Volume 11 | Issue 5

 Abstract

Bitumen concrete, commonly known as asphalt, is widely used in the construction industry for various applications such as road pavements, parking lots, and airport runways. The increasing demand for bitumen concrete and growing concerns about environmental sustainability have stimulated research efforts to incorporate waste materials into bituminous mixes. This paper aims to provide a comprehensive experimentation of tyre rubber waste in bitumen concrete ranging from 5 to 10 %. The test conducted is for Stability. The result shows that the case having waste tyre rubber having 10 % are showing better performance as compared to other cases. It has been concluded that the higher percentage of tyre rubber incorporated in bitumen will have better stability

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Bitumen, Stability, Tyre Rubber

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In the field of digital communication, the security of information is crucial that must be taken into consideration. Image steganography is defined as hiding any data inside an image. The proposed technique provides a comprehensive review of LSB-Based image steganography. There are many techniques in steganography used to conceal the information, Least Significant method (LSB) is one such technique which is used to hide data. The LSB technique involves embedding information within the least significant bit of the pixels of an image, making it difficult for the human eyes to detect the hidden information. The proposed method improves the embedding efficiency and reduces the visual distortion of the stego image and the proposed algorithm is applied in various applications that require secure communication of confidential information.

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Steganography, Cover Image, Secret Image, LSB method, Stego-key, PSNR and MSE

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In the modern, technologically advanced world, the Internet of Things (IoT) has gained popularity. a robust cloud computing architecture, supported by a seamless integration of sensors and This "network of networks of autonomous objects" is becoming a reality thanks to actuators working with the environment around us. The Internet of Things is growing in a variety of sectors, including smart wearables, smart cities, home life, and business. By 2020, the Internet of Things will have 26 billion deployed devices, predicts Gartner Inc. In-demand IoT applications include smart security solutions, smart home automation, smart health care, smart wearables, etc. In the near future, we anticipate seeing IoT applications in smart power grids and municipal transportation systems. In addition to discussing the effects of the IoT on our daily lives, this paper provides a brief review of various IoT developments. As well in the context of the IoT, addresses the significance of cloud computing, autonomous control, and artificial intelligence. In order to properly use IoT enabling technologies, the Internet, wireless sensors and actuators, and distributed computing must be coordinated.

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Smart Devices , Wireless Network, The Internet of Things, Cloud Computing, Embedded Systems, Machine Learning, Automation

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:- Agriculture is the pillar of the Indian economy and more than 50% of India's population are dependent on agriculture for their survival. Variations in weather, climate, and other such environmental conditions have become a major risk for the healthy existence of agriculture. Machine learning (ML) plays a significant role as it has decision support tool for Crop Yield Prediction (CYP) including supporting decisions on what crops to grow and what to do during the growing season of the crops. Agriculture is the pillar of the Indian economy and more than 50% of India's population are dependent on agriculture for their survival. Variations in weather, climate, and other such environmental conditions have become a major risk for the healthy existence of agriculture. Machine learning (ML) plays a significant role as it has a decision support tool for Crop Yield Prediction (CYP) including supporting decisions on what crops to grow and what to do during the growing season of the crops.

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:- Precision Agriculture, Machine learning, Crop prediction, Supervised Learning, Whether Forecast,Python,Effective farming

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The project's main objective is to design and implement automatic problem detection and location identification in transmission lines, as well as monitoring using the internet of things. Two single phase 230V transmission lines are being built for demonstration purposes, with continuous monitoring of the microcontroller's fault sensing. A sophisticated GSM-based defect detection and localization system was deployed to quickly and accurately pinpoint the precise spot where the problem had developed. The system provides precise fault location information, significantly cutting down on the time required to locate a flaw.

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Location Identification, Continues Monitoring, Transmission Lines, Precise, Location, Line, Fault Detection, GSM.

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- This project describe the concept, design and prototype of magnetic transmission system. Magnetic transmission become interesting area for research in last year. Several transmission have been developed all these transmission system required maintenance, lubrication . Time and money required to maintain these transmission system. We research on contactless transmission system in this transmission system we use neodymium magnets. These magnets are 12 times stronger than normal speaker magnets. So there is no contact between two gears and motion transfer by magnetic effect. So no longer maintenance required as lubrication, and no wear of gears.

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magnetic transmission, Contactless transmission

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Non-performing assets are a key source of worry for Indian banks. NPAs are a reflection of a bank's performance. A high level of Non-Performing Assets (NPAs) indicates a significant likelihood of a big number of credit defaults, which affects bank profitability and net worth. The increase in Non-Performing Assets necessitates the use of provisions, which affects total earnings and shareholder value. The topic of non-performing assets has been extensively explored in India's financial sector. The problem of Non-Performing Assets (NPAs) affects not only banks but the entire economy. In truth, the high level of Non-Performing Assets (NPAs) in Indian banks is merely a reflection of the industry's and trade's state of health. In public sector banks, the number of Non-Performing Assets (NPAs) is larger. NPAs must be scheduled in order to increase efficiency and profitability. The government has taken a number of efforts to minimize Non Performing Assets (NPAs). It is difficult to have no Non Performing Assets (NPAs). However, Indian banks can attempt to compete with foreign banks in order to preserve international standards. The problem of Non-Performing Assets (NPAs) losses and poorer profitability, as well as liability mismatch in banks and the financial sector, is dependent on how various risks are managed in their businesses. In this study an attempt is made to identify the challenges faced by Indian banks in COVID-19 era. The Secondary data has been taken from various sources to identify such issues and challenges further suggestions have been made to overcome through these challenges.

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Non-Performing Assets: A study on NPA in Indian banks and Issues and challenges.

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A magnetic coupling is a coupling that transfers torque from one shaft to another shaft, by using a magnetic field rather than a physical mechanical connection. Magnetic shaft couplings are most often used for liquid pumps and propeller systems, since a static, physical barrier can be placed between the two shafts to separate the fluid from the motor operating in air. Magnetic shaft couplings preclude the use of shaft seals, which eventually wear out and fail from the sliding of two surfaces against each another. Some diver propulsion vehicles and remotely operated underwater vehicles use magnetic coupling to transfer torque from the electric motor to the propeller. Magnetic gearing is also being explored for use in utility scale wind turbines as a means of enhancing reliability. The magnetic coupling has several advantages over a traditional stuffing box.

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Magnetic coupling, permanent magnets, power transmission efficiency etc.

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The current study deals with the isolation of L-Asparaginase enzyme from bacterial strains, through serial diluting the soil samples from Coimbatore, India. A total of 15 bacterial strains were isolated from the soil samples. The bacterial strains were subjected to primary screening where the positive strains are known to produce pink color zone around the colonies after incubation for 48 hrs on M9 media. Only 5 isolates were positive for producing L-Asparaginase. The positive strains were subjected to morphological studies, cultural characteristics and biochemical tests. The strains were subjected to secondary screening by submerged fermentation and the crude enzyme activity was determined by Nesselerization method, the highest enzyme activity was found to be 1.902 U/ml (B-I-13) and estimation of protein was determined by using Lowry's method. The organism which produced highest enzyme activity was identified by 16S rRNA sequencing method and phylogenetic tree was constructed. The isolated organism was found to be Bacillus subtilis which can be used to produce L-Asparaginase.

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L-Asparaginase, Bacillus subtilis, acute lymphoblastic leukemia, acrylamide.

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Vidanga is precious medicinal plant from myrsinaceae family. Having antihelminthic and antiparasotic property.It is widely used against intestinal worm infestation including round worms, thread worms, and tapeworms. This herb is very rejuvenating that provides good health and energy to body. Rajnighantu describe Vidanga with light properties, pungent taste, and hot potency. It used to make balance between vata and kapha. Vidanga is very useful to improve anorexia and digestive fire. It reduces symptoms like nausea, vomiting, flatulence, and abdominal pain. Vidanga is commonly used as krimighna (Antihelminthic), kushtaghana (skin disorder) ,Udar rogahar, to promote growth in children. The fruit of the plant is major ingredient of ayurvedic remedy prescribed for krimiroga and other skin infections. There is many references for the various formations of Vidanga like Vidanga churn, Vidanga loha,Vidangarishta which are widely used in general practice.

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Vidanga, Embelia ribes Burm.f, Krimighna, Medicinal uses.

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Wedelia chinensis Merrill (Syn. Wedelia calendulaceae, Solidogo chinensis) (Asteraceae, Sunflower family) is a small much branched annual herb, commonly known as "Pilabhangara" or "Bringraj" in hindi. Wedelia in chinese, Pitabhamga, Pitabhmgaraj in Sanskrit. Wedelia chinensis is a tender, spreding and hairy herb, with the branches usually less than 50cm long.The binding affinity and interactions with amino acids of phytochemicals were evaluated. Target protein protein homology modeling, protein structure validation, and energy minimization were all completed. A comparative in-silico docking analysis with the standard drug was conducted using phytochemicals that had been mentioned in the literature as having properties related to Alzheimer's activities. These phytochemicals were studied for their absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties and those that passed ADMET filters. Using AutoDock Vina, a preliminary docking study was performed, then AutoDock 4.2.6 and SwissDock were used to validate the results.

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Wedelia chinensis , Standard caffeine, Molecular Docking, PyRx Vina auto dock, Chemsketch, ADMET Prediction.

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The primary purpose of this study was to analysis the impact of high-performance HR practices on employee performance and job satisfaction. This is empirical research design. The population for the study will be HR managers and employees working in the service industries of Gwalior city. The sample size of the study will be 80 employees working in the service industries of Gwalior city. A structured questionnaire was developed for gathering data from the respondents.

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HR Practices, Job Satisfaction, Employee Performance, Service, OCB

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Ocular pathology detection from fundus images presents an important challenge on health care. Identifying ocular pathology from fundus images is a significant difficulty for the medical field. The existence of lesions can be used to determine the severity stages of each pathology. Morphological characteristics define each lesion. Additionally, several lesions with various diseases share characteristics. We see that a patient may experience multiple diseases at once. As a result, the multi-class classification and intricate resolution approach for eye pathology detection are presented. There are several techniques for detecting ocular diseases in fundus imaging. Due to their ability to configure the network with respect to the detection objective, deep learning-based approaches are distinguished by higher performance detection. This study suggests a deep learning-based survey of eye disease screening techniques. First, we research the pathology classification or lesion segmentation techniques that are currently in use. Following that, we extract the fundamental processing processes and evaluate the suggested neural network topologies. In the following section, we define the hardware and software environment needed to use the deep learning architecture. After that, we investigate the experimentation approaches used to assess the techniques and databases utilised throughout either the training or testing phases. Additionally presented and discussed are the execution timings and detection performance ratios.

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Ocular diseases, Fundus images, Age-related macular degeneration (AMD), Glaucoma, Diabetic retinopathy, Macula

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 Abstract

Traditional EVM is a robust device used for casting votes. Due to its stand-alone working nature, it cannot be hacked. But it doesn't content voter data due to which duplication of votes become serious concern. A manual checking of voter information is required to do by poling officer and their assistants which can cause error. A person can re-register his/her name in voting list from different state of India (if they migrated) without noticing to domicile state to remove names from previous voting lists. This cause voter duplication. Various studies on voting have been conducted which focuses more on online voting those cannot be trusted 100 percent. So, we developed a more secure and simple solution that can be integrated with traditional EVM to prevent duplication i.e., Bogus Voting. With the help of voter database, we are able to achieve accurate results on producing 100 percent accurate election results on small scale and can be scale up at larger level. The FUID SVEM lives to the fundamental principal of democracy that is 'One Voter One Vote' for Lok Sabha (Lower House of People) and Vidhan Sabha (Legislative Assembly) on two parameters which is Fingerprint and Unique ID. Digital verification of voter avoids error and only authentic voter gets verified and can cast his/her vote. All above mentioned things can be achieved only if accurate voter data is registered in centralized database and later distributed according to constituency to maintain proper stress of work force and EVM. This revolution will not just remove duplicate voters but also reduce election time and save cost with 100 percent accurate results.

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FUID, SEVM, PO, VC, VSDU

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Data production for transmission using any form of multimedia, including digital images, text, music, and video, is becoming more and more intriguing. Numerous techniques, including cryptography, are employed to maintain the secrecy, integrity, and confidentiality of sensitive information as well as to prevent unauthorised access. By transforming the original data into cypher data, cryptography protects it from being decrypted or altered when it is received by the recipient. In this study, we employed Arnold Cat Mapping to use confusion schemes to jumble the pixel coordinates of the coloured images. By altering the grey values of the image pixels using the traditional techniques for encrypting and decrypting digital colour images, the shuffling mechanism and diffusion mechanism are coupled to encrypt the scrambled image. The suggested techniques used traditional encryption systems like the hill cypher method and the Vegner substitution cypher system. We discovered that the hill cypher exhibits much greater security and fast speed than other approaches from all experimental and analysis methodologies utilised on some colour images to test the suggested image encryption and decryption methods. Additionally, the cypher pictures' unpredictability was increased, hiding the natural characteristics of the original images.

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Encryption,Decryption

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This study investigates the impact of macroeconomic factors on credit spreads in the Indian debt market through a multiple regression analysis. The research findings indicate that Repo rate, BSE Index, and Volume have a significant effect on the credit spread. The findings of this research can inform investors and financial professionals about the factors that influence credit spreads in the Indian debt market.

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Credit Spread, Indian debt market ,Macro economic Factors ,Yield, Regression Analysis

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Biometric human footprint detection refers to the process of identifying and analyzing unique characteristics present in the footprints of individuals for the purpose of identification and recognition. Footprints, as biometric traits, offer advantages such as being non-invasive, difficult to counterfeit, and relatively stable over time. This paper presents a comprehensive review of the existing methodologies and technologies employed in biometric human footprint detection. The review encompasses various aspects, including data acquisition techniques, feature extraction methods, and recognition algorithms. Additionally, the challenges associated with footprint analysis, such as variations due to different surfaces, foot positions, and deformations, are discussed. The study highlights the potential applications of biometric footprint detection across several domains, including forensic investigations, security systems, and healthcare. Furthermore, the paper discusses the advantages and limitations of using footprints as a biometric modality, comparing them with other commonly used biometric identifiers. Various case studies and experimental results are presented to illustrate the performance and accuracy of different footprint detection approaches. The analysis includes metrics such as false acceptance rate (FAR), false rejection rate (FRR), and receiver operating characteristic (ROC) curves, providing insights into the effectiveness and reliability of the proposed techniques.

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Biometrics, Footprint analysis, Human identification, Footprint recognition, False acceptance rate (FAR), False rejection rate (FRR), Inception V3

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The Real-Time Bus Tracking System is an innovative solution designed to enhance the efficiency and convenience of public transportation. This system utilizes advanced technologies such as GPS and mobile communication to provide real-time updates on bus locations, thereby allowing commuters to track buses and plan their journeys more effectively. By accessing the system through a user-friendly mobile application or web interface, passengers can view accurate arrival times, monitor bus routes, and receive alerts about delays or changes in schedules. Furthermore, transit authorities can utilize the collected data to optimize bus operations, improve service reliability, and make informed decisions regarding route planning and resource allocation. The Real-Time Bus Tracking System not only benefits passengers by reducing waiting times and enhancing travel experiences, but also contributes to a more sustainable and efficient public transportation network overall.

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internet of things, live bus tracking ,RFID Tracker

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 Abstract

Cholesterol detection and stroke prediction are crucial tasks in healthcare for early diagnosis and prevention of cardiovascular diseases. In this study, we propose a deep learning approach for cholesterol detection and stroke prediction using Fully Convolutional Network (FCN), ResNet18, and ResNet151 architectures. For cholesterol detection, we utilize a FCN model trained on a large dataset of medical images. The FCN model enables pixel-level analysis and segmentation, allowing accurate identification of regions associated with cholesterol deposition. The model is trained using annotated images, and the resulting cholesterol maps can aid in the diagnosis and assessment of cardiovascular risk. For stroke prediction, we employ transfer learning with the ResNet18 and ResNet151 models pre-trained on large-scale image datasets. These models have demonstrated excellent performance in image classification tasks. By fine-tuning the pre-trained models on a stroke dataset, we aim to leverage their learned features for stroke prediction. The models are trained on a combination of clinical data, such as patient demographics, medical history, and laboratory results. To evaluate the proposed approach, extensive experiments are conducted using a diverse dataset comprising medical images and patient records. The performance of the models is assessed in terms of accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC-ROC). Preliminary results show promising performance for both cholesterol detection and stroke prediction tasks. The FCN model achieves high accuracy in identifying cholesterol deposition regions, aiding in the early detection of cardiovascular risks. The ResNet18 and ResNet151 models exhibit strong predictive capabilities for stroke, leveraging their ability to capture complex features from the clinical data. The results of our experiments demonstrate outstanding performance with accuracy scores of 98%, 98.4%, and 99.6% for the FCN, ResNet18, and ResNet151 models respectively.

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Cholesterol Detection, Stroke Prediction, FCN, Resnet18, Resnet151, Cardiovascular Diseases, Transfer Learning, Fine-Tuning

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This paper examines the interconnectedness between housing and transportation, recognizing them as two vital components of urban and regional systems. Housing and transportation are inextricably linked, as the availability, affordability, and accessibility of housing directly impact transportation patterns and choices, and conversely, transportation infrastructure influences housing location decisions. The paper highlights key aspects and challenges associated with housing and transportation, and emphasizes the need for integrated and sustainable planning approaches to address these complex issues. The paper begins by discussing the significance of housing and transportation in shaping the quality of life for individuals and communities. Adequate and affordable housing options are essential for social well-being, while efficient transportation systems enable accessibility to employment, education, healthcare, and other essential services. However, the paper recognizes the existing disparities in housing affordability, availability, and quality, which often exacerbate social and economic inequalities. Similarly, transportation infrastructure deficiencies, traffic congestion, and limited mobility options present additional challenges for communities worldwide. Next, the paper explores the intricate relationship between housing and transportation choices. Housing location decisions directly influence transportation modes and commuting patterns. Proximity to transportation hubs, such as public transit stations, impacts the feasibility and attractiveness of alternative transportation options, including walking, cycling, and public transit. Conversely, transportation infrastructure development and policies affect housing development patterns, with transit-oriented development and mixed-use zoning encouraging compact, walkable communities. Furthermore, the paper addresses the environmental implications of housing and transportation systems. The increased energy consumption and greenhouse gas emissions associated with housing and transportation contribute significantly to climate change. Sustainable solutions, such as energy-efficient housing designs, mixed-use developments, and the promotion of public transit and active transportation modes, are crucial for mitigating environmental impacts and fostering greener, more resilient communities. Finally, the paper emphasizes the need for integrated planning and policy approaches to address housing and transportation challenges effectively. Collaboration between urban planners, policymakers, transportation agencies, and housing organizations is essential for developing comprehensive strategies that align housing and transportation goals. This includes promoting affordable housing near transit corridors, implementing transit-oriented development policies, improving infrastructure connectivity, and integrating land use and transportation planning. In conclusion, this paper highlights the intricate relationship between housing and transportation and the importance of adopting integrated and sustainable approaches. Addressing housing affordability, accessibility, and quality alongside transportation infrastructure development is critical for creating vibrant, equitable, and environmentally sustainable communities. By recognizing and prioritizing the interplay between housing and transportation, policymakers and planners can work towards achieving more livable, connected, and resilient cities and regions. KEY WORDS: HOUSING, TRANSPORTATION, SOCIETY, INCLUSIVITY, INTEGRATION.

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 Keywords

Housing, Transportation, Social issues, Inclusivity, Integration

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