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Interval-Valued Fuzzy Trees and Cycles
Interval-valued fuzzy tree (IVFT) and interval-valued fuzzy cycle (IVFC) are defined in this chapter. We characterize interval-valued fuzzy trees. We also prove that if G is an IVFG whose underlying crisp graph is not a tree then G is an IVFT if and only if G contains only ? strong arcs and weak arcs. It is shown that an IVFG G whose underlying crisp graph is a cycle is an IVFC if and only if G has at least two ? strong arcs. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Structural and morphological characterization of hydrothermally synthesized N-Carbon Dot @ Fe3O4 composites for heavy metal ion detection
Heavy Metal-ion contamination is one of the most serious issues facing day-to-day life. To address this issue, sensing and removal of heavy metal ions in contaminated water become indispensable. Carbon Dots are hydrophilic in nature with magnificent electron acceptor and electron donator and hence it has been used as fluorescent probes for sensing applications. The present study deals with the synthesis of N-Carbon Dot (N-CD) @ Fe3O4 composite which was successfully fabricated via the hydrothermal method. The surface structure and morphology of the synthesized composite were characterized using X-Ray Diffraction (XRD) and Scanning Electron Microscopy (SEM). The elemental analysis of a sample was characterized using Energy Dispersive Spectroscopy (EDS). Further, the phase occurrence and the molecular vibration were analysed using XRD and Fourier Transform Infra-Red Spectroscopy (FTIR). Finally, the optical studies were measured using Ultravioletvisible Spectroscopy (UV Vis) and Photoluminescence Spectroscopy (PL). The prepared composite exhibited noticeable fluorescence properties and has promising potential for the detection and removal of toxic heavy metal ions in water. 2022 -
P4 based Load Balancing Strategies for Large Scale Software-Defined Networks
To meet the large demands of future networks, several large-scale Software Defined Networking (SDN) test-beds have been designed. The increasing complexity of networks has resulted in convoluted methods for managing and orchestrating efficiently across a wide range of network environments. The load balance function is impaired when the controller fails to connect with the switches. A traditional Load Balancer (LB) must decapsulate layers one by one and get the information needed to run load balancing algorithms. For instance, OpenFlow, NetConf, Programming Protocol-independent Packet Processors (P4), and Data Plane Developement Kit (DPDK) provide network programmability at both the control and data plane levels. In this paper, authors implement load balancing using the P4 programming language without the need of a controller, the P4 load balancer can operate on its own. Controller's support is used to keep track on the health of the web servers. In this situation, the controller can identify a server failure and notify the P4 load balancer, which will restrict requests to the malfunctioning server, lowering the dispatching failure rate. A detailed investigation of various load balancing mechanisms is analysed in this paper followed by the identification of four potential approaches to large-scale SDN tests, including connection hash, weighted round-robin, DPDK technique, a Stateless Application-Aware Load-Balancer (SHELL). 2022 IEEE. -
Significance of extra-framework monovalent and divalent cation motion upon CO2 and N2 sorption in zeolite X
Experimental observations and the GCMC (Grand Canonical Monte Carlo) simulations with fixed and mobile cations in their cavities have been used to study nitrogen and carbon dioxide sorption in divalent cation (Ca, Sr, and Ba) exchanged Zeolite X. Simulations of carbon dioxide and nitrogen adsorption isotherms and the heat of adsorption in divalent cation exchanged zeolite X produced results that were similar to those found in experimental results. Both experimental and simulated isotherms showed that carbon dioxide adsorption capacity is saturated at lower pressure with high adsorption capacity than the nitrogen isotherm in all zeolite samples. In the order of electronegativity of the extra-framework cations, the isosteric heat of sorption results show that carbon dioxide as well as nitrogen molecules interact more with divalent metal ion exchanged zeolites. Simulations of carbon dioxide and the nitrogen sorption in zeolite -X revealed that the mobile extra-framework cations in the cages of zeolite X had a significant advantage over zeolite molecular sieves in the separation process. The simulation with mobile cations can be a good tool for developing selective and purposeful zeolite-based adsorbents by knowing the cation position and its migration upon the adsorption of various gases. 2022 -
Recurrent Neural Networks in Predicting the Popularity of Online Social Networks Content: A Review
An online social network is a web platform that individuals use to make social relationships with people who share similar interests, activities, connections, and backgrounds. All online social networks differ in the number of features they provide and their format. In recent years, drastic growth has been seen in the users of online social networks like Flickr, Instagram, Pinterest, Twitter, etc. Among all the features of online social networks, content sharing is the one being widely used by individual users and large organizations. Due to this, content popularity prediction has been extensively studied nowadays, considering various aspects related to it. The study throws light on the use of machine learning techniques in this field. Various algorithms have been used to handle popularity prediction, including classification, regression, and clustering techniques. It is feasible to extract the essential information from such content using machine learning algorithms and utilize the retrieved information in a variety of ways, the majority of which are commercial in nature. The goal of this study is to review and analyze various recurrent neural network (RNN) approaches for predicting the popularity of social media content. The Electrochemical Society -
AI and Machine Learning Enabled Software Defined Networks
The telecommunications industry has not been exempt from the technology sectors massive artificial intelligence (AI) and machine learning (ML) boom in recent years. Artificial intelligence (AI) and machine learning (ML) provide advanced analytics and automation that are in line with modern networking concepts like software-defined networking (SDN) and software-defined wide-area networks (SD-WAN). Work is being done to determine how AI/ML can benefit SD-WAN and to demonstrate these benefits in a real SD-WAN network using a workable example. Modern ML techniques and algorithms are the extent of AI/ML. Todays Internet is under constant threat from DDoS (Distributed Denial of Service) attacks. As the volume of Internet traffic grows, its getting harder and harder to tell whats legitimate and whats malicious. The DDoS attack was detected using a machine learning approach that makes use of a Random Forest classifier. To better detect DDoS attacks, we tweak the Random Forest algorithm. The proposed machine learning approach outperforms, as demonstrated by our results. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Smart Precision Irrigation Techniques Using Wireless Underground Sensors in Wireless Sensors
The term brilliant accuracy agribusiness alludes to advances like the Internet of Things, remote sensors, and artificial reasoning on the ranch. A definitive objective of this paper is to expand the quality and amount of the harvests while advancing the human work utilized, use of water system, and diminishing the water system times in light of climate forecast. This proposed framework utilizes the three kinds of sensors like Moisture sensor is used to detect the dirt dampness, the Humidity sensor is utilized to return how much water is present in the encompassing air, Temperature sensors are utilized to give the temperature of the dirt. Each of the three qualities is passed to the remote sensor hub and moved to the information lumberjacks. At long last, the information lumberjack will send the message like beginning the water system to a programmed water lock framework. When all water measures arrive at the water system limit, the programmed water lock framework will be shut. By using the underground, remote sensors, we can track the conditions of various agricultural applications such as soil properties, seed varieties and monitor the environmental situations. Every gadget contains significant gear like sensors, memory, a processor, and a power source. 2022 IEEE. -
Lithium photodisintegration with unpolarized photon beams at near threshold energies
The study of photonuclear reactions with lithium targets i.e. photodisintegration of lithium in addition to other photonuclear reactions is of considerable interest to the fields of nuclear physics, astrophysics, laser physics and several applications such as non - destructive testing of nuclear materials. We propose to study photodisintegration of lithium with unpolarized photon beams at near threshold energies. Our model independent theoretical approach, which makes use of irreducible tensor techniques, is well suited for making predictions on the spin observables as well as the differential cross section. In this paper we analyze the reaction channel 7Li + ? ? 6Li + n by using unpolarized photons. 2022 -
A Road to Become Successful in The Fashion Industry of China: A Case Study of Zara
In this research, it was found that Zara is facing issues while maintain its profitability and also while maintaining its large stores. Existing information collected from websites and articles show that Zara provides inferior quality products, does not have factory in China, focuses less on e-commerce activities and contributes directly to environment pollution through waste generation in China. These are reasons that the organization is losing its brand image in China. To improve its current condition, it is recommended that Zara should improve its products, focus more on marketing, develop factories in China and reduce environment pollution. The Electrochemical Society -
Customer Segmentation in the Field of Marketing
The motive of this work is to classify and categorize customers depending on their familiar traits/characteristics so as to enable a company or a firm to adequately market their products to each category more attractively and competently. It is imperative for a firm to educate themselves with each and every detail about the customer, such as age group, sexuality, social class, purchase pattern etc as it paves way for customer segmentation. Businesses may utilize segmentation to make better use of their marketing resources, get a competitive advantage over competitors, and, most importantly, display a deeper understanding of their consumers' requirements and desires. Customer segmentation, when combined with customer targeting and positioning, creates the foundation for strategic marketing. A manager can find new marketing possibilities and create or adjust the product to satisfy the demands of potential clients using the notion of strategic marketing. The product's quality level determines its position in the market's overall offering. It's a crucial aspect in selecting which market segment a collection will target. The commercial world has gotten more competitive over time, as enterprises like these have to fulfil their consumers' demands and aspirations, attract new customers, and enhance their bottom lines. In this research, I have put the spotlight on the information used by firms for the purpose of customer segmentation in the most valuable manner. In addition to that, I have portrayed different models of customer segmentation and the benefits reaped by a business in implementing them. 2022 IEEE. -
Plasma sprayed magnesium aluminate and alumina composite coatings from waste aluminum dross
The absence of structured waste management practices for tons of black aluminum dross (Al-dross) when land-filled affects the ecosystem we live in. Researchers and technologists are now working towards three goals (a) minimization of Al-dross production (b) reducing its toxic effects on the environment and (c) treating the Al-dross to beneficiate useful materials from it in an environmentally friendly manner and to generate useful industrial products. The third aspect has been addressed in this study. Al-dross is an aluminum industry generated waste that mainly contains Al metal (oxidized during processing), Aluminum Nitride (AlN), ?-aluminum oxide (?-Al2O3) and magnesium aluminate (MgAl2O4). The oxides are highly suitable for refractory and thermally insulating material applications, but AlN is detrimental for two reasons - (a) thermal conductivity higher than the oxides and (b) carcinogenic gas evolution during processing. Hence AlN must be removed from Al-dross for further processing into refractories. In this work, AlN with minor quantities of halides were removed from Al-dross to extract the major useful refractory oxide constituents in an environmentally friendly manner. The process methodology involved sieving Al-dross to < 600 m particles, aqueous media treatment to remove the nitrides in the form of NH3 gas, oven drying and calcination at 10001150 C for 2 h (in an electrical muffle furnace in ambient air atmosphere) to obtain a mixture of the composite oxide powder of ? 99.0% purity. The calcined compound was mixed with suitable organic binders and sieved to obtain plasma sprayable powder and plasma spray-coated onto bond coated (commercial NiCrAlY) steel substrates. XRD and SEM with EDS facility were used to characterize the powders and coatings. A polished metallographic cross-section was prepared to study the microstructure and interface characteristics. The findings are presented. 2022 -
Machine Learning Model for Depression Prediction during COVID-19 Pandemic
Depression is an unfamous mental health disorder that has affected half the population worldwide. In December 2019, the break of the COVID-19 pandemic was first spotted in Wuhan, China, and later spread to 212 countries and territories worldwide, impacting half the population. It took a significant toll on their physical health and their mental health. Many among the population lost their loved ones, businesses, and being in quarantine for years, completely shifted to the online mode made everyone's life miserable. Many may be dealing with escalated levels of alcohol and drug use, sleeplessness, and an anxious state of mind. So, the need to address this and help the severely affected ones is significant. Self-quarantine also causes additional stress and challenges the mental health of citizens. This paper intends to identify the people who were mentally affected by the pandemic using machine learning techniques. A survey was conducted among college-going students and professionals. The paper used classification techniques such as Naive Bayes, KNN, Random Forest, Logistic Regression, k-fold cross-validation to get results. Support Vector Machine gave the maximum accuracy of 99.35%. 2022 IEEE. -
Utilisation of Virtual Assistant and Its Impact on Retail Industry
Virtual assistant is nothing but an independent contractor, who offers administrative services to the clients of a particular organisation while operating outside of the office of the client. Generally, a virtual assistant operates from a home-based office. This virtual assistant application has the ability to access the required planning documents, such as shared calendars. The contemporary retail organisations like e-commerce companies in this competitive global business environment are using virtual assistant to enhance omnichannel experience, 24/7 customer service, order tracking, and product recommendations. Overall, virtual assistant helps the organisations in enhancing social media management activities. This concept of the use of virtual assistant has been significantly emerged after the increase in demands for e-commerce business activities in this decade. Research objectives related to the title of this research are developed and listed. Relevant theories on virtual assistant are applied in the literature review section of this study. The researcher has decided to adopt qualitative research methodology to achieve the objectives of the research. Moreover, the researcher has considered secondary data analysis approach to conduct this research. In terms of findings, it has been identified that virtual assistant has a positive impact on the business operation activities of retail organisations. Authentic secondary sources are considered to collect and analyse the data. Some challenges associated with the utilisation of virtual assistant also have been identified in the findings section. Some valuable recommendations are suggested for the future researchers to overcome those identified associated challenges. 2022 IEEE. -
Workplace spirituality in the Indian IT sector: development and validation of the scale
The Indian information technology (IT) sector faces a unique challenge of managing their knowledge workers. Workplace spirituality, defined as recognising employees as a spiritual being, is seen as a new solution to the challenges faced by the IT sector. There are many conceptual models, but very few empirical ones to measure spirituality at work in the Indian context. The present study aims to develop an instrument that measures workplace spirituality. In-depth interviews were conducted with 20 IT professionals and seven themes emerged from these interviews, based on which a 66-item questionnaire was developed which was further reduced to 33 items as per recommendations from experts. The questionnaire was administered to 172 Indian IT professionals and its reliability and construct validity were determined using convergent and discriminant validity. As a future scope, the questionnaire could be tested in other sectors and suitable changes be generalised in the Indian context. Copyright 2022 Inderscience Enterprises Ltd. -
A Study of Preprocessing Techniques on Digital Microscopic Blood Smear Images to Detect Leukemia
Digital microscopic blood smear images can get distorted due to the noise as a result of excessive staining during slide preparation or external factors during the acquisition of images. Noise in the image can affect the output of further steps in image processing and can have an impact on the accuracy of results. Hence, it is always better to denoise the image before feeding it to the automatic diagnostic system. There are many noise reduction filters available; the selection of the best filter is also very important. This paper presents a comparative study of some common spatial filters like wiener filter, bilateral filter, Gaussian filter, median filter and mean filter which are efficient in noise reduction, along with their summary and experimental results. Performing comparative analysis of result based on PSNR, SNR and MSE values, it can be determined that median filter is most suitable method for denoising digital blood smear images. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Comparison of DQ Method with I cos? Controller in Solar Power System Connected to Grid with EV Load
Electric Vehicles and Photovoltaic power generation integrated to grid introduces power quality issues. Power quality issues during power integration needs improvement. Control of grid interfaced converters improves grid side power quality in integrated solutions. Power injection to the grid is controlled to get rid of power quality issues. Control techniques that can improve the power injection to the grid needs to be analyzed. This paper compares DQ and I cos ? controller while PV and EVs with non-linear loads are also connected in the power grid. Performance evaluation of both controllers are analyzed by comparing power injection to the grid. 2022 IEEE. -
CNN based Model for Severity Analysis of Diabetic Retinopathy to aid Medical Treatment with Ayurvedic Perspective
One among the major modern life-style diseases is Diabetes. Diabetic Retinopathy is a major cause for blindness even at an early age. Clinical assessments for eye disease are done using visual examinations and probing. Retinal vessel segmentation is an important technique which helps in detection of changes that happens in blood vessel as well as gives information regarding the location of vessels. The work presented in this paper tries to detect and analyze the changes occurred in the blood vessels of human retina caused by diabetic retinopathy. Using digital imaging techniques, the severity screening technique facilitates the diagnosis of diabetic retinopathy. The model works in such a way that it helps the Ayurvedic treatment methodology for Diabetic Retinopathy. Results are obtained to categorize the data elements according to the severity of the disease and different classifications. 2022 IEEE. -
Approach for Preprocessing in offline Optical Character Recognition (OCR)
offline optical character recognition (offline OCR) is one of the important applications of pattern recognition. To achieve a better recognition result, the input character images must have good quality. That is why the preprocessing step be-comes essential for any image identification task. Lots of research has been performed in numerous jobs towards this preprocessing in the literature. Here, an attempt has been made to summarize different procedures and aspects of preprocessing adopted in implementing these preprocessing techniques. This is done in the hope that this may help the research community towards the gaining of knowledge of different preprocessing techniques used in offline OCR. offline OCR has several applications, such as old manuscript digitization, signature authentication, bank cheque automatic clearance and postal letter sorting, etc. Finally, an overall summary in a concise way has been presented based on different preprocessing techniques used in offline OCR. 2022 IEEE. -
Facilitating the New Normal: Challenges and Opportunities of Facility Management Companies in India
Covid 19 has brought the world to a standstill. The hospitality, Travel and tourism being affected the most due to travel restrictions across the world and within India. One of the sectors that have been affected majorly are the industries providing Facility Management services to core businesses. FM is dependent on the type of client business, the client organisation's structure and the market sector. This paper aims to gauge the impact of the pandemic on the Facility management companies in India. This also captures the positive and negative aspect of pandemic on the FM. An empirical research design has adopted to address the study objectives. This research involves both primary and secondary data. Primary data for the study have been collected in the form of structured questionnaire distributed among 300 respondents who are senior executives heading selected Facility Management companies in India. The target respondents have been selected based on simple random sampling to ensure the normal distribution of data. The Electrochemical Society -
Moving Towards Responsible Consumption: The Road Ahead for Sustainable Marketing
The fundamental tenet of consumerism revolves around the belief that the burgeoning consumption of goods is favourable for the economy. Since the dawn of the Industrial Revolution, humanity has witnessed an exponential upsurge in consumerism. It has been related both to the increase in the population size as well as an increase in our demands due to constant changes in lifestyle. Multiple sources have corroborated the fact that if this consumption behaviour continues unabated, we will soon face an acute shortage of resources of all kinds. Both consumer behaviour patterns such as addictive consumption and conspicuous consumption can be attributed to this. Amongst the solutions available, 'Demarketing' is one. It is a type of marketing when a brand wants to discourage you from buying its product. The paper is descriptive in nature and is based on secondary data which has been collected from journals, blogs, websites, magazines, books, etc. The paper intends to explore the theme of demarketing vis-vis the materialistic purchase behaviour of a modern-day consumer and green demarketing strategies that companies are adopting by way of sustainable marketing. The Electrochemical Society