be helpful for the decision-maker in promoting and devising necessary policies at the right time. The purpose of this paper is to understand the peoples’ sentiments and emotions about a recent social movement. Based on the result and analysis, the possible inferences have been presented. © Springer Nature Singapore Pte Ltd 2020.Item Cost-effective real-time aerial surveillance system using edge computing(Springer, 2020) Shahzad Alam, M.; Gupta, S.K.Nowadays there is an emerging need for surveillance in order to maintain the public places more secure and ensure the safety and security of the people. Many government agencies require some autonomous system for surveillance of the large areas which can give them precise and real-time information like number of vehicles, people, and other objects. An aerial surveillance system will be very effective in this scenario and platform like Unmanned Aerial vehicle (UAV) will be very reliable and cost-effective option for this task. To make the system fully autonomous, we require real-time object detection that is computationally complex and time consuming due to the heavy load on the limited processing and payload capacity of low-cost UAV. In this paper, we propose a cost-effective approach for aerial surveillance in which we move the heavy computation tasks to the cloud while keeping limited computation on-board of UAV system using Edge computing technique. Further this will maintain the minimum communication between UAV and the cloud thus proposed system will reduce the network traffic and also delay. Proposed system is based on the state-of-art technique YOLO (You Look Only Once) for real time object detection. © Springer Nature Switzerland AG 2020.Item Assessment of ferrous slag with relevance to physico-chemical properties(Springer, 2020) Anjali, M.S.; Poorani, M.; Shrihari, S.; Sunil, B.M.Blast furnace slag is generated as a by-product in the production of iron. Large quantities of slag are visible in the industrial premises that can have adverse effects on the environment. To mitigate such problems, proper environmental management of slag is of great concern. In this regard, a qualitative and quantitative evaluation of ferrous slags such as crystallinity, surface morphology, and elemental composition were done using X-Ray Diffraction and Field Emission Scanning Electron Microscope with EDS (Energy Dispersive X-Ray Spectrometer), respectively. It is also characterized to determine heavy metals and functional groups using Atomic Absorption Spectroscopy and Fourier Transform Infrared Spectroscopy techniques for various geo-environmental applications. The nonplastic slag material showed 85–92% sand-size particles and 8–15% silt-size particles. The SiO2 and CaO values were found to be high followed by Al2O3, MgO, and other compounds. Since slag performed similarly to sand, it could be used as an alternative source of sand. © Springer Nature Singapore Pte Ltd. 2020.Item 3D Printing of Syntactic Foams for Marine Applications(Springer International Publishing, 2020) Gupta, N.; Doddamani, M.Syntactic foams are hollow particle filled lightweight composite materials that are widely used in structural applications in underwater marine vessels. Additive manufacturing (AM), also called 3D printing, methods are now being developed for printing parts of syntactic foams. These methods provide advantage that the entire part can be printed without the requirement of machining or joining and eliminates stress concentration locations. The present work is focused on describing the method of creating a syntactic foam filament for fused filament fabrication type printers and then developing parameters for printing syntactic foams parts using commercial printers. High density polyethylene resin is used as the matrix material with fly ash cenospehres and hollow glass microballoons as the fillers for creating syntactic foams. One of the major challenges is to minimize the fracture of hollow particles during filament manufacturing and 3D printing, which is addressed by parameter optimization during processing. Results show that the syntactic foam specimens are successfully printed and their properties are comparable to the injection molded specimens of the same compositions. © Springer Nature Switzerland AG 2020.Item A review on mobile cloud computing interoperability issues and challenges(Springer, 2020) Debbarma, T.; Chandrasekaran, K.Mobile cloud computing (MCC) is the convergence of two recent technologies namely “Cloud Computing” and “Mobile Computing” with wireless networks as a communication backbone. There are mainly three paradigms that use the concepts of MCC, viz. edge computing, fog computing and cloudlets. Due to the presence of various heterogeneous hardware and software platforms in MCC, there are many interoperability issues which create vendor/services lock-in problems, it also makes data and application portability difficult. This paper studies the different paradigms of MCC and the challenges in making them interoperable in heterogeneous hardware and software platforms. We have summarized some of the MCC-based research papers and their findings. Contribution of this paper is the summary of challenges and research scopes in the field of MCC where it needs to be addressed to mitigate the interoperability issues. © Springer Nature Singapore Pte Ltd. 2020.Item Extraction of named entities from social media text in tamil language using N-gram embedding for disaster management(Springer Verlag service@springer.de, 2020) Remmiya Devi, G.R.; Anand Kumar, M.A.; Padannayil, K.P.In the present era, data in any form is considered with greater importance. More specifically, text data has rich and brief information than any other form of data. Extraction and analysis of these data can result in various new findings through text analytics. This has led to applications such as search engines, extraction of product names, sentiment analysis, document classification and few more. Companies are much focused on sentimental analysis to review the positive, negative and neutral comments for their products. Summarization of text is a notable application of Natural Language Processing that reveals the gist of brief documents. Apart from these, on concerning welfare of the society, application based on information extraction can be developed. Handling an emergency situation requires collection of vast information. Extraction of such data can be supportive during disaster management. In order to perceive such task, system must learn the meaning of human languages. To ease the accessibility of text data across language barriers is the primary motive of Natural Language Processing (NLP) systems. The proposed systems has utilized word embedding model, specifically skip gram model to implement the most fundamental task of NLP—entity extraction in social media text. Implementation of N-gram embedding methods paved way for creation of rich context knowledge for the system to handle social media text. Classification of named entities using the proposed system has been carried out using machine learning classifier Support Vector Machine (SVM). © Springer Nature Switzerland AG 2020.