scispace - formally typeset
Search or ask a question

Showing papers by "Chandigarh University published in 2019"


Journal ArticleDOI
TL;DR: This paper presents a detailed taxonomy on the applications, process models used, and communication infrastructure support needed to execute various applications in the execution of secure transactions on the blockchain.

241 citations


Journal ArticleDOI
TL;DR: BEST: a Blockchain-based secure energy trading scheme for electric vehicles (EVs) is proposed in this paper, and blockchain is used to validate EVs’ requests in a distributed manner, ensuring resilience against the single point of failure.

200 citations


Journal ArticleDOI
TL;DR: Results obtained prove that the proposed scheme is effective for trading the energy between EVs and CS while securing the underlying trading transactions using blockchain, and the communication and computation cost of the proposed framework comes out to be small which proves that it can be used in real-world applications.

174 citations


Journal ArticleDOI
TL;DR: In this article, an attempt has been made to evaluate the effectiveness of two cooling and lubrication techniques namely cryogenic cooling and hybrid nanoadditive-based minimum quantity lubrication (MQL).
Abstract: Owing to superior physio-chemical characteristics, titanium alloys are widely adopted in numerous fields such as medical, aerospace, and military applications. However, titanium alloys have poor machinability due to its low thermal conductivity which results in high temperature during machining. Numerous lubrication and cooling techniques have already been employed to reduce the harmful environmental footprints and temperature elevation and to improve the machining of titanium alloys. In this current work, an attempt has been made to evaluate the effectiveness of two cooling and lubrication techniques namely cryogenic cooling and hybrid nanoadditive–based minimum quantity lubrication (MQL). The key objective of this experimental research is to compare the influence of cryogenic CO2 and hybrid nanofluid–based MQL techniques for turning Ti–6Al–4V. The used hybrid nanofluid is alumina (Al2O3) with multi-walled carbon nanotubes (MWCNTs) dispersed in vegetable oil. Taguchi-based L9 orthogonal-array was used for the design of the experiment. The design variables were cutting speed, feed rate, and cooling technique. Results showed that the hybrid nanoadditives reduced the average surface roughness by 8.72%, cutting force by 11.8%, and increased the tool life by 23% in comparison with the cryogenic cooling. Nevertheless, the cryogenic technique showed a reduction of 11.2% in cutting temperature compared to the MQL-hybrid nanofluids at low and high levels of cutting speed and feed rate. In this regard, a milestone has been achieved by implementing two different sustainable cooling/lubrication techniques.

170 citations


Journal ArticleDOI
TL;DR: A smart security framework for VANETs equipped with edge computing nodes and 5G technology has been designed to enhance the capabilities of communication and computation in the modern smart city environment.
Abstract: With the exponential growth of technologies such as IoT, edge computing, and 5G, a tremendous amount of structured and unstructured data is being generated from different applications in the smart citiy environment in recent years. Thus, there is a need to develop sophisticated techniques that can efficiently process such huge volumes of data. One of the important components of smart cities, ITS, has led to many applications, including surveillance, infotainment, real-time traffic monitoring, and so on. However, its security, performance, and availability are major concerns facing the research community. The existing solutions, such as cellular networks, RSUs, and mobile cloud computing, are far from perfect because these are highly dependent on centralized architecture and bear the cost of additional infrastructure deployment. Also, the conventional methods of data processing are not capable of handling dynamic and scalable data efficiently. To mitigate these issues, this article proposes an advanced vehicular communication technique where RSUs are proposed to be replaced by edge computing platforms. Then secure V2V and V2E communication is designed using the Quotient filter, a probabilistic data structure. In summary, a smart security framework for VANETs equipped with edge computing nodes and 5G technology has been designed to enhance the capabilities of communication and computation in the modern smart city environment. It has been experimentally demonstrated that use of edge nodes as an intermediate interface between vehicle and cloud reduces access latency and avoids congestion in the backbone network, which allows quick decisions to be made based on the traffic scenario in the geographical location of the vehicles. The proposed scheme outperforms the conventional vehicular models by providing an energy-efficient secure system with minimum delay.

143 citations


Journal ArticleDOI
TL;DR: In this article, the impact of Er3+ doping on the response and selectivity of SnO2-based gas sensor has been investigated in detail, and it has been observed that specific surface area of nanoparticles has increased with increase in dopant concentration.
Abstract: In the present work, impact of Er3+ doping on the response and selectivity of SnO2 based gas sensor has been investigated in detail. X-ray diffraction (XRD) results confirmed formation of a tetragonal rutile structure of undoped and erbium doped SnO2 nanoparticles. It has been observed that specific surface area of nanoparticles has increased with increase in dopant concentration. The oxidation states and presence of erbium in SnO2 lattice has been confirmed by X-ray photoelectron spectroscopy (XPS). Photoluminescence (PL) analysis revealed that concentration of oxygen vacancies increases with increase in dopant incorporation. It has been observed that 3% Er-doped SnO2 sensor exhibited enhanced sensor response and temperature dependent selectivity towards ethanol and hydrogen at 240 and 360 ℃ respectively. The enhanced sensor response of the fabricated sensor has been ascribed to large surface area, enormous oxygen vacancies and elevated surface basicity of doped nanoparticles used. The tunable dual selectivity of 3% doped sensor towards ethanol and hydrogen makes it a perfect candidate for ethanol-hydrogen sensing for ethanol steam reforming systems combined to fuel cells.

125 citations


Journal ArticleDOI
TL;DR: In this article, the influence of pure cooling-lubrication (C/L) agents to reduce friction at faying surfaces can ameliorate overall machinability.
Abstract: In machining of soft alloys, the sticky nature of localized material instigated by tool-work interaction exacerbates the tribological attitude and ultimately demeans it machinability. Moreover, the endured severe plastic deformation and originated thermal state alter the metallurgical structure of machined surface and chips. Also, the used tool edges are worn/damaged. Implementation of cooling-lubrication (C/L) agents to reduce friction at faying surfaces can ameliorate overall machinability. That is why, this paper deliberately discussed the influence of pure C/L methods, i.e., such as dry cutting (DC) and nitrogen cooling (N2), as well as hybrid C/L strategies, i.e., nitrogen minimum quantity lubrication (N2MQL) and Ranque–Hilsch vortex tube (RHVT) N2MQL conditions in turning of Al 7075-T6 alloy, respectively. With respect to the variation of cutting speed and feed rate, at different C/Ls, the surface roughness, tool wear, and chips are studied by using SEM and 3D topographic analysis. The mechanism of heat transfer by the cooling methods has been discussed too. Furthermore, the new chip management model (CMM) was developed under all C/L conditions by considering the waste management aspects. It was found that the R-N2MQL has the potential to reduce the surface roughness up to 77% and the tool wear up to 118%. This significant improvement promotes sustainability in machining industry by saving resources. Moreover, the CMM showed that R-N2MQL is more attractive for cleaner manufacturing system due to a higher recyclability, remanufacturing, and lower disposal of chips.

106 citations


Journal ArticleDOI
TL;DR: A robust edge detection algorithm using multiple threshold approaches (B-Edge) is proposed to cover both the limitations encountered in edge detection: edge connectivity and edge thickness.
Abstract: An edge detection is important for its reliability and security which delivers a better understanding of object recognition in the applications of computer vision, such as pedestrian detection, face detection, and video surveillance. This paper introduced two fundamental limitations encountered in edge detection: edge connectivity and edge thickness, those have been used by various developments in the state-of-the-art. An optimal selection of the threshold for effectual edge detection has constantly been a key challenge in computer vision. Therefore, a robust edge detection algorithm using multiple threshold approaches (B-Edge) is proposed to cover both the limitations. The majorly used canny edge operator focuses on two thresholds selections and still witnesses a few gaps for optimal results. To handle the loopholes of the canny edge operator, our method selects the simulated triple thresholds that target to the prime issues of the edge detection: image contrast, effective edge pixels selection, errors handling, and similarity to the ground truth. The qualitative and quantitative experimental evaluations demonstrate that our edge detection method outperforms competing algorithms for mentioned issues. The proposed approach endeavors an improvement for both grayscale and colored images.

102 citations


Journal ArticleDOI
TL;DR: In this paper, the authors used advanced cooling lubrication, i.e., nanofluid assistance, besides dry and flood cooling, during machining and used as the basis for sustainability assessment.
Abstract: The constant pressure on the manufacturers to innovate and implement sustainable processes has triggered researching on machining with low carbon footprint, minimum energy consumption by machine tools, and improved products at the lowest cost—this is exactly done in this paper. Herein, the advanced cooling lubrication, i.e., nanofluid assistance, besides dry and flood cooling, during machining has been experimented, and used as the basis for sustainability assessment. This assessment is carried out in respect of surface quality and power consumption as well as the impact on environment, cost of machining, management of waste, and finally the safety and health issues of operators. For a better sustainability, a systematic optimization has been performed. In addition, the solution for an improved machinability has been proposed along with the statistically verified mathematical models of machining responses. Results showed that the nanofluid minimum quantity lubrication showed the most sustainable performance with a total weighted sustainability index 0.7, and it caused the minimum surface roughness and power consumption. The highest desirable (desirability = 0.9050) optimum results are the cutting speed of 116 m/min, depth of cut 0.25 mm, and feed rate of 0.06 mm/rev. Furthermore, a lower feed rate is suggested for better surface quality while for reduced power consumption the lower control factors are better.

95 citations


Journal ArticleDOI
TL;DR: The machinability of superalloy Inconel-800 has been investigated by performing different turning tests under MQL conditions, and MQL was found to be a better cooling technique when compared to the dry and the flood cooling.
Abstract: The manufacturing of parts from nickel-based superalloy, such as Inconel-800 alloy, represents a challenging task for industrial sites. Their performances can be enhanced by using a smart cutting fluid approach considered a sustainable alternative. Further, to innovate the cooling strategy, the researchers proposed an improved strategy based on the minimum quantity lubrication (MQL). It has an advantage over flood cooling because it allows better control of its parameters (i.e., compressed air, cutting fluid). In this study, the machinability of superalloy Inconel-800 has been investigated by performing different turning tests under MQL conditions, where no previous data are available. To reduce the numerous numbers of tests, a target objective was applied. This was used in combination with the response surface methodology (RSM) while assuming the cutting force input (Fc), potential of tool wear (VBmax), surface roughness (Ra), and the length of tool–chip contact (L) as responses. Thereafter, the analysis of variance (ANOVA) strategy was embedded to detect the significance of the proposed model and to understand the influence of each process parameter. To optimize other input parameters (i.e., cutting speed of machining, feed rate, and the side cutting edge angle (cutting tool angle)), two advanced optimization algorithms were introduced (i.e., particle swarm optimization (PSO) along with the teaching learning-based optimization (TLBO) approach). Both algorithms proved to be highly effective for predicting the machining responses, with the PSO being concluded as the best amongst the two. Also, a comparison amongst the cooling methods was made, and MQL was found to be a better cooling technique when compared to the dry and the flood cooling.

94 citations


Journal ArticleDOI
TL;DR: The objectives of SAFE include: first, an offloading scheme to support edge–cloud interplay, second, an SDN-assisted virtualized flow management scheme, and, third, a secure Lattice-based cryptosystem.
Abstract: Improved quality of life has lead the healthcare industry to geographically expand and support real-time services. Following this trend, a surge of healthcare monitoring devices has substantially overgrown in the global market. These devices tend to generate data in humongous quantity that need real-time analysis with seamless and secure transmission to the computing nodes. The existing computing and networking infrastructures fall short to cater the services with desirable quality of service. Hence, to overcome these challenges, the proposed work presents a comprehensive platform referred as software defined network ( SDN) Assisted Framework for Edge–Cloud Interplay in Secure Healthcare Ecosystem ( SAFE ). The objectives of SAFE include: first, an offloading scheme to support edge–cloud interplay, second, an SDN-assisted virtualized flow management scheme, and, third, a secure Lattice-based cryptosystem. Finally, the proposed scheme is validated on different performance parameters. Additionally, a security evaluation of the designed cryptosystem is also presented. The results obtained indicate the supremacy of the designed framework.

Journal ArticleDOI
TL;DR: It was shown that RHVT improved the results by nearly 15% for all of the responses, while the TLBO technique was found to be the best optimization technique, with an average time of 1.09 s and a success rate of 90%.
Abstract: Environmental protection is the major concern of any form of manufacturing industry today. As focus has shifted towards sustainable cooling strategies, minimum quantity lubrication (MQL) has proven its usefulness. The current survey intends to make the MQL strategy more effective while improving its performance. A Ranque⁻Hilsch vortex tube (RHVT) was implemented into the MQL process in order to enhance the performance of the manufacturing process. The RHVT is a device that allows for separating the hot and cold air within the compressed air flows that come tangentially into the vortex chamber through the inlet nozzles. Turning tests with a unique combination of cooling technique were performed on titanium (Grade 2), where the effectiveness of the RHVT was evaluated. The surface quality measurements, forces values, and tool wear were carefully investigated. A combination of analysis of variance (ANOVA) and evolutionary techniques (particle swarm optimization (PSO), bacteria foraging optimization (BFO), and teaching learning-based optimization (TLBO)) was brought into use in order to analyze the influence of the process parameters. In the end, an appropriate correlation between PSO, BFO, and TLBO was investigated. It was shown that RHVT improved the results by nearly 15% for all of the responses, while the TLBO technique was found to be the best optimization technique, with an average time of 1.09 s and a success rate of 90%.

Journal ArticleDOI
TL;DR: The almond skin powder is one of the biodegradable and biocompatible food wastes that can be used as reinforcement in polylactic acid (PLA) for preparation of biomedical scaffolds/implants as mentioned in this paper.
Abstract: The almond skin powder is one of the biodegradable and biocompatible food wastes that can be used as reinforcement in polylactic acid (PLA) for preparation of biomedical scaffolds/implants (for hig...

Journal ArticleDOI
TL;DR: In this article, a novel heat treatment approach has been utilized to improve the overall performance of printed parts by changing the levels of temperature (105, 115, and 125°C) and time duration (20, 25, and 30 min).
Abstract: Fused filament fabrication (FFF), an economic additive manufacturing (AM) method, is largely used for the fabrication of customized components (of medical, engineering, architectural, toy, artistic, etc. industries). However, the poor mechanical and surface properties are critical barriers limiting the growth of FFF. Therefore, a novel heat treatment approach has been utilized to improve the overall performance of printed parts. The parts were made with acrylonitrile-butadiene-styrene (ABS) with three infill densities (20, 60, and 100%) and annealing was carried out by changing the levels of temperature (105, 115, and 125 °C) and time duration (20, 25, and 30 min). The experimental design was conducted by Taguchi orthogonal array while the optimization was conducted using Taguchi S/N approach. The investigated responses were surface roughness, hardness, dimensional accuracy, tensile strength, flexural strength, and impact strength. Moreover, the reliability of the mechanical properties, with higher error (α > 5%), was verified by using the Weibull statistic to determine the survival rate of annealed FFF parts for functional applications. The adopted annealing approach was found to improve the physical and mechanical properties. The SEM analysis of fractured specimens revealed the type of failure (ductile or brittle). In recapitulation, the annealing process improved the quality characteristics of FFF parts.

Journal ArticleDOI
TL;DR: The novelty/robustness of the present study is represented by its great contribution to solve practical industrial application when is developed a new process using different CBN grades for hard turning and die makers of workpiece having the hardness between 45 and 55 HRC.
Abstract: Now-a-days, the application of hard tuning with CBN tool has been massively increased because the hard turning is a good alternative to grinding process. However, there are some issues that need to be addressed related to the CBN grades and their particular applications in the area of hard turning process. This experimental study investigated the effects of three different grades of CBN insert on the cutting forces and surface roughness. The process of hard turning was made using the AISI H13 die tool steel at containing different hardness (45 HRC, 50 HRC and 55 HRC) levels. The work material were selected on the basis of its application in the die making industries in a range of hardness of 45–55 HRC. Optimization by the central composite design approach has been used for design and analysis. The present study reported that the cutting forces and surface roughness are influenced by the alloying elements and percentage of CBN in the cutting tool material. The work material hardness, feed rate and cutting speed are found to be statistically significant on the responses. Furthermore, a comparative performance between the three different grades of CBN inserts has been shown on the cutting forces and surface roughness at different workpiece hardness. To obtain the optimum parameters from multiple responses, desirability approach has been used. The novelty/robustness of the present study is represented by its great contribution to solve practical industrial application when is developed a new process using different CBN grades for hard turning and die makers of workpiece having the hardness between 45 and 55 HRC.

Journal ArticleDOI
TL;DR: A renewable energy-aware multi-indexed job classification and scheduling scheme using container as-a-service for data centers sustainability and results obtained prove 15%, 28%, and 10.55% higher energy savings in comparison to the existing schemes of its category.
Abstract: Cloud computing has emerged as one of the most popular technologies of the modern era for providing on-demand services to the end users. Most of the computing tasks in cloud data centers are performed by geodistributed data centers which may consume a hefty amount of energy for their operations. However, the usage of renewable energy resources with appropriate server selection and consolidation can mitigate the energy related issues in cloud environment. Hence, in this paper, we propose a renewable energy-aware multi-indexed job classification and scheduling scheme using container as-a-service for data centers sustainability. In the proposed scheme, incoming workloads from different devices are transferred to the data center which has sufficient amount of renewable energy available with it. For this purpose, a renewable energy-based host selection and container consolidation scheme is also designed. The proposed scheme has been evaluated using Google workload traces. The results obtained prove 15%, 28%, and 10.55% higher energy savings in comparison to the existing schemes of its category.

Journal ArticleDOI
TL;DR: ECCAuth: a novel elliptic curve cryptography-based authentication protocol is proposed in this paper for preserving demand response in SG and shows that ECCAuth can withstand several known attacks.
Abstract: The devices in smart grids (SG) transfer data to a utility center (UC) or to the remote control centers. Using these data, the energy balance is maintained between consumers and the grid. However, this flow of data may be tampered by the intruders, which may result in energy imbalance. Thus, a robust authentication protocol, which supports dynamic SG device validation and UC addition, both in the local and global domains, is an essential requirement. For this reason, ECCAuth: a novel elliptic curve cryptography-based authentication protocol is proposed in this paper for preserving demand response in SG. This protocol allows establishment of a secret session key between an SG device and a UC after mutual authentication. Using this key, they can securely communicate for exchanging the sensitive information. The formal security analysis, informal security analysis, and formal security verification show that ECCAuth can withstand several known attacks.

Journal ArticleDOI
TL;DR: A novel multi-objective differential evolution based random forest technique is proposed that is able to tune the parameters of random forest in an efficient manner and outperforms existing techniques in terms of accuracy, f-measure, sensitivity and specificity.
Abstract: Many machine learning techniques have been used in past few decades for various medical applications. However, these techniques suffer from parameter tuning issue. Therefore, an efficient tuning of...

Journal ArticleDOI
TL;DR: A model grounded in the purchaser-brand relationship theory of remarketing is developed in order to develop the consumer-Brand relationship through mediator brand experience (BE) and moderator digital footprint and confirms that the comprehensive consumption values are the major influencing factors in the adoption of branded apps.

Journal ArticleDOI
25 Oct 2019
TL;DR: In this paper, the authors propose an integrated nexus modeling framework co-designed with regional stakeholders from the four riparian countries of the Indus River Basin and discuss challenges and opportunities for developing transformation pathways for the basin's future.
Abstract: The Indus River Basin covers an area of around 1 million square kilometers and connects four countries: Afghanistan, China, India, and Pakistan. More than 300 million people depend to some extent on the basin’s water, yet a growing population, increasing food and energy demands, climate change, and shifting monsoon patterns are exerting increasing pressure. Under these pressures, a “business as usual” (BAU) approach is no longer sustainable, and decision makers and wider stakeholders are calling for more integrated and inclusive development pathways that are in line with achieving the UN Sustainable Development Goals. Here, we propose an integrated nexus modeling framework co-designed with regional stakeholders from the four riparian countries of the Indus River Basin and discuss challenges and opportunities for developing transformation pathways for the basin’s future.

Journal ArticleDOI
TL;DR: Green synthesized nanoparticles can be used as an alternative in management of MDR infection at least for tropical application after careful in vivo validation.

Journal ArticleDOI
TL;DR: Through extensive analysis, it has been found that GPP based dehazing can effectively suppress visual artefacts for hazy images and yield high-quality results as compared to the competitive dehazed techniques both quantitatively and qualitatively.
Abstract: The dehazing techniques designed so far are not so-effective at preserving texture details, especially in case of a complex background and large haze gradient image. Therefore, the exploration of new alternatives for designing an effective prior is desirable. Thus, in this research work, Gradient profile prior (GPP) is designed to evaluate depth map from hazy images. The transmission map is also improved by utilizing Guided anisotropic diffusion and iterative learning based image filter (GADILF). The restoration model is also improved to reduce the effect of pixels saturation and color distortion from restored images. Performance analysis demonstrates that GPP can naturally restore the hazy image especially at the edges of sudden changes in the obtained depth map. Through extensive analysis, it has been found that GPP based dehazing can effectively suppress visual artefacts for hazy images and yield high-quality results as compared to the competitive dehazing techniques both quantitatively and qualitatively. Moreover, the relatively high computational speed of the proposed technique will facilitate it in real-time applications.

Journal ArticleDOI
TL;DR: The taxonomy of two major problems, namely, the shortest path and the closest path problems with respect to the applicability of lattice-based cryptographic primitives for IoT devices, and various LB-PKC techniques, such as NTRU, learning with errors, and ring-LWE (R-L THE AUTHORS) which are often used to solve shortest paths and lattice NP-hard problems in a polynomial time are discussed.
Abstract: Due to its widespread popularity and usage in many applications (smart transport, energy management, ${e}$ -healthcare, smart ecosystem, and so on), the Internet of Things (IoT) has become popular among end users over the last few years. However, with an exponential increase in the usage of IoT technologies, we have been witnessing an increase in the number of cyber attacks on the IoT environment. An adversary can capture the private key shared between users and devices and can launch various attacks, such as IoT ransomware, Mirai botnet, man-in-the-middle, denial of service, chosen plaintext, and chosen ciphertext. To mitigate these security attacks on the IoT environment, the traditional public key cryptographic primitives are inadequate because of their high computational and communication costs. Therefore, lattice-based public-key cryptosystem (LB-PKC) is a promising technique for secure communication. We discuss the taxonomy of two major problems, namely, the shortest path and the closest path problems with respect to the applicability of lattice-based cryptographic primitives for IoT devices. Moreover, we also discuss various LB-PKC techniques, such as NTRU, learning with errors (LWEs), and ring-LWE (R-LWE) which are often used to solve shortest path and lattice NP-hard problems in a polynomial time. We further classify the R-LWE into three categories, namely identity-based encryption, homomorphic encryption, and secure authentication key exchange. We describe the operations and algorithms adopted in each of these encryption mechanisms. Finally, we discuss the challenges, open issues, and future directions for applying LB-PKC in the IoT environment.

Journal ArticleDOI
TL;DR: A multi-leader multi-follower Stackelberg game for energy trading is proposed by assuming EVs as the consumers and CSs as energy providers, and a dynamic pricing scheme designed by taking parameters such as electricity usage, time-of-use, location, and type of EVs.

Journal ArticleDOI
TL;DR: From the soft computing modeling results, it has been observed that the HPSOSA improved the process performance and has revealed the global optimal solution within minimum interval of time.
Abstract: Recently, the pulsed current tungsten arc welding process (PC-TAW) has cemented their potential in various sorts of industrial application such as automobile, aerospace, and structural joining. However, the involvement of multiple process parameters in PC-GTAW process usually makes the process cumbersome to understand; and thereby, it is difficult to develop the mathematical model. Here, in this scientific work, the major efforts have been made to optimize multiple parameters for selected output responses through the use of evolutionary computational approaches. For this purpose, the particle swarm optimization (PSO), simulated annealing (SA) algorithm, and hybrid PSO-SA (HPSOSA) techniques have been employed and compared in terms of the quality responses for input parameters. From the soft computing modeling results, it has been observed that the HPSOSA improved the process performance and has revealed the global optimal solution within minimum interval of time. The developed models were statistically significant at 95% confidence interval. The experimental and mathematical outcomes for the welded specimens are duly supported with microscopic analyses.

Journal ArticleDOI
TL;DR: M moth flame optimization based threshold-sensitive energy-efficient clustering protocol (TECP) is proposed to extend the stability period of the network and significantly outperforms existing protocols in terms of energy consumption, system lifetime and stability period.
Abstract: The widespread use of wireless sensor devices and their advancements in terms of size, deployment cost and user friendly interface have given rise to many applications of wireless sensor networks (WSNs). WSNs need to utilize routing protocols to forward data samples from event regions to sink via minimum cost links. Clustering is an efficient data aggregation method that effectively reduces the energy consumption by organizing nodes into groups. However, in clustering protocols, CH has to bear an additional load for coordinating various activities within the cluster. Therefore, proper CH selection and their load balancing using efficient routing protocol is a critical aspect for the long run operation of WSN. Clustering a network with proper load balancing is an NP-hard problem. To solve such problems having vast search area, optimization algorithm is the preeminent possible solution. In this paper, moth flame optimization (MFO) based threshold-sensitive energy-efficient clustering protocol (TECP) is proposed to extend the stability period of the network. Multi-hop communication between CHs and BS is utilized using MFO to achieve optimal link cost for load balancing of distant CHs and energy minimization. Analysis and simulation results demonstrate that the proposed methodology significantly outperforms existing protocols in terms of energy consumption, system lifetime and stability period.

Journal ArticleDOI
TL;DR: In this article, a novel PMMA-g-Alg@Cys-Bentonite (BAPM) nanocomposite was synthesized by in situ chemical oxidative polymerization of methyl methacrylate in a colloidal solution of Alg/Cysbent.

Journal ArticleDOI
TL;DR: The proposed genetic algorithm (GA)-based threshold-sensitive energy-efficient routing protocol (TERP) is proposed to prolong network lifetime and significantly outperforms existing protocols in terms of energy consumption, system lifetime and stability period.
Abstract: The widespread use of wireless sensor devices and their advancements in terms of size, deployment cost and user-friendly interface have given rise to many applications of wireless sensor networks (WSNs). WSNs need to utilize routing techniques to forward data samples from event regions to sink via minimum cost links. Clustering is a commonly used data aggregation technique in which nodes are organized into groups in order to reduce the energy consumption. However, in clustering protocols, cluster-head (CH) has to bear an additional load for coordinating various activities within the cluster. Therefore, proper CH selection and their load balancing using efficient routing protocol is a critical aspect for the long-run operation of WSN. In this paper, genetic algorithm (GA)-based threshold-sensitive energy-efficient routing protocol (TERP) is proposed to prolong network lifetime. Multi-hop communication between CHs and base station (BS) is utilized using GA to achieve optimal link cost for load balancing of distant CHs and energy minimization. The paper also considers stability-aware model of TERP named stable TERP (STERP) so as to extend the stability period (time interval from initial time to the death of first node) of the network. In STERP, energy-aware heuristics is applied for CH selection in order to improve the stability period. Analysis and simulation results demonstrate that the proposed methodology significantly outperforms existing protocols in terms of energy consumption, system lifetime and stability period.

Journal ArticleDOI
TL;DR: In this paper, Ni 20Cr and Ni 5Al wires were used to deposit coatings on T22 and SA516 boiler steels for protection in high temperature environment, and the microstructure, mechanical properties and high temperature oxidation behavior of the deposited coatings were studied.

Journal ArticleDOI
TL;DR: In this article, the benefits of Al2O3 and palm oil-mixed nano-fluid in MQL-assisted milling of Inconel 690 for eco-benign and cleaner manufacturing were investigated.
Abstract: With the increased prerequisites for ecological protection, the vegetable oil and nano-fluid-based minimum quantity lubrication (MQL) technology have become a modern research trend. For instance, the palm oil exhibits superior lubricity owing to fatty acid and film-developing characteristics of the carboxyl group. Conversely, due to unique physiochemical properties of Al2O3 nano-particles, they exhibit superior lubricity during machining operations. Thus, here, it was attempted to discover the benefits of Al2O3 and palm oil–mixed nano-fluid in MQL-assisted milling of Inconel 690 for eco-benign and cleaner manufacturing. During the experiment, different concentrations (0.5–5%) of Al2O3 nano-particles were mixed with palm oil. Afterward, the performances were evaluated with respect to the surface roughness, specific cutting energy, tool wear, and cutting temperature. From an economic perspective, the determination of ideal concentration (%) of the Al2O3 nano-particle is a crucial concern. Thus, a fuzzy interference system (FIS)–based model has been developed to obtain the optimum concentration (%) of Al2O3 nano-particle. The multi-performance characteristics index (MPCI) values confirmed that 2.5% was the optimum concentration for Al2O3 in MQL milling environment. Afterward, the machining performances obtained from 2.5% Al2O3 particle concentration have been compared with dry, flood, and pure palm oil condition. It is clearly found from the comparison that MQL milling with 2.5% Al2O3 nano-particle concentration demonstrated much better machining behavior than another lubricating medium.