bluuebunny/crossref_metadata_2025 huggingface dataset:
Brief Overview on Synthesis and Application of Ni–Doped Carbon Dots
Authors: Khajuria Ajay , Sudan Shubam , Kapoor Mohit
Published: April 2022

Carbon dots (CDs) are semiconductor materials with sizes ranging from 2 to 10 nm. Among these CDs, nickel CDs (Ni@CDs) materials have piqued researchers' curiosity in the past years due to their specific properties, such as strong catalytic activity, good stability, great hydrophilicity, and high oxidation states. Several synthetic pathways exist for the synthesis of Ni@CDs, such as hydrothermal method, microwave irradiation, green synthesis, pyrolytic decomposition, precipitation method, and electrochemical route. These Ni@CDs have shown application in charge transfer, excellent thermodynamic stability, luminescent properties, high chemical and photo-stability, opto-electronic devices, catalysis, sensing, and drug delivery. In this review, various synthetic methods had been explored extensively along with their numerous applications.
A Review Paper on Machine Learning Applications, Advantages, and Techniques
Authors: Dahiya Neelam , Gupta Sheifali , Singh Sartajvir
Published: April 2022

With the enlightenment of knowledge and the inception of databases in large number, how to fetch the important information from the raw data is the major problem which is needed to be solved. Machine learning is a technique which is helpful in solving this issue with more accuracy and in a faster way. Machine learning working process is to train the data and the algorithm develops some rules, based on that learning, evaluation is done with the test data to generate results without human intervention. This paper portrays the various application areas of machine learning, along with its advantages and drawbacks. This paper also describes the various supervised and unsupervised algorithms with their categories, which are used to solve various problems. This paper will help the researcher in finding various application areas of machine learning and also help the researcher in selection of particular techniques according to the situation. Moreover, the researcher can also learn the detailed knowledge about machine learning. This work can be extended further with comparison of machine learning and deep learning techniques. This area has vast scope and is helpful for the researcher in detection of various crop problems, and disease detection like cancer detection, skin problems, etc.
A Systematic Review of Live VM Migration Techniques for Energy Management
Authors: Gupta Neha , Gupta Kamali
Published: April 2022

The present computing era has been inclined towards providing services to the customers all round the clock and is driven by utilization of existing resources in its entirety to assist service providers in extracting maximized profits. The key technique in achieving the automated services despite of geographical locations is creation of virtual machines using virtualization hypervisor. Though it entails several benefits of increased resource utilization, but it faces challenges of energy mitigation and related migration overheads originated due to balancing of load on the physical servers, fault handling in VM or server, transfer of irrelevant data, etc. If the total time and energy invested in every single VM migration can be minimized, it can give better results in term of energy consumption, total downtime, and migration time. Thus, the paper outlines a detailed review about various components of VM migration along with existing techniques and related aspects.
A Systematic Review of Fault Management Framework in Wireless Sensor Networks
Authors: Pundir Meena , Sandhu Jasminder Kaur , Kaur Rajwinder , Singh Gurjinder , Mehta Aina
Published: April 2022

Wireless Sensor Networks (WSNs) have progressively appeared as a buzzword for the prevalent research areas of networking in the twenty-first century. The main application areas include threat detection, industrial monitoring, environment monitoring, military surveillance, weather forecasting. Since the sensor nodes are deployed in a hostile environment, they can develop a fault due to this environmental impact. The occurrence of these faults must not hamper the functioning of the entire network. Hence, Fault Management plays a vital role in improving fault tolerance. To improve the Quality of Service (QoS) of the overall network, a fault management scheme has to be incorporated. This scheme can be further enhanced using Machine Learning. Fault Management scheme includes the fault prevention mechanism which is applied at the design level. Fault Detection is performed at the operational level using Machine Learning techniques. The classification of faults occurring in the network helps in Fault Identification and Isolation. The last step is fault recovery, which provides a suggestive countermeasure. This article discusses the taxonomy of fault management framework categorized into central, distributed, hierarchal, hybrid, classification based on their performance.
Popular Physiological Trait Based Biometric Authentication Systems
Authors: Bajaj Vandana , Kaur Navdeep
Published: April 2022

Biometric systems are mostly preferred by different fields because of their higher security features. In past, passwords were used to identify and validate the genuine users. However, it was not preferred because these can be easily accessed by the third party. Hence, consequently it increases the frequency of fraudulent and breach incidents. In contrast to this, biometric systems provide full authentication of an individual based on their physiological traits and modalities that are used as input to biometric system. The paper presents a review that is mainly focused upon the four physiological modalities; face recognition, fingerprints recognition, iris recognition, and retina scan. In the knowledge of existing challenges the paper illustrates the different studies presented by research community in the similar field. A comparative analysis of physiological modalities is presented in the paper that shows the rising popularity of deep learning techniques in the biometric design.
Carbon Dioxide Sampling and Analysis Technologies for Aquatic and Terrestrial Ecosystems
Authors: Deák György , Rotaru Anda , Enache Natalia , Laslo Lucian , Matei Monica , Boboc Madalina , Bara N.
Published: April 2022

One of the worldwide approaches for climate change mitigation is to act on reducing the anthropogenic contribution to the concentration of greenhouse gases (GHGs) in the atmosphere. The terrestrial and aquatic ecosystems are characterized by their natural exchange of GHGs with the atmosphere and also as a result of anthropogenic activities (management). The purpose of this work is to describe two complementary methods for measuring GHGs exchanges between atmosphere and aquatic or terrestrial lands. For this purpose, we conducted comprehensive CO2 field activities along two types of ecosystems. The goal of this study is to demonstrate the reliability of the injection kit for collecting the CO2 samples in order to later deduce EGM-5 values.
A Single Stage Sepic Converter for Electric Vehicles Charging
Authors: G Ramanathan , C Bharatiraja
Published: April 2022

This proposed system is about bidirectional power flow for charger of an E-Vehicles. The charger connected with PV source is designed, modelled, and implemented. In this topology, the output charging current is regulated by DC-DC converter. The bidirectional interleaved isolated SEPIC converter is proposed in this paper for charging the electric vehicle. The multi-step constant current charging method is used for charging operation. This reduces the number of power electronic components, which in turn minimizes the power loss. Simulation is carried out in MATLAB/Simulink, and the results are obtained, which shows that battery can be charged with this topology.
Factors Impacting Educators’ Intention Towards E-Learning Adoption
Authors: Kumar Pawan , Tandon Urvashi
Published: April 2022

Educators play a vital role in learning system and in the present scenario E-learning highly in use in the pandemic. There are gaps in studies. Most of the research are student centric whereas educator’s role is more important as a content developer as well an effective presenter. The challenges for educators are getting familiar with the resources and application platforms changing concurrently like time constraints, negative attitude from parties involved, a lack of technical skills, infrastructure, organizational strategies support, and cyber threats. This study with taking the support of UTAUT2 in academic context tries to discover the factors impacting educators' intention with E-Learning technology. Most of the research carried out has not worked on the risk factors like technological, evaluation, cyber, psychological, interaction, and time involved in E-learning, so the current study proposes a behavioral model TECPIT (Technological, Evaluation, Cyber, Psychological, Interaction, and Time) to overcome the risk factors.
Mental Health of Doctors During COVID-19
Authors: Sayyad Anjum Usama
Published: April 2022

Since its emergence, the COVID-19 virus has become a global threat. It was declared as a global pandemic by the World Health Organization in January 2020. The mutation of the COVID virus has raised concerns for all the health care professionals and decision makers. These have led the disease burden to rise in unexpected ways. Therefore there will be an increased mental burden on the health care workers, especially the doctors. By the time they got familiar and understood the nature of the virus and were able to treat the COVID patients the second wave of COVID has aroused in India. This has led to the need to study the mental health of the doctors. This study hence focuses on first to analyze the feelings, thoughts, and well-being of doctors, second to identify the practical adjustments made by doctors in COVID times. Based on the objectives, the researcher has statistically tested the hypothesis using correlation analysis. Apart from the hypotheses there were other relationships which are statistically analyzed and presented in the form of graphs. The sampling method used for this study was stratified random sampling. Since the respondents were doctors, it was difficult for the researcher to make the respondents answer the Google form. Hence, the sample size was 46. This was the limitation of the study.
Gharats: Ancient Technological Marvel at the Verge of Extinction
Authors: Malik Gautam , Saini Abhineet , Singh Harvinder
Published: April 2022

The Indian subcontinent has an abundant source of freshwater which flows in the form of rivers, streams, and khuds. These fresh sources of water are not only used to meet the requirements of water flowing through the villages, but have been harnessed for centuries by the people living in the mountainous region as a source to meet the demands of the people in a sustainable way. One of the ancient technological innovation was the establishment of Gharats, which served the people of the mountainous region for centuries by grinding the flour. This article studies the need and importance of Gharats and the challenges these Gharats face due to the industrialization. The paper is in sync with the Sustainable Development Goal 7: Affordable and Clean Energy and proposes to conserve these ancient technological masterpieces from being extinct and suggests the upgrade of these Gharats for the conservation of these heritage sites.
Effectiveness of Nurse-Led Educational Package (NLEP) on Knowledge Regarding HPV Infection, HPV Vaccination, and Cervical Cancer
Authors: Rani S , Raja A , Balasubramanian N , Malhotra Reetu
Published: April 2022

The authors developed the Nurse-Led Educational Program (NLEP) about HPV infection, HPV vaccination, and cervical cancer. They evaluated its efficacy by using descriptive and inferential statistics. The research plan was a quantitative research study that included one group, pre-and post-test. The cluster sampling technique was employed to select the sample. The data was gathered through the structured closed-ended interview. A greater or less similar set of information about demographics was observed in both the experimental and control group. In the experimental group, the significance of differences between pre-tests and post-test was tested statistically by using a paired test and found to be extremely relevant and there was no correlation between pre-test knowledge scores and post-test knowledge score demographic variables. The results of the study showed that there was a substantial improvement in the knowledge level of rural women about HPV infections, HPV vaccination, and cervical cancer. This means that NLEP is highly effective in rural women.
Probing Outcomes of Trait Emotional Intelligence: A Narrative Review
Authors: Nanaware Rajkumar Baburao
Published: April 2022

In the present endeavor, the researcher intends to emphasize the current understanding pertinent to trait emotional intelligence and explore its shift in conceptualizing sub-dimensions of emotional intelligence in the general population. Out of the 60 studies analyzed from the open-access electronic databases, the investigator selected 12 for critical narrative review, primarily focusing on (i) articles published in double-blind peer-reviewed journals in English between 2010 and 2020; (ii) covering student populace; (iii) the use of EI and Trait EI scales; and (iv) longitudinal, conceptual, research-oriented quantitative, and qualitative designs. The treatise was narrowed down to 12 studies by systematically applying the exclusion criteria. On scrutiny, it was revealed that most of the investigations were focused on the general population’s good mental health, including emotional functioning, leadership, and academic achievement. This covered an individual’s personality and well-being. Some studies focused on physical health and stress management. To a greater extent, the Trait EI constituent elements were associated with better mental health, academic excellence, cognition, and unique personality and leadership abilities.
The Household Financial Management during the Covid Pandemic – a Comparative Analysis
Authors: Gade Surendar
Published: April 2022

Purpose: to understand and personal financial management before and during the Covid Pandemic and its impact. Further, to make certain suggestions to better personal and household financial management. Methodology: This study was survey based, 192 respondents were picked from Government, private, business, self-employees and others. Paired t-test was applied to know whether the mean difference between financial behavior of individuals before and during the pandemic along with required descriptive statistics. Findings: Study found that there is a significant difference in financial behavior of individuals before and during the pandemic. It is found that around 30% of income has come down during the pandemic, according their spending been also affected. They opined that their priorities have changed due to this pandemic and they need advises from experts to get out this. Further, study has offered some suggestions to better their financial management to face such kind crises.
Antecedents of Green Purchase Behavior: A Study of Consumers in Northern India
Authors: Kour Manjit , Kaur Rajinder , Sharma Anmol
Published: April 2022

Environmental degradation and depleting natural resources are the biggest concern for the whole world. Green purchase behavior will go a long way toward bringing sustainability to the environment. It will help us in adopting ‘Responsible Consumption and Production,’ which is one of the 17 sustainable development goals (SDGs) of UN. This study is an attempt to find the gap in awareness about environmental concerns and actual green purchase behavior. The main objective of the study is to examine the antecedents of purchase behavior and their influence on green purchase behavior. A sample of 200 consumers from the Punjab region of India is used for this study. Factor analysis, regression analysis, and correlation analysis are used to analyze the relationship between green purchase behavior and its antecedents. The results of the study confirm that green purchase behavior has a positive and significant association with green attitude and green self-concept, whereas no significant relationship is found between green purchase behavior and green perception.
Chromatic Dispersion Compensation Using Adaptive Fiber Bragg Grating for High-Speed Optical Communication
Authors: Pradhan Somya Ranjan , Sahoo Soumya Ranjan , Pradhani Gyan Ranjan , Panda TusarKant
Published: April 2022

Optical fiber is a glass or plastic like wired structure used to transmit information in the form of optical signal from transmitter to receiver end. Whenever we talk about any communication system, we always look over losses. This paper is focused on dispersion loss and how to reduce it. When the pulses travel through optical fiber, after travelling some distance, each pulses start spreading and overlaps with each other and leads to dispersion loss. A phenomenon in which the optical signal gets spread into different colors, each color has its own wavelength and respectively each wavelength travels in different velocity, which cause time delay, and this leads to chromatic dispersion. This paper analyzed the optical fiber performance and reduced dispersion loss in fiber by taking various of FBG function and grating length into consideration. The performance of FBG examined in terms of bit error rate, quality factor value in eye height.
Improvement on Tensile Properties of Epoxy Resin Matrix Sugarcane Fiber and Tamarind Seed Powder Reinforced Hybrid Bio-Composites
Authors: Jayaraman R , Girimurugan R , Suresh V , Shilaja C , Mayakannan S
Published: April 2022

Nowadays, hybrid bio-composites are being developed by combining different natural resources as reinforcement and filler components, and this has raised their necessary qualities dramatically. Sugarcane fibre and tamarind seed powder particles added to an epoxy resin matrix to test the material's tensile strength were the focus of this study. A reinforcing material is sugarcane fibre, while filler components include tamarind seed powder particles. Different reinforcement and filler materials were used to make hybrid bio-composite specimens, while the epoxy resin weight percentage was maintained constant. Utilizing the hot press compression moulding technology, hybrid bio-composite boards were manufactured from start to finish. Water jet machining is used to remove hybrid bio-composite specimens for compression tests in accordance with ASTM standards from the hybrid bio-composite boards. It has been shown in experiments, for example, that adding tamarind seed powder particles to a sugarcane fiber/epoxy resin matrix considerably increases the hybrid bio-composites' tensile characteristics.
A Comprehensive Survey on Lightweight Asymmetric Key Cryptographic Algorithm for Resource Constrained Devices
Authors: Sundararajan Ananiah Durai Durai , R Rajashree
Published: April 2022

Elliptic Curve Cryptography, being a popular lightweight asymmetric key cryptographic algorithm that is widely adapted to meet high security requirement of resource constrained devices, were surveyed in this work. Further, ECC-based ElGamal cryptosystem, Elliptic Curve Digital Signature Algorithm, and Elliptic Curve Diffie Hellman Key Exchange Algorithm have been comprehensively reviewed with its characteristics and preferred applications. In addition, few related work are analyzed and suggestions for suitable target applications were provided. Moreover, ECC being a popular asymmetric key cryptographic technique is reported to be modeled using Vivado tool for various target implementation on FPGA devices. Techniques that enhances throughput, area, and computation time that caters for IoT applications were also reviewed. Design implementations on the advanced FPGA boards for IoT device/similar applications were also analyzed and compared.
Binding Interaction Analysis of Phytoconstituents of Commiphora mukul with 3CLPro and PlPro Enzymes of SARS-CoV-2 Virus
Authors: Rajeswari Kalepu , Jun Chen W , Aashika A , Xian Ying T , Choon Hoong C , Kuha S , Chinta Diya Rajasekhar
Published: April 2022

The SARS-CoV-2 belongs to a family of coronaviruses, responsible for the COVID-19 pandemic. The Chymotrypsin-like protease (3CLpro) and Papain-like protease (PLPro), two important enzymes of the SARS-CoV-2, play a key role in translating the viral RNA genome into functional proteins. This study aimed to evaluate and analyze the binding interactions of phytochemicals of oleoresin of Commiphora mukul plant with 3CLPro and PLPro enzymes of SARS-CoV-2 virus. Docking studies were performed on 3CLPro and PLPro with 30 phytoconstituents using AutoDock Vina. A total of 12 compounds were shortlisted based on their minimum binding energies. Their minimum binding energy ranged from -9.2 to -7.1 kcal and the analysis and interpretations are tabulated. Further, the ADME, drug-likeness, and bioactivity scores were documented. The current study enlightened the binding abilities, and the interactions of constituents present in the oleoresin of Commiphora mukul plant with the active sites of 3CLPro and PLPro enzymes.
Design of Mono Stage Luo Converter for Electric Vehicles Charging System
Authors: G Ramanathan , C Bharatiraja , C Santhakumar , Munda Josiah Lange
Published: April 2022

The electric vehicle charger with modified LUO converter is proposed in this paper that has High Frequency Transformer (HFT) to isolate the input and load side. The primary of the HFT contains two switches and two diodes that reduces the voltage stress in switches. The proposed topology operates in Discontinuous Conduction Mode (DCM), which reduces the components and control complexities of the converter. The charger is operated in Constant Voltage (CV) - Constant Current (CC) modes, which increases the battery life at long term. The proposed topology delivers better performance that is evaluated by performing the simulation in MATLAB/Simulink. The resultant output voltage from modified LUO converter charges the battery of 48V.
Leeder Ville Reimagined (Perth, WA)
Authors: - Jasleen , Boity Antony Kumar
Published: April 2022

Small towns and suburbs have a lower capacity to absorb changes at various socio-economic fronts with an increased population, unlike big metro cities. Leeder Ville Reimagined aims to redefine Leeder Ville in such conditions as an accessible and sustainable forward-moving place, which constantly thrives to celebrate diversity, a sense of community, and character. This paper is focused on four key themes as guidelines to achieve this vision. The themes include making Leeder Ville more accessible, enhancing connectivity, densifying the housing, and creating a more defined and characterized Leeder Ville. In assessing the current conditions and intricacies of the site, a range of methods were undertaken to obtain an overall holistic understanding of Leeder Ville. Numerous site visits, public life, and comprehensive research and analysis were utilized and conducted to better understand the site. Through this case study, it was evident that Leeder Ville needed change and rejuvenation.
Dielectric Properties of Soils Affected by Sewage Waste Pollution
Authors: Palta Prachi , Kaur Prabhdeep , Mann K. S.
Published: April 2022

Soil pollution has become one of the major issues in current era. Increasing population, industrialization, and human activities have contributed immensely to increase in sewage waste. Undisposed and poorly managed sewage waste has contaminated soil and water resources badly and affected their dielectric properties. In this study, the dielectric properties of soil affected by sewage waste pollution have been presented in the broadband frequency region of 200 MHz to 14 GHz with the use of open ended coaxial probe method. Moreover, the effect of contamination on soil pH has also been recorded. The results showed that the values of dielectric constant (Ɛ’) and dielectric loss factor (Ɛ’’) increases with escalation of contaminant content. The regression equations for Ɛ’, Ɛ’’, and pH values are also generated in this work. The results presented in this paper can be helpful in developing new approaches to study soil pollution and its type in comparison to conventional soil study approaches.
Performance Analysis of Five-Phase NPC MLI with Phase Shifting Carrier Pulse Width Modulation
Authors: Jayakumar Vinoth , C Bharatiraja , C Santhakumar , Munda Josiah Lange
Published: April 2022

The five-phase loads with Multi-Level Inverters (MLI) are preferred by industries in high and medium power applications due to lower switching loss, voltage stress across switches, etc. The controlling of a five-phase motor drive is done by Pulse Width Modulation (PWM) techniques. This paper discusses different multi carrier PWM techniques, such as Level Shifting Carrier (LSC) PWM and Phase Shifting Carrier (PSC) PWM techniques available for controlling the inverter drive. The simulation is carried out for all PWM techniques and load voltage, voltage THD, Common Mode Voltage (CMV), and DC-link voltages are noted and compared among the PWM techniques.
Performance Evaluation of 4*15 Gbps CWDM Optical Transmission Link for Metropolitan Areas
Authors: Behera A.B. Mukesh Kumar , Kiran G. Uday , Subudhi Sivani , Panda Tusharkant
Published: April 2022

In this growing world, communication to every corner of the globe is the most important factor. Although technology is touching heights it is a great challenge to connect to subscribers present at different territories. For long distance transmission, Dense Wave Length Division Multiplexing (DWDM) has been preferred always as it provides a better bandwidth to operate, but when we comes to short term or short distance transmission it has some drawbacks, such as wide band change, more power consumption, and high cost factor for lower channels. CWDM can easily overcome these disadvantages. In this paper, the performance of 4*15 Gbps optical transmission link for Coarse Wavelength Division Multiplexing (CWDM) based optical network has been analyzed and compared using different photodetectors. Here we’ve compared the performances in terms of Q-Factor (Quality Factor), BER (Bit Error Rate), and eye height in the eye diagram. For experimental setup and simulation, Optisystem-18 software is used.
Building Rules of Some Influential Technological Factors on Sewing Time for Products from Knitted Fabrics
Authors: Phan Thanh Thao , Nguy Thi Thu Uyen , Phan Duy-Nam
Published: April 2022

This paper presents the results of research on building empirical regression equations showing the law of simultaneous influence of the group of technology factors on the upper sewing time when sewing polo shirt and t-shirt products from single jersey at Star Hanoi Fashion Co., Ltd. The studies on the factors affecting time on the sewing machine include the length line (cm) and the stitch density (stitch/cm), the experiment on 04 devices, and 03 patterns of knitted fabric different thickness single woven tops. Thereby showing the difference in sewing time value on 04 sewings, corresponding to specific values of 2 research variables, which are stitch density and seam length when sewing on single fabric with 03 different thicknesses for polo shirt and t-shirt.
Evaluation of Uranium Concentration in Some Water Samples of Anandpur Sahib
Authors: Kaur Jaswinder , Kapil Chandan , Shikha Deep , Mehta Vimal
Published: April 2022

Uranium is the most radiotoxic and heaviest element with a very long half-life, present in the earth crust naturally. Due to various health risks of uranium, worldwide a lot of research has been done on its concentration in naturally occurring radioactive materials by various researchers. The present study deals with assessment of uranium in drinking water samples of the city of Anandpur Sahib in Punjab by fluorimeter technique. 15 different locations water samples, including tube well, borewell, and hand pumps, were taken for this study. A surface water sample taken from a river named ‘Sutlej’ contained 1.25 μgl-1 of uranium. However, the uranium concentration in all the collected water samples ranged from 2.79 μgl-1 to 18.4 μgl-1. One of the physiochemical parameters, i.e. pH, was also measured for all the water samples. The results of all the water samples were compared with the permissible limits specified by numerous health authorities.
Analyzing the Role of User Experience for Continued Usage on the Internet of Medical Things.
Authors: Singh Manpreet , Mittal Amit , Tandon Urvashi
Published: April 2022

Covid-19 has thrown a lot of challenges to address the gaps in our existing healthcare ecosystem, especially in the remote areas, where providing quality healthcare services is a challenge. Digital healthcare or the internet of medical things is viewed as a new age weapon to provide healthcare services to the masses at an affordable price. One such way is by connecting the end-user with physicians through mobile applications or devices, however, this demands thorough research and validation to understand the underlying needs of the users and physicians interacting in this connected eco-system In this study our focus is to identify the role of ‘user experience for continued usage on the internet of medical things’ or connected device eco-system. Through this study, we intend to probe and analyze the role of user interaction and user experience (UI/UX) in discovering the features and services provided through connected devices and mobile applications and their subsequent usage over a prolonged period of time. This study aims to present a theoretical framework utilizing the UTAUT-2 framework to hypnotize the identified problem statement.
Resemblance of Image Classification Methods in Computer Vision
Authors: Bhadoriya Varun , Jain Niharika , Verma Neeraj Kumar , Kumar Ravi
Published: April 2022

Exploding data with the transformation of IT Sector have led to the increase in demand of the classification algorithms. In the world with Artificial Intelligence (AI) Image data and classification of Image is very crucial. The Computer vision is as a saviour to the applications of meteorology, robotics, screen reader etc. Whenever the software need to analyze things and objects from surroundings using INTERNET OF THINGS in these scenarios where identification of living and non living objects is done by machines. “Image Classification” is a fundamental aspect. The main aim is to classify the objects in particulars of their labels. In this paper a brief description of when and How to use different Image classification algorithms in particular scenario’s.
Triple-Helical Target Sites of Oncogenes to Direct Therapeutic Triplex-Forming Oligonucleotides for the Management of Colorectal Cancer
Authors: Rajeswari Kalepu
Published: April 2022

The triple helix formation is an intranuclear process. The therapeutically targeted Triplex-Forming oligonucleotides (TFOs) can bind to Triplex Targeted Sites (TTS) located on double-stranded DNA and subsequently can inactivate a gene or can induce a mutation. The current study is intended to identify the total TTS in the human genome along with the number of TTS at promotor and protein-coding regions of genes, oncogenes and narrow down the TTS associated with oncogenes that are responsible for colorectal cancer (CRC). The TTS Mapping and integration (TTSMI) database is used to identify the TTS sites. The total number of TTS in the human genome were retrieved, segregated the TTS located on oncogenes, total number of oncogenes associated with TTS sites and sequences with respect to CRC was tabulated. The identified TTS sequences can be utilized to develop TFOs to target corresponding oncogenes associated with CRC.
Highly Phosphorescent Iridium Metal Complexes for Energy-Efficient OLED Applications
Authors: Rao Ankit Kumar , Sharma Harshit , Srivastava Ritu , Kaur Amarjeet
Published: April 2022

A highly efficient iridium metal complex based on 2-phenylpyridine and acetylacetone is prepared via a chemical route. The structural conformation of the complex was achieved using NMR and elementary analysis CHNS. The complex was further analyzed through various photophysical and electrochemical techniques. The energy transfer mechanism has been studied between our guest molecule and a well-known host molecule Poly (n-vinyl carbazole) (PVK). Furthermore, a preliminary OLED device has been prepared to investigate the role of the complex in phosphorescent light-emitting devices.
Review on Behavioral Factors and Individual Investors Psychology Towards Investment Decision Making
Authors: Kumari Anita , Goyal Ruchi , Kumar Sunil
Published: April 2022

This study has reviewed various concepts, theories of behavioral finance regarding the irrationality of individual investors’ behavior. Investment is one of the important driving pillars of the economic growth of the country. During the past few decades, investment pattern is more driven by irrational factors. So the behavioral finance theories, such as prospect theory, heuristic, herding, and theory of planned behavior, etc., came into the limelight. That captured the researchers’ attention towards behavioral factors that affects the investors’ decision making. The main intents of the study are to give insight into various behavioral biases and other psychological variables that drives the investment decision making of investors. This study would be helpful for emerging researches that are focusing on the improvement of the efficiency of the capital market for good economic growth. Financial advisors and fund houses could get clear insight for increasing the efficiency of investors, market, and so the economic growth.
Identifying the Predictor Antecedents of Green Purchase Intentions of Millennials in India
Authors: Kaur Balween , Gangwar Veer P
Published: April 2022

The present study seeks to explore the impact of Environmental Concern (EC), Health Consciousness (HC), and Social Influence (SI) on green buying intentions of millennial consumers in Indian settings. The target population is Indian millennials who are born between 1981 and 1997 and are in age range of 24 years to 40 years. The sample size has been calculated as 385 by using appropriate formula. Primary data was collected using a self administered questionnaire. It is hypothesized that environmental concern, health consciousness, and social influence significantly affects green purchase intentions of millennials in India. The relation between three independent variables (EC, HC, and SI) and one dependent variable (GPI) has been empirically analyzed by applying multiple regression technique using SPSS software. The findings suggest that green purchase intentions of Indian millennials are significantly affected by social influence, less affected by health consciousness, and least impacted by environmental concern.
Renewable Energy Sources – A Review
Authors: Kandpal Rohan , Singh Rajendra
Published: April 2022

The development of technology combined with the surge in population has led to a new era of living that has increased energy demand. Fossil fuel has been the main energy source for so many years, but it is no longer sustainable with its depletion and negative consequences. A need has arisen for a replacement resource to replace the depleting fossil fuels using right now. This need is what pushes us towards renewable energy. An examination of renewable energy sources: their uses, potentials, and limitations, as well as their effects on the climate and human health, is presented in this work. As final recommendations, the paper outlines policies and strategies to address climate change and fully integrate renewables as a sustainable energy source.
Educational Applications of Immersive Technology: A Technical Report
Authors: Kaur Amanpreet , Datta Priyanka , Mantri Archana
Published: April 2022

Immersive technologies bring the physical world together with a virtual or digital reality to create new experiences. Augmented reality, virtual reality, and mixed reality are examples of immersive technologies. The technique of superimposing auditory, visual, or any other sensory data on top of the real world to improve one's experience is known as augmented reality. Unlike virtual reality, which creates its own virtual world, augmented reality adds to the one that already exists. In education, augmented reality includes elements that improve collaboration, creative skills, and problem-solving in order to better prepare pupils for the future. This paper survey research papers on augmented reality application developed for learning physics, chemistry, biology, and mathematics.
Odia Text Classification Using Naïve Bayes Algorithm : An Empirical Study
Authors: Sahoo Rekhanjali , Mishra Brojo Kishore , Das Biswa Ranjan
Published: April 2022

Text classification is recognized as one of the key techniques basically used for classifying the text in different classes including positive, negative and neutral. This paper illustrates the Odia text classification process using Naïve Bayes Algorithm, which is a very fast growing discipline in computer science. This classification algorithm is suitable for binary and multiclass classification in machine learning concept and belongs to supervised classification category used to classify future objects by assigning class labels to instances using conditional probability. In this paper, an auxiliary feature method for Odia text is proposed. It determines features by an existing feature selection method of Naïve bayes algorithm, and selects an auxiliary feature which can classify the text at the selected features, and then the chosen conditional probability is used to improve high classification accuracy. Illustrative examples are shown that the proposed method increases the performance of Naïve Bayes classifier. Around one thousand sentences are taken to be considered as both training and tested for empirical diagnosis of the proposed work. Accuracy is depending on mainly training the corpus size which is designed by own and may be increased to some extend depend on the parameters as well as the large size of corpus further. The result shows that Naïve Bayes technique significantly outperform many other technique like HMM (Hidden Markov Model), CRF (Conditional Random Field) and KNN (K Nearest Neighbourhood). Text classification plays an important role in Sentiment Analysis, Information Extraction, Text Summarization, Text Retrieval, and Question Answering.
Lightweight Secure Key Distribution Protocol (LSKDP) for Wireless Sensor Networks
Authors: Roja P.Ezhil , Misbha D.S.
Published: April 2022

Because of the enormous technological revolution, the most difficult tasks that humans cannot perform are now easily addressed by small digital gadgets. An example of this technological revolution is Wireless Sensor Networks (WSN). In the WSN, numerous heterogeneous types of sensors work together to sense, monitor, capture, process, and control the physical condition of a specific region or object. The WSN has been used extensively in a number of key areas, particularly in the medical, agricultural, military, and traffic management sectors. The little electronic gadget that forms the WSN is composed of three major components: a sensing component, a power storage component, and a wireless transmission component. Despite the numerous benefits of this modern technology, security remains an unresolved concern. The goal of this work is to develop an efficient Lightweight Secure Key Distribution Protocol (LSKDP) for enhancing the process's safety in heterogeneous medical WSNs. Additionally, security and performance analyses were conducted to demonstrate the suggested methodology's efficacy. The security analysis is performed to ascertain the proposed method's vulnerability to network threats. Additionally, performance analysis is used to determine the CPU utilization, memory consumption, processing power, and computational overhead of the suggested methodology. The experimental results indicate that the suggested strategy detects attacks more accurately and with a lower computational overhead.
Face Mask Detection for Real Time Video Streams
Authors: Pople Vedant , Kanaujia Ayush , Vijayan R , Mareeswari V
Published: April 2022

The Face Mask Detection model is used to make sure a person is wearing a mask or not. This model results from the grappling situation presented by COVID-19, resulting in the mandatory use of masks at public places. Security agencies need to plant actual personnel to make sure all the people in public are wearing ‘masks’, this model will lessen the risk of people being contacted by COVID-19. This research helps us understand a broader perspective about the Face Mask Detection models by comparing different state of the art models. The model uses MobileNetV2 architecture that has inverted bottlenecks and depth-wise convolutions to filter features. The complete model is built in two phases, the first one consisting of making a Face Mask Detection model trained to detect the face and mask, and then placing it in the Real Time environment by using the OpenCV for actually predicting the usage of face mask.
Corporate Social Responsibility (CSR) Practices of Small Finance Banks in India
Authors: Joy Felice , V. Ambilikumar
Published: April 2022

A holistic approach to business growth based on the dual goals of commercial success and social impact is the aim of every small finance bank (SFB) in India. The Corporate Social Responsibility (CSR) activities of these banks pay attention to develop the society. Also, it is essential for a competitive edge. This paper made an attempt to identify the thrust area of CSR activities of SFBs and examine their CSR spending. The findings reveal that SFBs are given less attention to CSR activities related to environmental protection. Equitas and ESAF SFBs are the major contributors to CSR activities.
Non-Toxic L-Phenylalanine Doped Carbon Dots: High Performance Photoluminescent Agent for Bioimaging
Authors: Zaidi Fareen , Rais Anam , Chand Preeti , Malik Megha , Kulanthaivel Senthilguru , Mishra Prashant , Prasad Tulika
Published: April 2022

Carbon dots (CDs) are promising new generation bioimaging agents which possess remarkable properties such as excellent biocompatibility, stability, low toxicity, high luminescence, large surface area to volume ratio, flexible surface for conjugations with various biomolecules, tunable size, and optical properties. Among the essential amino acids, phenylalanine was selected for this study. One-pot microwave-assisted method was used to synthesize phenylalanine carbon dots (Phe-CDs) from citric acid and phenylalanine. The UV–visible spectrum of Phe-CDs showed two absorption peaks at 250 and 340 nm depicting the characteristic absorption of an aromatic π system.
Effecting the Change: Problem Based Learning (PBL) as a Pedagogy to Improve Achievement in Physics in Relation to Cognitive Styles
Authors: Singh Sukhjit , Dutt Sunil
Published: April 2022

This study investigates the effect of Problem Based Learning (PBL), a constructivist teaching strategy, on achievement in physics and attitude towards physics. Cognitive styles of students have been taken as classifying variable to include learning condition in the context of study. The sample of the study included 115 11th class students of the Government School of Chandigarh. Two classes of same school were randomly selected as experimental and control groups. The study was quasi experimental in nature. 2x2 between-subject design with pre-test post-test control group condition was used to study interaction and main effects of independent (teaching method) and classifying variable (cognitive style) on dependent variable (achievement in physics). 2- way ANOVA was mainly used as statistical technique to analyze data quantitatively. The experimental results indicated that PBL group students outperformed LBL (Lecture Based Learning) group students on achievement in physics. Even though interaction effect of teaching method and cognitive styles was not significant for achievement in physics and attitude towards physics. No significant difference between field independent and field dependent cognitive style students on achievement in physics. Moreover, implications, limitations of the present study, and recommendations for further studies are also discussed.
Introducing Intelligence in Vehicular Ad Hoc Networks Using Machine Learning Algorithms
Authors: Seth Ishita , Guleria Kalpna , Panda Surya Narayan
Published: April 2022

The automotive industry has gained popularity in the past decade, leading to tremendous advancements in intelligent vehicular networks. The increase in the number of vehicles on the roads makes it essential for vehicles to act intelligently as humans do. The concept of machine learning is that when vehicles learn and improve to operate by the previously processed data. The machine learning techniques have helped the automotive industry develop the driverless car. With the help of sensors and cameras, it is quite possible to use the machine learning algorithms and provide the user with its benefits. It helps to allow the vehicle to perform specific tasks that actually can replace the vehicle's driver. The Artificial Intelligence (AI) chips integrated into the vehicles enable the vehicle to navigate roads. This paper provides insight into the machine learning algorithms widely used by the automotive industries, and a comparison is made between them concerning the Vehicular Ad Hoc Network (VANET) applications.
Assessing the Sacrality of Religious Historic Destinations: A Case of Braj Mandal, India
Authors: Kapoor Sunanda , Sehgal Vandana , Mathur Mayank , Bhandari Harveen
Published: April 2022

Sacrality of a place is attributable to both tangible and intangible features. This research assesses the sacrality of a religious-historic destination using qualitative and quantitative methods. The assessment of sacredness has been approached through the lens of cognitive perspective of pilgrims. The research identifies and assesses some key parameters that define the sacrality of a religious place. Preliminary identification of parameters has been done through the Delphi method and the analytic hierarchy process (AHP) has been used to understand the significance of those parameters. To assess sacrality, Braj Mandal, India has been taken as a case example as it comprises of various temple towns that are religious and have historical significance. This assessment will help in devising appropriate urban conservation policies for maintaining the religious significance of historic towns.
Fluorescence-Based Sensing Assay for Point of Care Detection of Healthcare Parameters in Food Samples
Authors: Choudhary Sandeep , Vyas Tanmay , Joshi Abhijeet
Published: April 2022

Nowadays, awareness and concern regarding food safety are growing publicly in developing countries across the world. Various factors like sickness, misery, and even death are caused by contaminated food consumption. The increasing population across the globe increases food consumption. To overcome the gaps between the demand and supply of food products, people practice adulterating the food products (urea in milk). This work reports the synthesis of a solution-phase system containing fluorophores (FITC: act as indicator and Rubpy, serves as a reference) and enzymes (urease) for the real-time monitoring of samples. A color sensor-based device (CSD) has been developed and used to analyze the pH (4-9 pH) and urea (0-70 mM) in milk. The results obtained on CSD were cross-referenced on FOS simultaneously and found to be suitable for detecting degradation and urea adulteration in milk.