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Development of Internet of Things Platform and Its Application in Remote Monitoring and Control of Transformer Operation
Internet of Things platforms deployed on the system will exhibit numerous benefits such as real time monitoring, faster operation and cost effectiveness. A system oriented IoT platform is developed which features database connotation, web services, setup portal, cloud hosting, drivers or listener for programming languages and hardware devices. The functional parameters of transformer in electrical power system vary around the limit and beyond, which is observed by the IoT platform for remote analysis and to report deformation in the winding. The frequency response measurement from the transformer terminal unit is send to cloud database which is then fetched to remote application through IoT client. At remote monitoring tool, the diagnostic algorithm is executed to estimate the location and extent of deformation. IoT based frequency response analyzer and transformer diagnostic tools developed reports the status of the transformer health condition. Depending upon the extent of deformation, the transformer is isolated from power system. Springer Nature Switzerland AG 2020. -
Optimal Charging Strategy for Spatially Distributed Electric Vehicles in Power System by Remote Analyser
The burden on the consumer for the price of fuel for classic vehicles is the root cause for the emergence of the fast growing trend in the power driven vehicles or electric vehicles. Less acceptance of electric vehicles by the customers and the hesitancy to replace traditional fuel powered vehicles by considering the economic factor is a major concern that existing in the current scenario. Therefore, for the proper balancing of the load with respect to the power available among different neighbouring charging stations in a given area, a load scheduling algorithm is used. The optimal route planner for the electric vehicles reaching the charging station is identified and then the power carried by each feeder is calculated by cumulative power of all the charging stations. The identification of the possible route is performed by the spatial network analysis which will be executing at remote analyzer. The location, state of charge, and other details of the electric vehicle through telemetry is used to find the best charging station for the particular vehicle in view of the cost, distance and the time. The performance of the technique is evaluated with and without optimization by considering the logical constraints; and the results are presented. Springer Nature Switzerland AG 2020. -
The aesthetics of corpses in popular culture
[No abstract available] -
A secured predictive analytics using genetic algorithm and evolution strategies
In the banking sector, the major challenge will be retaining customers. Different banks will be offering various schemes to attract new customers and retain existing customers. The details about the customers will be provided by various features like account number, credit score, balance, credit card usage, salary deposited, and so on. Thus, in this work an attempt is made to identify the churning rate of the possible customers leaving the organization by using genetic algorithm. The outcome of the work may be used by the banks to take measures to reduce churning rates of the possible customers in leaving the respective bank. Modern cyber security attacks have surely played with the effects of the users. Cryptography is one such technique to create certainty, authentication, integrity, availability, confidentiality, and identification of user data can be maintained and security and privacy of data can be provided to the user. The detailed study on identity-based encryption removes the need for certificates. 2020 by IGI Global. All rights reserved. -
Nanoarchitectures as photoanodes
This chapter looks into providing detailed information on the state-of-the-art and recent trends on materials and nanoarchitectures for improved photoanode device. It provides a roadmap for researchers toward optimization of photoanodes using advanced material engineering. The chapter casts some light on the performance of various photoanode materials and nanostructures, such as TiO2, ZnO, SnO2, Nb2O5, Al2O3, ZrO2, CeO2, SrTiO3, Zn2SnO4, and carbon in dye-sensitized solar cells (DSSCs). Plasmonic photoanodes are an emerging field in DSSC spanning a wide range of materials where the paramount challenge is coming up with effective strategies to incorporate suitable plasmonic structures into nanocrystalline and nanostructured electrodes. Optical excitation of the dye is the basis of DSSC operation, where an electron is excited from the dye molecule into the conduction band of a wideband metal oxide. 2020 JohnWiley & Sons Inc. All rights reserved. -
An experimental study on utilisation of red mud and iron ore tailings in production of stabilised blocks
Construction of bricks using waste materials is one among the many ways to address the problems encountered in infrastructure. In the present study, various industrial and mining wastes have been used to manufacture stable bricks. These wastes include red mud (RM) from Hindalco, and iron ore tailings (IOT) from BMM Ispat, Bellary. Both RM and IOT were combined in different proportions with ground-granulated blast furnace slag (GGBS) and waste lime. In first series, IOT was replaced in the range of 45% to 60% with increments of 5%, and RM was replaced in the range of 15% to 30% with increments of 5%. In the second series, RM was replaced in the range of 45% to 60% with increments of 5%, and IOT was replaced in the range of 15% to 30% with increments of 5%. Tests were performed as per the Indian and ASTM standards on both the raw material and the developed composites. These tests include liquid, plastic limit, particle size, XRF, XRD, and SEM on raw materials, while tests performed on composites were compressive strength, water absorption, efflorescence, porosity, apparent specific gravity, and bulk density. Results of the study indicate that addition of IOT up to 55% is acceptable as brick material. Springer Nature Singapore Pte Ltd 2020. -
Internet of things: Service-oriented architecture opportunities and challenges
Internet of Things is now a subject that is increasingly growing on both the job and modern devices. It is a concept that maybe not just get the potential to influence how we live but in addition how we work. Intelligent systems in IoT machines in many cases are used by various events; consequently, simultaneous information collection and processing are often anticipated. Such a characteristic that is exclusive of systems has imposed brand new challenges towards the designs of efficient data collection processes. This article is to be discussing various layers in Internet of things. Those layers are sensing layer, network layer, service layer and application layer. Various data processing techniques are integrated along with data filtering and data conversion. Protocol transformation is also feeling the major challenges faced by enterprises wanting to shift to the style in brand new technology. Springer Nature Singapore Pte Ltd. 2020. -
The industry use cases for the Digital Twin idea
Digital Twin Technology has taken the place in top 10 strategic technology trends in 2017 termed by Gartner Inc. Digital Twin concept brings out the virtual depiction or the digital representation of the real world equipment, device or system whereas the real world and the virtual world gets the highest synchronization. The digital representation of the complete life cycle of a product from its design phase to the maintenance phase will give the prophetic analysis of the problems to the business. This greatest advantage of foreseeing problems in the development of a device will give early warnings, foil downtime, cultivate novel prospects and inventing enhanced devices or gadgets for the later use at the lesser expense by means of digital representations. Indeed, these will devise a larger influence on conveying superior consumer feeling also in the enterprise. The emerging trends such as Artificial Intelligence, Machine Learning, Deep Learning, Internet of Things and Big Data used in Industry 4.0 play a vital role in Digital Twin and they are mostly adopted in the world of manufacturing, Industrial Internet of Things, and automobile business world. The penetration, wide coverage and the advancement of the Internet of Things in real-world have elevated the power of Digital Twins more economical and reachable for the world of various businesses. 1. Manufacturing: Digital Twin has brought out the change in the existing manner of the manufacturing segment. Digital Twins have a substantial influence on the design of products and their manufacturing and maintenance. Because of its influence the manufacturing more competent and augmented while dropping throughput times. 2. Industrial IoT: Integrating digital twin with industrial firms will facilitate the activities such as monitoring, tracking and controlling industrial systems in digital means. We can potentially experience the power of digital twin since it captures environmental data such as locality, settings of the devices, financial frameworks, etc., other than the operational data, which benefits in foreseeing the forthcoming operations and incongruities. 3. Healthcare: Since the healthcare sector demands higher accuracy in diagnosis and treatment, with the important data from IoT, digital twins can play a vital role by reducing the expense for the patient, precautionary alerts to avoid health deterioration and giving tailored health support system. This will be great support especially in developing countries like India. 4. Smart cities: Digital Twin coupled with IoT data can augment the efficient planning of the smart city and execution of its building by supplementing financial progress, effectual administration of resources, lessening of environmental impression and escalate the complete worth of a resident's life. The digital twin prototypical can aid city organizers and legislators in the smart city planning by retrieving the visions from numerous sensor networks and smart systems. The information received from the digital twins supports them in reaching well-versed choices concerning the future as well. 5. Automobile: Automobile industry can get voluminous benefits out of Digital Twins for producing the simulated framework of a coupled vehicle. It retrieves the behavioral and functional information of the vehicle and services in examining the inclusive performance efficiency of the vehicle as well as the features connected along with it. Digital Twin also supports in supplying a justly enhance support and service for the consumers. 6. Retail: Alluring client satisfaction is a fundamental factor in the merchandising world. Digital twin employment can play a key role in supplementing the retail customer experience by forming virtual twins for customers and modeling fashions for them on it. Digital Twins also supports enhanced planning of stock maintenance, safekeeping procedures, and human resource administration in an augmented means. 2020 Elsevier Inc. -
Smart Portable Neonatal Intensive Care for Rural Regions
Every year, an increasingly large number of neonatal deaths occur in India. Premature birth and asphyxia are being two of the leading causes of these neonatal deaths. A well-regulated thermal environment is critical for neonatal survival. In the current scenario, it is impossible for the health centers in the rural areas of India to afford a neonatal incubator for every newborn due to its price and transportability. The successful delivery of neonates is hampered in India due to its increasing population along with limited technology and resources. Thus, a prototype of an incubator has been designed that is affordable, transportable, and energy saving for the health centers in the rural regions, with an AI-based decision support system. Springer Nature Singapore Pte Ltd 2020. -
Discovering patterns using feature selection techniques and correlation
Term Frequency and inverse document frequency is reported to have a significant contribution for various text categorization, document clustering and many other text mining related tasks. A collection of the applications and the enhancements of the Term Frequency and Inverse Document Frequency based document representation technique is examined in this work. The document representation algorithm is essential in the field of text - script mining. In this algorithm, unstructured data is converted into a vector space model where each related document is considered as a point in the vector space. Related documents come in proximity to the other related documents while the documents that are very far away from being coherent remain different from each other. In this paper, four feature selection techniques are implemented to discover the patterns from a repository of unstructured data by using correlation similarity measure. Analysis and comparison with other existing technique is also included. The validation of the patterns formed is performed by using silhouette values. Experiments are conducted to compare performance. Results indicate that TDMp1 performance is poor compared to others. Springer Nature Switzerland AG 2020. -
Character Recognition of MODI Script Using Distance Classifier Algorithms
Machine simulation of human reading is an active research area since the introduction of digital computers. Optical character recognition aims at the recognition of printed or handwritten text from document images and converting the same into a machine-readable form. The focus of this work is handwritten character recognition of MODI Script. A proper recognition system for handwritten documents enables it to be conveniently viewed, edited, and shared via electronic means. The development of a character recognition system for some of the ancient script is still a challenging task due to the complex nature of the script. MODI script is one such script which is the shorthand form of the Devanagari script in which Marathi was written. Though at present MODI script is not an official script, there exists a huge collection of MODI documents in various libraries. In addition, it is observed that scholars and historians are taking serious effort to revive the script. The purposed study based on the implementation of two algorithms for the classification of handwritten MODI script. The algorithms use distance classifier method. The first experiment is done using Euclidean distance classifiers and the second one is with Manhattan distance classifier and the accuracy achieved is 99.28% & 94% respectively. Springer Nature Singapore Pte Ltd 2020. -
AI Based Non-invasive Glucose Detection Using Urine
This proposed device uses urine to predict the glucose level present in the patient using non-invasive technique with a high level of accuracy for detection of diabetes. The paper presents a urine glucose level diagnosing and prediction using a computer-based polarimeter held in a portable device, to provide a fast and accurate on-field result. The instrument consists of an LCD screen, optical sensor, Benedicts reagent, a detachable tank, and an embedded system-on-chip (SoC). Springer Nature Singapore Pte Ltd 2020. -
Computational Model for Hybrid Job Scheduling in Grid Computing
Grid computing the job scheduling is the major issue that needs to be addressed prior to the development of a grid system or architecture. Scheduling is the users job to apropos resources in the grid environment. Grid computing has got a very wide domain in its application and thus induces various research opportunities that are generally spread over many areas of distributed computing and computer science. The cardinal point of scheduling is being attaining apex attainable performance and to satisfy the application requirements with computing resources at exposure. This paper posits techniques of using different scheduling techniques for increasing the efficacy of the grid system. This hybrid scheduler could enable the grid system to reduce the execution time. This paper also proposes an architecture which could be implemented ensuring the optimal results in the grid environment. This adaptive scheduler would possibly combine the pros of two scheduling strategies to produce a hybrid scheduling strategy which could cater the ever changing workload encountered by the gird system. The main objective of the proposed system is to reduce to overall job execution time and processor utilization time. 2020, Springer Nature Switzerland AG. -
Idealised Bilinear Moment-Curvature Curves of Reinforced Masonry (RM) Walls
In this paper, an analytical investigation of the axial loadflexural strength interaction of reinforced masonry walls is carried. The curvature ductility of masonry walls is evaluated for walls with different modes of reinforcement configurations under different levels of axial loads. An analytical expression for evaluating the curvature ductility of masonry walls at varying axial loads is proposed in this paper. Value of curvature ductility obtained from the proposed expression is compared with existing methods. Results indicate the proposed model can be used to determine the ductility of reinforced masonry walls. 2020, Springer Nature Singapore Pte Ltd. -
Activity Classifier: A Novel Approach Using Naive Bayes Classification
Activity movements have been recognized in various applications for elderly needs, athletes activities measurements and various fields of real time environments. In this paper, a novel idea has been proposed for the classification of some of the day to day activities like walking, running, fall forward, fall backward etc. All the movements are captured using a Light Blue Bean device incorporated with a Bluetooth module and a tri-axial acceleration sensor. The acceleration sensor continuously reads the activities of a person and the Arduino is designed to continuously read the values of the sensor that works in collaboration with a mobile phone or computer. For the effective classification of a persons activity correctly, Nae Bayes Classifier is used. The entire Arduino along with acceleration sensor can be easily attached to the foot of a person right at the beginning of the user starts performing any activity. For the evaluation purpose, mainly four protocols are considered like walking, running, falling in the forward direction and falling in the backward direction. Initially five healthy adults were taken for the sample test. The results obtained are consistent in the various test cases and the device showed an overall accuracy of 90.67%. Springer Nature Switzerland AG 2020. -
Internet of Things Enabled Device Fault Prediction System Using Machine Learning
Internet of Things (IOT) started as a niche market for hobbyists and has evolved into a huge industry. This IoT is convergence of manifold technologies, real-time analytics, machine learning and Artificial Intelligence. It has given birth to many consumer needs like home automation, prior device fault detection, health appliances and remote monitoring applications. Programmed recognition and determination of different kinds of machine disappointment is a fascinating process in modern applications. Different sorts of sensors are utilized to screen flaws that is discovers vibration sensors, sound sensors, warm sensors, infrared cameras, light cameras, and other multispectral sensors. The modern devices are becoming ubiquitous and pervasive in day to day life. This device is need for reliable and predicate algorithms. This article is primarily emphases on the prediction of faults in real life appliances making our day to day life easier. Here, the database of the device includes previous faults which are restored in online by using cloud computing technology. This will help in the prediction of the faults in the devices that are to be ameliorated. It additionally utilizes Nae Bayes calculation for shortcoming location in the gadgets. The proposed model of this article is involves the monitoring of each and every home appliance through internet and thereby detect faults without much of human intervention. Springer Nature Switzerland AG 2020. -
Heightening Satellite Image Display via Mobile Augmented Reality A Cutting-Edge Planning Model
This paper summarizes on object detection, classification, analysis, and display for optical satellite image. Initially, all the existing object detection and object viewing system based on AI techniques are introduced. Various optical imaginary methods and the possibility of immersing optical and 3D data with other data sources are also explained. The surveyed literatures show that in most of the case, the detected objects are taken as resource for planning. We also observed that the image viewing and displaying model was ignored by many authors which is one of the key concepts for next phase. Satellite AR plays a vital role in displaying the images. Overall, it can be seen that optical image view along with AR display can be used for better planning, which is one of the popular research topics and has an excessive operational potential which is the need of the hour dealing with analyzing, predicting, and viewing large amount of data. 2020, Springer Nature Switzerland AG. -
Advanced Load Balancing Min-Min Algorithm in Grid Computing
Framework figuring has turned into genuine distinctive to old supercomputing situations for creating parallel applications that bridle huge process assets. In any case, the quality acquired in building such parallel Framework mindful applications is over the ordinary parallel registering conditions. It tends to issues like asset disclosure, heterogeneous, adaptation to non-critical failure and assignment programming. Load balancing errand programming inconceivably indispensable downside in cutting edge lattice environment. Load balancing ways is normally utilized for the development of appropriated frameworks. Normally there is a three kind of stages related with Load compromise that is information arrangement, higher psychological process, learning Relocation. Take a gander at the impact of surveying on load assignment by contemplating a fundamental expense in limit. There are three completely hovered tallies to lift which put away the stack ought to be doled out to, pondering the framework action cost among get-togethers. These tallies utilize grouped data trade frameworks and an asset estimation framework to redesign the constrained air framework exactness of load adjusting. Springer Nature Switzerland AG 2020. -
Recommendation of diet using hybrid collaborative filtering learning methods
These days, various recommender systems exist for online advertisement services which recommend the products considering users interests. Similarly, health recommendation systems are becoming most important component in individuals life. Due to the modernization and busy schedule, people give less concern to their eating patterns. This leads to various health issues like obesity, thyroid disorder, diabetes and others. Every individual has different health issues and food habits. Therefore, diet recommendations should be suggested by considering their personal health profile and food preferences. So, it becomes essential to analyze individuals health concerns before recommending the diet with required nutrient values. Thus, it helps people to minimize the further risks associated with the current health conditions. The proposed diet and exercise recommender framework suggests a balanced diet for thyroid patients. It takes care of the food intake with necessary nutrients requirement based on thyroid disorders. This paper applies K-nearest neighbor collaborative filtering models using various similarity measures. The paper assessed two-hybrid learning methods, KNN with alternating least squares: KNN-ALS and KNN with stochastic gradient decent: KNN-SGD. The experimental setup analyzed and evaluated the performances of all algorithms using mean absolute error (MAE) and root mean squared error (RMSE) values. Springer Nature Singapore Pte Ltd 2020. -
Detection of Disease in Mango Trees Using Color Features of Leaves
The goal has been to detect disease in mango trees. This paper compares different approaches to extract color features and check the accuracy and applicability for mango trees. The paper proposes variations which helped in increasing the accuracy of features extracted for mango trees: firstly, a customized method of splitting leaf into layers while doing K-means clustering, and secondly, segmenting the region of interest to blocks to help in applying statistical functions more accurately over a region. 2020, Springer Nature Singapore Pte Ltd.