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Lifestyle Diseases Prevalent in Urban Slums of South India
Lifestyle diseases have always been considered to be a malady of the middle and upper classes of society. Recent findings indicate that these chronic non-communicable diseases are common among the lower socioeconomic classes as well. The objective of this study was to assess the prevalence of lifestyle diseases in three cohorts of urban slums, namely, waste pickers living in non-notified slums, communities living in notified slums, and BBMP Pourakarmikas, and to identify the risk factors among the three cohorts contributing to the common lifestyle diseases including hypertension, diabetes, and cardiovascular diseases. In this study, the data was collected by conducting health camps, followed by analysis of the data using logistic regression, HosmerLemeshow test and ROC Curve Analysis. The prevalence of hypertension was found 13.35%, diabetes-8.53% and cardiovascular disease-3.59%. These were significantly associated with substance abuse, high BMI, and age. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Eccentric Graph of Join of Graphs
The eccentric graph Ge corresponding to a graph G is a derived graph with the same vertex set of G and two vertices in Ge are neighbours if one of them is the eccentric vertex of the other. Motivated by the studies on derived graphs and graph operations, in this article, the eccentric graph of the join of two graphs is analysed based on the variations in the radius. The notion of eccentric join of two graphs with at least one of them having radius 1, is introduced. The eccentric graph of eccentric join of graphs is also examined. Finally, the concept of r-eccentric join of graphs is also introduced. This study is analytical in nature, which involves deductive and logical reasoning. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Proficient technique for satellite image enhancement using hybrid transformation with FPGA
Visual quality of images is improved by digital techniques for the improvement of photographs. The main purpose of image improvements is to process an image to make the output more desirable for a particular use than the original image. This paper proposes a new approach, which improves the picture of the satellite by the use of the SVD DWT concept, the Gaussian transformation DWT and multiwavelet transformation. This suggested approach would convert and approximate the single-colour value matrix of the low-flowing sub-band into one low-frequency and 15 high-frequency sub-bands, and then recreate the improved picture using the inverse transformation. In terms of technical criteria as PSNR, RMSE and CC, this approach can have higher quality and quantitative performance. This paper introduces strategies for improving hardware images using a programmable door array in real-time (FPGA). The suggested algorithm is implemented successfully with Xilinx ISE, MATLAB and ModelSim on different scale satellite images in Verilog HDL. In this article, these algorithms should be simulated and implemented using Verilog HDL. The Spartan-3E from Xilinx is the unit chosen here. 2021 IEEE -
Detection of Fraudulent Alteration of Bank Cheques Using Image Processing Techniques
In todays world illegal alteration and illegal modifications of authenticated financial documents is increasing rapidly as a fastest growing crimes around the world. The result of this kind of crimes may result in a huge financial loss. In this paper image processing and document image analysis techniques are used to examine such cases in order to identify the fraudulent bank cheques. However, it is very difficult to detect an alteration made on documents once the printing ink of alike color is employed. In this paper, alterations and modifications caused with handwritten ball point pen strokes are considered and proposed a technique for recognition of such types of corrections by employing standard techniques under Digital image processing and pattern recognition. The results are quite promising during the experiments conducted. 2021, Springer Nature Singapore Pte Ltd. -
Parallel Algorithm to find Integer k where a given Well-Distributed Graph is k-Metric Dimensional
Networks are very important in the world. In signal processing, the towers are modeled as nodes (vertices) and if two towers communicate, then they have an arc (edge) between them or precisely, they are adjacent. The least number of nodes in a network that can uniquely locate every node in the network is known in the network theory as the resolving set of a network. One of the properties that is used in determining the resolving set is the distance between the nodes. Two nodes are at a distance one if there is a single arc can link them whereas the distance between any two random nodes in the network is the least number of distinct arcs that can link them. We propose two algorithms in this paper with the proofs of correctness. The first one is in lines with the BFS that find distance between a designated node to every other node in the network. This algorithm runs in O(log n). The second algorithm is to identify the integer k, such that the given graph is k-metric dimensional. This can be implemented in O(log n) time with O(n2) processors in a CRCW PRAM. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Fabrication of Didactic Model to Demonstrate Bottle Filling System Using Programmable Logic Controller
Automation is the evolution of manufacturing process which will ideally lead to e-governance. It helps humans and machines to be connected at the hip, blending the cerebral aptitudes of human and specialized abilities of automated bots to immune the workspace. Automated system has enhanced the modern day market by increasing the quality of the product as well as making the fabricating process time efficient. Lights out technology in industry promotes the robots to do work even after working hours when the lights are shut down in industry. In this research paper, a unique approach is used to fabricate a didactic model which demonstrates the working of a bottling plant which may be preferred for medium and small scale industries. To implement the process, CODESYS is used to program CPX-CEC-C1 PLC, a digital computerized system which performs logical decisions and provides outputs based on sensor inputs. The main focus is towards interfacing pneumatics and hydraulic components with PLC. 2021, Springer Nature Singapore Pte Ltd. -
Automatic Generation Control of Multi-area Multi-source Deregulated Power System Using Moth Flame Optimization Algorithm
In this paper, a novel nature motivated optimization technique known as moth flame optimization (MFO) technique is proposed for a multi-area interrelated power system with a deregulated state with multi-sources of generation. A three-area interrelated system with multi-sources in which the first area consists of the thermal and solar thermal unit; the second area consists of hydro and thermal units. The third area consists of gas and thermal units with AC/DC link. System performances with various power system transactions under deregulation are studied. The dynamic system executions are compared with diverse techniques like particle swarm optimization (PSO) and differential evolution (DE) technique under poolco transaction with/without AC/DC link. It is found that the MFO tuned proportional-integral-derivative (PID) controller superior to other methods considered. Further, the system is also studied with the addition of physical constraints. The present analysis reveals that the proposed technique appears to be a potential optimization algorithm for AGC study under a deregulation environment. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Comparative Analysis of Sentiment Analysis Using RNN-LSTM and Logistic Regression
Social media analytics makes a big difference in the success or failure of an organization. The data gathered from social media can be used to get a hit type product by analyzing the data and getting important information about the need of the people. This can be done by implementing sentiment analysis on the available data and then accessing the feelings of the customers about the product or service and knowing if it is actually being liked by them or not. Tracking data of the customers helps the organization in many ways. This study was done to get familiarized with the concept of data analytics and how social media plays an important role in it. Furthermore, Web scraping of Twitter and YouTube data was done following which a standard dataset was selected to do the other analytics. The field of sentiment analysis was used to get the emotions of the people. Logistic regression and RNN-LSTM models were used to perform the same, and then, the results were compared. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
ETL and Business Analytics Correlation Mapping with Software Engineering
Large information approach can't be effectively accomplished utilizing customary information investigation strategies. Rather, unstructured information requires specific information demonstrating methods, apparatuses, and frameworks to separate experiences and data varying by associations. Information science is a logical methodology that applies scientific and measurable thoughts and PC instruments for preparing large information. At present, we all are seeing an exceptional development of data created worldwide and on the web to bring about the idea of large information. Information science is a significant testing zone because of the complexities engaged with consolidating and applying various strategies, calculations, and complex programming procedures to perform insightful investigation in huge volumes of information. Thus, the field of information science has developed from enormous information, or huge information and information science are indistinguishable. In this article we have tried to create bridge between ETL and software engineering. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Fog-Based Retrieval of Real-Time Data for Health Applications
Fog computing is an emerging technology that offers high-quality cloud services by providing high bandwidth, low latency, and efficient computational power and storage capacity. Although cloud computing is an efficient solution so far to store and retrieve the huge data of IoT devices, it is expected to limit its performance due to low latency and storage capacity. Fog computing addresses these limitations by extending its services to the cloud at the edge of the network. In this paper, we use a fog computing network approach for efficiently retrieving the real-time patient data. The performance of our proposed approach has been compared with the cloud computing approach in terms of retrieval time of real-time data. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
On Statistical Tools in Finding Equitable Antimagic Labeling of Complete Graphs
Graph theory is a branch of mathematics that deals with representation of graphs with vertices and edges. Graph labeling is the assignment of integer labels to either vertices or edges. For a given graph G= (V, E), an edge-weighting is a function f:E(G)?{1,2,3,..,|E(G)|}. For a vertex v of G, let Wf(v) denotes the sum of edge-weights appearing on the edges incident at v under the edge-weighting f. A bijective edge-weighting f of G is said to be an equitable antimagic labeling (EAL) of G if |Wf(u) - Wf(v) | ? 1 for any pair of adjacent vertices u and v of G. A graph admitting an EAL is called an equitable antimagic graph (EAG). In this paper, the characterization of complete graphs Kn, for n? 6 is dealt using an algorithmic approach. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Evaluation of ML-Based Sentiment Analysis Techniques with Stochastic Gradient Descent and Logistic Regression
In recent times, along with the expansion of technology, the Internet also has flourished exponentially. World is more connected today not only through the technology, but also through sharing sentiments to express views, either be constructive or destructive in front of the world through social media. Twitter, Facebook, Instagram, etc., are being used as social media to reach the world. The study of understanding peoples emotions, intentions, attitudes from unstructured data is opinion mining/sentiment analysis. This is an application of NLP or text mining. In this paper, an attempt is made to realize sentiment analysis's multiple dimensions using approaches such as ML and NLP-based technqies like word frequency and TF-IDF. Using ML approach, experiments were conducted, and the performance of the predictions was visualized. Three different datasets are used. A comparison of logistic regression (LR) and stochastic gradient descent (SGD) algorithms are compared using two different document representation. An extensive comparison is carried out using three different types of dataset. Amazon instant video datasets, bank dataset and movie reviews datasets are being used for the same. Analysis of performance is accomplished by using different graphs. The results indicate that logistic regression performs better than stochastic gradient descent for movie review dataset by using word frequency and TF-IDF-based approach. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Indian Road Lanes Detection Based on Regression and clustering using Video Processing Techniques
Detecting the road lanes from moving vehicle is a difficult and challenging task because of road lane markings with poor quality, occlusion created by traffic and poor road constructions. If the driver is not maintaining the road lanes properly, the proposed system detects the road lanes and gives the alarm to the driver so that driver can take the corrective actions there by we can avoid the accidents. The paper mainly focusses on detection of road lanes from sequence of image taken from the video from moving vehicle. The Methodology mainly consisting of lane segments merging and fitting using clustering and weighted regression techniques to fit the curve in the place of group of lane segments and curve fitting separately. 2021, Springer Nature Singapore Pte Ltd. -
Stability Analysis of AFTI-16 Aircraft by Using LQR and LQI Algorithms
The stability analysis of the dynamical system of linearized plant model of Advanced Fighter Technology Integration (AFTI)-16 aircraft was proposed along with the optimal control methods by applying linear quadratic regulator (LQR) and linear quadratic algorithm (LQI) algorithms. The LQR and LQI algorithms results were compared with state-space model analysis results. The state-space methods like pole placement method, without using the LQR algorithm the negative feedback system were found to be unstable. By the application of LQR and LQI algorithms to the linearized plant AFTI-16 aircraft open-loop system having negative feedback found to be stable. The stability parameters were verified by using MATLAB programming software. The eigenvalues play a key role in finding closed-loop system stability analysis. MIMO dynamical system with state feedback gain matrices is calculated by using MATLAB programming software. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Survey on Solution of Imbalanced Data Classification Problem Using SMOTE and Extreme Learning Machine
Imbalanced data are a common classification problem. Since it occurs in most real fields, this trend is increasingly important. It is of particular concern for highly imbalanced datasets (when the class ratio is high). Different techniques have been developed to deal with supervised learning sets. SMOTE is a well-known method for over-sampling that discusses imbalances at the level of the data. In the area, unequal data are widely distributed, and ensemble learning algorithms are a more efficient classifier in classifying imbalances. SMOTE synthetically contrasts two closely connected vectors. The learning algorithm itself, however, is not designed for imbalanced results. The simple ensemble idea, as well as the SMOTE algorithm, works with imbalanced data. There are detailed studies about imbalanced data problems and resolving this problem through several approaches. There are various approaches to overcome this problem, but we mainly focused on SMOTE and extreme learning machine algorithms. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Butterfly Optimization Algorithm-Based Optimal Sizing and Integration of Photovoltaic System in Multi-lateral Distribution Network for Interoperability
In this paper, a new and simple nature-inspired meta-heuristic search algorithm, namely butterfly optimization algorithm (BOA), is proposed for solving the optimal location and sizing of solar photovoltaic (SPV) system. An objective function for distribution loss minimization is formulated and minimized via optimally allocating the SPV system on themain feeder. At the first stage, the computational efficiency of BOA is compared with various other similar works and highlights its superiority in terms of global solution. In thesecond stage, the interoperability requirement of SPV system while determining the location and size of SPV system among multiple laterals in a distribution system is solved without compromises in radiality constraint. Various case studies on standard IEEE 33-bus system have shown the effectiveness of proposed concept of interline-photovoltaic (I-PV) system in improving the distribution system performance in terms of reduced losses and improved voltage profile via redistributing the feeder power flows effectively. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Mathematical Correlation of Compressive Strength Among Silica, Alumina and Calcia Present in Composite Red Mud and Iron Ore Tailingbricks
Waste Red Mud generated from bauxite beneficiation in aluminium industry contains sodium oxide in minor amount along with silica and alumina in significant quantities. Waste iron ore tailings from beneficiation of iron ore in steel industry contain silica and alumina in significant quantities. A combination of both these materials in different amounts along with GGBS and lime addition resulted in complex alkali-activated reaction products consisting of (Si/Al), (Ca/Si) and (Ca/(Si+Al)) complexes which influence compressive strength of the test samples on curing for extended time periods at room temperature. Individual correlation coefficients of these complexes with compressive strength yielded high values with (Si/Al) and (Ca/Si+Al) ratios (0.92 and 0.96, respectively) while showing a poor correlation coefficient with (Ca/Si) ratio (0.88). A direct regression analysis between compressive strength and (Si/Al) ratio and (Ca/Si+Al) ratio indicated negative values with (Si/Al) ratios but positive values with (Ca/ (Si+Al)) ratios. It is therefore concluded that the addition of lime and GGBS (contributed from both GGBS and lime addition) resulted in Ca-Si-Al complex formations which are responsible for improved compressive strength of the samples. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Fraud Detection in Credit Card Transaction Using ANN and SVM
Digital Payment fraudulent cases have increased with the rapid growth of e-commerce. Masses use credit card payments for both online and day-to-day purchasing. Hence, payment fraud utilizes a billion-dollar business, and it is growing fast. The frauds use different patterns to make the transactions from the cardholders account, making it difficult for the organization or the users to detect fraudulent transactions. The studys principal purpose is to develop an efficient supervised learning technique to detect credit card fraudulent transactions to minimize the customers and organizations losses. The respective classification accuracy compares supervised learning techniques such as deep learning-based ANN and machine learning-based SVM models. This studys significant outcome is to find an efficient supervised learning technique with minimum computational time and maximum accuracy to identify the fraudulent act in credit card transactions to minimize the losses incurred by the consumers and banks. 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. -
Pad Vending Machine with Cashless Payment
A vending machine aims to provide required product or the service to the customer with certain ease, wherein not much effort is required. This research work aims to design a pad vending machine with an option of payment using QR code which is implemented using blockchain to make the system much more efficient and reliable than the existing systems present in the Indian market. The system is divided into two parts, first being the working of the machine and second being the mode of payment which is implemented using a blockchain. It is noticed many times that due to unpredictable menstrual flow women tend to face a lot problems. To overcome this problem, a pad vending machine is proposed with certain advancements through which women can help themselves in the stated circumstances. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Captcha-Based Defense Mechanism to Prevent DoS Attacks
The denial of service (DoS) attack, in the current scenario, is more vulnerable to the banking system and online transactions. Conventional mechanism of DoS attacks consumes a lot of bandwidth, and there will always be performance degradation with respect to the traffic in any of the communication networks. As there is an advent over the network bandwidth, in the current era, DoS attacks have been moved from the network to servers and API. An idea has been proposed which is CAPTCHA-based defense, a purely system-based approach. In the normal case, the protection strategy for DDoS attacks can be achieved with the help of many session schedulers. The main advantage is to efficiently avoid the DoS attacks and increase the server speed as well as to avoid congestion and data loss. This is majorly concerned in a wired network to reduce the delays and to avoid congestion during attacks. 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.