bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing the Potential for Adaptive Reuse of the Town Hall, Shimla Using the Adaptive Reuse Assessment Model
Authors: Bansal Kanika , Chhabra Pankaj
Published: April 2022

Built heritage as a manifestation of cultural heritage can be conserved if it continues to function through adaption or adaptive reuse. In reality, this process encompasses complex decision-making and remains a challenge amongst stakeholders. This study aims to evaluate the contemporary challenges in the convoluted process of adaptive reuse of the Town Hall, a significant heritage building of the colonial times in Shimla. It aims to identify the varying challenges in the adaptive reuse of the Town Hall, Shimla through the Adaptive Reuse Assessment Model (ARAM). Qualitative content analysis through structured and semi-structured questionnaires along with case study method has been adopted. The study suggests that the adaptive reuse of Town Hall is significantly impacted by locational, legal, and social challenges, while political and technical challenges effect moderately. The study also brings out that environmental, physical, and economic challenges have insignificant impact on the adaptive reuse of the Town Hall.
Meta Heuristic Algorithm for Vehicle Routing Problem with Uncertainty in Customer Demand
Authors: Garg Neha , Kakkar Mohit Kumar , Gupta Gourav , Singla Jajji
Published: April 2022

The Vehicle Routing Problem is an optimization problem with number of applications in the transportation field. In this paper, Vehicle Routing Problem (VRP) with uncertainty in customer demand is considered. Often in real world situation, the information on demand on each customer is not accurate enough. Here, in this article we are assuming that the customer demands in each time period are uncertain and are considered as fuzzy variables. This kind of problem is known as an NP-hard problem. The main purpose of this article is to give conceptual and practical idea on how fuzzy logic with meta heuristic algorithm can be implemented to improve the optimization of vehicle routing problem with uncertainty in customer demand. To solve this problem, a hybrid Meta heuristic algorithm (HMHA) including clustering is proposed, with the objective of determining an optimal route to minimize the total cost.
Initial Beam Characteristics Calculations of 6 MV FF X-Ray Beam from Elekta Versa-HD Linac Using Topas MC Simulation Code
Authors: Singh Avtar , Saini Amit , Kinhikar Rajesh A. , Kumar Pankaj
Published: April 2022

The focus of this research was to calculate initial beam characteristics of a 6 MV X-rays with flattening filter (FF) from Elekta Versa-HD linear accelerator (Linac) using the Tool for Particle Simulation (TOPAS) Monte Carlo (MC) simulation code. TOPAS 3.6 simulated data was compared with the measured data. During simulation, all the main component were simulated including Linac head, Multi-Leaf Collimators (MLCs), and uniform water phantom, while the SNC 3D scanner phantom and SNC125c Chamber were used for measurements. At collimator sizes of 5x5, 10x10, and 20x20 cm2, the depth dose scans (PDD) distribution and beam profiles (BP) were measured. The estimated tissue phantom ratio (TPR20,10) was 0.669, which was -1.1 percent lower than the measured TPR20,10 of 0.681. The obtained results show that the simulated and measured data were in good agreement, with gamma rate analysis of 3%/3 mm criteria reaching 95% and 99 % for PDD and BP respectively.
Gender Prediction Based on Morphometry of Eyes Using Deep Learning Models
Authors: Aruna Sri Talluri , Sangeeta Gupta .
Published: April 2022

In the modern days, the growth of online social networking websites and social media leads to an increasing adoption of computer-aided image recognition systems that automatically recognize and classify human subjects. One such familiar one is the anthropometric analysis of the human face that performs craniofacial plastic and reconstructive surgeries. To analyze the impact on facial anthropometrics, it is also essential to consider various factors such as age, gender, ethnicity, socioeconomic status, environment, and region. The repair and reconstruction of facial deformities to find the anatomical dimensions of the facial structures as used by plastic surgeons for their surgeries result from the physical or facial appearance of an individual. Gender classification plays an important role of identifying the person as either male or female using biometric images. The main goal is to interact with the system, so that gender differences are produced effectively and accurately. Hence, it is essential to select the features optimally to achieve better accuracy. Data mining or machine learning techniques can be useful to infer properties such as the gender or age of the people involved to analyze the human activities. Towards this end, the proposed work focuses on gender recognition thereby building a model to scan the eye image of a patient and determine if the gender of the patient is either male or female by applying deep learning methods. It is identified from the work that deep learning network yields a better performance for gender based classification based on the morphometry of eyes.
Next Generation Parking System with Computer Vision and Machine Learning
Authors: T Naga Swathi , V Megala , S Yokesh babu , R Harshini , V Sumedhae
Published: April 2022

Parking management is a term that describes methods for making better use of parking resources. The first step toward successful parking management is to identify the cause of the problem. Finding suitable parking is among the fastest-growing industries of all, given the ever-increasing number of cars on the road. Traditionally, traffic has been a nightmare. To address these issues, businesses adopted intelligent parking systems from large hardware vendors. These, on the other hand, are unfit for purpose and also have resulted in major parking issues at many businesses. The approach attempts to offer a practical answer to the problem of smart parking. We aim to create a functioning software that will inform requesting customers if there is still a free parking spot near their location using technologies like Machine Learning, CNN, OpenCV, and React.
A Qualitative Evaluation of ADR Reporting in India: Non-Regulatory Confronts and Their Possible Solutions
Authors: Joshi Deeksha , Gupta Saurabh , Singh Thakur Gurjeet , Parashar Abhimanyu , Singh Sachin Kumar
Published: April 2022

Adverse drug reactions (ADRs) are one of the major causes of mortality as well as morbidity. They do have a substantial influence on human health, lowering quality of life for patients, and increasing morbidity and mortality rates, while also putting a significant financial strain on health-care systems. According to a 1998 study, ADRs are the 4th leading cause of death in the United States, accounting for up to 7 percent on average of all hospitalizations. In India, a similar situation, where physicians' inability to diagnose ADRs has caused a lot of hospitalizations and fatality cases. There are many observational studies and KAP (Knowledge, Attitude, and Practices) studies performed across the country to evaluate this issue, but none has summarized the important points at one platform to give the readers, regulatory agencies, and policymakers an idea to improvise the ADR reporting process. This comprehensive review has revealed a major KAP gap in India, and has summarized the different reasons for this gap, as well as their relevant solutions. The provided solutions help to achieve the sustainable goal of ‘good health and well-being.’
Visual Functional Limitation in Amblyopia: A Review
Authors: Thakur Ajit , Raj Joshi Nabin , Gupta Anita
Published: April 2022

Amblyopia is a unilateral or bilateral reduction in visual acuity in absence of any pathological causes. It results in limitations of various visual functions including visual acuity that are essential for performing daily living activities. In this study, we conducted a comprehensive review of affected visual functions in amblyopia through a Pubmed search with an extensive search strategy. Seventeen research articles were selected out of 420 possible research articles and included in the study. Besides visual acuity, other visual functions such as contrast sensitivity, fixation stability, accommodative functions, visuomotor behavior, binocularity, stereopsis, and visual attention were found to be significantly affected in amblyopia. Interestingly, the visual functions corresponding to the "normal eye" of the amblyopic patients were also found to be significantly affected in all forms of amblyopia.
Predictors of Academic Buoyancy: A Study of Demographic Correlates
Authors: Panjwani Divya R. , B Balaji
Published: April 2022

Academic buoyancy refers to to learners’ potential to face challenges and difficulties that are regular in nature under educational settings or environment. Demographic correlates were found and its effect on academic buoyancy was obtained through regression analysis. The sample consists of 1200 high school students belonging to three different boards of Lucknow City. Multiple regression analysis was done in variables where independent variables which are non-metric and a single dependent variable viz. academic buoyancy is metric in nature. Regression analysis is done through dummy coding where predictors of academic buoyancy are found by keeping one benchmark sub-category in each category.
Social Servicescape: Understanding the Impact of Customer to Customer Interactions in Beauty Salons
Authors: Kampani Nidhi , Jhamb Deepika
Published: April 2022

The presence of customers and the interactions within customers has a very integral role in determining the service experience. Within a service setting the social behaviour of customers affects the overall experience. The impact of customer’s presence and interactions among customers belonging to different backgrounds has a very little understanding impacting service experiences which further effect future interactions and visits. The physical environment has been researched by many researchers and individually there has been a lot of research on its major elements which are ambient conditions, spatial layout and functionality as well as sign, symbol and artifacts. There has been a very little understanding of the impact of social aspect of the servicescape created by customers on the service environment also known as servicescape. The article focuses on finding out the perspective of customers and what they perceive in a service environment in the context of beauty salons.
Inhibition of Mild Steel Corrosion in Acidic Media Using Palmyra Palm Peduncle Extract: Experimental and Theoretical Investigation
Authors: P.R Vijayalakshmi , R Rajalakshmi
Published: April 2022

Utilizing gravimetric and electrochemical measurement techniques, the effective performance of inhibitive and adsorption properties of aqueous extract obtained from destructive distillation of palmyra palm (Borassus flabellifer Linn.) peduncle (BFP) for the corrosion of mild steel (MS) in 0.5 M H2SO4 and 1 M HCl were investigated. From the experimental results, an aqueous extract of BFP was found to be a good adsorption inhibitor for the corrosion of MS in 0.5 M H2SO4 and 1 M HCl solutions. The inhibition potentials of the aqueous extract of the palmyra palm peduncle are enhanced by its phytochemical constituents. The density functional theory was utilized to examine the BFP extract/mild steel surface mechanism's properties and to describe the inhibitor's structural nature on the corrosion process. The surface morphological alterations of metal specimens in both inhibited and uninhibited solutions were studied using scanning electron microscopy (SEM). Fourier transform infrared (FT-IR) spectroscopy was used to validate the presence of phenolic components in the BFP extract.
Monitoring Students Attention on Smart Phone for E-Learning
Authors: A Abirami , M Vishnupriya , A Rubika , S Rithanya
Published: April 2022

Due to the COVID-19 pandemic schools are closed and students are taught to require up their categories via online. Parents will also be busy with their work-from-home duties. Many tasks are allocated to the students who are attending their online categories however there's no plan concerning their completion of their activities given by their staff. It's troublesome to observe the students throughout their online exams/daily tests and online classes by their teacher. Throughout online classes, the staff might teach the topics and provide some activities through the classes supporting the student grade. Some students might complete however some might not. Deep learning is an application of computing (AI) that provides systems the facility to mechanically learn and improve from expertise while not being expressly programmed. Activities of the scholar and results are sent to their parents to assist the degree of attention of every student by enforcing this law.
Multiclass Intent Analysis: Beyond the Conventional Polarities
Authors: Khan Hera , Srivastav Ayush , Mishra Amit Kumar
Published: April 2022

The sentiment polarity for an element determines the orientation of the conveyed feeling, namely, whether the text communicates the user's positive, negative, or neutral sentiment toward the object in question. Sentiment analysis is a crucial task in natural language processing, with numerous real-world applications. Most sentiment analysis attempts to predict whether a given text is positive or negative. One of the most efficient and robust methods applied in the domain of sentiment analysis is deep learning. The recent advancements in social networking sites and their growing impact on the behavior of individuals have led to many pieces of research in the field of study of such networking platforms. Multiclass sentiment analysis identifies the exact sentiment delivered by the tweets instead of merely generalizing those sentiments as positive, negative, and neutral. In the case of online buying, most clients resort to the reviews about the same product they want to buy that are posted on the website. This work incorporates understanding the real-time situations of different customers' reviews about several products purchased through online shopping platforms thereafter determining whether their review is an Appreciation, Complaint, Enquiry, or Non-Intent. This paper includes Max-Vote Ensemble Technique, comprising three deep learning models: Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), and a combined model of CNN and LSTM. These models predict the review’s sentiment and strive to classify multiple polarities breaking through the three conventional polarity categories.
Recognition of COVID-19 Affected Lungs Using CNN and Grad-Cam on Chest X-Ray
Authors: Moud Deepak
Published: April 2022

The COVID-19 disease which was initially originated from Wuhan, China continues hampering people's lives. With mutation (change in DNA) the virus is transforming into several different strains and causing respiratory problems by affecting alveoli in the human lungs. The latest strain B.1.1.529 has been named as an “Omicron” variant by the WHO. Due to the large numbers of cases reported every day there is a shortage of test kits in hospitals. Considering this factor we will be building a deep learning convolutional neural network that will classify an X-ray image between normal and infected lungs. The comparative analysis of trained models is also discussed based on various optimizers. The dataset has been collected from multiple sources from the internet including Kaggle and has 8000+ COVID-19 infected and normal lungs X-ray images. Gradient Class Activation Maps are also being used to highlight the infected portion from the COVID-19 infected image.
Performance Analysis of a High-Speed Optical Transmission System Using Various Pulse Generator
Authors: Muduli Sudha Subhalaxmi , Padhy Laxmikanta , Polei Swadhin , Panda Tusharkant
Published: April 2022

The future generation technology needs network expansion, large bandwidth capacity, and modern application development. Due to dielectric in nature, having electromagnetic immunity, having larger bandwidth, and being a lightweight cable, the demand for optical fiber has grown expeditiously. ISI (Inter Symbol Interference) hampers the performance of optical communication drastically. It induces a superabundant increment in pulse duration, rolling out in time and space engrossed by the pulse as it propagates. As the pulse propagate along the optical fiber, this spread can be so enormous that a photo detector can no longer discriminate boundaries between pulses. Due to ISI, path loss increases rapidly and causes broadening of pulses and achieving high data rates becomes difficult. To reduce the effect of ISI pulse shaping technique is used. In this paper the channeling performance of optical fiber and DCF is estimated by using different pulse generator. Here we collated the performance of APD photo diode and PIN photo diode value in terms of Q-Factor and Bit Error Rate in the eye diagram. We have used a DCF to mitigate the effect of dispersion produced in the channel.
One-Pot Green Synthesis and Catalytic Activity of Bismuth/Reduced Graphene Oxide (Bi/rGO) Nanocomposite Using Lemon Juice
Authors: Mahiuddin Md. , Ochiai Bungo
Published: April 2022

A facile, cost-effective, and one-pot green strategy was introduced to prepare a nanocomposite (Bi/rGO) of reduced graphene oxide (rGO) decorated with bismuth nanoparticles (BiNPs) using lemon juice as a reducing agent. Simultaneous reduction of Bi3+ to BiNPs and GO to rGO produced the Bi/rGO nanocomposite consisting of 20-50 nm of BiNPs and a few layers of exfoliated rGO sheets. The obtained Bi/rGO nanocomposite showed excellent catalytic efficacy for the reduction of 4-nitrophenol to 4-aminophenol in the presence of sodium borohydride.
Effective Demarcation of Coronavirus Disease Transmission Rate Using Rule Based Techniques
Authors: SP Srinivasan , J Anitha
Published: April 2022

COVID-19 is a real life-threatening disease which has locked up the whole globe. In spite of the rapid sharing of information and inculcating social responsibilities by multiple factor such as personal hygiene, social distancing, and self-isolation, the spread of COVID-19 is increasing day by day. Controlling the spread of disease in early stage becomes the primary responsibility of the government. The judicial administration, along with the health care workers, struggle tirelessly to flatten the curve by taking measure to reduce the spread of disease. The primary objective of this paper is to help the government in this aspect of buying time to control the spread of virus. The World Health Organization notified that “COVID-19 is transmitted via droplets and fomites during close unprotected contacts between an infector and infected.” Hence, the key strategy should focus on preventing the virus before becoming a community transmission. Locating the area of very high possibilities of COVID victims becomes the highest priority to block transmission. This can be done by identifying the parameters which influence the spread of disease and applying on the large volume of data obtained by the area wise survey information. In this paper, a decision tree is built using Iterative Dichotomiser (ID3) and it is further compared using Naive Bayes classification algorithm to check the accuracy of the result obtained by ID3.
Opportunities Created by Digital Technology and Increased Data
Authors: Chauhan Abhay , Sharma Akshay , Sikhwal Om Prakash
Published: April 2022

The major goal of this paper is to raise awareness of how digital technologies are altering traditional practices in a variety of sectors. When it comes to education, digital technologies have revolutionized it by replacing paper books with e-books, and classroom instruction with live video streaming. Connecting teachers and students across the world through internet. How storage evolves from hardware to completely online. How managing data is big domain for MNCs to work upon it.
Effects of Free Convective Flow of Electric Field in Couple Stress Fluid with Isothermal Boundaries
Authors: Prasad M Siddalinga , B S Shashikala
Published: April 2022

Electrohydridynamic Oberbeck convection of a couple stress fluid bonded between two isothermal boundaries in the presence of an external constraint of applied electric field is investigated analytically and numerically. An induced electric field is also produced due to the temperature difference, which intern produces an additional body force. Analytical solution for velocity and temperature is obtained using the perturbation technique and the numerical solution through the finite difference technique. The effect of flow and thermal parameters on velocity and temperature are studied and presented graphically. It is observed that the fluid velocity is augmented by the increase in x0, α, W, suppresses by the increase in N and λ, and flow reversal by varying Re. The temperature is augmented by increase in W, N, Re, and suppressed by the increases in λ, α, x0.
Toxicity at Work Place: Coping Strategies to Reduce Toxins at Work Place
Authors: Pimenta Francis Xavier Elston
Published: April 2022

Employee or leader negativity affects the performance of the workforce, thus leading to loss and poor growth of the organization. The purpose of this research is to understand toxins at work place and their impact on performance of employees. This research reviews the literature associated with factors leading to toxicity at work places. The study also provides an overview of the issues faced by the organisations due to toxic behaviour of the employees especially working in IT firms. Data was collected from IT employees and was analysed by using Structural Equation Modelling(SEM). There results indicated that these toxins had negative relationship with employee engagement. Toxins present in organisations lead to a feeling of dissatisfaction, and unwillingness to take initiative. Dynamic changes in the IT sector with the behavioural issues were not addressed adequately in the reported literature. With newer generations, Gen Z and centennials, taking up key positions in the organizations it was imperative to conduct such study. Keywords: Employee toxicity, employee engagement, IT employees
State-of-the-Art Dynamic Load Balancing Algorithms for Cloud Computing
Authors: Rani Meena , Guleria Kalpna , Panda Surya Narayan
Published: April 2022

Cloud computing is a technological commitment that allows it to achieve a set goal, improving business performance. Cloud computing offers many applications like scalability, extensive infrastructure, storage, resource pooling, virtualization, and a wide range of online services. Cloud service providers provide a variety of technologies to cloud computing users all the time. Algorithms for load balancing were applied to enhance the speed and performance of nodes in cloud environments and protect each device from affecting their threshold by reducing their performance. Classification of different algorithms was made according to two factors, i.e., the person initiating the algorithms and the current state of the process. Dynamic load balancing algorithms are based on challenges like high availability, scalability, fault tolerance, virtual machine migration, and low response time. Dynamic load balancing algorithms apply some policies because they use the current state of a system. This paper provides the study of state-of-the-art algorithms used in cloud computing and performance parameters, which are based on different load balancing systems.
Investigation for Performance Comparison of Solar Tracking System with Static Solar System
Authors: Mamodiya Udit , Tiwari Neeraj
Published: April 2022

Around the world, sun oriented force has become the third greatest wellspring of vitality after hydro and twist, in this manner, grabbing a worldwide eye. This investigation draws a correlation between the presentation of Solar Tracker and Static Solar System or a nearby planetary group with fixed pivot to evaluate the sunlight based force. By utilizing different sun points, for example, peak, sunlight based elevation, and solar altitude, sun powered irradiance was determined during a day either shady or radiant, while the aggregate vitality created during the entire month was additionally estimated. In addition, for a more clear understanding, proficiency contrasts during a day just as during the entire month were considered as well. The outcomes of simulations show that implementing the sun tracker concept can increase the efficiency of a solar PV system. It has been determined that by implementing the azimuthally tracking system and the elevated tracking system, PV system efficiency is increased by 37% and 12%, respectively.
Factors Influencing the Policy Formulations and Strategies for Disaster Risk Reduction
Authors: Dutta Atul , Kumar Ambuj
Published: April 2022

Disasters are evolving and creating impacts in new shapes and sizes with each passing year. Identification and clear understanding of the various significant factors is required for the development of appropriate policies and strategies for disaster risk reduction. There were few empirical investigations that established causative variables in the desired field. The literature was reviewed in the research area with due consideration to multidisciplinary nature of disaster management and after analyses and synthesis recurring factors were identified and summarized in the paper. Understanding underlying factors having influence on formulations of various strategies and policies can add new dimensions and values to the multidisciplinary nature of disaster management.
Conflicting Overlaps Between the Public and Private Realms Within the Heritage Precincts in India
Authors: Nayak Bibhu Kalyan , Kapoor Sunanda , Bhandari Harveen , Saxena Neha
Published: April 2022

Significant changes in the architectural character of traditional buildings have led to various issues of difference in imageability. Thus there is difficulty in identifying the specific characteristic of heritage values of the past context. Lack of appropriate guidelines and poor awareness of the importance of heritage among property owners and authorities has led to unplanned development/growth, spoiling the overall ambience of the place. The socio-legal perspective is also a very crucial aspect that researchers often study in isolation. However, the contextual interpretation of the law often defines and defends socio-cultural boundaries. Hence, understating legal viewpoints in such a situation can aid in the informed decision-making process.
A Survey Study Impact of Mergers on Indian Banking Industry
Authors: Bhargave Harshita , Tandon Dinesh
Published: April 2022

Indian economy is growing and developing at rapid pace. Big corporate and industrial houses perceive the Indian market as hub for investment. Mergers and acquisitions activities have increased substantially. Mergers in India as a rule have encountered an expanded number in banking division. Therefore, this study has been proposed in which survey and personal interviews are conducted to study the impact of mergers on Indian public sector banks. A structured questionnaire has prepared and, on this account, the key opinions and suggestions of senior bank employees are reported. Further, data analysis and interpretation has been considered. The results revealed that the reasons behind mergers in banking industry are robust banking systems, compensation of losses, and enhancing the capital capacity. 40% of the banks believe that mergers help in achieving economies of scale. 74% of the respondents asserted that to increase capital without any difficulties, merger is the best strategy.
Comparative Analysis of Deep Learning Based Automated Segmentation of Pneumothorax on Chest X-Ray Images
Authors: Malhotra Priyanka , Gupta Sheifali , Koundal Deepika
Published: April 2022

Pneumothorax is a deadly chest disease causing human lungs to collapse due to leakage of air into the area around the lungs and the walls of the chest. Chest X-ray is an imaging technique for diagnosing pneumothorax. A CAD or computer aided diagnosis system can identify pneumothorax in the chest X-ray. The present work uses a U-Net based deep learning model to segment the regions of pneumothoraces in chest X-ray images. The paper highlights the improvement in the performance of U-Net model by utilizing hypercolumns. The model is trained and tested using SIIM-ACR pneumothorax segmentation challenge dataset. The results show that the model performance improves with hyper columns. The U-Net model without hypercolumns generated the best DICE coefficient of 0.778, while the model with hypercolumns gave best DICE coefficient of 0.822.
Ex-Vivo Evaluation of Eflornithine Hydrochloride Loaded Solid Lipid Microparticles Based Cream
Authors: Grewal Ikmeet Kaur , Singh Sukhbir , Arora Sandeep , Sharma Naleem , Behl Tapan , Zahoor Ishrat
Published: April 2022

Hirsutism is an unpleasant condition that affects a large number of women. Hirsutism can make females feel exceedingly self-conscious, jeopardizing their sense of femininity as well as their self-esteem. They are employing established treatments without evaluating their negative consequences, necessitating the development of new procedures. EFH loaded solid lipid microparticles (EFH-SLM) were manufactured using the solvent evaporation technique using polymers. Hair regrowth investigations in healthy Swiss albino female mice were carried out ex-vivo. Animals treated with EFH-Cream and EFH-SLM-Cream had the fairest and least dense hair densities on day 21. In comparison to regular EFH-Cream, this revealed that cream loaded with EFH-SLM was more efficient. On day 21, hair weight per cm2 was weighed for all groups of animals, and it was discovered that there was a substantial difference between animals treated with EFH-cream and EFH-SLM-Cream, which could be related to EFH-increased SLM's permeability. In comparison to animals treated with EFH-Cream and marketed EFH cream, animals treated with EFH-SLM-cream had fewer or no skin rashes or inflammation.
Magnetic Ferrites: A Brief Review About Substation on Electric and Magnetic Properties
Authors: Kaur Baljinder , Kaushal Gaytri , Rana Shikha , Kumar Pankaj , Khanra Partha , Dhiman Meenakshi
Published: April 2022

The bulk and nano dimensional ferrites have been widely studied over the last five decades to offer novelty of processing, structural variation during synthesis, and its possible utilization for the advancement of modern devices. Precisely, in order to improve the magnetic properties, the orientation of the atoms or electronic structures inside the crystal are the major causes. Many attempts have been made to understand the behavior of dopants in electronic structures as well as magnetic effects. In addition, an in-depth analysis of the findings published by various researchers is offered here to assist readers in evaluating the previously investigated, variably doped ferrites for their electric and magnetic properties.
Utilization of Plastic Waste and Its Management: A Mini-Review
Authors: Dhiman Vishal , Kumar Akhilesh , Chaudhary Akshay , Singh Jagdeep , Goyal Ajay , Kanoungo Abhishek
Published: April 2022

Developing countries including India suffer significant environmental issues as a result of plastic waste generation and insufficient waste collection, transportation, treatment, and disposal that adversely impact the ecosystem, human health and sustainable future. In India, plastic waste is generated at a rate of 26,000 tonnes per day (TPD). Even though 60% of India's plastic is recycled, the country still has 9,400 TPD of plastic waste. This paper focuses on a mini-review of the recent available literature on the utilization of plastic wastes in India and its management. The analysis offers a comparison of plastic consumption across India's states. Effects of plastic waste on the different environments (soil, water, and marine) and human health are also elucidated. To reduce plastic use and address the problem of plastic waste accumulation, efforts must be made to examine the usage of renewable raw materials in innovative goods as a result of recent technological advancements.
A Review Based Study on Transformational Leadership and Its Future Prospects
Authors: Malhotra Nidhi , Aggarwal Rashmi
Published: April 2022

The objective of this review was to systematically retrieve and review the key literatures pertinent to the concepts and aspects of Transformational Leadership. As the literature appraisal was the crucial module of this research, identifying relevant studies had to be a systematic as well as significant process. To retrieve as many pertinent published articles as possible, this study referred the different database and search engines and various pre-synthesized keywords, including Transformational leadership style, Transformational leadership behavior, leadership, and Transformational leadership in industry. “Transformational leadership” and “transformational leadership in industry” were used as the main keywords and phrases which retrieved enormous amounts of original peer-reviewed studies. The literature search identified many published articles indicative of the significance of the Transformational leadership. The subject of operative leadership in organizations had been indicated by recent many studies. When selecting, promoting, and appraising employees, leadership skills were taken into account. In credit of its standing, organizations stereotypically assisted and encouraged the development of employees' leadership skills as evident. The review provided a comprehensive assessment of different transformational leadership scales and suggested MLQ as a short scale that was found to be easy to administer and score. The evidence indicated that it had acceptable reliability and construct validity.
A Study of Investment Risk Tolerance Among Teachers in Higher Education Institutions
Authors: Agarwal Richa , Jain Mukul , Arora Richa
Published: April 2022

Risk tolerance is an important dimension of the investment and financial planning behavior and hence it is important to understand educators’ perception of financial risk to interpret their investment behavior. This paper examines the investment risk tolerance abilities of teachers from various disciplines working in higher educational institutes and tries to test whether demographic factors like gender, age and income have any significant influence on their risk-taking abilities. The study would try to find out whether teachers in higher education are risk-averse, risk-tolerant or risk-takers. It would try to find if risk-taking capacity is dependent on age, (i.e., older Verses younger teachers), gender and income. The study would be beneficial to policymakers, wealth managers, investment planners, institutions etc., to construe various aspects of economic behavior and develop programs for the improvement of the financial well-being of higher education teachers.
A Study of Financial Planning Behavior of Women College Teachers Working in Delhi-Ncr
Authors: Agarwal Richa , Jain Mukul
Published: April 2022

Women constitute nearly half of the world population; more Indian women are joining the service sector especially teaching. Financial planning awareness among them will ensure more gender equality through financial independence. It will also reduce inequality in society. Women teachers’ active participation in financial markets will help financial resources to be channelized in the system through capital generation, which is essential to ensure trending economic growth. It is important to understand the financial behavior of female college teachers to ensure quality education by preparing more fiscally aware and responsible youth. An attempt is being made to examine the personal financial planning behavior of women teachers in higher education in Delhi-NCR. The data of 428 women teachers of Delhi-NCR colleges analyzed using the percentage method, correlation, and factor analysis revealed a satisfactory level of financial planning awareness among them. The study will prove beneficial to agencies and institutions to draft policies to strengthen the country both economically and socially.
Design and Analysis of Real-Time Applications Based on Software Designed Radio (SDR) Using 2×2 MIMO USRP 2920 and LabVIEW
Authors: Soni Gaurav , Sharma Manish
Published: April 2022

The utilization of radio spectrum is becoming more necessary in light of recent advancements in wireless technologies. The available spectrum, on the other hand, is very constrained. In other words, Cognitive Radio (CR) is utilized to make the best use of the spectrum that is available. While unlicensed users should use CR technology to validate the spectrum before utilizing it, licensed users should always employ CR technology. Using dual antenna arrays to produce multiple-input multiple-output (MIMO) setups in wireless communication has sparked a great deal of interest in wireless technology. In this research work, M-ary QAM modulation scheme is used to investigate SDR based link using 2x2 MIMO system and implemented on USRP 2920 with the help of LabVIEW 2015. LabVIEW was used to operate the NI USRP 2920, a universal software radio peripheral. With the introduction of MIMO, greater use of limited spectrum may be accomplished by utilizing lower power usage. This article further explores the methods and techniques to design a real-time applications using concept of SDR and provides optimized data rate, link range using MIMO implementation. USRP 2920-based MIMO experimentation is used in this paper's findings (Universal Software Radio Peripheral). 7-inch vertical tri-band antennas are employed in the present research. Further open loop (OL) MIMO methods for mobile broadband radio access technologies like 4G and 5G are examined in this study. The proposed SDR setup based on 2x2 MIMO and USRP 2920 can be used for bandwidth efficient design and implementation of IoT based real-time applications.
State-of-Art Review on Automated Glaucoma Detection Using Machine Learning Techniques
Authors: Lamba Kamini , Ahuja Sachin
Published: April 2022

Glaucoma is one of the biggest factors of blindness as it leads to illness of neuro-degeneration. Early detection can help in controlling its progression although it cannot be cured. A systematic analysis was conducted on the basis of publications acquired from Scopus, IEEE Xplore, Science Direct and PubMed databases. Focus was on the papers comprising computer aided diagnosis techniques of glaucoma. As evident from literature, there is a possibility of developing an automated system for detection of glaucoma by employing existing techniques of deep learning, machine learning etc. This paper provides a systematic overview of techniques which aids glaucoma detection based on Fundus images using computer-aided methods. Results obtained from comparative analysis of various techniques help in identifying challenges presented from image processing to machine learning and suitable technique of detection as per the types of glaucoma.
Examining the Role of Fintech in the Future of Retail Banking
Authors: Varma Parminder , Nijjer Shivinder
Published: April 2022

This manuscript aims to examine how Financial Technologies (FinTech) influence the efficiency and market power of banks in India. This assessment is made based on a quantitative analysis of private and public banks from 2011 to 2019. The research uses the Data Envelopment Analysis (DEA) and panel regressions with pooled Ordinary Least Squares, Fixed Effects, and Random Effects. FinTech is represented by the volume of mobile banking transactions. The results show that FinTech has a significant negative relationship with market power proxied by the concentration of banks. FinTech also has a significant negative effect on technical efficiency. Market power and efficiency of banks are found to share a positive association. The research is limited by the narrow representation of FinTech and inferring about the market power based on the industry structure alone. Future studies are recommended to use alternative proxies and consider more disruptive and sustaining innovations to represent FinTech.
Electrical Performance Analysis of AlGaN/AlN/Sapphire MSM Photodetector for Threshold Voltage Using Varying Doping Levels
Authors: Kaur Harpreet , Kaur Harsimranjit , Hooda Manish Kumar
Published: April 2022

It has been demonstrated in past studies that doping concentration of photo-absorbing layer has a significant impact on the electrical characteristic of MSM detectors. However, effect of doping concentration on threshold voltage and over desired RB (Reverse Bias) range of AlGaN MSM detectors is studied in few research reports. In the present study, photocurrent at threshold voltage and beyond it have been investigated for 1e18 cm-3 and 1e19 cm-3 doping concentrations basedAl0.5Ga0.5N/AlN/Sapphire MSM detectors. For both detectors, key electrical parameters like electric field, dark current density, and recombination rate at the top surface have been analyzed using I-V characteristics and cut-line plots extracted by Atlas simulator. It is observed that the magnitude of photocurrent and threshold voltage remains very high of higher doping detector as compared to lightly doped case. Thus comparative analysis can be helpful for selecting suitable doping at particular bias for high performance, low noise communication, and reliable UV detection applications.
The Scope and Functions of Health Information Management in e-Health
Authors: Nair Deepa P
Published: April 2022

e-Health adoption in health care leads to a clinical transformation, affecting the scope of health data, work processes, roles, interactions, and above all, the culture of the global health system as a whole. Advancements in the application of health information technology (HIT) have certainly reformed the health care landscape and how health data are being documented, processed, and disseminated This review paper aims to explore the expanding scope and functions of health information management in e-health. The study also intends to identify the evolving functions of health information management for the meaningful use and transmission of health data in e-health environment. The study reveals the challenges of transmitting health data in the e-health systems and the areas of e-health where meticulous health information management is required.
Magnetic Nanoparticle Tracking for One-Step Protein Separation and Binding Kinetics Analysis
Authors: Zhao Yunlei , Ma Guangzhong , Wang Shaopeng
Published: April 2022

Label-free techniques for quantification of protein-protein interaction often requires protein samples separated from complex media using affinity purification tools such as magnetic nanoparticles. However, the separated proteins are attached to the nanoparticles and need additional preparation steps, including elution and immobilization to a sensor surface before measurement. To streamline this tedious process, we present a method that can directly quantify the protein binding kinetics on nanoparticles without elution and immobilization, by optically tracking the nanoparticle size change upon ligand binding. We measured antibody binding to nanoparticles with captured protein, which was pulled down from a different medium prior to the measurement. The source of noise for the method was also analyzed. We anticipate this method can simplify the workflow from protein separation to detection while providing sufficient binding kinetics and affinity information for protein studies.
Scene-Specialized Multitarget Detector with an SMC-PHD Filter and a YOLO Network
Authors: Liu Qianli , Li Yibing , Dong Qianhui , Ye Fang
Published: April 2022

You only look once (YOLO) is one of the most efficient target detection networks. However, the performance of the YOLO network decreases significantly when the variation between the training data and the real data is large. To automatically customize the YOLO network, we suggest a novel transfer learning algorithm with the sequential Monte Carlo probability hypothesis density (SMC-PHD) filter and Gaussian mixture probability hypothesis density (GM-PHD) filter. The proposed framework can automatically customize the YOLO framework with unlabelled target sequences. The frames of the unlabelled target sequences are automatically labelled. The detection probability and clutter density of the SMC-PHD filter and GM-PHD are applied to retrain the YOLO network for occluded targets and clutter. A novel likelihood density with the confidence probability of the YOLO detector and visual context indications is implemented to choose target samples. A simple resampling strategy is proposed for SMC-PHD YOLO to address the weight degeneracy problem. Experiments with different datasets indicate that the proposed framework achieves positive outcomes relative to state-of-the-art frameworks.
A Clinical Analysis and Literature Review of Six Cases with Primary Pulmonary Lymphoepithelioma-Like Carcinoma
Authors: Ye Lingyan , Luo Dinghai , Li Haiyan , Zheng Haihong , He Susu , Lin Ling , Fang Yicheng , Ye Junhui , Chen Chengshui
Published: April 2022

Object. To investigate the clinicopathological features, imaging findings, treatment, and prognosis of primary pulmonary lymphoepitheliomatoid-like carcinoma. Methods. The clinical data of six patients with primary pulmonary lymphoepithelioma-like carcinoma treated in Zhejiang Taizhou Hospital of Taizhou Enze Medical Center (Group) from May 2014 to December 2018 were summarized and analyzed. Combined with the relevant literature, the primary pulmonary lymphoepithelioma-like carcinoma was analyzed retrospectively. Results. The main manifestations of six patients were respiratory symptoms, and cough was the most common. The imaging features of six patients were mainly round-like high-density mass shadow or nodule shadow. All patients were diagnosed by pathology. Microscopically, the cancer cells were nested, with large nuclei and vacuoles and abundant lymphocyte infiltration in the tumor stroma. The positive rates of EBER, p63, CK5/6, and Ki-67 were high, and TTF-1 was negative. Five patients received surgical treatment. One patient developed brain metastasis 12 months after operation and received craniocerebral radiotherapy. The other patients did not receive radiotherapy and chemotherapy, and one patient did not receive treatment. After follow-up, four patients survived so far, the longest survival time was 82 months, one patient lost follow-up, and one patient died of lung metastasis 24 months after operation. Conclusion. Primary pulmonary lymphoepitheliomatoid-like carcinoma is a rare lung malignant tumor, whose pathogenesis is related to Epstein-Barr virus infection. The clinical manifestations are nonspecific, but with unique pathological characteristics. Surgical resection is the proper treatment for early-stage patients, and comprehensive treatment with surgery as the main treatment is suitable for late-stage patients. The prognosis is good.