bluuebunny/crossref_metadata_2025 huggingface dataset:
Privacy Preserved Smart Security System for Elderly Community
Authors: Mathew Arul Treesa , Mani Prasanna
Published: April 2022

The rapid expanding modern world has left behind a huge number of old-aged persons alone at home. Most often, the security provided to them is limited to deploying CCTV surveillance or appointing security personnel. Current real-time health monitoring devices concentrate on the regular health check, and fail to address the emotional elements of the users (1-3). In majority of the attacks aimed against stranded persons, the attackers impose a sudden mental shock on the target which is not addressed by the current wearable health monitoring devices (4-5). In this work, we propose an efficient solution that can effectively monitor the health and security of such persons. It offers a smart system that ensures better security and immediate attention of caretakers. The system analyzes the signals from the sensory module and gives out health related information and most importantly produces alerts whenever it senses an abnormal change in pulse. The system also takes into account the privacy of the contained data through a distributed nature of operation. It is aimed to provide quick response to rapid changes in vitals thereby ensuring the availability of an immediate attention, with a firm assurance on the privacy that only the necessary information will be sent out to the outer world.
Metal Oxide Based Electrochromic Materials: Recent Advances in Synthesis, Characterization, and Applications
Authors: B Sudarshan , BS Shantanu , S Srivaths , S Neethu , C Manjunatha
Published: April 2022

This paper is a qualitative and systematic study on electrochromic materials and the advances that have been made in recent times. It starts with the basic introduction to electrochromic materials and goes on to explain the working principle, the components involved, and its basic construction, citing the examples of Di-Urethane Materials and Polyamide Electrochromic materials. The process of selecting the correct materials is also explained followed by the methods involved in its synthesis, including the photo deposition technique of the materials such as WO3. Additionally, a few practical applications such as smart windows, self-dimming rear mirrors, and others have been explained. The study concludes with an overall summary of all the research done based on papers authored and referenced, and provides an affirmation that electrochromic devices are going to be relevant and widely used in the upcoming future.
Sustainable Tourism: Elevating Collaboration between the Hospitality Industry and Local Citizens
Authors: Gupta Manasi , Hasnain Ali
Published: April 2022

Eco-tourism is a crucial aspect of sustainable development for any nation. Hotels are one of the most significant waste produce sources in tourism. The amount of waste generated and the variation in waste products is astounding, requires attention, and needs to be addressed at the earliest. [1] This challenge allows the development of a solution-oriented approach to have more sustainably sound practices in hotels. The wastage varies and ranges from plastics, food waste to paper & glass. The paper's objective is to identify the core areas of wastage and recognise past practices used to combat those challenges. The local citizens play a significant role in encouraging sustainable practices in a centre. The paper deliberates and explores innovative solutions to elevate collaboration and engage local communities to deliver sustainable impact in cities.[2] This is done by reviewing previous collaboration models in different cities and assessing their shortcomings and successes. The paper will construct a thorough stakeholder analysis of a city- pointing to the majority of waste sources in hotels of the city, the woes of the local communities, and suggesting the collaboration measures that can be taken, accordingly. Keywords: Eco-tourism, Hotel waste, local communities, collaboration, sustainable collaboration
Enhanced Retinal Biometric System for the Diabetic Population using Modified Discrete Grey Wolf Optimization Algorithm
Authors: Jothi Sivakamasundari , Francis Sheeja V , Priya S. Rasiga
Published: April 2022

Biometric system is the most widely used technology for automatic recognition and authentication of an individual in this modern world. Retina based identification is one such robust and reliable form of biometric solution. As the blood vascular patterns of retina are unique for individuals, these are used as features for developing a retinal biometric system. However, in diabetic persons, retinal complications such as exudates and hemorrhages may obscure these vascular patterns, cause mismatch in the authentication process. This paper proposes an enhanced retinal biometric system, where retinal vasculatures are extracted by an automatic segmentation technique using Modified Discrete Grey Wolf Optimizer (MDGWO). This algorithm is a population-based meta-heuristic swarm intelligence method to find optimal solutions of threshold values in Kapur’s Multilevel Thresholding (KMLT). A post processing step is included before the authentication both in the enrollment and verification process. In this step, findings due to diabetes seen in the segmented image are removed by a morphological processing method before the matching process. This retinal biometric system shows improved matching accuracy of 97.5%. Hence, MDGWO based enhanced retinal biometric system is optimal for building robust biometric systems for the entire population.
Harvested Rainwater Quality of Dhaka and Its Importance as the Alternative to Surface and Groundwater
Authors: Tarek Yeasin Arafat , Debnath Sumon Chandra , Uddin Md. Ripaj , Ahmed Shamim , Moniruzzaman Mohammad , Jahan Tajnin , Sultana Shahnaz , Hasan Mehedi , Jamal A. H. M. Shofiul Islam Molla
Published: April 2022

Dhaka, like many other megacities in southern Asia, has been struggling with urban flooding and droughts. The main reason behind the problem is thought to be the propagation of the city's built-up area and a significant decrease in rainwater infiltration in the capital. On the contrary, the continuous safe water supply in Dhaka is becoming an impossible task for the authority as the ground and surface water is being depleted over the years. In this regard, proper rainwater management, even at the individual plot level, has the potential to bring up a significant difference in the present crisis. In this report, the total physiochemical quality assessment of the harvested rainwater from Dhaka city has been presented and compared with that of the World Health Organization (WHO) standard. For the first time, this study reveals the applicability of this harvested rainwater to be used in several aspects including drinking, cooking, agricultural, industrial, and household purposes.
Histogram Based Optimized Reversible Steganographic Scheme
Authors: Nallasivam Manikandaprabu , D Femi , J Raja Paulsingh
Published: April 2022

A novel prediction-based Reversible Steganographic scheme based on image inpainting can be optimized by choosing the reference pixels using optimization technique. Partial differential equations based on image inpainting are introduced to generate a prediction image, from the reference image that has similar structural and geometric information as the cover image. Then the histogram of the prediction error is shifted to embed the secret bits reversibly using two selected sets of peak points and zero points. From the stego image, the cover image can be restored losslessly after extracting the embedded bits correctly. Since the same reference pixels can be exploited in the extraction procedure, the embedded secret bits can be extracted. Through optimization of reference pixels selection and the inpainting predictor, the prediction accuracy is high, and more embeddable pixels are acquired with greater embedding rate and better visual quality, and reduced time required for the stego00 image generation.
Regression Analysis on Compaction Characteristics of Sand Clay Soils
Authors: V. Giridhar , Jagadeesh G. , Kumar P. Rajendra
Published: April 2022

Soil compaction is one of the major geo technical engineering applications in infrastructure development of the nation. Large volumes of soil are used in the construction of flyovers, earth dams, and railways. There is a need to understand comprehensively in a unified and coherent manner. Thus the knowledge of compaction behavior and its characteristics of fine grained soils at different compaction energies assume great importance from they viewpoint of practical significant. In the present work, compaction parameters such as (MDD) (max) and optimum moisture content (OMC) care determined at various compaction energies by conducting the laboratory compaction tests. In the field, the compaction of soils usually involves using different compaction energies. A limited experimental investigation has been taken up in the present study. The cardinal aim of the present study is to focus on effect of compaction energy on the behavior and compaction characteristics and unconfined compressive strength (qu) of soils.
Investigating Sustainable Education and Positive Psychology Interventions in Schools Towards Achievement of Sustainable Happiness and Wellbeing for 21st Century Pedagogy and Curriculum
Authors: Alam Ashraf
Published: April 2022

The aim of this paper is to investigate sustainable education and positive psychological interventions in schools towards achievement of sustainable happiness and well-being for 21st century pedagogy and curriculum. The growing awareness that sustainability, happiness, and well-being are intertwined takes the discussion of happiness and sustainability to newer levels. Even though scholars and governments are now grappling with questions about policies for sustainability, happiness, and well-being, the general public may not be aware of these connections and none of these topics are well integrated into formal education. Nevertheless, the necessity for transforming education to play a leading role in sustainable education has never been more imperative, and thus it has been taken up extensively in this paper. The concept of sustainable happiness offers an innovative perspective to reinvigorate sustainability education and shape priorities for 21st century learning: contributing to resilient, sustainable happiness and well-being for all. The education sector, however, is conservative and slow to adapt. The author recommends that happiness should be an aim of education, and a good education should contribute significantly towards personal and collective happiness. Broadening this recommendation to consider sustainable happiness and well-being for all is an overarching aim that could assist to reimagine the role of education in the 21st century and serve as the foundation for setting new priorities.
Migrating Data Semantic from Relational Database System To NOSQL Systems to Improve Data Quality for Big Data Analytics System
Authors: Erraji Abdelhak , Maizate Abderrahim , Ouzzif Mohamed , Ibn BATOUTA Zouhair
Published: April 2022

Today, in the computer science world, data has become an essential hub for information processing in general. These data continue to progress in a progressive and exponential way, especially in storage and its technologies. The term big data as we use it for mass volumes of data, offers important techniques for processing, analyzing, and proposing useful information for decision making. NOSQL databases become a modern and indispensable technology to use, to provide scalability to support large data. This is why there is always this challenge for organizations to transform their existing databases to NOSQL databases by considering the heterogeneity and complexity of relational data. In this paper, we propose an approach for the migration of a relational database to another NOSQL. This method has two phases, the first is to transform the relational database to a NOSQL database, and the second is to enhance and improve the quality of the data with cleanup processes to provide and prepare them for big data analytics systems.
A Sense Amplifier Based Modified Low Voltage Two Stage Flip-Flop with CNTFETs
Authors: K , KomalShrivastavaa , Garg Parul , Srinivasulu Avireni , Sharma Jyoti
Published: April 2022

The transformation from the event of enabling technology to the assembly of consumer-centric semiconductor products has empowered the designers to consider characteristics like robustness, compactness, efficiency, and scalability of the merchandise as implicit precursors. The Carbon Nanotube Field Effect Transistors (CNTFETs) are nowadays popular emerging technology. The paper proposes the sense amplifier-based two-stage flip-flop working within the sub-threshold region. the primary stage produces full swing conditional inputs for the latch stage. The proposed circuit has been designed using 16 CNTFETs. This circuit contains a significantly low clock load which reduces the power consumption. An improvement in the propagation delay and power delay product has also been achieved. Comparisons with other flip-flop designs manifest the robustness of the proposed circuit. The HSPICE software is used for simulating and verifying the theoretical results.
Role of Artificial Intelligence in Parenteral Formulation: A Review
Authors: Mohan Bharathi , Kamaraj R. , Navyaja K.
Published: April 2022

Artificial Intelligence is defined as the division of computer science which tackles the simulation of human intelligence processes by machines and refers to the usage of automatic algorithms, machine vision, and technologies in various sectors of the pharmaceutical field. As this intelligent system has a handful of applications it is utilized by pharma industries for various pharmaceutical product developments mainly in sterile preparations, such as parenterals, vaccines, seras, and other blood products. In our country, parenterals are the second most widely used means for drug delivery after oral dosage forms. Therefore, the quality of the parenterals is crucial. In the present scenario, inspection of parenterals products during the manufacturing is quite important. Aiming at that difficulty hence it is considered for combining the manual process with automated technologies like artificial neural networks, deep learning, and clustering algorithms. In this way, liquid preparations can be more accurately identified and the accuracy of detection can be greatly improved.
Review of Minimally Invasive and Invasive MEMS Devices for Biomedical Diagnostic Applications: Design Aspects
Authors: Sundararajan Ananiah Durai Durai , S Aaron
Published: April 2022

The demand of MEMS biosensors in biomedical applications is enormous which has driven the review of such devices. Various biosensors that are available in the market and under research are inadequate in providing pickup and amplification of the bio-signals for diagnosis and treatment purposes. In this review, various biosensors implemented and deployed through invasive and non-invasive techniques are reviewed to determine their adequacy in diagnosis and treatment. A MEMS device also has been specifically designed for the pickup of intra-ocular pressure for early diagnosis of glaucoma. Piezoresistive type pressure sensor is designed to provide better accuracy in the pickup of such biomedical signals. The designed device which is analyzed using the COMSOL Multiphysics provided better sensitivity of around 26.6mV/V/MPa and a non-linearity of < 1%, which will promote better diagnosis.
Prediction of Tomato Plant Disease with Meteorological Condition and Artificial Intelligence
Authors: Wagle Shivali Amit , R Harikrishnan
Published: April 2022

Predicting disease in advance plays a vital role in taking preventive measures towards plant protection. The work proposes predicting tomato plant disease with meteorological conditions and artificial intelligence. Support Vector Regression (SVR) and Random Forest Regression (RFR) models are employed for the time-series forecasting of temperature and relative humidity. The models are optimized with GridSearchCV to fine-tune the hyperparameters to better forecast weather parameters. The RMSE for temperature is 0.0369; relative humidity is 1.8442 for the SVR model, 0.0246 for temperature, and 0.5918 for relative humidity with the RFR model. The R2 values show a good prediction performance. The correlation between actual and predicted test values is positive.
Green Conductive Construction Materials Toward Sustainable Infrastructures
Authors: Ahmed Sirwan , Kamal Ibtisam
Published: April 2022

Smart construction materials are intelligent composites that have properties different from normal materials. The smartness of building materials and structures is achieved through material composition design, special processing, the introduction of other functional components, or modification of the microstructure. Conductive concrete is one of the smart construction materials. It is a mixture containing a certain amount of electrically conductive components (filler). It is designed to enable the conduction of electricity. When the conductive filler used is a natural material, the result is green conductive concrete. The current work deals with a review that summarizes the vital points of the incorporation of conductive fillers in construction materials. The types of conductive filler, including green ones, the methods of production, testing, and applications of conductive cement-based composites are addressed and highlighted. Conclusions are made according to the literature reviewed, and some points of view are proposed for future perspectives.
An Investigation of Various Versions of AODV Protocol for Discovering Routing Path and Eliminating Packet Loss
Authors: Trivedi Veena , Nayak Padmalaya
Published: April 2022

A Mobile Ad hoc Network (MANET) is a network made up of mobile nodes that communicate through radio. It is a self-contained computer that can be individually programmed, ordered, and controlled. The nodes of an ad hoc network move at their own pace. Ad hoc network nodes are unable to communicate directly with one another due to their short propagation ranges. The topology of the network moves as nodes in a network switch, resulting in frequent route failures. The nodes of the ad hoc network are powered by a battery with a limited energy supply. When a node's battery dies, the network lifespan is shortened, resulting in network loss. Routing is a critical component of MANETs. As a result, Energy Efficient Routing Protocol is chosen to boost network efficiency. There are many routing protocols used to transfer data packets in wireless Ad hoc networks, the most important of which is the Ad hoc On-demand Distance Vector (AODV) Routing Protocol. The key issue with using AODV is that connection errors occur as a result of node movement that is unpredictable. As either the source node or an intermediate node shifts during data packet transfer, the energy in the nodes is lost again due to the additional path exploration process, which occurs several times. This paper provides a literature review of various implementations of the AODV protocol in the form of routing route exploration and packet loss reduction.
Towards Investigation of Various Load Balancing Techniques in Cloud Computing
Authors: Quereshi Zeba , Kothari Abhay
Published: April 2022

Cloud computing is an on-demand service where customers may access any time common IT resources, information, software and other equipment. It is a web-based development that offers virtual resources over the Internet as a service. The higher the cloud use, the higher the charge. The allocation of loads to components processing is a challenging phenomenon.In a multi-node system, there is a very good possibility that some nodes will be idle while others will be overloaded. The load balancing algorithms' objective is to keep the load on each processing element constant. A technique for Random Load Balancing in Cloud Computing is devised, in which the amount of user requests is instantly assigned to the resources. This method employs a random strategy to decrease the request's waiting time. This proposed load balancing technique is simulated in Cloud Analyst tool. The performance comparison study between proposed random method and other available load balancing methods is conducted. It is found that the performance of proposed random method is better in terms of response time.Keywords: Cloud Computing, Load Balancing, Response Time, Virtual Machine, Sorting
Sarcasm Detection: A Contemporary Research Affirmation of Recent Literature
Authors: Sayeedunnisa S. , Hegde Nagaratna Parameshwar , Ur Rahman Khan Khaleel
Published: April 2022

Sarcasm identification is a confined research area in NLP, a specific case of opinion mining where the focal point in the process is identification of sarcasm, instead of sentiment extraction. Sarcasm is a specific type of opinion which is expressed as a negative feeling in form of anger, frustration, or derision veiled by the intense positive words in the text. Detection of sarcasm, which is an elusive problem for machines, has gained wide popularity in the research community in recent years. Accurate identification and analysis of sarcasm improves the performance of sentiment identification models. This manuscript details various sarcasm detection approaches, models and features used, issues, challenges, and further research scope. The various machine learning and deep learning models used to identify sarcasm are detailed in this script.
A Comparative Analysis of Clustering Algorithm
Authors: Vaghela Rajdipsinh Dhirubhai , Iyer Sailesh Suryanarayan
Published: April 2022

Cluster analysis is an unsupervised learning method which identifies similar objects from dissimilar objects based on characteristics. This paper explores the data mining domain and classification of data mining. This paper discusses at length the various clustering methods comparing them on parameters like dataset, size, complexity and accuracy, high dimensionality, etc. The findings of this paper reveal various conventional mechanisms for clustering are not giving the required efficiency. This paper also highlights the features required in the novel algorithm for clustering.
An Effective Workflow Scheduling Algorithm in Cloud Computing Using Cat Swarm Optimization
Authors: Mangalampalli Sudheer , Pokkuluri Kiran Sree , Naga Satish G , Varada Raj Kumar K
Published: April 2022

Effective workflow scheduling approach is needed, as it is huge challenge in cloud computing as variable and heterogeneous workflows comes onto cloud console. To handle these complex workflows and to schedule them onto appropriate virtual resources an effective workflow scheduler is necessary. Earlier authors used various nature inspired algorithms to solve this workflow scheduling by minimizing makespan and maximizing resource utilization, but still there is a chance to minimize makespan and improve resource utilization. In this paper, we have calculated the task priorities of all tasks, which are incoming onto cloud console, and thereby mapping tasks onto VMs to effectively map tasks. Cat swarm optimization used to solve scheduling problem and finally we have addressed parameters named as makespan and resource utilization. Simulation was carried out on workflowsim and we evaluated the efficacy of our algorithm by comparing with existing algorithms PSO and CS. From simulation results we observed that our algorithm shows great improvement over existing algorithms for mentioned parameters.
Development of Trip Generation Model by Using Artificial Neural Network Algorithm: Wolaita Sodo City as a Case Study
Authors: Denno Habte Debisa , Reddy Raju Ramesh , Durga M.
Published: April 2022

Trip generation is the first step model in the transportation forecasting process. In this study, there are six developed models. Such as the general trip generation model, work trip generation model, educational trip model, shopping trip model, recreational trip generation model, and social trip generation model by using an artificial neural network. The mail-back survey method was adapted to collect pilot data, and household interview surveys were adapted to collect main trips and socio-economic household data. A sample size selected by stratified random distribution method from each TAK of Wolayta-Soddo city is 718 households. And the essential data is collected from all the households that enable to development of different models. The results of the developed models are to identify the possible modifications required in the study area to improve the transportation facilities and policy decisions furthermore for the economic development of the country in general and state in particular.
Temperature Excursion Management in Cold Supply Chain of Pharmaceutical Products
Authors: Srivastava Shruti , Bhadauria Arun , Gupta Suneel , Dhaneshwar Sunil
Published: April 2022

India’s cold chain industry is currently estimated to be worth $8 million which is composed of a combination of refrigerated transportation and surface storage mechanism. Managing the quality of pharmaceutical product during cold supply chain and the distribution process is a complex challenge for the pharmaceutical industry. The Indian cold chain market is anticipated to be more organized in setting up the cold chain facilities across India in coming years. There is a need of special handling and monitoring of the refrigerated product to ensure the proper packaging configuration and transit methods meet the predetermined cold chain criteria. Improper handling might deteriorate the quality of the product thereby lowering the therapeutic properties. The study focuses on a system-based quality management in pharmaceutical operations, quality assurance and enhancement, concerted efforts, concepts, consequences and handling mechanism to ensure product quality. Keywords: Temperature excursion, distribution, pharmaceutical products, transportation
Machine-Learning Assisted Prediction of Light Consumption
Authors: Faraz Ahmad , Siddiqui Farheen , Zafar Sherin , Naaz Sameena
Published: April 2022

IoT devices enable an assortment of large amounts of information from the environment that may well be used to produce sensible autonomous buildings. For example, within the context of public buildings like hospitals, it's necessary to regulate and predict the indoor environment. Just in case of emergencies or failures, the facility is going to be able to automatically regulate the indoor parameters by using models that learn from the previous usage. This can allow us to acquire advantage of the IoT sensor data and to understand real-time control of the building. The information stream will be unendingly processed and analyzed on-premises. Anomalies can be monitored, and alarms can be triggered accordingly. The objective of this research paper is to construct a classifier to predict the usage of light from the IoT information stream. One manner might be to implement a cloud-based device where all IoT sensors send measurements to an endpoint on the cloud for storage and training of the model. Proposed model will process the IoT data stream and construct a classifier that will be able to accurately predict the target label. The target label for use case is “light.” The research study goal is to suit a model that may predict if the light is on or off and to determine the accuracy of the predicted model using Hoeffding and Naïve Bayes classifier.
Land Use and Land Cover Change Detection Using Remote Sensing in the Trans Himalayan Region of Ladakh, India
Authors: Bhasin Anchal , Dolker Padma , Raina Pankaj , Ghosal Sunetro
Published: April 2022

Mapping and monitoring of land use and land cover types along with detection of change are essential in the Trans Himalaya to understand landscape dynamics and assist with planning for sustainable development. This study attempts to monitor land use and land cover in Ladakh and identifies patterns of spatio-temporal change in land use using multi-temporal satellite images. Landsat images for three different time-periods (1999, 2009, and 2019) were used to quantify changes between 1999 and 2019. Eight major classes were identified on satellite images: barren land, agriculture, built-up, waterbody, wetland, range land, scrub land, and snow/glacier. Results indicate that major land use in Ladakh is barren land in all three time-periods and that built-up area has increased significantly by 123 sq km (800%) between 1999 and 2019. The possible causes for change in the region include geopolitical importance of the region, growth of the tourist sector with increase in number of tourists, and change of socio-cultural lifestyle.
Exploring the Work-Family Integration During COVID-19 and Beyond
Authors: Gupta Sangeeta , Devdutt Poonam
Published: April 2022

Due to the COVID-19 pandemic, influence on business and organization practices and policies, and the number of couples joining the workforce in India has increased significantly. Due to forced work-from-home strategy and rigid work policies, couples struggle to integrate their professional and personal lives effectively. Various work and family-related topics are examined in this study to see how Indian couples manage work and family. An exploratory qualitative research article interviewed ten couples from Indian software companies. The six main themes that emerge from the stories include the impact of family on life choices, the difficulties of balancing many roles, and the need for coping methods in the workplace.
Nanopattern Formation on Indium Phosphide Using Energetic Ions: An Overview with Various Ion Beam Parameters
Authors: Sulania Indra , Avasthi D K , Tripathi Ambuj , Hussain Mushahid
Published: April 2022

Nanopattern formation using energetic ion beams has attracted interest due to their important applications in varied fields. Ion beams play a crucial role in the formation of nanostructured materials in different energy regimes. Low energy ions of a few Kiloelectron volt (keV) energy have been used for growing thin films using sputtering process. A few ~10 to 100s of keV ions are used for the growth of nanopatterns (nanodots or nanoripples) through self-assembly or self-organization. Such pattern formation depends hugely on ion beam parameters such as angle of incidence of the beam, ion fluence, ion energy, and target material properties. Thereby, tuning the ion beam parameters, the desired shape and size of the nanopatterns may be achieved on wide variety of substrates. In this paper, effect of the above-mentioned ion beam parameters, especially, on Indium Phosphide (InP), is reported from our earlier studies. Further, the correlations have been made where such patterns have been used for various applications.
Pollution Control Applications of Nano Titanium Dioxide in the Construction Industry
Authors: Mandi Ujwal Arun , Meda Ujwal Shreenag , Vora Khsuhi , Athreya Yash N
Published: April 2022

There is an upsurge in air pollution due to urbanization and industrialization across the globe. This calls for immediate action. Large exterior surfaces of high-rise buildings and civil infrastructure can be utilized to one’s advantage by applying nanocoatings that are capable of alleviating the concentration of air pollutants in the surrounding atmosphere. Few nanomaterials with their photocatalytic property can degrade some of the air pollutants such as oxides of nitrogen (NOx) and sulfur (SOx) to their respective non-harmful counterparts, thereby bringing down the concentration of actual pollutants. Most of the metropolitan cities which have high-rise buildings are the ones that have more concentration of pollutants. Therefore, these buildings can be employed for coating nanomaterials on the exterior surface of these buildings. Nano-photocatalysts can be either incorporated onto a surface as a coating or into the outer layer of the building during construction. The most commonly used semi-conductor nano-photocatalyst for this purpose is nano titanium dioxide (TiO2) or its composites, such as silica-doped TiO2. This review paper consolidates various methods of synthesizing TiO2 and its composites, their characterization, different methods of incorporating nanomaterials onto construction materials, and degradation mechanism.
The Food Recognition and Nutrition Assessment from Images Using Artificial Intelligence: A Survey
Authors: Makwana Yogeshvari , Iyer Sailesh Suryanarayan , Tiwari Dr.Sanju
Published: April 2022

There are three basic needs for human living: food, home, and clothes. As a result, food plays a critical part in human life. In today's world, every field achieves some level of accomplishment. We should take food as per our body needs. In recent times, many dangerous diseases have taken place in the human body. During this time, awareness of our health is an essential factor for humans. It is essential to know what we should eat in our diet. This paper explores different methods and datasets for food recognition and nutrition assessment from the images of different foods using artificial intelligence and compares different methods and technologies also. Convolutional Neural Network (CNN) is one of the most successful deep learning algorithms for food recognition. As a finding, several existing models of CNN have been explored with different accuracy and results.
Gamification: A New Approach to Facilitate Recruitment
Authors: Singh Aditya Pal
Published: April 2022

Gamification has been considered as the inclusion of game features into non-game context. With the advent of novel technologies, gamification has provided novel opportunities for recruiting talented professionals. While undergoing the recruitment process, it is obvious that many young talented professionals may get disengaged and bored. On the contrary, gamification, which has gained popularity after 2010, has been considered as a novel approach to engage and inspire candidates appearing for interview (1-3). Gamification has been defined as, “the use of game design elements in non-gaming contexts” (1). Zickermann and Cunningham (4) defined gamification as “the process of game-thinking and game mechanics to engage users and solve problems” (p.14). The primary goal of using gamification in recruitment is to engage the candidates so that their training and hiring process may be facilitated and candidates may feel enthusiastic about the organization (4-5). Gamification has been into practice to facilitate the interview process by making it attractive, collaborative, and productive. Gamification evaluates a candidate on the basis of his performance in solving a particular role assigned to him (6). The explanation provided by the candidate on the basis of gamified problem help HR managers to evaluate the analytical skills of the candidates in an improved manner (7-8). Recruitment games provide realistic and case-based situations to the candidates making him acquainted with the actual nature of job. In such situations the candidate presents solutions based upon his analytical skills, thus is at more liberty to discuss his thinking and talent (9).
An Approach for Drug Delivery to the Brain Via External Acoustic Meatus
Authors: Raina Deepika , Singh Siddharth , Negi Rohit Singh , Sharma Bunty
Published: April 2022

Depression is momentous mood chaos marked by a mixture of symptoms that interfere with a person’s daily activities. The oral administration serves dose dumping issues of therapeutic molecules in specially targeted delivery. So, the external auditory canal pathway was explored to deliver the API and it help to bypass the above-mentioned problem. Sonication bath method was used to prepare bio-nanosuspension loaded with escitalopram and biopolymer extracted from Tagetes patula. Different ratios of drug and biopolymer were considered and 10 formulations were formulated followed by evaluation parameters like SEM, FTIR for biopolymer and ex-vivo, stability, drug release studies, etc., for the final formulation was performed. Formulations were examined through many evaluation parameters, such as content uniformity, pH, in-vitro drug release, and many more. It was found that STP 1 (1:0.5) was the best formulation. From pharmacokinetic data and in-vitro studies revealed and concluded that acoustic meatus is a feasible pathway for molecules delivery to the brain for depression treatment.
COVID-19 Vaccination and Case Fatality Rate in India
Authors: Zuber Mohd , Khosla Charu , Javed Nargis Begum
Published: April 2022

India has experienced two severe waves of infection with COVID-19. Since there isn’t any effective drug, emerging variants of the virus, an unknown epidemiological life cycle, lockdown, and restrictions at public places slowed the spread of novel Coronavirus in the country. However, a large number of new COVID-19 cases and deaths have been reported from across the country. We carried out a study to evaluate the effectiveness of vaccination in India, randomly selected five states and a union territory to control the severity of COVID-19 (case fatality rate). During the study period, March 21st 2020 to 6th August 2021, with the initiation of vaccination, the case fatality rate was reduced to less than 1.0% in the selected states and union territory. Thus, vaccination for COVID-19 infection is found to be effective in decreasing the severity of the disease. The eligible population should get themselves inoculated at the nearest health facilities.
Review of Spatial Transformations in Indian Cities Post Economic Reforms 1991
Authors: Aggarwal Shilpi
Published: April 2022

Spatial transformation of settlements is a continuous process. City planning governs land utilization, and policies adopted by government authorities result into changes happening in cities. Also, cities are drivers of economic growth and countries must invest in cities to attain higher economic growth. From 1991, post adoption of economic reforms, an emerging socio-economic and cultural structure has been observed which has driven changes into city fabric and evolved a new physical form of human habitation. Along with significant economic growth, phenomenon of disparity resulted in uneven geographic development. This research explores influence of economic reforms adopted in 1991 on evolving spatial changes in Indian cities. Research findings suggest that spatial transformations in Indian cities is a resultant of reform led investment, demanding new set of spatial requirements complimenting current pattern of growth. Cities contributed in achieving economic growth, but failed to cater holistic progress of all sections of society.
Managing Business in COVID-19 Era: Opportunities in E-Commerce and Teleworking Sector
Authors: Pathrose Eugin Prakash , Shetty Bharati
Published: April 2022

This paper is critical analysis of the in-depth content of the newspaper about the COVID-19 outbreak and its impacts. The Chinese and international media news have been scrutinized. To analyze the impact level of the coverage on COVID-19 by global media comparing with Chinese news content from January 1st to 20th March 2020, we have reviewed web-based newspapers as a tool of data collection for content analysis of research. The results suggest that the news framing of COVID-19 in global media psychologically affected the people, causing panic and fear, which has adversely affected the business, economy, and routine life worldwide. The results reveal that 27.6% of the Chinese news coverage has a high impact on readers, comparing with global media, where harmful content has recorded 93.75%. The results also suggest that sensational news made the conditions caused by the coronavirus more serious. The sensation created by the world media at the beginning of the outbreak left a significant impact on the viewers that caused panic, uncertainty, and apprehension.
Discursive Narration of the Collective Self in the International Speeches of the Baltic Presidents
Authors: Romāne-Kalniņa Līga
Published: April 2022

National identities are fluid and artificial rather than natural and static concepts that have been investigated by numerous scholars through the later part of the 20th century and the beginning of the 21st century. A common agreement is that group identities are negotiated, constructed, perpetuated, transformed, and in some instances, also destructed through discourse as a social practice. Thus, it is seen to be imperative for independent nation-states that are part of larger supra-national bodies to construct and upkeep their national identity not only on the group-internal level, but also to negotiate and represent the identity internationally. Moreover, the construction of a unified collective self may pertain to forming effective international partnerships which can foster the achievement of common supra-national, international, and individual national goals. Therefore, the current study employs Corpus-Assisted Critical Discourse Analysis (CACDA) to investigate how the presidents of the Baltic States have negotiated their respective national identities in international meetings in the period from the early 1990s until 2021 via the various discursive strategies and linguistic means of collective self-presentation and what common goals have been represented in the process of forming international partnerships.
Competitor Analysis of Hydrogen Sensing Systems
Authors: Prabhu Ashni Melissa Mery , Meda Ujwal Shreenag , Joshi Anupama V , C Vidya , D Ranganath
Published: April 2022

The demand for hydrogen is likely to grow as it could potentially be a suitable alternative for fossil fuels. Hydrogen is used extensively for a variety of purposes in major industries, such as refineries for hydro- desulphurization and hydrocracking operations. In ammonia production it reacts with nitrogen to produce ammonia, in metallic ore reduction, hydrogen is commercially used to procure tungsten from its ore, and various other applications. Hydrogen being a colorless, odorless, and tasteless gas, which is flammable, can’t be identified or recognized by the human senses, and needs to be detected by other means so that one could quantify its concentration if present. There is a need to estimate and determine the concentration of hydrogen so that it can help prevent any potential hazards. This article gives an insight on all the hydrogen sensors that are available in the market, a comparison between all the different hydrogen sensors with different attributes, such as stability, sensitivity, response time, etc., and the different manufacturers who produce this sensor.
Estimation of Chemical Composition and Soil Quality in an Agricultural Belt of Haryana, India
Authors: Kumar Parul , Jain Sushma
Published: April 2022

The proper management of soil quality is a very important criterion for the sustainability of the soil system. The knowledge of soil quality is extremely important for proper growth and yield of the crop. Soil provides essential minerals and water through roots and helps to sustain plants in it. A fertile soil is good for agricultural purpose. The yield of crops is equally important for the farmer as well as for the nation. Keeping this in mind, the present investigation was carried out in Sirsa district to determine the soil quality parameters of agricultural soil near some villages of Rania city. The samples were collected from fifteen different villages in pre-monsoon season of 2016 and analyzed. Several parameters like pH, EC, total N, OC, K, Zn, Mn, P2O5, Fe2O3, and CaO were evaluated to determine the soil quality. Rania is an agricultural belt where rice and wheat are the main crops. The values of these parameters suggest that the soil in the study area was suitable for most of the crops.
Block Chain and Edge Computing Base Design Secured Framework for Tender Allocation
Authors: S RanjithKumar , RM Karthic , N Nandhini , PL Kaliappan
Published: April 2022

Online technology has improved a lot and it plays a major part in this generation. The government and private sectors are actively moving through this technology to make their work faster, more efficient, and grow cost optimization. One such technology that has grown in this past year is blockchain. It has been established in all the parts of the domain because it is more secured and available at a low cost provides more security and improved traceability. Normally government will post the tender details to some of the other companies as outsourcing. We are going to create a secured website for government tender using blockchain technology. Blockchain is a system of recording information. It is difficult to cheat or hack the system. With the help of blockchain, the government data will be stored securely. Cryptography technique is used for security and it is difficult for hackers to hack. The goal of our work is to provide industry innovation and infrastructure.
Cloud Deployed PHR Using ABE Scheme
Authors: Jaiswal Rajyalakshmi , Iyer Sailesh Suryanarayan
Published: April 2022

Personal health record (PHR) is a patient’s personal health information where a patient can store and maintain his personal health details in a cloud server which is a third party. Therefore, security and sharing of personal health information is a concern from parties like cloud server and unauthorized users. It is very important for a patient to have full control on their personal PHRs, hence it is important that PHRs have to be encrypted before outsourcing them to cyber service provider. In this paper, analysis of various PHR schemes for encryption is compared and results are analyzed.
A Collaborative and Early Detection of Email Spam Using Multitask Learning
Authors: Chelliah Balika J , Sasidharan Anand , Singh Dharmesh Kumar , Dangi Nilesh
Published: April 2022

Email spam has become a huge nuisance since the last couple of years. It not only wastes valuable time but is also extremely dangerous as well. The various solutions that exist to detect spam do so by manual input of keywords or filtering particular domains. But no matter the amount of filtering, it is quite tedious and difficult to check for spam. This paper includes a unique solution that attempts to use deep neural network, a machine learning technique which detects any pattern of recurrent words which may have been classified as spam. Every other parameter of the email is examined as a feature and applied accordingly to the machine learning algorithm. Deep neural network is quite advanced and can easily differentiate between a proper and an improper output.
Significance of Machine Learning Algorithms to Predict the Growth and Trend of COVID-19 Pandemic
Authors: Singh Soni , Ramkumar K.R. , Singh Soni
Published: April 2022

The current outbreak like coronavirus is detected in December 2019. The first case of coronavirus (COVID-19), detected in China, after that it has spread very fast in others countries. In this research, Machine Learning (ML) is a method which helps in predicting the future or categorized data to help people in making essential decisions. In the presence of massive epidemic data, the machine learning techniques help to find the epidemic patterns so that the early action can be planned to stop the spread of the virus. Machine learning models are used to observe everyday behavior, along with the prediction of future reachability of the COVID-19 across the nation by utilizing the real-time information. The research focuses on herd-immunity that is used to analyze the spread of virus in human according to their immunity system. Based on herd immunity, we make prediction applying different machine learning models.