bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring Learning Mode Preferences of College Students in Kerala: A Comparative Study of Online, Blended, and Traditional Education Trends
Authors: Semeer Khan. P Shameera. T ,
Published: December 2023

This study investigates college students in Kerala preferences for online, blended, and traditional learning methods. 1,963 students from various institutions in Kerala were surveyed using a questionnaire in order to gather first-hand information about their preferences and experiences. According to the study, most students (72.8%) preferred traditional learning methods, while only 4% preferred online learning. 23.2% of students said they preferred blended learning. The study found that important factors in students' preferences for various modes of learning include things like the device used for online classes, teacher assistance, the development of communication and technical skills, mental stress, and part-time job opportunities. The chi-square test results showed a significant relationship between students' preferences and their preferred mode of learning, with traditional mode being the most preferred. The study highlights the need to address obstacles to online learning and the potential advantages of blended learning, which has significant implications for policymakers and educational institutions in Kerala. The effects of various factors on students' preferred modes of learning as well as potential regional variations in these preferences could be explored in more detail.
Biomedical Waste Management among Nursing Students
Authors: K. Silambarasan Prakash D, Anupama. A, Margaret J, P. Punitha,
Published: December 2023

Any waste generated during the diagnosis, treatment, or immunization of people is referred to as biomedical waste. It is now well established that hospital waste produced during patient care has a variety of adverse and harmful consequences on the environment, including people. Assessment of knowledge, attitude, and practice of biological waste management (BWM) was one of the study's main objectives. The study used a descriptive research design and non-probability volunteer selection techniques to gather a sample of 100 nursing students who met the inclusion criteria. A questionnaire, a standardized method for evaluating knowledge, attitude, and practice of BWM, was used for the pre-test and post-test. The pretest mean was 56.51 (Standard deviation: 20.5229). Chi square analysis revealed that, with the exception of education and training, there was no significant correlation between demographic factors. The results showed that regular BWM training programs are necessary for nursing students to improve their skill on BWM.
Conversion of Earthquake Vibrations in to Electricity
Authors: Geetha L. Ashwini Satyanarayana,  Apeksha S. A.,
Published: December 2023

Energy is produced by nature, and humans have always sought to manipulate this source for their own gain. Different strategies for reaching this goal have been developed over time. Due to the underutilized yet significant energy that may be acquired from earthquakes,this article investigates a different source of power. By catching this energy and turning it into electricity, a novel sort of generation could be accomplished. It's not widely understood that seismic mechanical waves can be used as a source of energy, and there isn't much literature on the subject either. The focus of this research paper is to convert earthquake vibrations into electrical signals by using vibration sensor in Servo electric shake table apparatus. The model is tested for El Centro earthquake time history data, Chile earthquake data and for random sine waveforms.
Comparative Studies on Mechanical Properties and Corrosion Rate of Nickel Chromium Carbide (Cr3C2-NiCr) Coated on Inconel 600, 625, 718 Specimen
Authors: Yuvaraja Naik Vinod Kumar, Udaya Ravi M.,
Published: December 2023

In this present work, Nickel Chromium Carbide (Cr3C2-NiCr) coated on three different Inconel 600, 625, 718 Specimen are used and the mechanical properties, corrosion resistance and morphological properties of the specimen were investigated by conducting Brinell hardness test, Vickers Hardness Test, Tensile test and electrochemical test experiments respectively and found that Inconel 625 has maximum hardness, maximum tensile strength and less corrosion resistance as compared to the remaining two coated Inconel specimen 600 & 718. And then coated surfaces of Inconel 600, 625 and 718 specimens were analyzed by using Scanning Electron Microscope (SEM), XRD, EDAX and optical microstructure techniques.
Perception-Satisfaction Based Quality Assessment of Public Transportation Services using SERVQUAL Model.
Authors: Vivek R. Gandhewar Sunil R. Kewate,
Published: December 2023

The performance evaluation of any public transportation mainly depends on the customer satisfaction level of passengers (referred to as customers). To evaluate the performance of any public transport business, a systemic survey-based model is needed, which critically analyzes the customer's requirement and designs the future line of action for improvement. In the present work, an attempt is made to understand better passenger attitudes and the level of passenger satisfaction towardsservices provided by the public bus Maharashtra State Road transportation Corporation in India (MSRTC) using the SERVQUAL model. Further, it focuses on the measures taken by the bus transport industries to improve the level of satisfaction of passengers and to avert their problems to retain the passengers' loyalty. This study aims to identify the causes due to which quality is affected and study the responses from a total of 4000 different respondents.
Guideline for the Educational Management of Culture Inheritance in Nakhi People, Yun Nan Province
Authors: Niran Sutheeniran, Patchara Dechhome Yang Haiping, Buranajit Kaewsrimon,
Published: December 2023

Explore the educational management culture inheritance Nakhi People,Yun Nan Province 2) To develop guidelines to the educational management of culture inheritance in Nakhi People,Yun Nan Province and the managerial to educational culture inheritance Nakhi People,Yun Nan Province. Were 268 instructors 160 key informants Yun Nan high-level administrators Yun Nan Province. the educational management of culture inheritance in Nakhi People,Yun Nan Province in five aspects of educational management of culture inheritance Nakhi People,Yun Nan Province in five 39 the educational goals of colleges and universities, 6 guidelines for Promoting the multiple education model, 11 guidelines for enhancing funding guarantee mechanism, 4 guidelines for Encouraging ethnic Minority-Nakhi Culture Course and 11 guidelines for Supporting faculty training of educational culture inheritance in Nakhi People,Yun Nan Province in five aspects were at highest level.
VLSI Implementation of 3-Parallel FIR Filters through Coefficient Symmetry Property and Fast FIR Algorithm
Authors: Ananta Patnaikuni Mythri Pondreti Pushpalatha,
Published: December 2023

In multirate digital signal processing systems, polyphase filters are frequently used. The challenges in multirate digital signal processing systems primarily relate to efficiently processing signals at different rates while maintaining high-quality output. These challenges include computational complexity, power consumption, and signal delay. The coefficient symmetry property plays a key role in systematically arranging of filter taps in symmetric manner to improve operating efficiency. With a major focus on using the coefficient symmetry characteristic, this paper addresses the VLSI implementation of traditional Type-1 polyphase FIR filters. Furthermore, this paper incorporated 3-parallel FIR filters especially for sequences with odd lengths in order to take full advantage of the coefficient symmetry characteristic. The Fast FIR Algorithm (FFA) method is used to increase overall efficiency. Furthermore, in order to achieve better performance, a modified FFA technique is introduced to enhance overall performance. The paper thoroughly investigates important VLSI factors, such as power consumption, utilization, and delay, and shows how, by utilizing coefficient symmetry and applying this modified FFA technique, filters that are optimized for both power consumption and area utilization are able to be implemented. The results illustrate a significant reduction in both area and power consumption, particularly for longer filters, attributed to the reduced number of multiplication operations inherent in the fast FIR algorithm approach. Additionally, image processing application using 3x3 FIR filter is executed.
One Dimensional (1D) Column Buckling Factor Analysis of Al-2024 Alloy Panel
Authors: Mir Safiulla Syed Kashif Hussain,
Published: December 2023

The failure mode of buckling in science is caused by mathematical instability. Material failures and structural variability, acknowledged as buckling, are two of the most common causes of the failure of mechanical components suddenly. Whenever a wall made of a larger material than either of the two other dimensions of the wall is put under axial compression, because of its size, its axial displacement will be much smaller than the size of its lateral deflection, which is a phenomenon known as buckling. In the present study, Al 2024 alloy panel, is used for buckling factor analysis and understanding the effect of boundary conditions based on Euler's formulae approach. The buckling factor was obtained for different boundary conditions by taking the length, width, and thickness panel. The theoretical buckling factor is calculated using the abovementioned formula for other boundary conditions. Then the panel analysis is done in Nastran-Patran software for different boundary conditions to compare results.
Silver Nanoparticle Research for Plasmonic Solar Cell
Authors: Sanjay Kumar Sharma Satyarth Tiwari,
Published: December 2023

Environmental concerns and limitation of fossil fuels have motivated the researchers to explore green energy as the solution to the energy crisis in the modern era. Solar energy is the most widely available and potential source of green energy. Solar cells or photovoltaic cells are semiconductor transducers that convert the solar energy into useful electrical energy. Inside the solar cells, absorption of photon energy leads to electron-hole pair generation then the generated charge carriers contribute as the useful photocurrent by the solar cell. We demonstrate that how shape and size of the silver nanoparticle changes by changing their precursor concentration. We demonstrate how these findings will promise in the design of ultrathin film plasmonicsolar cell.
Fashion Library: Bridging Environmental Sustainability and Innovative Marketing for a Sustainable Future
Authors: Manan Shah Neha Patel , Rajeshwari Jain ,
Published: December 2023

The UN Environment Programme states that thefashion business is the additional largest user of water while emitting 8 to 10% of global carbon. Fashion Libraries, a novel idea in India as a form of pooling or renting are considered as possible paths to sustainable clothing. Research in foreign counties has associated the acceptance of fashion libraries with psychological, social, and financial risks among others. The rationale of this study is to find out the acceptance and perception of fashion libraries; identify the early adopters of fashion libraries, the risk associated, and the decision-making factors for becoming members of collaborative fashion consumption. Further, the exploratory study aims to obtain a psychographic valuation of Collaborative Fashion library users/potential users and comprehend their cause and factors for joining it.Data were collected through structured questionnaires administered to 410 respondents across various cities of Gujarat, India with respondents in the 18 to 60 age group. Statistical tools like Exploratory factor analysis, ANOVA testing, and correlation were used to corroborate the results.The effect of the exploratory study identified three early adopter segments –Early adopters of fashion, Fashion Influencers with environmental concerns, and Possible Green early adopters. The acceptance of these libraries was based on certain factors like sustainability, hygiene and cleanliness, store layout, easy accessibility to store location, product width and depth availability in all sizes, styles, designs, and good maintenance of the garments.
Inheritance of Lint Weight Per Boll in Specific and Interspecific F1, F2 Hybrids in Cotton
Authors: Abror Mamajonov Gayrat Jurakulov,
Published: December 2023

The experiment aimed to study the inheritance patterns of lint weight per boll in F1 and F2 hybrids. The parental forms, including varieties and lines, were reciprocally hybridized to analyze the impact on lint weight per boll. The results showed variations in lint weight among the parental forms and their hybrids. No heterosis was observed in F1 hybrids with similar lint weight per boll. Positive and negative dominance patterns were identified in F1 hybrids involving different parental forms. In F2 hybrids, transgressive variability and genetic contributions were observed, indicating potential for selection and breeding. The results suggest that distant parental forms and gene combinations influence the lint weight per boll in subsequent generations.
Soybean Seed Peroxidase
Authors: Z. L. Abdurazakova Sh. Yunuskhanov, M. Sh. Jaynakov,
Published: December 2023

Research has been carried out to study the peroxidase activity of seed coats and the surface layer of seeds of various soybean varieties. It has been shown that the peroxidase activity of soybean seeds is located mainly on the surface layer behind the thin soybean shell, which plays a protective role against various agro-ecological stress factors. The content of proteins with peroxidase activity in soybean shells of the Vilana variety is 3.29-3.36% and the surface layer of seeds after separation of the shells is 0.95-1.1% of proteins containing peroxidase activity. The total protein content with peroxidase activity on whole seeds averages 1.7%.
Reptile Search Algorithm with Deep Convolutional Neural Network for Cloud Assisted Colorectal Cancer Detection and Classification
Authors: S. Murugappan Rajeev Kumar Tiwari,
Published: December 2023

Cloud-based automatic colorectal cancer (CC) detection involves the usage of cloud computing technology and system to help in the earlier and accurate diagnosis of CC in medical images and patient information. This cloud-based technology aims to improve the efficiency and reliability of CC screening, monitoring, and diagnoses. Automatic CC detection refers to the use of computer-based technology and systems to aid in the earlier and accurate detection of CC in patient data and medical images. This automated system aims to increase the reliability and efficiency of CC monitoring, screening, and diagnosis. Deep learning (DL) methods, especially convolutional neural networks (CNNs), exhibit promising results in automatic CC diagnosis. They can be trained on wide-ranging datasets of medical images to learn patterns and features related to precancerous and cancerous lesion. This study develops a new Reptile Search Algorithm with Deep Learning for Colorectal Cancer Detection and Classification (RSADL-CCDC) technique. The main aim of the RSADL-CCDC method focuses on the automaticclassification and recognition of the CC in the cloud environment. Once the medical images are stored in the cloud server, the detection process is carried out. In the presented RSADL-CCDC approach, the initial stage of preprocessing is performed by bilateral filtering (BF) approach. For feature extraction, the RSADL-CCDC technique applies ShuffleNetv2 model. Besides, the recognition and classification of CC take place using convolutional autoencoder (CAE) model. Finally, the hyperparameter tuning of the CAE technique takes place by utilizing RSA. The experimental validation of the RSADL-CCDC system is performed on benchmark medical database. Extensive results stated the enhanced performance of the RSADL-CCDC technique on CC recognition over other models with respect tovarious actions.
A Novel Security Model for Password Encryption Using Aadhaar and Amicable Number
Authors: Gaurav Agarwal Mohammed Shakeel, Akash Sanghi, YDS Arya,
Published: December 2023

In this day and age, data hacking has become a major source of fear. In order to avoid any further theft of data, we must stop this criminal hacking. Backups, encryption, access control, and other techniques are just a few that may be used to ensure data integrity. We did not combine the existing approaches when we announced our encryption process. The secret to encrypting user passwords is to utilize a mathematical calculation equation that is well-defined and a number conversion mechanism. Users must provide their password and Aadhaar number in order to register. Encrypted password has been recorded in the database. Every industry uses encryption to secure data, and there are many potential applications for it in the future.
Youtube Comment Feature Selection And Classification Using Fused Machine Learning
Authors: R. Rooba, A.R.Karthekeyan,
Published: December 2023

The exponential rise of internet platforms, notably YouTube, has resulted in a massive volume of user-generated material, including video comments. Understanding audience input and enhancing user experience require analyzing and forecasting the mood of YouTube comments. This work provides a comprehensive method for YouTube comment prediction and sentiment classification that combines feature selection using Recursive Feature Elimination (RFE), Elastic Net Random Forest with Logistic Regression (RF with LR), and Principal Component Analysis (PCA). The first stage is to choose the most informative features from a given dataset using RFE, a common approach for doing so. RFE aids in the elimination of unnecessary or redundant features, resulting in enhanced model performance and decreased computing complexity. The Elastic Net Random Forest with Logistic Regression (RF with LR) technique is then used to construct a robust sentiment classification model. Elastic Net regularization combines the advantages of both L1 (Lasso) and L2 (Ridge) regularization, allowing for improved feature selection and management of multicollinearity concerns. By integrating many decision trees, the Random Forest ensemble approach improves the model's predictive potential even more. We employ Principal Component Analysis (PCA) to increase the classification model's effectiveness and solve possible difficulties created by high-dimensional data. PCA decreases the dataset's complexity while retaining its fundamental qualities, resulting in a more manageable and efficient feature space for classification. Finally, we compare the performance of three prominent classifiers on the preprocessed dataset: Linear Support Vector Machine (LSVM), Gaussian Naive Bayes (GNB), Logistic Regression (LR), and Decision Tree (DT). We can select the best-performing model for YouTube comment categorization by comparing these classifiers.
Experimental Evaluation of New-Generation Waste Material as a Substitute in M-50 Concrete Mixes
Authors: Tushar G. Shende Pawan K. Hinge,
Published: December 2023

The journey of concrete began around 600 BC, when the ancient Romans began widely using concrete for construction by mixing volcanic ash, lime, and seawater. Centuries later, it was in 1824 that Joseph Aspdin invented Portland cement by burning finely crushed chalk and clay until the carbon dioxide was eliminated. Between 1850 and 1880, Francois Coignet used Portland cement extensively for the first time in the construction of homes in England and France [17]. Since then, though there have been vast innovative leaps, improvements and inventions in the material used in construction, the construction industry is still heavily reliant on Portland cement and aggregates. This excessive use and mass dependence on concrete is now a concern for the construction industry as the natural resources used in concrete like sand and gravel are slowly being depleted. In addition, the environmental concerns relating to CO2 emissions from concrete have forced the industry to start looking for alternatives for the ingredients used in concrete.

On the other hand, electronic waste, also known as electronic waste, is considered one of the harmful types of electronic waste in today’s new age world. Drinking water supplies are becoming polluted, and the environment and ecosystems are being impacted all around the world as a result of the unceasing increase of these technological wastes. Both of these current environmental issues can be mitigated to some extent by experimenting with and utilizing electronic waste materials in the construction industry. Along with traditional aggregate alternatives such as fly ash and rice husk ash, the industry is now experimenting with E-waste to determine if it can be a viable material for improving concrete strength and longevity.

The primary objective of this research is to better understand the behavior of M-50 grade high strength concrete when coarse aggregate is replaced by E-waste plastics in staggered percentages. The strength of concrete containing E-waste plastic was tested at different time intervals after coarse aggregates were replacement with varying percentages of E-plastic waste by the volume range from 0 to 30 percentage. When compared to normal concrete, concrete with E-waste had comparable compressive, flexural, and tensile strength for 28 days up to a specified percentage of replacement. When the E-waste plastic component percentage is considerably high, however, there is a decline in strength after a certain point
Investigation of Ionospheric Disturbance in ALOS PALSAR Images Using Machine Learning
Authors: G Raju Manaswini R  ,
Published: December 2023

The ionospheric disturbance is a very significant problem in remote sensing and navigation related applications. Dynamic ionospheric layers will witness variation of the plasmatic content which will results in generation of distorted radar images and often the most of the information captured by the image will be lost. The SAR images have vital applications in disaster monitoring, earth’s surface monitoring, mapping of afforestation urbanizations hence the precision level required is higher. In the present study a fusion model of machine and deep learning approach is conducted a combination of GoogLeNet model with KNN, decision tree and SVM classifier is implemented for detection of Synthetic aperture radar image that is subjected to ionospheric variation. The results prove the detection of image affected by ionosphere can be detected put to 96 % and effective in implementing in real time. The data considered in the study is ALOSPALSAR data which is a L band radar data, the raw data is processed in a software called Envi SAR and the images as subjected to preliminary detection phase change method to check image is subjected to ionospheric and latter machine and deep learning approaches are considered.
Faults Identification in Digital Counter Using Naïve-Bayes’ Algorithm
Authors: Manaswini Ramakrishnappa Shruthi Modem, Hamsa Girish, Joseph Anthony Prathap,
Published: December 2023

This paper elaborates on the implementation of the Naïve Bayes Algorithm to identify the faults occurrence in the digital counter circuits. The digital counters are circuits utilized to count the values in increasing order, decreasing order, or both directions. The digital counters find applications in real time from simple wristwatches to the industrial conveyor belt that is automated based on timings. The fault happening in the digital counter circuit is to be identified using Fault detection methods such as modular redundancy methods and error detection methods. With the advent of Artificial Intelligence algorithms, the identification of faults and errors in circuits is attained rapid manner. Though there are several machine learning algorithms such as Decision trees, Random Forest, K-Nearest Neighbor, and Support Vector Machines, the naïve Bayes algorithm is an easy and efficient algorithm to identify the errors in the circuits. This work concentrates on the naïve Bayes algorithm by developing the HDL code to predict the faults in the counter circuits. The proposed HDL code is validated for parameters namely power, area, and timing using the EDA tools.
Fermatean Uncertainty Soft Sub Algebra in terms of Ideal Structures
Authors: R. Nagarajan K. Balamurugan,
Published: December 2023

Ideal concepts are discussed in many mathematical applications. Various author has been studied and analytical in different ways. In this article, the idea of bipolar fermatean uncertainty sub algebra’s in terms of R-ideals is planned. Also the correlation among bipolar fermatean uncertainty soft ideal and bipolar fermatean uncertainty soft R-ideals is expressed some interesting ideas also analyzed.
Wind-Related Structural Stiffness and Stiffness Reduction Factors
Authors: Dung Do Thi My
Published: December 2023

One of the most important parts of a building is its columns. When columns are destroyed, it can lead to the destruction of other structures or be the major cause of the destruction of the whole structure. Building stiffness is a very important factor when looking at how structures behave because it affects how buildings vibrate and, by extension, how much horizontal wind they can handle. It is possible to be more specific about how to plan high-rise buildings that are subject to wind loads by looking at how buildings behave when their structural stiffness decreases. The objective of the study is to investigate through the effects if reinforced concrete buildings reduce stiffness and how that changes how wind affects the structure. The author of this study looks at how reinforced concrete high-rise buildings behave. The results will be used to look at changes in the horizontal displacements and internal forces in buildings so that project design suggestions can be made.
Beyond the Quota: Unravelling Legislative Dynamics and Public Sentiment on Women's Reservation"
Authors: Dhar Sohong
Published: December 2023

“Achieving the aim of equal involvement of men and women in decision-making will establish a balance that greater accurately describes the makeup of society, which is required to improve democratization and encourage its effective functioning. The goals of fairness, outcomes, and security cannot be attained without the active engagement of women and the adoption of women's viewpoints at all phases of decision-making." The Women's Reservations Bill is a critical piece of government legislation having the potential to alter the foundation of Indian democracy. It has always sparked intense arguments both inside and outside of Parliament. Its supporters argue that the Bill is vital for woman's active engagement with politics. Opponents believe that reserve would mainly benefit women from aristocratic groups, exacerbating the suffering of those with limited resources and underprivileged. The Women's Reservation law, also known as the Constitutional Amendments (108th Amendment) Bill, is an ongoing law in India that intends to reserve 33% of all seats in the Lok Sabha, India's Lower House of Parliament, and the state legislatures for women. This essay investigates gender inequalities in legislative decision-making in the context of the gender quotas. I utilize two empirical methodologies to randomize parliamentarians' gender and sentiments analysis to discover legislative issues in the French Assembly from 2001 to 2017. It might even go one step further and investigate the current state of support for policies on each issue, for example, by using analysing sentiment methods or embedding models to calculate the distance across a piece of text and the material of interest.
Policy Implementation Strategy of Link and Match for Vocational High School with Industry and the World of Work in Tangerang District, Indonesia
Authors: Bambang Heru Purwanto Iman Sutarya, Thomas Bustomi,
Published: December 2023

This research aims to analyze the implementation of the link and match policy for Vocational High Schools with Industry and the business world in Tangerang Regency, determine the causes of the low success of implementing this policy, and formulate a strategy for implementing the link and match policy for Vocational High Schools with Industry and the business world in Tangerang Regency. The research utilizes Goggin's policy implementation theory as its analytical framework. The research method employed is descriptive research, supplemented by strategic analysis through SWOT analysis. The study focuses on Vocational High Schools in the Tangerang Regency area and the Education and Culture Office in Banten Province. The findings of the research indicate that the implementation of the link and match policy for Vocational High Schools with the industry and the business sector in Tangerang Regency has not reached its full potential. The suboptimal implementation of the link and match policy can be attributed to subpar message content, ineffective message formats, and less-than-optimal leader perceptions. The weakest elements according to research are the content of the message, the indicator of the credibility of the message as a solution, and the resource costs on the perception of the leader. The strategy formulated to optimize the implementation of the Vocational School link and match policy with Industry, Business & Entrepreneurs in Tangerang Regency, is to implement a progressive or aggressive strategy.
Satellite Temperature Modeling in Geostationary Orbit Using COMSOL
Authors: Shakila Hosseinzadeh Kondori, Mustafa Helvacı
Published: December 2023

In our world, communication satellites are becoming more and more significant. They are costly to create, launch, operate, and maintain, thus these costs are crucial. Due to the fact that electronic and satellite components can only operate within a limited temperature range, it is crucial to understand and manage the satellite's temperature in order to maximize efficiency both before and during the mission. This study considers GEO and comparable satellites with the goal of showing satellite temperature. We ignored the entire satellite's internal structure and focused only on the external heat generated by its surface (main body and solar panels). COMSOL is used in this project that is a simulation platform. Finally, the results have been displayed for the model at different times.
A comparative study on rutting behavior of unbound and cement stabilized base layers in flexible pavements
Authors: Shiva Prasad N , B V Kiran Kumar
Published: December 2023

Rutting distress, a phenomenon characterized by formation of ruts in high-stress areas of flexible pavements, necessitates material enhancements due to increased vehicular loads resulting from national and international trade via highways, highlighting the need for revised prediction methods utilizing laboratory tests with standardized protocols to evaluate asphalt mixtures before field application. While pavement construction consumes substantial non-renewable resources, there's an increasing emphasis on sustainability over initial costs in government decision-making, underscoring the importance of sustainable development to reduce investments and preserve natural resources. Notably, cement-treated bases are effective in extending the fatigue life and reducing cracking in flexible pavements. Various testing devices, such as the Georgia loaded-wheel tester, French wheel tracking tester, Hamburg wheel-tracking device, and asphalt pavement analyser, assess asphalt mixture properties, but mainly target bound bituminous layers. This study's primary goal is to compare the rutting performance of two pavement sections using a novel device called the 'Roller compactor cum rut analyser' (RCRA), capable of compacting and analysing all layers of flexible pavement. By applying the RCRA model, the research demonstrates that the section with cement-stabilized layers displays enhanced resistance to rutting and deformation, providing valuable insights for the construction of durable road infrastructure.
Mathematical Approach to Study of Complex Behaviour of Students Educational Stress During Covid – 19
Authors: Vijayalakshmi.G.M, Susila.G , Kalaivani
Published: December 2023

In this study, a fresh attempt was made to examine dynamic behavior and estimate the ultimate amount of the psychological stress spread among students caused by a rapid breakout of COVID-19. The multicompartmental model makes enquiry about the impact of stress on student education and the significance of stress management to learning successfully. Through qualitative and quantitative studies we show some adequate constrain for the disappearance or spread of psychological stress. To demonstrate theoretical conclusions, numerical simulations are also provided.
Implementation of Digital Differentiators using Quantum-dot Cellular Automata
Authors: Sreelekha Busi, A Durga Bhavani, Tirumala Krishna Battula
Published: December 2023

when it come to scaling of the circuits, the CMOS (Complementary metal-oxide-semiconductor) technology  is no longer in the effect, as the semiconductor industry  has come up with many number of technologies to reduce the size of the circuit and a single component the technologies has been changed. One of them is the Quantum-dot Cellular Automata. The size of the basic cell used in QCA is in nanometer. Hence by using the Quantum-dot Cellular Automata(QCA) various circuits are designed, here in this work the design of a digital differentiator has been considered. The digital differentiators like First Difference Differentiator, Central Difference Differentiator and the Bilinear Transformation of the IIR filters has been realized. These simple circuits can be further extended to the higher number of bits and be used in the DSP filters. These are realized by using the software QCADesigner, the software used to realize the QCA circuits. By using the arrangement of the cells of the size in terms of nanometers the circuits are designed.
SVMVC: A Refinement to classical MVC for enhancing the Performance of web applications
Authors: Rajneesh Chaturvedi, Swati V. Chande, Amita Sharma
Published: December 2023

Web application architectures are established design patterns employed to structure the design of web applications. Typically, web application architecture is divided into distinct layers and components, each catering to various quality enhancement requirements. These design patterns are crucial for creating web applications that are scalable, maintainable, and well-organized. Among the most renowned and widely used design patterns for web applications is the Model-View-Controller (MVC) pattern. The MVC architecture's inherent attributes, such as reusability, testability, scalability, and separation of concerns, have played a pivotal role in its widespread adoption.

As performance stands out as a prominent quality indicator for web applications, this  paper introduces a novel refinement to the MVC architecture, with a primary focus on enhancing the performance of web applications.
Innovative Downstream Technology in Agriculture; A Case Study on Rice and Shallot Commodities
Authors: Zulkifli, Siti Bulkis, Imam Mujahidin Fahmid, Rahmadanih
Published: December 2023

The pace of downstream agricultural technology implementation by the government currently legs behind the needs of farmers and the advancement of modern science and knowledge. This study aims to1) analyze institutional patterns in the downstream application of innovative technology in agriculture, 2) examine farmers’ responses to downstream innovative technology, 3) identify the factors influencing the success of downstream innovative agricultural technology. The research was conducted in two districts across two provinces from December 2022 to September 2023, with case studies focusing on rice and shallot commodities. Data were collected through a survey of 240 randomly selected farmer respondents. Data analysis was performed qualitatively and descriptively, involving both formal and non-formal institutions from the central to regional levels. The results indicated that: 1) formal and non-formal institutional support from the central to regional levels significantly affected the downstream process of agricultural innovation; 2) farmers’ response to rice cultivation technology was more favorable than that to shallot cultivation technology; 3) internal factors such as age, education, farming experience, and land area, and external factors such as access to capital, technology, and transportation influenced the success of downstream agricultural innovation. In general, a deep understanding of these factors is crucial for designing more effective strategies to promote technology adoption among farmers. The government should consider the local characteristics of farmers in downstream innovation to increase production and productivity, thereby enhancing farmers’ economic income.
DEEP LEARNING FRAMEWORK FOR HUMAN ACTIVITY DETECTION BASED ON WIRELESS SENSORS.
Authors: G. ANANDHARAJ, G.Bharathi
Published: December 2023

Recognizing human athletic behaviors has grown in importance as a component of analysis during the last few years. For upcoming training, FPGA-based recognition has been built to perfectly predict human actions. Intelligent environments where human athletic movements may be automatically recognized are required to ensure the viability of such long-term athletic training monitoring systems. The system discussed here employs an Artificial Neural Network (ANN) based Field-Programmable Gate Array (FPGA). In order to infer human behavior from the data collected by a smart environment, machine learning algorithms must first be trained on annotated datasets. To effectively extract characteristics from unprocessed data and develop a machine learning model for anticipating an individual's movement, conventional signal processing techniques and domain knowledge are required. The purpose of this work is to show how a hybrid deep learning model may be applied to recognize human behavior. Convolutional neural networks and continuous neural networks, for example, are deep learning techniques that will extract the features and help with categorization. The proposed model forecasts human activity using wireless sensor data mining datasets. Accuracy, training loss, testing loss, the confusion matrix, and other metrics have all been used to evaluate the model's performance.
An analysis of gis and gps-enabled traffic violation management in bengaluru city traffic police, karnataka, india.
Authors: Vinayak  Nidasosi, R. N. Mangoli
Published: December 2023

The twenty-first century has also been dubbed the "technological era" because everything is powered by technology and even humans live with it. Geographical Information Systems (GIS)[1] and Global Positioning Systems (GPS)1, which we use in our daily lives, plays a crucial role in the maintained order in the society, so making this the Police Department is the primary institution for maintaining order in society. And the police department has two major actions includes pre-action and post-action  in the response to any violations, issues, public nuisance, anti-social behavior, and crime, among others. So with this in mind traffic management is also one of the phenomena under social order; a lack of attention to traffic management may lead to road accidents and other issues. Management of traffic violations is a tough task for the police officials to tackle and trace out manually, but at present the Karnataka State Police Department is fully fledged with technology, as a result of which the department now has E-Policing under the Karnataka Police-IT, with this discipline of geography as a professional discipline, by using GIS and GPS applications in traffic policing to prevent potential traffic violations and to tackle and trace out these issues.
Optimizing Machine Learning Models in Human Activity Recognition with the WISDM Dataset
Authors: M.Sridevi, Selvi.V
Published: December 2023

Human Activity Recognition (HAR) is a technology with significant potential, utilizing data from various devices like smartphones and cameras. It finds applications in daily activities such as driving, cleaning, and gaming, involving fundamental movements like standing, sitting, jogging, and typing. Accurate identification of these actions is crucial for effective human-computer interaction systems. This work incorporates a HAR module to extract valuable insights from data signals. It employs Machine Learning (ML) models to automatically detect human activities using raw data from Internet of Things wearable sensors, including innovative combinations like Adagrad and ELU within the MLP algorithm. The ML models' performance is evaluated using statistical metrics such as accuracy, precision, recall, and f1-score, and comparisons are made with existing models.
Heat Gneration on Three Dimensional Casson Nanofluid Motion with Arrhenius Activation Energy Effect Via Stretching Sheet
Authors: Adilakshmi Velivela, G. Venkata Ramana Reddy
Published: December 2023

The current study Arrhenius activation energy effect on 3D porous Casson nanofluid (NFs) motion via stretching sheet (SS) is explored in this study using numerical process based on Runge Kutta Fehlberg (R-K-F). To provide useful visions into the physical and dynamic examinations of this study, convective heat and mass boundary conditions are used. The established of nonlinear partial differential equations (PDEs) has been transported into ordinary differential equations (ODEs) by helping suitable similarity transformations. The translated ODEs are computed by help of shooting iterative approach. The outcomes of this study are validated with previous investigations, and get excellent agreements. The behaviour of different physical parameters is analysed. It is observed that, the heat transfer rate is high in presence of Activation energy for large values Prandtl number and mass transfer rate decline low in presence of Activation energy for numerical values of Lewis number.
Emerging Trends in Online Impulse Buying Behavior: A Bibliometric Analysis and Future Research Directions
Authors: M.Ruby Evangelin, A.Gokulakrishnan, P.Sasikumar
Published: December 2023

Online impulse buying behavior has become a rapidly growing area of research in the study of online consumer behavior over the past two decades. With increasing academic attention and publication opportunities, this paper presents a bibliometric review of the scientific literature in this field. The study examines 363 articles from the Scopus database, spanning the period from 2000 to 2023, to identify the most relevant and influential authors, countries, affiliations, highly cited documents, and commonly used keywords. Through bibliometric analysis, the study suggests specific future research agendas in online impulse buying behavior. This analysis provides valuable insights for researchers and practitioners, offering a roadmap to address key research gaps and emerging trends in this field. By understanding the major research streams and influential contributors, academics can direct their efforts toward critical areas of investigation, while practitioners can use the findings to formulate effective strategies for online retail and marketing. Overall, this study contributes to the understanding of the evolution of online impulse buying behavior research and its potential impact on consumer behavior. As the field continues to grow, it presents both challenges and opportunities for academics and practitioners alike. The bibliometric analysis serves as a foundation for further exploration and offers a comprehensive view of the research landscape, enabling scholars and industry professionals to make informed decisions and advancements in this dynamic domain.
Distribution network reconfiguration using improved colonial competition optimization algorithm
Authors: Aghil Salarpour MohamadMoradi
Published: December 2023

The implementation of a distribution network is generally aimed at increasing system efficiency, increasing the level of optimal operation, increasing the stability of the power grid, reducing blackouts, and increasing reliability. By providing general definitions of networks and the principles of optimal operation and reliability indicators and loss reduction in power systems, the general principles of network control and optimal operation are presented and finally, practical ideas for the optimal operation of power networks with The approach of increasing system reliability and maximum productivity of distributed production resources is presented. In the presence of a distribution network and by using appropriate control algorithms, it is possible to optimize the power network in different working conditions; After the occurrence of a disturbance in the network, the power system is exposed to instability. The network can restore the stability of the system by communicating critical conditions to the subscribers as well as rearranging the network structure and shut down the least number of subscribers. Implementation of a distribution network in general with the aim of increasing system efficiency, increasing the level of optimal exploitation, increasing the stability of the power grid, reducing outages and increasing reliability.
Growth and production of rice (oryza sativa l.) With several application doses of urea fertiliser and cow manure
Authors: Salwah, Rusnadi Padjung, Muhammad Irfan Said
Published: December 2023

Integration of fertilisation using organic and inorganic fertilisers is one of the efforts to increase rice growth and production. This study aims to evaluate and analyse the effect of urea fertiliser and cow manure application on the growth and production of rice plants. This study used a separate plot design with three groups. The main plot was the dose of urea fertiliser including 100 kg ha-1, 200 kg ha-1, and 300 kg ha-1. The subplots were doses of cow manure including 500 kg ha-1, 1000 kg ha-1, 1500 kg ha-1, 2000 kg ha-1, and 2500 kg ha-1. The research data were then analysed by means of variance with BNT test as a further test. The results showed that the interaction of urea 300 kg ha-1 and no manure on panicle length (23.28 cm), urea 100 kg ha-1 and 2000 kg ha-1 on panicle weight per plant (2.85 g), urea 200 kg ha-1 and 2500 kg ha-1 manure on the number of filled grains per panicle (101, 67 grains), urea 100 kg ha-1 and 2500 kg ha-1 manure on the percentage of empty grains per panicle (12.12%), and urea 200 kg ha-1 and 2500 kg ha-1 manure on the weight of 1000 seeds (26.87 g). The single treatment of urea dose, 200 kg ha-1, gave the best effect on chlorophyll a (234.55), chlorophyll b (96.04) and total chlorophyll (337.27). Based on the results of the study, it can be concluded that the application of urea fertiliser with cow manure has a positive impact on the growth of rice plants.