bluuebunny/crossref_metadata_2025 huggingface dataset:
Designing of Solid State SIW Antenna for 5G Application
Authors: Bhatt Maharshi K , Borisagar Komal R , Kotak Nirali A , Sedani Bhavin S
Published: April 2022

This experimental research paper presents the plan of a solid single band microstrip patch Substrate Integrated Waveguide(SIW) antenna, which might be suitable candidate for 5G wireless application working at 3.5GHz. Right now, the full world is within the surge of satisfying the request of capacity boosting highlights of remote eras, such as huge data rate in conjunction with moo inactivity, ultra-reliable communications, and enormous network. These all over said highlights of 5th era remote innovation might be for the most part held within the 3.5GHz band. The plan of SIW antenna proposed in this paper is carried on Roger RT3203 with 3.02 dielectric, 0.0016 misfortune digression, and 1 Oz thickness utilizing inset bolstering. The overall dimension of the patch antenna is 60.4523×34mm2. In this work, rectangular fix is planned with U-shape opened radio wire with utilizing SIW methodology. The antenna is outlined and recreated and the investigation was carried out on Computer Simulation Technology (CST) studio. The antenna attains gain of 2.61dB at 3.5GHz frequency, which is the most preferred feature that facilitates to implement this antenna plan in the 5G applications.
Digital Short Stories and Narrative Approach: A Great Combo in Developing Cognitive Abilities and Skills
Authors: Anuradha V
Published: April 2022

The research is to establish the usefulness of narrative approach in ELT classroom amongst B.Tech. first year engineering students from Dr. M.G.R. Educational and Research Institute in enriching the language skills of English utilizing the digital short stories. As narration is part of their syllabus for the first-year engineering students, they were chosen as the samples. The narrative approach helps the learners in developing cognitive skills, as the brain completes the process fast and competent enough. It also helps to perform better in every aspects of life. After the intervention of digital short stories, the attention skills helps to stay on the task and make the learners an active listener who improves good relationships. This approach builds the logic and reasoning skills to generate creative solutions in complex challenges.
Artificial Intelligence Framework Based on Dconvnet for Skin Cancer Detection.
Authors: Subramanian Muthukumar , Aksenova Е.I. , Kamynina N.N. , Shvets Yuriy
Published: April 2022

Abstract— From the past and current few years, the furthermost common type of cancer is skin cancer out of all the cancers of human. Every year, more than 1 million new cases are occurring in a predictable situation. Different research methods have been proposed by researchers to detect the skin cancer. To classify normal and abnormal form of skin cases, a system for screening is discussed in this article which is developed with a framework of artificial intelligence with deep learning convolutional neural networks. It is focusing on hybrid clustering for segmentation on skin image and crystal contrast enhancement. Initially filtering and enhancement algorithms will be applied, later segmentation will be done followed by Feature’s extraction and classification are included in the developing process. Each step is designed with effective algorithms to achieve the higher accuracy for the detection of cancer. Images are divided into sub-bands to extract the features and those are the inputs for classification system to find either image is cancerous or noncancerous. The different state of art methods is compared with the method proposed in this article.
Nanobot Swarm for Targeted Elimination of Tumor in Brain
Authors: Sarkar Shravasti , V Suchithra , Makuteswaran Sridharan , C Manjunatha
Published: April 2022

An in-vitro nano-swarm has the potential to revolutionize the medical field, from the diagnosis of ailments to targeted delivery of drugs. A nanobot swarm uses swarm intelligence to allow simple devices to communicate in a decentralized, distributed manner, within any given environment to achieve a common goal or arrive at an optimal solution quickly. This review discusses the different factors to consider and components necessary to deploy an in-vitro nano-swarm for targeted drug delivery to eliminate cancerous cells in the brain. It also discusses some swarming techniques that can be implemented for the decentralized control and acoustic communication between individuals in the nanobot swarm. Finally, there is discussion about the different challenges faced while deploying a nanobot swarm in the brain. This review hopes to give direction to other researchers through a comprehensive compilation about different practices and advancements in the field.
Quad-Element MIMO Antenna with Enhanced Isolation for UWB Applications
Authors: Bsrat Giday Gebrehiwot , Aruna Singam , Naik K Srinivasa
Published: April 2022

This study proposes a quad-element MIMO antenna for ultra-wideband applications. Several design evolutions have been carried out in order to achieve a UWB impedance bandwidth and good positive gain across UWB frequency ranges. In MIMO antenna construction, the best-performing antenna design is used as a basic radiator element. S-parameters, gain, radiation pattern, and diversity performance findings are used to investigate dual and quad-element MIMO antenna designs with various layouts. As a result, the proposed quad-element MIMO antenna operates in the frequency range of 3.5-11.2 GHz with >-20dB isolation in the majority of the operating band. The ECC and DG values are both less than 0.006 and greater than 9.9, respectively, while the MEG and CCL are within acceptable ranges. The simulated findings agree well with the measured results.
Contributions to Hadoop File System Architecture by Revising the File System Usage Along with Automatic Service
Authors: Maurya Jay
Published: April 2022

The usage of unstructured data is becoming obvious by companies and social media is raised heavily from past decade. The sharing of images, audio, and video content by the individual user and corporate can be observed everywhere. The current work focused on the Hadoop framework revision contributions so as to improve the performance of the eco system in the context of space and time parameters. The architecture basically provides the usage of Hadoop Distributed File System (HDFS) and MapReduce (MR). We are proposing certain revision contributions so that the process of importing and processing of the tasks can get the benefit of time and space usage in the effective and efficient manner. The work provides the service running in two different ways which reduces the time requirements of the cluster management. In the distributed environment, this revision helps in the reduction of waiting time for the start of the service. The other context we have focused on, the local file system handler in the data storage and processing of the data, the provision of using the file system according to the proposed architecture, will handle the CPU context switch while performing the import and export process in the running of the jobs. The outcome of the work is revision architecture to reflect the service initiation by all the machines in the cluster and file system revision approach to minimize the CPU context switch, while performing the storage and processing relevant aspects of the Hadoop cluster.
Perceived Reality of Self and Others with Two Childhood Trauma Survivors – An Idiographic Case Study
Authors: Ravishankar Ashwini , Sathiyaseelan Anuradha
Published: April 2022

Impacts of childhood trauma can be crucial in understanding personality traits and psychological distress. However, it could be hard to predict if these individuals develop posttraumatic stress or growth. Several quantitative research studies have concluded the connections between childhood trauma and psychopathology or maladaptive personality traits. Various researchers have discovered the negative consequences of early childhood trauma and its long-term effects which may be rudimentary in understanding the causation of life-long psychological and medical deficiencies. This has been very elementary in understanding trait patterns and psychopathology for outcome generalizability and implementing prevention and intervention models. However, these studies still fail to spotlight the importance of the lived experiences of trauma survivors. Nevertheless, the present study is an idiographic single-case study research design used in the exploration of the lived experiences and perceived reality of self and others with two childhood trauma survivors.
The Cubic Dihedral Permutation Groups of Order 4k
Authors: Fakher Hussein Taleb , Khalil Shuker Mahmood
Published: April 2022

Given any mathematical system with identity and any positive integer k≥1, the structure of any dihedral group is generated by only two elements which are satisfy some conditions and belong to the set of mathematical system. Here in this work, we will give new structure to consider new groups are called cubic dihedral groups which are generated by three elements instead of two elements . That means we make to solve all the problems that maybe appear when we increase the elements to generate this new structure of groups. Next, new class of cubic dihedral groups is given they are called cubic dihedral permutation groups. Also, in this new class the specifying condition of positive integer k≥1 to get cubic dihedral permutation groups is shown as k=ord(a). This condition is important and we explained that the structure is not necessary satisfy requirements for group if k≠ord(a).
Predicting the Influence of Air Pollution on Residential Human Health
Authors: Mathur Sandeep
Published: April 2022

Perilous engineered blends break up to the Earth through distinctive typical or possibly phylogenesis routines and may drive frightful effects on individual well-being and the natural world. The stretched out the start of the non-sustainable power station is one of the principal outstanding centuries that may be liable for the renascent alter noticeable all-around association. Air poisons, case in point, monoxide, sulphur dioxide (SO(2)), nitrogen oxides (NOx), precarious feature fits (VOCs), ozone gas (O(3)), irresistible metals, and respirable particulate issue (PM2.5 and PM10), differentiate in their substance game plan. Their reaction properties, transmission, time of disintegrating, and ability to diffuse in long or short detachments. They are affecting different platforms as well as organs. It varies from minor cardiovascular aggravation to perpetual metabolism and cardiovascular disease, respiratory organ mendacious virilization, exceptional respiratory pollution in children, and steady bronchitis in adults, disturbing past heart, and lung affliction asthmatic attacks. The effects containing air poisons on individual well-being and their instrument of the campaign are instantly discussed in the paper. We proposed and proved a hypothesis to explain that there are no adverse effects of air pollution in residential human health.
Renewable Energy Integration in Conventional Grid: Potential, Challenges, and Aspects
Authors: Joshi Satyanarayan , Sharma Virendra Kumar , Deegwal Jitendra Kumar
Published: April 2022

Integration of renewable energy sources to the conventional grid and the power flow management among various components of the hybrid power system offers many challenges. In this paper a brief summary of different renewable sources, their potential, advantages, and problems rose due to integration with existing grid are presented and renewable energy technologies are discussed. Future power demand cannot be met out by the fossil fuel. Therefore, the replacement of fossil fuels may be done by non-conventional and renewable energy sources. These sources are pollution free and exist in sufficient amount, are the best alternative but are associated with certain integration problems. This paper presents comparative study of pre fault and post fault parameters with and without renewable integration to grid Simulink model of grid combined with renewable energy source is designed in MATLAB. The results depict improvement in quality and status of the existing power system parameters.
Humanities, Science, and Technology: The Nexus
Authors: Arthi R. , Bhuvaneswari V.
Published: April 2022

Science and technology are complex terms as it involves laws, logical array of concepts, and series of practical experiments when compared to literature, which is an art form abounding in expressions. In science and technology, there are only two opinions: something could be only right or wrong. In literature, there are multitudes of opinions since it is viewed with different prisms. Moreover, there is no right or wrong in the humanities. Science concepts could only be understood by the field experts. However literature grants everyone the access to comprehend. When a research article elaborates on how technology would assist in forging a sustainable environment, the readers from non-technical background would find the concepts obscure because of the technical terms, laws, theories, and empirical results. Humanities address lifestyle, culture, philosophy, psychology to science, and technology. When technology infused concepts are furnished with literary narratives, the readers could effortlessly decipher. This style of writing marked its beginning when Rachel Carson published Silent Spring. The work addressed the adverse effect of using pesticides, inculcates environment friendly thoughts and insights, and stresses the need in educating the people on malign effects of pesticides. Even before that, writers like Henry David Thoreau and Ralph Waldo Emerson shaped their works artistically whilst insisting the readers to aim for a sustainable and harmonious living space. The primary objective of the paper is to unveil how literary chef d'oeuvre educates the readers on sustainable living through literary narrations and the role of humanities in promoting science and technology.
Impact of Organizational Culture on Performance and Effectiveness
Authors: Mishra Amresh Kumar
Published: April 2022

Organizational performance and effectiveness have remained one of the prime objectives of all businesses. Various social, economic, and environmental factors, along with organizational functions, influence the performance and organizational effectiveness. This research sets up a model of organizational culture on performance and effectiveness that was examined through literature reviews and past work done on the subject area and the theoretical framework is used. The four attributes studied augurs well of other effectiveness factors, such as quality, staff happiness, morale, and broad performance. This study argues that culture can be found to be an integral part of adaption process of any firm and it suggests that identified culture attributes should be examined to find its impact on performance and effectiveness. The research assessed organizational performance and effectiveness that is not always dependent on strategies or other visible factors, but may have root cause into organizational culture and its traits.
Incorporation of Nanoparticles in Building Materials
Authors: . Radhakrishna , K C Sachin , G Lokesh Kumar , Meda Ujwal Shreenag
Published: April 2022

The production process of cement is emitting a huge quantity of greenhouse gases and heat into the atmosphere. It is the prime time to explore amendments to the existing and to develop new generation material without compromising properties. New generation products must have an extended life, lesser impact on the environment, and adaptable properties so that carbon footprint can be minimized. Geopolymer composites are a promising substitute for conventional building materials with high early strength, resistance to chemical ingress, increased durability, and above all a low carbon footprint product. To overcome the challenges and to enhance the properties of conventional or substitute composites, nanotechnology provides better prospects. The chemical composition, particle size, and surface morphology of nanoparticles perform a vibrant role to escalate the behavior of the building composites. This review provides an overview of various nanomaterials, which bring about positive changes in the building materials.
Supply Chain in Msme Sector: Concerns and Mitigation
Authors: V P Rameshkumaaar , B Balaji
Published: April 2022

Supply chain management practices ensure better quality improvement and entails the process of transforming information, goods and services in many ways thereby ensuring cost and time efficiency so as to attain desired results. The study was commenced with the motive of examining the issues and remedies apropos supply chains in MSME sector. Enterprises of different proportions that are involved in production of material for industrial and direct consumption were considered for the study. The sample size consisted of 227 entrepreneurs of MSME in different parts of the city. Questionnaire was used for survey among the entrepreneurs. Simple percentage analysis, factor analysis, and Garrett ranking were used for analysis. Findings showed that procurement, production, distribution, cost and external factors were the significant issues in supply chain activities of such enterprises.
Plastic Processing MSMEs and Triple Bottom Line: Perceptions Regarding Factors Contributing to Business Sustainability
Authors: Bisht Hemendra Singh , Singh Dilpreet , Sandhu Namrata
Published: April 2022

This study empirically examines the perceptions of the owners of plastic processing MSMEs regarding the factors that contribute to business sustainability. The census technique was adopted to collect the data using exploratory factor analysis to identify the variables. The output was integrated with the triple bottom line framework of sustainability. Exploratory factor analysis yielded a 21-item, three-factor solution, which when subjected to confirmatory factor analysis established the awareness of the owners of plastic processing MSMEs regarding the three pillars of business sustainability: profits, society, and environment. This study documents the awareness of the owners of small businesses regarding sustainability initiatives and adds to the emerging sustainability research that is grounded in evidence gathered from the owners of MSMEs. The results of this study can be a helpful input into policy formation.
A Transformed Perception of Customers Towards Digital Banking During the COVID-19 – A Study Across Bengaluru City
Authors: Pillai Rajani H. , Bi Aatika
Published: April 2022

The RBI and the National Payment Corporation of India have made a number of significant actions and attempts to improve the payment and settlement system in banks, including the creation of the Unified Payments Interface and the Bharat Interface for money. The purpose of this research study is to examine how the move to digital banking affects customers. It also aims to look at customer perception of digital banking during COVID-19, as well as analyze the factors influencing use of digital banking during the Pandemic. This study seeks to provide a clear picture of how consumers feel about their banks' e-services.
Critical Review of Policy Making Process and Policy Indicators for Governance in Indian Context
Authors: Kaushal Ajay
Published: April 2022

This paper points to policy making process based on governance theories with set of policy indicators necessary for quality governance in development efforts while making decisions. The fact is governing system is run by making public policies and the implementation of the policies is the indication of good governance. Governance theories address social issues of coordination and the nature of all formats of rule. But the foremost issue is whether public policies decide the functioning of government or the government decides what would be the best public policy to run the system. This paper draws the focus to identify the major policy indicators to provide better policies for good governance.
Comparative Study: Synthesis, Characterization, and ORR Activity of Pot and TiO2-Pot Nanocomposites
Authors: Rajakani P. , Vedhi C
Published: April 2022

o-toluidine was polymerized with the incorporation of different amount of titanium dioxide (TiO2) by chemical oxidation method using potassium perdisulphate as oxidizing agent. Comparative studies were carried out with different nanocomposites of varying compositions of TiO2/PoT against poly-o-toluidine (PoT). The resulting poly-o-toluidine – TiO2 nanocomposites (PoTTNCs) were characterized by UV–Vis and FTIR spectral studies. TiO2 has a deep influence in the crystallinity of PoT chains order in nanocomposite structure as observed in the XRD pattern. Electrochemical characterization studies were carried out to compare the improved performance of varied compositions of TiO2/PoT with respect to PoT in different atmospheres.
Comparative Performance Analysis and Optimization of Acrylic Evacuated Tube Solar Collector with Water in Glass Tube Collector Through RSM
Authors: Mandanka Pravin B , Patel Dilipbhai M
Published: April 2022

The dominant technique used to utilize solar energy to heat water for domestic, industrial, and commercial requirements is a solar water heater. This research work aims comparative performance analysis of acrylic evacuated tube solar collector with water in glass evacuated tube solar collector and also, to investigate the optimal value of process parameters affecting the performance of water in glass and acrylic evacuated tube solar collectors. In this research work, the intensity of solar radiation, tilt angle of the collector, and the time are considered as independent variables. The temperature difference of water of glass evacuated tube solar collector and acrylic tube solar collector is measured as a response. The input parameters are optimized by using CCD method in RSM for the maximized value of the temperature difference. The result of the experiment shows that optimal values of solar radiation 843 W/m2, tilt angle of solar collector 32.1°, and time period is 59.2 min are for maximized value of temperature difference of water 7.4°C for glass and 7.7°C for acrylic evacuated tube solar collectors respectively. The experimental result deviates 1.33% in glass and -1.3% in acrylic tube solar collector from simulated values.
Technology Innovation: Detection of Counterfeit Region in an Image
Authors: S Shashikala , G K Ravikumar
Published: April 2022

With availability of advanced photo editing tools today, digital images can be tampered with malicious intention at ease. The image tampering can create various ill effects like false disease diagnosis of medical images, defaming people, hiding evidences, creating false claims etc. Since images are being increasingly used as the most creditable information for inferring various conclusion and judgments in many application scenarios, it is necessary to ensure the authenticity of the image and detect any counterfeit regions in the image. Nowadays tampering can be done in sophisticated manner without leaving any trace and it becomes difficult to detect with naked eye. In this work, we survey the state of art existing works on detection of counterfeit or tampered regions in the images. The survey is done to identify the challenges in existing counterfeit detection techniques.
Hybrid Action-Allied Recommender Mechanism: An Unhackneyed Attribute for E-Commerce
Authors: Patro S Gopal Krishna , Mishra Brojo Kishore , Panda Sanjaya Kumar , Hota Amrutashree
Published: April 2022

The users of electronic commerce (e-commerce), otherwise known as internet commerce portals, most commonly depend upon the customer reviews when they make any purchase decisions. But it is observed that one product may have more than hundreds of miscellaneous reviews, which leads to an overload of information on the customer. This information overload tends one to work on the objective of developing a recommender mechanism to recommend a review subset having high content score as well as various aspects of products with associated sentiments. Therefore, these recommendation systems (RSs) have been established parallel to web networks. This contribution delivers an orderly explanation for hybrid RS along with a novel method with slight modification of the contemporary techniques, such as collaborative filtering. It also describes their evolution, progression, and fruitfulness and also identifies various future implementation areas selected for future, present, and past importance.
Security Architecture and Its Methodology for Fog Computing
Authors: . Shruti , Babbar Himanshi , Rani Shalli
Published: April 2022

With the rise of Internet of Things (IoT) based applications, cloud computing faced lots of challenges like bandwidth limitation and latency in real time applications. Therefore, fog computing came into existence. It is not a replacement of cloud computing but complements it. The services of fog computing are extended to the edge of the network making communication fast and secure. On the other hand, Software Defined Network (SDN) is also discussed, which is helpful in providing network virtualization. In this paper, study about fog computing and SDN, their characteristics, architecture, applications, key technologies of fog computing are over-viewed, and how fog computing in collaboration with these technologies will be deployed in different applications and areas. Along with it, security of fog computing and a methodology to secure a fog computing environment is proposed.
AI Based Novel Approach to Detect Driver Drowsiness
Authors: Bajaj Jaspreet Singh , Kumar Naveen , Kaushal Rajesh Kumar
Published: April 2022

Vehicle accidents due to driver drowsiness is the major problem all over the world. It leads to millions of road accidents that result in fatal and non-fatal injuries and huge financial losses. To overcome vehicle accidents and provide safety to all commuters on the roads, a smart driver drowsiness detection system is required which can detect the drowsy state of the driver at an early stage. The behavioural measure provides the promising results to detect driver drowsiness at an early stage due to its non-intrusive nature. In this measure, various facial features, ML (Machine Learning) or DL (Deep Learning) based algorithms are analyzed various states of the driver to detect drowsiness. In this paper, a comparative study has been conducted that use ML and DL based algorithms to detect driver drowsiness. This study is aimed of finding effective AI (Artificial Intelligence) approach to detect driver drowsiness at an early stage.
Electrolyzers for Green Hydrogen Generation and their Integration with Fuel Cells
Authors: Rajyaguru Yashesh Vijay , Meda Ujwal Shreenag , Pandey Aditi , Manjunatha C
Published: April 2022

Mankind is being alerted about the gravity of the imminent global cataclysmic event through various forms of messages from Mother Nature. Global stakeholders and government officials around the world are enforced to take up the daunting task to solve intricate issues such as global energy security, mitigating climate change, abating the release of greenhouse gas emissions, etc. Scientists are exploring avenues to tackle these major issues sustainably and in the greenest way possible. Green hydrogen is one such potential answer to all the global concerns. It can quench all the energy requirements for a plethora of applications without adversely impacting the environment. An attempt is made to elucidate the potentiality of green hydrogen generation using electrolyzers and their integration with fuel cells by the medium of this review.
A Review on the Development of Iot Enabled Hydrogen Sensing Systems
Authors: Adithya Sourav , Meda Ujwal Shreenag
Published: April 2022

Hydrogen as a fuel is gaining more traction owing to its non-toxic nature and abundant availability. Hydrogen is highly flammable and can be dangerous under certain conditions. It is highly important for industries utilizing hydrogen to employ rigorous detection frameworks that can rapidly detect even minute concentrations of hydrogen. This article intends to provide a review of the various components required to establish an efficient IOT enabled sensing system for hydrogen gas. The article analyses the different options available for components, such as signal conditioning, analog to digital converters, microcontrollers, wireless communication systems, and data logging and analysis services to create a smart sensing ecosystem, weighing in on the pros and cons of all options. Thus, identifying the best choice of components that can detect hydrogen on a real-time basis, send alerts, and make the collected data available across the globe for swift action to help prevent catastrophes.
Design and Experimental Investigation of XY Compliant Mechanism for Precision Applications
Authors: Sollapur Shrishail , Waghmare Pratik , Adarsha H
Published: April 2022

A XY compliant mechanism is designed for the precision application with higher range, precision, and accuracy. In earlier work, many researchers have used different methods to design compliant mechanism. In this paper, XY positioning stage is designed using blocks method. However, the model is monolithic in nature to avoid joints. By using wire EDM, the XY model is manufactured. Voice coil actuators are used for the displacement, which give larger range. Analytical modeling is carried out and is validated with MATLAB results. Finally, experimentation is done for performance analysis. The XY model gives ±6mm with motion direction. The XY model evaluates both static and dynamic performances.
Data Mining and Machine Learning Techniques for Credit Card Fraud Detection
Authors: Kalhotra Satish Kumar , Dongare Shivprasad Vaijnathrao , Kasthuri A , Kaur Daljeet
Published: April 2022

In the recent era, everybody is dealing with digital data. In such a scenario, individual one heavily depends on credit card. Therefore, the demand of online transactions and usage of e-commerce sites are rising at the rapid rate. The online payments are the main cause of increasing crime rate heavily. Hence, it is the biggest challenge for the IT sector to identify and solve such critical problems. This critical issue can be tackled with the help of machine learning. This paper mainly emphasis on various data mining algorithms such as C4.5, CART algorithms, J48, Naïve Bayes algorithm, EM algorithm, Apriori algorithm, and SVM, and inform the accuracy and precision of the result. The machine learning finds the genuine and non-genuine transition using learning pattern matching and classification technique. The machine learning also normalized the data, identified the anomalies in transaction, and provided appropriate results.
A Systematic Review of Swarm Intelligence Algorithms to Perform Routing for VANETs Communication
Authors: Kaushal Payal , Khurana Meenu , Ramkumar K.R.
Published: April 2022

The performance of Vehicular Adhoc Networks (VANETs), the underlying technology for intelligent vehicles, has shown improvement with the application of swarm-based algorithms for routing. Swarm Intelligence is a self-intelligence group of similar agents functioning on distribution, flexibility, and communication among the agents. The multiple problems occurring in the modern communication systems, including VANETs, have been tried to be resolved by the application of swarm intelligence algorithms viz, Genetic Algorithms (GA), Differential Evolution (DE), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Cuck-oo Search Algorithm (CSA), Glowworm Swarm Optimization (GSO), etc., have been proposed in the literature. This paper provides a comparative analysis of operations of swarm-based algorithms. Points like their operations, basic entities, advantages, disadvantages, and applications are discussed.
Real-Time Face Detection and Recognition Using Deepface Convolutional Neural Network
Authors: R Poorni , S Charulatha , B Amritha , P Bhavyashree
Published: April 2022

Many trendsetting inventions are often founded as technology improves, and face acknowledgment innovation plays a vital role. The surveillance camera recognizes and photographs a person's face. The image recorded is then compared to the image stored in the database. Face detection and recognition is the process of identifying faces and recognizing certain features in a photograph. We investigate facial recognition approaches utilizing a deepface convolutional neural network in this paper. The faces are matched using the Euclidean distance technique. The fundamental advantage of CNN over its counterparts is that it recognizes significant highlights without the need for human intervention. By preserving the fully linked layer of the real network, the number of parameters is minimized, and overfitting is avoided by employing adam. To identify and recognize masks in the image, the Softmax classifier is utilized. This system's algorithms have a higher accuracy rate and are more efficient.
Accelerated AI Inference at CNN-Based Machine Vision in ASICs: A Design Approach
Authors: Jain Aabha , Sharma Neha
Published: April 2022

Machine Vision (MV) has become an increasingly popular technology in Industry 4.0 for advanced manufacturing processes. Specially, assembly lines require fast MV of the machine objects, assembly-functions, and operations to improve accuracy and quality. In order to achieve this, MV deployed customized Application Specific Integrated Circuits (ASICs). These ASICs designed to run Convolution Neural Network (CNNs) and perform AI inference. The processing needs high performance computing (HPC) of a large number of tensors with least energy spending in the ASICs. In the paper, we propose a design approach for efficient tensor processing in tensor cores for accelerated AI inference at CNN based MV in ASICs. The design approach deploys the small DNN (Deep Learning Neural Network) model SqueezeNext along with application of quantization, fast arithmetic reduction, tensor cores aware tuning, pruning, and fusion for the efficient AI inference in ASICs. Successful implementation of proposed design can provide a competitive advantage to industries in terms of quality and cost of product along with time saving in manufacturing process.
Comparative Efficacy Evaluation of Quaternary Ammonium Disinfectants as Per EN 1040:2005
Authors: Sharma Gaurav , Kaur Kiranjeet
Published: April 2022

Microbial infections are the most complicated challenges of modern-day medical practices. Such infections become fatal when acquired from hospitals or other health care facilities. To tackle the challenges of hospital-acquired infections (HAIs), different classes of chemical disinfectants are used. Out of these chemical disinfectants, Quaternary Ammonium Compounds (QACs) based disinfectants are widely used because of their advantageous properties. Large-scale use of QACs led to reporting of resistance. To further enhance the efficacy and reduce toxicity, manufacturers of QACs developed newer compounds. However, disinfectants in hospitals are solely used in good faith and hospitals don't have an adequate policy to see the efficacy using standardized methods. Efficacy testing of QACs disinfectant is very important to reduce HAIs. Hence, bactericidal activities of different generation QACs disinfectants were evaluated as per the standardized method EN 1040. All QACs disinfectants demonstrated more than 5 log reductions and complied with the requirement of EN 1040.
An Insight Into the Effect of Drug Betaine Hydrochloride on the Micelle Forming Tendency of Surfactant AOT
Authors: Kaur Ramanjeet , Kumar Harsh
Published: April 2022

The present analysis employs an electrical conductometric measurements to monitor the effect of addition of drug Betaine hydrochloride (BH) on the double chain anionic surfactant sodium bis(2-ethylhexyl)sulfosuccinate (AOT). Different concentrations (0.10, 0.25, and 0.50) mmolkg-1 of drug Betaine hydrochloride have been added to the aqueous solution of surfactant AOT at three various temperatures (298.15, 308.15, and 318.15)K in order to examine the micellization properties of the surfactant AOT. The values of critical micelle concentration, and various thermodynamic quantities, which include Gibb’s free energy of micellization (ΔG0
m), enthalpy of micellization (ΔH0
m), and entropy of micellization (ΔS0
m), have been computed from the conductivity measurements. The interactions prevailing among the surfactant-drug system have been discussed in order to explore their applications in drug delivery systems.
Unravelling the Interactions Prevailing in Mixed Micellar System of Surface-Active Ionic Liquid and Cationic Surfactant
Authors: Kaur Gagandeep , Kumar Harsh
Published: April 2022

The investigation of mixed micellar behavior of surface-active ionic liquid (SAIL) i.e. 1-butyl-3-methylimidazolium hexadecyl sulfate [C4mim][HS] with cationic surfactant cetyltrimethylammonium bromide (CTAB) has been done to explore the type of interactions prevailing in SAIL/Surfactant mixed system. Thus, the conductometric measurements are performed at (298.15, 308.15 and 318.15) K for various mole fractions of [C4mim][HS]. Different theoretical models like Clint, Rubingh, Motomura and Rodenas have been applied to understand mixed micellar behavior of SAIL/Surfactant mixed system. The value of critical micelle concentrations (cmc), micellar mole fraction based upon various models, ideal critical micelle concentrations (cmc*), interaction parameter (β) and thermodynamic parameters have been evaluated for the mixed systems. The variations of various parameters with respect to temperature and mole fractions give insight to sort of interactions present in studied system.
Design and Reliability Evaluation of Switching Element for Improving the QoS of Multistage Interconnection Network
Authors: Gupta Shilpa
Published: April 2022

Reliable and cost effective multistage interconnection networks (MINs) are the backbone of efficient distributed computing in supercomputer systems. In this paper new 3×3, 4×2, and 4×4 switching element (SE) structures are introduced which can be employed in various existing MINs to provide enhanced reliability at much reduced cost. The reliability function of proposed as well as the existing SEs have been formulated on basis of which their reliability values have been computed. The computed reliability values of all SEs (existing and proposed ones) have been compared and analyzed. The achieved results clearly depicts that the proposed SEs possess higher reliability and can replace the existing SEs of similar size without changing the existing design of MIN to improve reliability.
Renewable Energy Enhanced Smart Energy Management System Using Internet of Things
Authors: G Ramya , P Suresh , R Arthi , K Murugesan
Published: April 2022

The paper presents the renewable energy enhanced smart energy management system using Internet of Things (IoT). As we are living in a world where climate change is unpredictable, we chose the combination of solar and wind energy as renewable sources of energy, which has a rapid growth in the last decade. The renewable source of energy will be utilized alternatively when there is insufficient grid power and it will be achieved using an industrial microcontroller. The power generated by the renewable sources is sensed by the sensors and the data is transmitted to the microcontroller, which chooses what sources to be supplied based on availability. These enable users to monitor renewable energy as well as it can be controlled by switching it from grid power to any one of the renewable sources. The transmitted data can be controlled and monitored remotely using IoT platform.
FPGA Implementation of Secure Block Creation Algorithm for Blockchain Technology
Authors: Peroumal Vijayakumar , R Rajashree , Kulkarni Anusha , Thakur Prachi
Published: April 2022

Blockchain technology is essential to secure storage, authenticate data, and protect information from being misused and exploitation. Traditional methods of securing data using cryptographic algorithms include hashing functions like SHA-0, SHA-1, which have limitations like excess computational time, collision attacks, scalability, backtracking to retrieve the original message, etc. Using a combination of RSA and SHA together allows us to create a block on an FPGA, which when combined with other blocks establishes an encrypted Blockchain, which overcomes such limitations. Synthesis and implementation of the encrypted block have been compared and analyzed on Virtex-4, Virtex-5, and Spartan-6 FPGA boards. Based on the resource requirement like the slice registers, LUT-FF pairs and memory, Virtex-5 was chosen. Complete security is achieved as the hashing process is irreversible and backtracking of data is not possible. Previous problems of strengthening security, backtracking, excessive memory usage, and zero collision attacks are addressed and solved.
Influence of Diverse Feature Selection Methods in Sentiment Analysis
Authors: Madhusudhanan S , N.M Jyothi , J SenthilMurugan , S Sathya
Published: April 2022

With the enormous comments on social media and ecommerce, government, companies, and individuals eagerly want to know about people opinion about their policies, services, or any other. Sentiment analysis plays a major role to understand people emotions. Sentiment analysis alias opinion mining uses machine learning techniques to classify the given review as positive, negative, or neutral. This paper provides implementation of diverse feature selection techniques with different classifiers in sentiment analysis. The method is evaluated on various domains. Bag of Model with SVM provides satisfactory result on the datasets.
Power Reduction in 4T DRAM Cell Using Low Power Topologies
Authors: L Saranya , Inbamani Abinaya , A Nivedita , D Arulanantham
Published: April 2022

In today’s world there is a high demand in the development of VLSI circuits. The designers are paying attention to designing a good performance with zero hunger circuits in terms of power. At present, to design a high speed and a low cost device is becoming a major challenge for designers. In order to enlarge the demand of VLSI, CMOS technology plays a fundamental role. Dynamic Random Access Memory is the volatile memory, which is used in wide ranges of electronic based gadget applications. In this paper, the low power techniques like sleep transistor logic and Self Voltage Controllable Logic (SCVL) are implemented. A 4T DRAM cell using these low power logics has been designed and implemented. The power has been analyzed at 90nm technology. The simulation is done using the Tanner 13.1.EDA tool.
Brand Loyalty and Customer Satisfaction in Online Retailing with Amazon
Authors: Jayadeva Sujay , Acharya Sujit Kumar , S Rani , Singh Arun Kumar
Published: April 2022

The purpose of this research was to find out how Amazon through different strategies or steps are ensuring customer satisfaction and brand loyalty. In order to identify the same, in this research, primary data was collected. Data was collected by sharing survey questionnaire with 50 random consumers of Amazon. From their responses it was found that factors such as low price of products, convenient and fast website, fast delivery, safe payment methods, high quality of products, and individuation are helping Amazon to ensure customer satisfaction and customer loyalty.
Power Quality Enhancement Using Multi-Level Inverter with UPQC and Robust Back Propagation Neural Network Strategy
Authors: Sekhar Hema , S Lakshmi Kanthan Bharathi , N Ahamed Hussain Asif , P Veera Manikandan
Published: April 2022

More pollutants for coal, oil, natural gas, and others, a viable alternative to sustainable and renewable energy sources, have increased significantly over the past decade. These can then be seen as the first step in the global movement to reverse the problems resulting from slow climate change. Therefore, in this work, use solar power source-based power quality improvement in a system. The main aim of this work is multi-level inverter associated UPQC for power quality enhancement. In this work, multi-level inverters are used in a series shunt controller for producing accurate sinusoidal wave shape. The series controller is connected to the grid side for grid power quality improvement. In this work, grid side voltage sag/swell was reduced by a series controller. The advantage of the proposed system is the high-efficiency enrichment of quality power. The MATLAB/Simulink environment verifies the simulated results of the proposed system.
E-Waste: A Global Hazard and Management Techniques
Authors: Tanwani Lakshay , Agarwal Saurabh
Published: April 2022

Nowadays with the advancement in technology there is more and more use of electronic items and appliances, which results in e-waste. Waste due to electrical items (e-waste) includes the electrical waste of machines or the electronic appliances which are discarded after their use. E-waste is a source of a number of toxic chemicals that are harmful to the environment and nature. The purpose of this paper is to raise global awareness about e-waste and hazards related to it. Hence, this paper deals with the description of e-waste, the problems related with it, various methods to recover valuable items from e-waste, and its environment friendly disposal. Also from this paper we get to know about the best management techniques for waste, i.e. recycle and reuse, and we need to adapt proper management techniques for sustainable development. Otherwise, in the future, waste of electronics will be harmful.
Comparative Analysis of Air Quality Prediction Using Artificial Intelligence Techniques
Authors: P ShreeNandhini , P Amudha , S Sivakumari
Published: April 2022

Air population is the primary concern in most urban areas because of its notable impact on the economy and health across the universe. The emergence of industry and automobiles made air pollution worldwide, which causes a highly critical issue and a more significant impact on humans' health than the contaminants. It causes health-related problems like lung-related diseases, namely respiratory problems and cardiovascular disease, and increases cancer. Accurate monitoring of air quality is of great importance to daily human life. The consuming time delay long-term delay is essential for long-term predictions. In this article, proposed Enriched Spatial-Temporal Sequence (EISAE-DL) improves the prediction accuracy by considering the long time delay based on locations and compared for experimental algorithm Improved Sparse Auto Encoder with Deep Learning (ISAE-DL) The experimental results show the effectiveness of the proposed EISAE-DL in terms of accuracy, precision, sensitivity, specificity, Area Under Curve (AUC), and Matthew's Correlation Coefficient (MCC).
Multi-Image Cryptographic Based Two-Factor Authentication in Banking Systems and Services
Authors: S Bhuvaneswari , M Deepak kumar , N Keshav , S Hariharan
Published: April 2022

Core banking is a back end system with a set of services provided by a cluster of bank branches which is associated with retail banking. Core banking functions include many operations like bank patrons can access their deposits and achieve fundamental transactions from the associate branch offices. The most important problem in core banking is the credibility of the client. It is quite tough to trust the data on the net due to the inevitable hacking of the record on the network. To resolve this downside of authentication, a system is proposed with algorithmic rules associated by IP and VC. This paper defines a method of processing the signature and dividing it into shares of a client. The total diversity of shares will be created based on the premise preferred by the bank. Once two shares are formed, one is held on within the bank information and therefore the difference is unbroken by the client. The client has to demonstrate the share all through of his transactions. This share is laden with the major share to induce the first signature and the correlation methodology has been employed to lay hold of the conclusion on adherence or decline of the output and display to the client.