bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection of Depression and Anxiety through Speech, Voice, and Sentiment Analysis
Authors: V. M. Diwate, P. S. Oza, O. N. Wagh S. M. M. Naidu, Y. A. Chavan, M. R. Pillai,
Published: June 2023

This study investigates the potential of using speech, voice, and sentiment analysis for detecting depression and other mental health disorders among 3,995 employees in the IT sector. The study aims to explore the feasibility of using these technologies to detect mental health concerns earlier, to improve diagnosis and treatment outcomes. Participants in the study provided speech and text samples, which were analyzed using various machine-learning algorithms to identify patterns associated with depression and other mental health disorders. The results suggest that speech, voice, and sentiment analysis have the potential to be effective tools for the early detection of mental health concerns among employees in the IT sector.            

 However, ethical and privacy concerns must be addressed before widespread implementation of these technologies. The study highlights the importance of balancing the potential benefits of these technologies with the need to protect individual privacy and ensure the ethical use of sensitive health data. Overall, the study highlights the promise of speech, voice, and sentiment analysis in the field of mental health and the potential for these technologies to improve the lives of individuals in the IT sector and beyond.
Toward Sociable City Park: The Relationship between Sociopetality of Seating Facilities Design and Communities’ Social Activity in Khon Kaen, Thailand
Authors: Badri, Chantanee Chiranthanut
Published: June 2023

Green space in urban areas, including city parks, is one of the essential components and inseparable elements of the urban structure. Not only have environmental benefits, but city parks are also beneficial for the community in social improvement, as they become places for human interaction and integration. Khon Kaen City, one of the city centers in Thailand, continues to grow from what was originally only a small rural area. Thus the existence of city parks is fundamental. Since sitting is an activity that can open opportunities for social interaction and create the vitality of urban space, the importance of creating seating that can maximize the social interaction (sociopetal) of the community in the city park is needed. However, the seating facilities in Khon Kaen city parks are dominated by linear seating characteristics that can minimize social interaction (sociofugal). This study aims to investigate the relationship between the sociopetality of seating facilities design and communities' social activity. Data on seating facilities design characteristics and communities' social activity collected through behavioral mapping in three city parks in Khon Kaen were analyzed using chi-square and odd ratio. The results showed a significant relationship between the sociopetality of seating facilities design and communities' social activity. Sociopetal seats tend to be used 2.4 times more often for social activity than individual activity. This finding can be a reference for architects, planners, and designers to increase social activity in city parks.
An Artificial Intelligence-Based System to Assess Nutrient Intake for Hospitalized Patients
Authors: T. Anita, Saniya Begum, Nazmeen, Shahista Parveen
Published: June 2023

Reducing the risk of disease-related malnutrition requires routine monitoring of nutritional intake in hospitalised patients. There is still a definite need for a more dependable and totally automated way to estimate nutrient intake, since this might increase data accuracy and lessen the burden on participants as well as health expenditures. In this research, we offer an innovative artificial intelligence (AI) method that uses simple RGB Depth (RGBD) picture pair processing to estimate nutritional intake effectively. The system contains a unique multi-task contextual network for food segmentation, an algorithm for 3D surface generation, and a few-shot learning-based classifier for food identification. This enables entirely automated calculation of the nutritional intake for each meal via the sequential segmentation, identification, and estimation of the eaten food volume. A new database specifically created for the system's development and testing, complete with 322 meals' nutritional information and photos of each, has also been built. The predicted nutritional intake outperforms currently available methodologies for nutrient intake evaluation, according to experimental data, which reveal that it is well linked (> 0.91) to the ground truth and exhibits extremely modest mean relative errors ( 20%).
Additive Inverse Cordial Labeling of Graphs
Authors: P. Manisha Rebecca, G. Priscilla Pacifica
Published: June 2023

Let  be a  graph. Consider the function  from    to the set  and the induced surjective edge function  defined by . Let  and  respectively denote the number of vertices labelled by x, where , and number of edges labelled by , where . Then Ψ is said to be an additive inverse cordial labelingif , where  and . If G has an additive inverse cordial labeling Ψ then we say that G is an additive inverse cordial graph.
The Critical Application of Internet of Things (IoT) in the Overall Development of Education
Authors: Sunil Chahal
Published: June 2023

The advent of internet IoT devices can be used in any kind of industry for its growth. The applications and benefits of IoT in the education industry are diverse. The teachers and the parents can collect the personalized data about students in the classrooms and use them to improve the personalized learning using this will not disturb their learning process. The schools with limited valuable resources can make use of IoT to control the students from overusing activities which will be helpful to other students to utilize the resource. IoT helps the teacher to see the full view of students' mental state, stress level with the help of their heart rate. In this paper the IoT is used as a wearable band. The band will be tied on the hand of the student to monitor the vital readings of heart beat over the time during the school hours. The vital readings are compared with the standards. If the deviation between the actual and the standard found is large scale then it would be informed as alert to the class teacher for further action. Usually this can be used to give counseling to the students having difficulties, stress in different activities as part of the curriculum.
An Innovative Method for Mitigation of Radon: A Case Study in Bangalore Area, Karnataka, India
Authors: Sathish L. A.
Published: June 2023

Introduction:

Elevated radon levels in the indoor environment in many countries that led to the realization of residential radon as being a possible public health issue in the western world. It was also hoped that in conjunction with epidemiological studies, large-scale indoor radon surveys might lead to quantitative understanding of the low dose effects of radon exposures. Earlier work for the environment of Bangalore city reveals that, the activity concentrations of 226Ra in soil varied in the range of 7.7–111.6 Bqkg-1 with a mean value of 26.2 Bqkg-1. The concentration of 232Th varied in the range 16.7–98.7 Bqkg-1 with a mean value of 53.1 Bqkg-1 and that of 40K in the range 151.8 –1424.2 Bqkg-1 with a mean value of 635.1 Bqkg-1. An attempt has been made to observe the reduction in radon concentration by deploying lamination on the walls and mosaic tiles on the floorings of the room.

Objectives: Radon mitigation is a new approach to minimize the radioactive gases in the working environment.  In view of this an attempt has been made to witness the reduction in radon concentrations due to Formica laminate on the walls and placing mosaic tiles on the flooring of the room. 

Methods: CAN technique and solid state nuclear track detectors based dosimeters are used for the observation of radon exhalation and the concentration of radon/thoron levels in a room. .

Results: Good reduction in radon levels were observed after deploying the Formica laminate on the walls of the room and the mosaic on the floorings of the room. This is an innovative method needs to be incorporated for the reduction in higher level concentrations. 

Conclusions: Reduction in concentration is more than 50% after renovation and it may be used as an innovative approach.
Cross Border Insolvency: A Pearl in the Ocean
Authors: K. V. D. Kishore Kumar K. Hari Hara Sudhan, B. Someswara Rao,
Published: June 2023

International Insolvency can also be termed as Cross Border Insolvency, when the debtor having assets or liabilities in more than one jurisdiction. International insolvency sometimes termed as Cross-Border insolvency was in practice since early stages in England and it was governed by the common Law of England. The Solomon v. Rosswas the first case recorded in 1764, in this case English creditor brought action in England against the sum owing to the Dutch firm which was declared as bankrupt in Netherlands. The historical development of Cross-Border insolvency can be traced back since modern Private International Law’s birth, when state use to enter into agreements and sign treaties, to harmonize their relationship and to resolve their conflicts. The treaty of Montevideowas signed by five countries in 1889 to harmonize their fiscal policies, was the first to recognise Cross-border Insolvency. Due to the Advent of globalisation, The insolvency Law Committee was formed for drafting the bill of Insolvency and Bankruptcy bill and it Included 2 provisions for dealing with the Cross Border Insolvency issues and the increasing foreign direct investment in India, there is a strong need of increasing incorporation of company in various jurisdictions and there is an urgent need for Law on Cross Border Insolvency for solving the disputes across jurisdictions
Assessment of Lung Efficiency of Individuals Exposed to Various Foundry Industries in Satara City
Authors: Abhijit M. Avasare, Ashish V. Mane, Satish Kulkarni
Published: June 2023

The airborne dust as pollutants plays a major role in the overall atmospheric pollution. Silica is a chemical term for silicon dioxide (SiO2). The term crystalline silica refers to a crystallized form of SiO2 known as quartz, crystobalite or tridymite; it is the most abundant compound on the earth’s crust capable of causing silicosis and lung cancer upon inhaling large doses in course of occupational exposure. The present study was aim to evaluate the lung efficiency of individuals who worked in various foundry industries in Satara city. Around 300 individuals were enrolled. From selected three locations, 100 individuals were enrolled. All the individuals from the test were given a pulmonary function test. Before the test, a questionnaire was given to them to collect their basic information. Their age, height and weight were also entered in the spirometer. The spirometer gives two values; one is the expected value and the other is actual value. The predicted values are based upon the age, height and weight of the person while the actual values are dependent upon the maximal inspiration and expiration of the person. All the parameters, i.e. FVC, SVC and MVV showed impairment in the large industry workers compared to other two industries workers. A significant difference (p < 0.01) in the actual and expected values was observed in the pulmonary function test individuals of all the three selected industries. The percentage efficiency for all parameters for small industry workers, i.e. FVC (96.42 %), SVC (95.71 %) and MVV (88.69 %) was also good as compared to large and medium industries. At large industry, MVV efficiency was very less (59.66 %) as compared to the medium industry (68.61 %) and small industry (88.69 %) workers. In the SVC also, a large industry worker (69.72 %) showed less value as compared to the medium industry (79.99 %) and small industry (95.71 %) workers. Restrictive defect was 14 %, 36 %, 33 % and 17 % in the large industry workers which was normal, mild, moderate and severe, respectively. These values were very low as compared to small industry workers. Individuals exposed to heavy load of pollutants in air are susceptible for many respiratory disorders. Decrease in the FVC, MVV and SVC parameters were observed in the individuals of large industry assz compared to medium and small industry. This impairment in the pulmonary test parameters are indications of an accumulation of pollutants in the airways, which intern reduces inhalation and exhalation force. So, the people exposing continuously to such silica or particulate matter pollution should be made aware about pulmonary disorders.
Effect of Building Geometry on its Performance Under Earthquake and Wind Loading
Authors: A. V. Gorle, R. S. Tatwawadi
Published: June 2023

Recently new trend generated to resist lateral forces using truss system called as diagrid structure. Diagrid structural system adopted to resist lateral load due to its structural efficiency and flexibility of architectural planning. This study report contain effect of geometry of structure on its performance. To find out effect of geometry of structure on performance. Comparative analysis is done on circular and square shaped diagrid steel structure under earthquake and wind loading. To analyse models under earthquake and wind loading, response spectra method and gust factor method are adopted respectively. E tabs 2015 software used for modelling and analysis of diagrid steel structure. The loading conditions is based on their action of transmission like wind loading acting exposed surface to ground and earthquake loading acting ground to structure. Comparison of structural performance is done on the basis of storey displacement, storey shear, time period, material consumption.
Multivariate Vocal Data Analysis with Deep Learning Applied for Parkinson Disease Detection
Authors: Marupaka Nagaraju, Dhanalaxmi Vadlakonda
Published: June 2023

Different decision-making skills are used differently in the advancement of ML and DL techniques. In particular, it will probably be necessary to use ML and DL approaches for disease detection. The proposed effort uses acoustic-based DL approaches' ability to detect PD symptoms. This investigation also examines a number of motor metrics such as nonmotor PD measurements in this regard. Many DL approaches, including deep knowledge generation networks and recurrent networks, can be employed to identify this disease. Different decision-making capabilities are used differentially in the deployment of ML and DL methods. In particular, it will soon be necessary to use Machine learning and Deep Learning techniques for disease detection. The proposed effort uses acoustic-based DL approaches' ability to detect PD symptoms. This investigation also examines a number of motor metrics such as nonmotor PD measurements in this regard. Many DL approaches, including deep knowledge generation networks and recurrent networks, can be employed to identify this disease.
The Mean Duration of COVID-19 Found Closely Associated with the Ayurvedic Pathognomic Model Shatkriyakala (SKK): Inference of an Observational Cross-Sectional Exploratory Study
Authors: Charu Sharma et al.
Published: June 2023

A valid measurement for Corona virus disease is needed for case definition and adopting appropriate therapeutic measures. Identification of epidemiology and etio-pathogenesis is must for case definitions. The incubation period The incubation period is the time elapsed between pathogen exposure and appearance of symptoms. It can be utilized to trace the contact history of population at high risk.  Incubation, latent and generation periods may help both in understanding transmission and developing therapeutic measures. The evidenced incubation period of covid-19 infection is found to be 5.6-6.7 days. Ayurveda advocates Shatkriyakala pathognomic model i.e. six stage model of disease progression. Aims and Objective: The present study focused to trace –pathological model in context of covid-19. Material and method: This study was conducted in Government ayurvedic institute, COVID testing centre, New Delhi. The tool of data collection was Questionnaire 1 &2. Result:We report a temporal pattern of COVID-19 pathology which corresponds to six-stages of disease progression.(shadvidh kriyakala).

Discussion: Assessment of relationship between the variables (Hetu-dosha and Dushya) responsible for pathogenesis temporal dynamics of covid-19 may serve as an instrument for mapping the pathogenesis.

Conclusion: Clinical staging of covid-19 can be potentially mapped by six stage classical pathological model.
Problems Facing by the Polytechnic Engineering Students in Studying the English for Engineering Course In Assam
Authors: Md. Isthaque Ahmed
Published: June 2023

The main problems facing by the polytechnic engineering students in their conduit is English skills since they get less exposure to English in their engineering courses. The importance of English can’t be denied in the global world.   It is now generally acknowledged that English is the most important language in the world. Because a strong command of the English language is beneficial to students in their career search, many technical and engineering schools make the study of English a required subject for all students. Even after finishing their education at a college, the vast majority of students are unable to attain the needed competency in written and spoken English, according to observations that have been made. Within the scope of this research, an effort was made to determine the degree of knowledge possessed by Polytechnic Engineering students hailing from the state of Assam. In order to accomplish this goal, a questionnaire of the respondent's own design was utilized to determine their degree of English abilities. It is anticipated that this research would speed up the process of introducing different changes to the teaching of English for Engineers in order for those Engineers to achieve the requisite level of proficiency. Many different types of businesses are looking for graduates with technical training, but they are also interested in individuals who are well-versed in "soft skills," or people skills. A solid basis for the development of soft skills may be laid with the help of an orientation in communication skills. The entire growth and development of professionals is significantly aided by a strong command of the English language. Hence the study has been made to throw a light on the problems and difficulties facing by the polytechnic engineering students of Assam.
Performance Evaluation of Hybrid Fibre Reinforced High Volume Fly Ash based Self Compacting Concrete
Authors: Yashawant Prabhakar Pawar, Chetan P. Pise
Published: June 2023

Self-compacting concrete has become increasingly popular lately for usage in crowded concrete-reinforced buildings having challenging casting circumstances. New cement needs to have high fluidity and strong cohesion for these applications. The necessary concrete characteristics can be ensured through the use of fine elements like fly ash. The preliminary findings of a trial to produce and assess SCC created using large amounts of Fly ash is given and discussed. During this investigation, few SCC combinations and a control concrete is examined. The water/cementitious material ratio is ranges from 0.35 while cementitious material amount remained constant (300 kg/m3). Its self-compacting mixes replaced 25%,35%,37.5%,40%, and 50%, of the cement with fly ash. All mixes were put through tests to determine their viscosity and stability as fresh concrete. Additionally, the compressive strength, Flow Ability Test, Flexural strength and Split Tensile Strength of cured concretes were measured. For the purpose of testing the flow characteristics and mechanical properties of Hybrid Propylene Steel Fibre Self-Compacting Concrete (HPSscc), Steel Fibre in combination with Poly Propylene PP Fibre (Hybrid Fibre) are used to regulate SCC at concentrations of 0.25+0.15%, 0.50+0.30%, 0.75+0.45%, 1.0% + 0.60%, and 1.25+0.75%.The ideal quantity of hybrid fibre is established. The 28-day compressive strengths of the SCCs ranged from 35 to 54 MPa. It is important to research the effects of adding steel fibres to control SCC of various types, aspect ratios, and volume fractions.  Concrete can benefit from having its tensile strength increased by using synthetic fibres like polypropylene PP. It is important to achieve the ideal quantity of PP fibres to be added for a specific characteristic of the mix's constituents. Hybrid fibre is used in concrete when more than one fibre is included. The performance of concrete can be improved by using the characteristics of one type of fibre with another type of fibre.  Also Flow Ability Test carried out immediately after producing concrete earlier and Split Tensile Strength tests are conducted. The outcomes demonstrate that a cost-effective SCC might be successfully constructed by adding significant amounts(35%) of fly ash.
mSVM: An Approach for Customer Churn Prediction using modified Support Vector Machine and various Machine Learning Techniques
Authors: S Brinthakumari, Priyanka Dhiraj Sananse, Punam Bagul
Published: June 2023

Consumer attrition is a major issue across the world companies and that is one of their primary worries. Organizations, specifically in the telecommunication sector, are working to build technologies to forecast future customer churn due to the obvious direct impact on profits. It's essential to define the variables that lead to customer churn before making the required efforts to minimize churn. An important impact was the creation of an attrition estimation method that aids telecommunication corporations in predicting which consumers are willing to churn. The methodology proposed in this study employs mathematical methodologies on a big data framework to provide a unique strategy to feature design and evaluation. This research work has proposed a customer churn prediction using a modified Support Vector Machine Learning (mSVM) classifier. The significant contribution of this research is that we have changed the distance function of SVM in both training and testing. Similar machine learning algorithms are also validated on similar datasets such as Naïve Bayes (NB), K-nearest Neighbor (KNN) and Decision Tree (DT) with J48 classifiers. The BigML dataset has been used for detecting churn in the telecom industry in a real-time scenario. In an extensive experimental analysis, we demonstrate mSVM which produces higher accuracy over the traditional machine learning algorithm for different cross-validation methods.
House Price Prediction Using Texture and Visual Features
Authors: Sweety G. Jachak, Sayantan Nath
Published: June 2023

Real estate sector has been growing at a rate never seen before. For this sector, a key role is played by the pricing of the property. Gone are the days when the price of the property was based on whims and facies of the real estate dealers. Machine learning has numerous applications in the domain of real estate, and one of the most popular ones is predicting house prices. The application of machine learning in house price prediction involves training a model on a dataset that includes a variety of visual and texture features related to the property. The model is then used to predict the price of a new property based on its features.

This paper successfully explores machine learning based house price prediction. The methodology followed was to first use data sets to train the model. Later, using correlation-based hybrid GA-reinforcement strategy, a suitable set of features has been selected. In the end, these features are applied to a XG boost regressor to get results. The accuracies are compared with the cases of without feature selection of different regressors. This algorithm, if successfully deployed will be beneficial to both sellers and buyers, because it sets a data-based benchmarking for pricing the property.
Development Education in Digital Era
Authors: Gupta Shubh
Published: June 2023

Development education has been acknowledged for a long time as an essential instrument for advancing social justice, global citizenship, and sustainable development. The field of development education is entering a new era that is fraught with both new opportunities and new problems brought about by the proliferation of digital technology. This paper explores the role of development education in the digital era, focusing on how digital technologies are being incorporated into educational settings to enhance learning and engagement, as well as the theoretical and practical repercussions that these changes have for the field of development education. The paper argues that while digital technologies offer new possibilities for engaging learners and promoting global understanding, they also present challenges related to access, equity, and critical engagement. Drawing on existing literature and case studies, the paper concludes by outlining some of the key issues and opportunities for development education in the digital era.
Review on Suicidal Ideation among Juveniles and Adult Prisoners in Indian Prisons
Authors: Malavika Panicker et al.
Published: June 2023

Suicide can be defined as a deliberate act of taking one’s own life. Suicide may result from psychological, physiological, and societal factors where the person may feel hopeless and have difficulty handling the situations in their life. The scenario of committing suicide by an individual remains the same for the general population and the incarcerated. It is important to assess suicidal ideation among people and provide a suicide-resistant environment. This paper focuses on suicides in prison, suicidal statistics, psychological causes, and preventive measures taken by the authority.
Written Discourse Investigation a Study Based on Undergraduate Students
Authors: Kiranmai P., P. V. Ravi Kumar
Published: June 2023

Discourse analysis in terms of both spoken and written language is believed to be helpful for both linguists and language teachers. Written discourse is considered an imperative aspect that needs to be analyzed. Cohesion, coherence, clause relations and text patterns are all parts of written discourse. This study attempts to provide a vehicle for understanding student perceptions about writing and writing instruction through a case study supported by discourse analysis of student talk. The undergraduate students in this study participated in interviews and focus groups about their experiences with writing. The findings reveal deep seeded notions about writing enculturated through their under-graduation. Students were not likely to take ownership of their writing, rather considering it a teacher construct, and could not typically describe the application of writing skills.
Accounting “In the Cloud”: A New Paradigm of Accounting.
Authors: Amar Jyoti Borah
Published: June 2023

Accounting, the dialect and technique of assessment of business accomplishment is constantly conforming to the fiscal framework. The automation of accounting information was first started in the year 1950, and what succeeds subsequently was a non-reversible process. Cloud accounting is somewhat a modern concept. Accounting is a quite conservative area and a particular subject related to modern information technology. Due to globalization and innovation in market competition, in recent years, the availability of the latest financial and accounting data which can accessed from anywhere of the globe and at any time becomes essential for the business. The cloud computing is an allusion or metaphor for the internet as till date there is no unified definition of cloud based computing is available. As long as the users use a terminal to connect the internet, they can enjoy limitless resources and computing capability as in cloud based computing every data or the resources are put together in the cloud storage center. The main objective of this paper is to explore the concept, background, benefits and challenges in adoption of Cloud Based Accounting in any organization. This study is descriptive and conceptual in nature. This article is conducted on the basis of secondary data. This paper is aimed at searching the existing literatures related to Cloud Accounting and cloud technology. Finally, we can conclude that the cloud based accounting technology helps and assist accountants to do their activity and can, in fact, the cloud based accounting makes accountant job a lot easier.
Smart Wi-Fi Doorbell Using Esp32cam with IoT
Authors: Jagadeesh K. et al.
Published: June 2023

Regardless of whether they are present at the moment, people need to know who is visiting their organizations regularly. For those who experience a disability that prohibits them from meeting the visitor, this need is much more pressing. This paper suggests a smart doorbell that performs the function of a doorbell to address this issue. It should identify the visitor and notify the user. This proposal includes technology for visitor facial recognition, user alerting, and reaction management to do. The entire procedure, including visitor recognition, user notification, related management challenges, interconnected stages, and standardization concerns, is covered later. Finally, three scenarios were combined to test the model's efficacy. Each scenario was made up of several organizations, and an analysis of the recognition of known and unknown individuals was conducted across each scenario.
Interpretable Deep Learning Models: Enhancing Transparency and Trustworthiness in Explainable AI
Authors: R. S. Deshpande, P. V. Ambatkar
Published: June 2023

Explainable AI (XAI) aims to address the opacity of deep learning models, which can limit their adoption in critical decision-making applications. This paper presents a novel framework that integrates interpretable components and visualization techniques to enhance the transparency and trustworthiness of deep learning models. We propose a hybrid explanation method combining saliency maps, feature attribution, and local interpretable model-agnostic explanations (LIME) to provide comprehensive insights into the model's decision-making process.

Our experiments with convolutional neural networks (CNNs) and transformers demonstrate that our approach improves interpretability without compromising performance. User studies with domain experts indicate that our visualization dashboard facilitates better understanding and trust in AI systems. This research contributes to developing more transparent and trustworthy deep learning models, paving the way for broader adoption in sensitive applications where human users need to understand and trust AI decisions.
Generation of Regular Expression from Aligned Sequences of Text Snippets
Authors: Girishkumar K. Patnaik, Dinesh D. Puri, Akash D. Waghmare
Published: June 2023

Introduction: Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Vitae sapien pellentesque habitant morbi tristique senectus et netus. Dignissim cras tincidunt lobortis feugiat vivamus at augue eget arcu. At risus viverra adipiscing at in. Cras semper auctor neque vitae tempus quam. Sed cras ornare arcu dui. Turpis massa sed elementum tempus. Risus commodo viverra maecenas accumsan lacus vel facilisis volutpat est.

Objectives: Effective data management has become an absolute necessity in today's world as a direct result of the widespread adoption of electronic medical records for patients. For medicine and healthcare domains, particularly effective web healthcare providers, computer-assisted categorization of such information into functional classifications such as medical issues or illnesses may save time and efforts. However, a substantial volume of data in the healthcare domain is still unstructured.

Methods: The utilization of unstructured text datasets is a challenge in comparison with structured text datasets. Many researchers in various domains have proposed to convert unstructured text into structured text. The text needs to be built in a fixed and aligned pattern for easy comparison, matching, and classification. In the text classification process, accuracy is one of the challenges when text is unstructured. The text with a fixed pattern is easy to classify. The regular expressions are sequences of characters with fixed patterns of text. This strength of regular expression is used in the proposed text classification. Finding patterns in unstructured text is possible with the use of sequence alignment. Basically, sequence alignment is a concept of biomedical research, but the same concept is used to align text snippets that are not perfectly similar to each other.

Results: The sequence alignment technique detects the similarity score assigned to each potential alignment in order to choose among the numerous local alignments of sequences. The proposed local pairwise alignment method is used to get sequence alignments, which are useful to generate regular expressions.

Conclusions: A regular expression is a string of characters used to describe a text pattern. The regular expressions are typically created manually by the domain experts. The proposed work is the automatic generation of regular expressions from aligned sequences with a bottom up approach. The generated regular expressions are used as a dataset on which various machine learning algorithms are applied for text classification.
Cinema in the World of OTT and the Ethics of Visual Representation in a Fictional World
Authors: Rahul Mahajan, Santosh Kumar Gautam
Published: June 2023

Research has revealed that during the Corona Pandemic almost a thousand single screen theatres shut down for good in India. Meanwhile, a huge surge was seen in the viewership of OTT platforms. Producers who could not release their films in theatres sold their films to OTTs instead; and this trend has continued even in the post-pandemic environ. It is believed that this growth in the popularity of streaming platforms is facilitated by the bolder content that OTTs offer, raising several ethical dilemmas for both viewers and the government over censorship issues. A survey conducted by this researcher amongst more than 350 young students across Delhi, Haryana, Rajasthan and Uttar Pradesh revealed that 47.5% of the respondents (311) go only once a year to watch a film in a cinema hall, while 14.3% do not go to a film theatre at all. On the other hand, among the same set of respondents, 13.2% watch a film every day, 38.5% watch every week and 40.8% every month on an OTT platform. 51.3% of the youth who responded to the survey also revealed that the explicit scenes of nudity and violence in OTT content, does not bother them. There is however also the view shared with this researcher by Jyotsana Garg, an advisory panel member of the Central Board of Film Certification, who says that the present guidelines enacted to regulate OTTs in India are not adequate; as the foul language, nudity and violence in OTT content will negatively impact the youth, and there is a need for greater censorship. The moral compass is obviously divergent between the youth and policy makers. In conclusion, there are contrary ethical standards and many dilemmas surrounding visual representations in the fictional world of cinema and OTT, especially with OTTs showcasing bolder content and threatening the very survival of cinema halls.
Embedded IoT Car Parking and Billing System
Authors: M. Geethanjali Mohammed Hameed Ullah, Mohammed Faizaan Ali, Sadia Anjum,
Published: June 2023

As of late, huge vehicles are going through trouble finding a parking area because noappropriate data is available on whether the leaving space is full or void. Altogether this can cause a clog, contamination, and fuel failure. Because of these conditions, there could likewise be trouble in controlling the stopping the board. By utilizing a Microcontroller keen stopping framework (given IOT), stopping issues are regularly settled. The Web of things might be a new subject that assumes a pivotal part in our everyday lives. IOT decreases human work, exertion, time, and mistakes because of human carelessness. Subsequently, an Embedded IOT Smart Parking System is proposed which is intended to shape it simpler for stopping clients to encourage data on the stockpile of unfilled and filled stopping spaces and can likewise book stopping openings utilizing electronic applications.
Automatic Detection of Covid-19 from Chest X-ray Images using Corona Net
Authors: D. L. Asha Rani, P. Anishiya, T. Pramananda Perumal
Published: June 2023

The most devastating pandemic to ever infiltrate humans is COVID-19. An automatic detection system is an instantaneous diagnosis option to prevent COVID-19 transmission. The objective of this research work is to propose a novel CNN (Convolutional Neural Network) based   Covid-19 detection system to classify the radiological (chest X-ray) images into binary classes (Covid-19 and Non-Covid-19) and three (multi) different classes ( Normal Lungs, Lungs infected by Covid-19 and Lungs infected by Pneumonia). The efficiency of the proposed CNN(CoronaNet) model is compared with six existing pre-trained models (AlexNet, GoogleNet, VGG-16, SqueezeNet, Inception-V3 and ResNet-50) for identifying Covid-19 from radiological images. The computer experimental results demonstrate that the proposed CoronaNet model has achieved an overall accuracy of 96.4% for binary-class classification (Covid-19 and Non-Covid-19) and 94.4 %  for multi- class classification (Normal, Covid-19 and Pneumonia). The proposed technique could be a useful tool for radiologists to diagnose and treat Covid-19 patients promptly.
"Navigating Human Resource Practices: Insights into Job Satisfaction in Tamil Nadu's Non-Banking Financial Companies"
Authors: V. Jithin kumar
Published: June 2023

Because of the vital responsibilities they play in nation-building and financial inclusion, non-banking financial companies are playing a significant role in encouraging inclusive growth in the nation. The primary concentration of NBFCs is on loan-related activities, particularly gold loans, and advances, as well as shares, bonds, debentures of various kinds, leasing, hire-purchase agreements, and the insurance industry. Respectively, they constantly view their employees as the foundation of their business and work to ensure employee satisfaction. However, the Human Resource Department has a difficult time getting to know its workers, which means that the majority of NBFCs experience greater attrition rates. Thus, 450 respondents were used in this study to identify and comprehend the human resource policies and practices used by NBFCs and determine the relevant links between these practices and job satisfaction. For this descriptive study, data were gathered from 450 employees of top Gold Loan NBFCs in Tamilnadu State using a stratified random selection method. Correlation analyses were used to create and test research hypotheses. The findings show that job satisfaction is strongly correlated with performance evaluation, extrinsic and intrinsic motivation, talent acquisition and selection, employee engagement, and human resource development.
Infrastructure-Less Wireless Networks Employ Reactive Routing with Knapsack-Based Buffer Management
Authors: Sanjay Nausheen Fathima, Mohd. Abdul Bari,
Published: June 2023

Wireless infrastructure-less networks provide network resources independent of location. These networks are mobile, resource heterogeneous, peer-to-peer, self-forming, and adaptable. Health management, military, and disaster aid use such networks for reliable communication. These networks use routing to connect source and destination nodes and forward data packets. Network nodes' buffer sizes hinder efficient routing. We present a buffer-aware route-finding system that optimises nodes' packet processing based on their residual buffer size using the knapsack algorithm. Our buffer overflow-prevention method improves network performance. Using the NS-2 simulator, the suggested mechanism reduces packet loss, improving network performance. Our work proposes an effective routing protocol for wireless infrastructure-less networks that takes into account nodes' restricted buffer sizes. The proposed system could be used where efficient and reliable communication is needed.
Review of Counter-Based Digester ACK's Effectiveness in MANET Packet Loss Prevention
Authors: Guddi Singh Afsha Nishat, Mohd. Abdul Bari,
Published: June 2023

a wireless peer-to-peer network with a mobile component adaptability and self-formation characteristics that lacks infrastructure. The network is ideal for use in emergency and disaster assistance applications that need reliable communication.. Finding the channel between communicative entities and sending information across it enables communication. There are several routing protocols in the literature that are developed to achieve reliable communication. Routing protocols are susceptible to packet losses because they consider network nodes to be receptive to communication. Due to malicious behavior or a shortage of resources, nodes trash packets. To address the problem, a number of intrusion detection systems have been suggested in the literature. In order to prevent packet losses in MANET, the newly created counter-based digested Acknowledgement (CDACK) was developed. This study's objective is to assess the CDACK protocol's performance in relation to current MANET intrusion detection systems. The findings demonstrate that, in terms of avoiding packet dropping nodes from the routing path, the CDACK protocol is a good fit for MANET..
Policy Recommendations to Prevent Loss of Agricultural Lands and Livelihood of Agricultural Communities in Indian Growing Cities
Authors: Mahendra Joshi Ar. Swapnil Sheth,
Published: June 2023

India is primarily an agriculture base country and undergoing tremendous development in the sectors of technology, industry and IT sectors. Cities are rapidly growing and undergoing rapid unstoppable urbanization.  In 2011, India's urban population was 377 million, and it will be 600 million by 2031. India's rapid urbanization threatens arable land. Urbanization consumes 0.12 million hectares of agricultural land annually in India.. This paper aims to recommande changes in existing planning policies in India that are responsible for agricultural land loss and devastation of livelihood of agricultural communities in the process of urbanization. Planning policies are studied and compaired in detail for the developing cities of Pune and Bangalore with respect to regional plans and development plans of respective cities. The study reveals tremendous shift in planning policies over the period of time giving priority to development agenda for economic development of the region without giving deu consideration to preservation of farmlands that are coming under urbanization for all these growing cities. Many of the planning policies are common for all cities studied however few policies are seen to be in consideration to local conditions and political agenda. Study demand an immediate intervention towards planning weaknesses and change the few of the planning policies that can help preserving the farmlands that are coming under urbanization.
Various Feature Extraction and Selection Techniques for Lexicon Based and Machine learning Sentiment Classification
Authors: Girishkumar K. Patnaik Shital A. Patil, Krishnakant P. Adhiya,
Published: June 2023

Introduction: Natural Language Processing (NLP) is a kind of software that gives computers the ability to comprehend human languages. Words are often used as the fundamental unit for grammatical and semantic analysis on a deeper level, and the major objective of most natural language processing (NLP) projects is word segmentation

Objectives: Proposed System uses the feature extraction method for generating the hybrid feature to get good accuracy for classification in order to solve the practical problem of huge structural differences between different data modalities in a multi-modal environment, where traditional machine learning methods cannot be directly applied to solve the problem.

Methods: In order to do so, this paper introduces the method for generating the hybrid feature. In this System, we utilise a various feature extraction and selection technique from large text. The data has collected from students’ feedback and these feature extraction techniques has applied

Results: Each technique provides different feature extraction while NLP based dependency features provides homogeneous feature set with relationship.

Conclusions: In extensive experimental analysis NLP based features obtains higher precision over the other feature extraction techniques in classification.
Analyzing the Effectiveness of the Forest Rights Act in Mitigating Displacement Issues Among Forest-Dependent Communities: A Case Study of the Dudhwa-Katarniaghat Tiger Reserve in Uttar Pradesh
Authors: Keshav Walke, Shyamrao Koreti, Amen Xavier
Published: June 2023

The Dudhwa-Katarniaghat Tiger Reserve is a protected area situated in the Terai region of Uttar Pradesh, India, which has caused the significant displacement of indigenous communities, particularly the Tharu indigenous group. The Tharu community has lived in the Terai region for centuries, but their displacement from their lands and homes due to the establishment of the Tiger Reserve has resulted in the loss of traditional livelihoods, cultural practices, and a sense of identity(Paul & Bahuguna, 2015).
Uncovering the Realities of Forest-Dwelling Communities in Kanha-Kisli Protected Area of Madhya Pradesh: An Examination of Livelihood and Socio-Economic, Challenges
Authors: Keshav Walke, Shyamrao Koreti, Amen Xavier
Published: June 2023

Forests are essential ecosystems that support biodiversity, regulate climate, and provide critical resources for local communities. However, forest-dwelling communities face numerous challenges, including poverty, lack of access to education, healthcare, and basic infrastructure, and conflict with wildlife conservation. The Kanha-Kisli Protected Area (KKPA) in Madhya Pradesh, India, is one such forest landscape where tribal communities have been living for generations. Despite efforts to integrate forest conservation and community development, forest dwellers in KKPA continue to struggle with various issues.
Big Data Enabled Realtime Crowd Surveillance and Threat Detection Using Artificial Intelligence and Deep Learning
Authors: Deepali Ujalambkar Aquib Hasware,
Published: June 2023

In recent years, security precautions at public events have become increasingly important as a direct response to the growth in the number of disruptive actions. There are several various varieties of closed-circuit televisions that are employed to perform 24-hour surveillance of public areas and the people that live such areas. Every person in a socialised society with a population of 1.6 billion is subjected to imprinted pictures an average of 30 times each day. Since the entire participation of the community is required to safeguard public areas from the most unexpected and lethal of events, it is difficult to discern whether an incident is an exceptional or casual occurrence because continual monitoring of human data makes it difficult to distinguish the difference. Within the scope of this study, we propose a method for identifying potentially threatening actions within footage obtained from closed-circuit television systems. To accomplish this objective, we must first extract individual still frames from the video and then examine the actions of the people seen in those still frames. We have placed a significant amount of reliance on both machine learning and deep learning algorithms to make this a reality. To automate this process, we must first develop a training model that makes use of many photos and a "Convolution Neural Network" that makes use of the Tensor Flow Python package. This model must be created before we can move on to automating the process. Every frame from every video that is provided will be used to train an algorithm that will analyse the film and evaluate whether it contains suspicious content or merely everyday activities. If we conclude that the activity was suspicious, the next phase of the study will concentrate on locating any weapons that may have been concealed on the corpse.