Showing papers by "Narula Institute of Technology published in 2020"

A review on fabrication, characterization and implementation of wearable strain sensors

Abstract: The paper presents a substantial review on the different kinds of strain sensors that have been employed as wearable sensing prototypes. The importance of strain sensors lies in their low cost, high sensitivity and multifunctional applications. The flexible strain sensors have been developed with printing techniques that have generated prototypes with varied electrical, mechanical and thermal characteristics. These types of devices have been primarily used for biomedical applications, where a small amount of deflection holds a crucial worth to monitor acute and chronic anomalies in human beings. Among the major areas in healthcare applications where strain sensors have been utilized, wearable sensing holds a pivotal role due to their capability of ubiquitous monitoring. The wearable sensors have been designed and fabricated with a range of processing materials, based on their respective applications. Along with the significant research related to the fabrication and implementation of wearable strain sensors, explanation related to the challenges of the current sensors and their futuristic possibilities have also been showcased in the paper.

Melanoma Diagnosis Using Deep Learning and Fuzzy Logic.

Abstract: Melanoma or malignant melanoma is a type of skin cancer that develops when melanocyte cells, damaged by excessive exposure to harmful UV radiations, start to grow out of control. Though less common than some other kinds of skin cancers, it is more dangerous because it rapidly metastasizes if not diagnosed and treated at an early stage. The distinction between benign and melanocytic lesions could at times be perplexing, but the manifestations of the disease could fairly be distinguished by a skilled study of its histopathological and clinical features. In recent years, deep convolutional neural networks (DCNNs) have succeeded in achieving more encouraging results yet faster and computationally effective systems for detection of the fatal disease are the need of the hour. This paper presents a deep learning-based ‘You Only Look Once (YOLO)’ algorithm, which is based on the application of DCNNs to detect melanoma from dermoscopic and digital images and offer faster and more precise output as compared to conventional CNNs. In terms with the location of the identified object in the cell, this network predicts the bounding box of the detected object and the class confidence score. The highlight of the paper, however, lies in its infusion of certain resourceful concepts like two phase segmentation done by a combination of the graph theory using minimal spanning tree concept and L-type fuzzy number based approximations and mathematical extraction of the actual affected area of the lesion region during feature extraction process. Experimented on a total of 20250 images from three publicly accessible datasets—PH2, International Symposium on Biomedical Imaging (ISBI) 2017 and The International Skin Imaging Collaboration (ISIC) 2019, encouraging results have been obtained. It achieved a Jac score of 79.84% on ISIC 2019 dataset and 86.99% and 88.64% on ISBI 2017 and PH2 datasets, respectively. Upon comparison of the pre-defined parameters with recent works in this area yielded comparatively superior output in most cases.

A comprehensive study of a backlogging EOQ model with nonlinear heptagonal dense fuzzy environment

Abstract: This paper deals with an adaptation of an application of nonlinear heptagonal dense fuzzy number. The concept of linear and as well as non-linear for both symmetric and asymmetric heptagonal dense fuzzy number is introduced here. We develop a new ranking method for non-linear heptagonal dense fuzzy number also. Considering a backorder inventory model with non-linear heptagonal dense fuzzy demand rate we have utilized a modified centroid method for defuzzification. For decision maker’s aspects, numerical examples, comparative study with other dense fuzzy numbers and a sensitivity analysis show the superiority of the nonlinear heptagonal dense fuzzy number. Finally, graphical illustrations are made to justify the model followed by a conclusion.

A Cross-Sectional Study on Central Sensitization and Autonomic Changes in Fibromyalgia.

Abstract: Fibromyalgia is a multi-symptomatic disorder characterized by generalized pain. The pathophysiology of fibromyalgia is supposedly an interplay between central nervous system hyper-responsiveness, autonomic dysfunction, and peripheral pain. In this cross-sectional study, the objective was to assess central sensitization and autonomic activity in patients with fibromyalgia compared with control. Fifty adults diagnosed with fibromyalgia by the modified American College of Rheumatology 2010 criteria and an equal number of age- and sex-matched controls participated in the study in an urban tertiary care hospital. Central sensitization was assessed by history and by evidence of increased prefrontal cortical activity as measured by cortical oxygenation using functional near-infrared spectroscopy. Autonomic activity was assessed by heart rate variability, electrodermal activity, and deep breathing test in three physiological states: rest, sympathetic stress (cold pressor test), and deep breathing. Mann-Whitney U-test, paired t-test, Wilcoxon test, and Friedman test with Bonferroni a priori were used to analyze the data. Cortical activity was significantly higher in the fibromyalgia group than control. There was no significant difference in autonomic activity between the fibromyalgia and control groups. In the fibromyalgia group, variable degrees of sympathetic hyperactivity and normal parasympathetic activity were observed. Central sensitization may be playing a primary role in the pathophysiology of generalized pain in fibromyalgia.

Influence of Gate and Channel Engineering on Multigate Tunnel FETs: A Review

Abstract: The continuous progress in the development of tunnel field-effect transistors (TFETs) by replacing the conventional metal-oxide field-effect transistors is to satisfy the development of continuous device dimension down-scaling. In this paper, a detailed review is made on non-conventional TFET structures owing to the inbuilt benefit of band-to-band tunneling (BTBT) phenomenon carrier conduction mechanism, thereby reducing short-channel effects (SCEs). The work presents the drain current evaluation of various non-conventional device structures, viz. double-gate tunnel FET (DG-TFET), triple-gate tunnel FET (TG-TFET), double-gate pocket intrinsic tunnel FET (DG-PI-TFET), and triple-gate TFET structures with pocket intrinsic layer (TG-PI-TFET). The variation of drain current for different device parameters has been reviewed and demonstrated with Silvaco TCAD simulator.

A graph theory application for fast and efficient search of optimal radialized distribution network topology

Abstract: The topological changes and re-configuration can be brought into an existing power network by operation of sectionalizing switches on the feeder lines. Distribution networks can be operated either in meshed or in radial configuration. While primary meshed distribution networks have advantages like lower short circuit current, reduced overall conductor length and increased reliability and fault tolerance, the radial networks on the other hand stand-out on their merits of simple installation and easier relay coordination. An optimal radial network can operate at higher efficiency owing to its reduced power losses and can offer higher voltage stability. Transformation of a primary meshed network to a radially reconfigured optimal network requires selection of the “best” set of switches on the feeders that are to be opened or closed so that each feeder can be operated close to its maximum loadability limit and the resulting optimal network operates at its lowest feasible value of power loss and highest voltage stability index. This theoretical concept of optimal power network radialization is however difficult to implement in practice due to the heavy computational burden and unacceptably long searching time as the number of feasible alternative configurations is usually massive for large power networks. Given the extent of the search space, the heuristic search approaches are usually more practical and common in power network reconfiguration. This paper presents a novel guided search approach based on Edmond’s Maximal Spanning Tree Algorithm to achieve the optimal radial configuration for an arbitrary power network rapidly and efficiently. Efficacy of the proposed method has been tested on 30-node and 57-node mesh distribution networks with encouraging results.

SSTRNG: self starved feedback SRAM based true random number generator using quantum cellular automata

Abstract: The information are need to modulate using irreproducible and unpredictable digital bit stream to get a secure digital communication systems. Hence, True random number generator (TRNG) is a significant aspirant in digital circuit to yield unpredictable digital bit stream. In this assignment self starved feedback SRAM based TRNG is proposed in quantum cellular automata (QCA) technology. Moreover, QCA technology is adopted to design TRNG components due to its features like ultra low power dissipation, low area and ultra high operating frequency. The proposed TRNG is comprised of self starved feedback circuit and floating clock generator. Again, the basis of self starved feedback circuit is a single bit QCA SRAM cell, which extracts the random digital bit. Furthermore, to enhance the randomness, floating clock generator is implemented across self starved feedback circuits input. The functionality of proposed TRNG is accomplished through QCA Designer tool and its architecture is also passed NIST statistical test of randomness. Hence proposed 8 bit TRNG can be interpreted as a novel contender for security applications due to its 14.82 GHz operating frequency, 0.36 μm2 area, latency of 1 QCA clock cycle, 28.53 meV average power dissipation and high tail probability of NIST test battery report in QCA technology.

Minimal Spanning Tree in Cylindrical Single-Valued Neutrosophic Arena

Abstract: In this chapter, the concept of cylindrical single-valued neutrosophic number whenever two of the membership functions, which serve a crucial role for uncertainty conventional problem, are dependent to each other is developed. It also introduces a new score and accuracy function for this special cylindrical single valued neutrosophic number, which are useful for crispification. Further, a minimal spanning tree execution technique is proposed when the numbers are in cylindrical single-valued neutrosophic nature. This noble idea will help researchers to solve daily problems in the vagueness arena.

Experimental and Numerical Free Vibration Analysis of Laminated Composite Plates with Arbitrary Cut-Outs

Abstract: Cut-outs are the integral parts of laminated plate components in a variety of civil, aerospace and marine engineering applications. Cut-outs alter the dynamic behaviour of the structures by reducing mass and stiffness simultaneously. The glass epoxy laminates are fabricated by resin infusion method through vacuum bagging system in the laboratory. The experimental studies are carried out on composite plates with cut-out positioned at different locations in the laminate. A finite element formulation based on the first-order shear deformation theory is developed in the present study using nine noded isoparametric shallow shell elements. The effects of rotary inertial contribution of mass on the natural frequencies are studied in the present paper. The present finite element formulation is validated by comparing the solutions obtained in terms of natural frequencies with the relevant published results and also experimental data. The correlation between experimental and numerical mode shapes is established by using modal assurance criteria.

Blockchain vs GDPR in Collaborative Data Governance

Abstract: Data Governance is the trending topic in today’s security-privacy-concerned digital ecosystem. Blockchain technology is probably one of the most acclaimed evolutions in recent times. Blockchain technologies can be a game-changer for data governance in the areas of transparency and data provenance. As a distributed ledger technology (DLT), blockchain is being touted as a potentially transformational force in collaborative data governance. The General Data Protection Regulation (GDPR) entered into force on May 25, 2018. It is the latest in a series of European Union (EU) legislative measures designed to give EU citizens more control over their data. GDPR, which directs a centralized ‘data controller’ (GDPR Article 4) to manage user data, clashes with the blockchain’s decentralized data storage and management process. The GDPR and the blockchain both have a common ideological ground, emphasizing the need for a change in managing personal data. While GDPR takes care of the policy side by setting up a standard, the blockchain helps enable the implementation side by providing a unique framework. In this paper, the authors analyze the clashes between the two and the potential solutions to those clashes for blockchain to comply with GDPR.

An Ensemble Learning-Based Language Identification System

Abstract: Speech recognition from multilingual voice signals is a challenging task. It is essential to distinguish the language of the spoken phrases prior to recognizing them. This is known as automatic language identification. Automatic language identification is very much important for multilingual countries like India as people often use more than a single language while talking. In this paper, a language identification system for seven different languages from the IIIT-H Indic Speech Databases is presented. We have used line spectral frequency-based features for modelling the languages. The highest accuracy of 99.71% has been obtained with ensemble learning-based classification technique.

Quantitative Structure–Activity Relationship (QSAR) Study of Some DNA-Intercalating Anticancer Drugs

Abstract: Small molecular anticancer drugs bind reversibly to DNA and are used in chemotherapy. The experimental measurements of the inhibition activity of drugs are difficult, expensive, and time-consuming. So, quantitative structure–activity/property relationship method (QSAR) is adopted where the dependency of drug binding affinity with their structural features is exploited. To explore whether molecular descriptors can explain their DNA-binding affinity and toxicity, 23 antitumor molecules, which are being used clinically as drugs, are analyzed by rigorous statistical calculations. The 50% cancer cell growth inhibition constant (IC50) for any particular cancer cell line is obtained from the NCI/NIH database. Molecular descriptors (geometrical, physicochemical, and quantum chemical) are calculated for the molecules. A mathematical model is built to predict DNA-drug-binding constant and growth inhibitory concentration by multiple regression which can be useful for rational drug design.

Even big data is not enough: need for a novel reference modelling for forensic document authentication

Abstract: With the emergence of big data, deep learning (DL) approaches are becoming quite popular in many branches of science. Forensic science is no longer an exception. However, there are certain problems in forensic science where the solutions would hardly benefit from the recent advances in DL algorithms. Document authentication is one such problem where we can have many reference samples, and with the big data scenario probably we would have even more number of reference samples but number of defective or forged samples will remain an issue. Experts often encounter situations where there is no or hardly a scanty number of forged samples available. In such situation, employment of data-hungry algorithms would be inefficient as they will not be able to learn the forged samples properly. This paper addresses this problem and proposes a novel reference modelling framework for forensic document authentication. The approach is based on Mahalanobis space. Two questioned document examination problems have been studied to show the effectiveness of our reference modelling algorithm which has also been compared to a commonly used learning approach, namely neural network-based classification.

A Comprehensive Assessment of the Need and Availability of Smart Grid Technologies in an Electricity Distribution Grid Network

Abstract: The electrical distribution grids face major problems such as aggregate technical and commercial losses and integration of distributed energy resources. There are also several operational problems such as inaccurate meter reading, blackouts and outages, huge data compilation, etc. With the availability of automatic metering infrastructure and phasor monitoring units, many of these problems can be addressed. With the rapid progress in power electronic converter technology, the problems in integration of distributed energy resources can be efficiently resolved. However, the necessary prerequisite for getting all these benefits is remote monitoring and control. For effective demand response and price responsive demand, transparency and communication with the consumer and consumer—end systems are essential. For interoperability between the devices of various smart grid technologies, the rapid advances in communication technologies on Zig Bee, cellular communication WiMAX, power line communication are being used. In spite of the smart grid communication standards being not in place, the present standards from various bodies are being used. This has given shape to several data analytics applications with crunching of huge data from smart grid network operations.

Physical Proof and Simulation of Ternary Logic Gate in Ternary Quantum Dot Cellular Automata

Abstract: Ternary quantum dot cellular automata (tQCA) is an emerging as well as an interesting field of research area after successful fabrication of binary QCA. Ternary logic is a critical choice for solving greater data storage, faster arithmetic operation on complex data, and so on. In this paper, tQCA basic logic gates like ternary AND, OR, NOT gates and buffers have been reported. tQCA layout for basic logic gates is simulated with tQCA simulation software (TQCA_1.7.0.2). Involvement of coulombic interactive force is also explored as physical proof of NOT gate operation in eight-dot tQCA device model.

Artificial Intelligence-Based Economic Control of Micro-grids: A Review of Application of IoT

Abstract: India is a developing country, and the economic conditions of Indian citizen in some rural areas are ambiguous. It is extremely important to reduce the financial burden so that people can use electricity. Incorporation of solar and wind energy in a micro-grid along with a small storage unit can be used to feed a whole block of rural electricity demand which is absolutely pollution free and maintenance less. The only problem is the initial investment and recurring cost of misutilization of electricity. The micro-grids can be operated as an autonomous unit or may be used to share the load with the main grid for the area. During load shedding, which is a common phenomenon during summer, a storage unit will be used as a backup. These micro-grids are connected with bus bars that are directly connected with remote terminal unit which can feed us the necessary data for optimization. As several units are a part of this optimization, artificial intelligence (AI) may be used for a quicker and improved solution with the available data bank of the resources. The data bank can be optimized in a cloud-based server, and the whole electrical network can be controlled by a cyber-physical network or Internet of things (IoT) technology. Optimization can be used to upload the data in the cloud computing server. This paper presents a review of excellent endeavors in the field of IoT-based micro-grid control in the recent past. The review also includes a conceptualization of a method which may substantially reduce the budget of electricity in rural areas of a process that may be beneficial for people dwelling in rural areas.

Applying Encryption Algorithm on Text Steganography Based on Number System

Abstract: Nowadays as there is huge transfer of information throughout the world so there are adequate chances of leakage of information. Standard algorithms fail to protect data/information. This is the primary purpose for developing a number system-based technique for data/information hiding. This is a combination of art and science where the original data is hidden, which appears as nonexistent, so keeping it out of sight. All the characters, numbers can be hidden by using a novel method, and so it is applicable to any language. Any message can be hidden by transmitting it in the encoded form over any electronic media. This work is not a comparison or improvement of the previous works but it is a different approach to text Steganography to hide the information. A superb blend of number, word to hide information. For developing the application, this paper could be very useful for any defence, force to transmit highly secret data securely.

Emergency Restoration Based on Priority of Load Importance Using Floyd–Warshall Shortest Path Algorithm

Abstract: This work presents a novel algorithm for service restoration with an aim to provide power to each important load by the black-start generator during emergency after an immediate blackout. In this process of the restoration, total network must be clustered satisfying all of the electrical constraints based on load priority. To achieve the above objectives, priority-based Floyd–Warshall all-pair shortest path algorithm (FWA) has been utilized. This algorithm will provide the shortest distance between all the pairs of the buses (i.e., vertices in graph theory). Simulation on IEEE 14 bus system has been carried out. The result shows that the proposed method can effectively determine the cluster by means of shortest path algorithm for the reenergizing network after the blackout satisfying all constraints in a very small operating time.

Measures of Linear and Nonlinear Interval-Valued Hexagonal Fuzzy Number

Abstract: In the view of significant exposure of multifarious interval-valued fuzzy numbers in neoteric studies, different measures of interval-valued generalized hexagonal fuzzy numbers (IVGHFN) associated ...

MVTRNG: Majority Voter-Based Crossed Loop Quantum True Random Number Generator in QCA Nanotechnology

Abstract: True random number generator, commonly known as TRNG, is an important candidate in today’s cryptography process. TRNG is only innovative design which can generate non-deterministic and unique digital bit stream to any communication systems or secured system. Quantum cellular automata (QCA) technology is adopted to design TRNG due to its low area, ultra high operating frequency, and low power dissipation. This article presents a QCA majority voter-based TRNG, which is comprised of crossed loop circuit and seed circuit. The random bits are extracted from crossed loop circuit which is composed of “OR” gate. Again the seed circuits are used here to enhance the unpredictability of generated number sequence and quality of random number. The proposed TRNG design is verified through QCADesigner tool 2.0.3, and its architecture is passed industry standard successfully. In area, latency, and energy point of view, the proposed 8-bit TRNG is consumed 0.36 um2 area, 1 QCA clock cycle latency, and 49.7 mev energy (per bit). So, proposed TRNG will be interpreted as a promising design in next-generation cryptography domain.

Triangular Neutrosophic Based Production Reliability Model of Deteriorating Item with Ramp Type Demand under Shortages and Time Discounting

Abstract: An economic production quantity model with triangular neutrosophic environment has been developed for deteriorating items with ramp type demand rate and reliability dependent unitproduction. The main objective of this paper is to determine the most cost effective production to generate better quality items under time discounting. Additionally, it is considered that the deterioration function deals with three parameters Weibull's distribution under finite time horizon. Moreover, it also considered the effect of shortages which are partially backordered and partially lost in sale. Here the reliability of the production process along with the production period is considered as decision variables. A numerical example is studied in both crisp and neutrosophic environment and a comparative analysis is performed here. It is observed that the model performs better in triangular neutrosophic arena ratherthan crisp domain. Finally, a sensitivity analysis of optimal solution is observed for some parameters and some crucial decision is taken with managerial insight.

Estimation of Power and Delay of CMOS Phase Detector and Phase-Frequency Detector Using Nano Dimensional MOS Transistor

Abstract: In this paper the design of phase detector circuit using nano dimensional transistor has been presented .The conventional circuit of phase-frequency detection has been realized and presented. The circuit schematics are simulated with the help of Tanner SPICE software. The power dissipation, transistor delay, product of power and delay of the phase detector circuit has been estimated at 16 nm and 22 nm gate length of transistor. Power and speed performance analysis is carried out varying the value of VDD in the range 0.5 V - 1.2 V and aspect ratio of PMOS to NMOS from 1 to 5 . Moreover, the power, gate delay and PDP of the phase-frequency detector has been stated at 150 nm channel length .The results are pleasing context to the design of Very Large Scale Integrated (VLSI) circuit having high speed and low power dissipation.

Prototype Model for Controlling of Soil Moisture and pH in Smart Farming System

Abstract: In this prototype model, soil moisture sensor and pH sensor are the main sensors used in an automated way. Here, the farming field has been divided into four numbers of zones according to moisture content and pH value. The optimum quantities and proportion of nitrogen, phosphorus, and potassium (NPK) values have been made based on balanced fertilization. For controlling, AVR microcontroller has been used with supporting modules like DS3231 RTC module, SD card module, servomotors, and GSM module. The desired requirement of water content in irrigation for different crops is measured, and accordingly, the frequency and quantity of water distribution in the irrigation system have been fixed up. A robotic hand-type mechanism has been made to supply water and fertilizer to different zones in the field whenever required. A message alert will automatically be sent to the phone of the farmer whenever the pump is turned ON for effective irrigation as well as balanced fertilization.

A Comparative Study on Slope Stability Analysis by Different Approaches

Abstract: Slope stability analysis is of particular significance to geotechnical engineers for construction of railway embankments, canal, road embankments, earth dams, etc. Slope failures can have devastating social and commercial impacts. To assess the safe design of slopes, factor of safety values acts significant roles. Factor of safety values is used to define how close or far slopes are from failure either occurring naturally or induced by manmade activities. Traditional limit-equilibrium method is the most common technique for analysis of slope. In recent times, finite element method (FEM), a powerful, viable alternative technique is available to the geotechnical engineers. In the present investigation, an attempt has been made to study the analysis of slope based on the numerical simulation using Geo-studio software. The parameters of soil strata constituting the slope are determined from laboratory results. The main objective of the present study is to indicate the correlation between factors of safety of embankment using different approaches, e.g., analytical approach and analysis as per “Guidelines for Earthwork in Indian Railway Projects” with finite element modeling. Finally, the paper presents the correlation between the slope angle and factor of safety for cohesive and cohesionless soil.

Utilization of LTEx Feynman Gate in Designing the QCA Based Reversible Binary to Gray and Gray to Binary Code Converters

Abstract: The Quantum-dot Cellular Automata explores a unique perspective in the arena of the architectural design of future quantum computers, precisely due to its ultra-low packing density, high operating speed, and low power dissipation. On the other side, reversible computing allows the implementation of extreme low power-consuming circuits by avoiding energy dissipation during the time of computation. In this paper, we have explored the QCA design of reversible binary to gray and gray to binary code converters based on the application of a unique model of Feynman gate using the layered T exclusive-OR module (abbreviated in this work as LTEx Feynman gate). We have proposed algorithms to produce multi-control reversible binary to gray and gray to binary code converters and to develop cost-efficient QCA layouts. Our systematic literature survey on the existing QCA designs of reversible binary to gray and gray to binary code converters helped us to compare and analyze the proposed design with the existing ones and identify it as the best design in terms of reversible, and QCA design metrics. Significant improvements in design metrics owing to successful experimentations over the previous designs are reported while instantiating 3X3,4X4, and 8X8 counterpart layouts.