Volume 11 | Issue 8

 Abstract

It's no wonder that criminals would want to take advantage of the financial system by flooding it with counterfeit notes that seem very comparable to the genuine thing, given that bank cash is our country's greatest asset. When demonetization takes place, counterfeit banknotes flood the economy. A genuine banknote and a counterfeit one have numerous characteristics, making it difficult, if not impossible, to tell them apart without special equipment or training. It is a challenging task to distinguish real banknotes from fake ones. Therefore, a completely automated system is essential, and it must be available through tellers at banks and ATMs. Because counterfeit banknotes may now be made with such high quality, it is crucial that a reliable algorithm be created to evaluate whether or not a

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The Use of Machine Learning to Spot Counter feit Currency

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Evidence management is highly valued in the field of forensic science. In order to solve crimes and bring perpetrators to justice, evidence gathered at the site of the crime is essential. Therefore, it is essential to keep these goods protected from any kind of manipulation. Chain of custody is a method used to ensure that evidence is kept secure. If the chain if custody is broken, the evidence cannot be used in court, which might lead to an automatic dismissal of the proceeding. Because the standard practice for handling forensic evidence is so wasteful, moving toward a digital system is crucial. Blockchains are public, digitally distributed ledgers comprising transactions that have been signed cryptographically and divided into blocks. The Linux Foundation created Hyperledger Fabric, a blockchain platform designed specifically for enterprise use cases. Based on the concepts of Hyperledger Fabric, this study aimed to provide a framework for implementing Blockchain Technology into the criminal records administration system while maintaining the Chain of Custody.

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AN IMPLEMENTATION OF BLOCKCHAIN TECHNOLOGY IN FORENSIC EVIDENCE MANAGEMENT

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Among many types of web-based applications, real-time streaming footage has become the standard broadcast standard. In this paper, we investigate Amazon Prime Video, which is an online video-on-demand service that allows us to view sporting activities, motion pictures, and other events. Each component of the video that streams online is then further broken into various bit rate variants. The quantity of bits sent in a specific amount of time is known as the rate of transmission for videos. Utilizing the wireless network analysis programme Wire shark, we quantify the bit rates modulated throughput of Amazon Prime Video Streaming. The rate of modulation depends on a pair of factors, like traffic rate and video resolution; the latter is used to gauge a video's capacity and network capacity, which takes into account the higher bandwidth requirement, the better the quality must be.

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Wireshark, Amazon Prime, Bandwidth, Resolution, Streaming

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Satellite photos are widelyusedinfieldsincludingemergencymanagement,security,andenvironmentalmonitoring.Thesegoalscan'tbeachievedwithout the help of humans and the ability toproperlyidentifyobjects.Withsomanypossiblesearchspaces and so few analystson hand, automation is essential. However,owingtotheirfocusonaccuracyandprecision,conventionaltechniquestoidentifyitemsandcategorizationareconstrainedintheircapacitytodeliverasolution.Automatingthesestepsusingsupervised neural class ML algorithms hasshownsomesuccess.Thereissomeevidence that convolutional neural networks,akindofartificialneuralnetwork,mayenhancebothpictureidentificationandunderstanding. In this case, we use them tolearnhowtoidentifyartificialfeaturesinhigh-resolution,multispectralsatelliteimagery.Weprovideadeeplearningapproachtoclassifyingfeaturesor

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Classification of Satellite Images Using Deep Learning

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Congestioninbigcitiesisbecomingmoreproblematicas urban populations & automobileownership both grow. Everyone suffers inconvenient delays when traffic is backed up. motorists,but it does increase fuel consumption and pollution. Despite its apparent global prevalence, bigurbancentersare especially at risk. Therefore, it is becoming more vital to calculate trafficdensityinrealtimeinorder to optimize signal timing and manage traffic flow. The trafficcontroller plays a crucial role in the smooth flow of traffic. Therefore, there is an urgent need forenhanced traffic management to fulfill the expanding demands of the public. To measure trafficlevels, our system would utilize artificial intelligence and processing of images to examine livefeeds via cameras installed at crossings. The algorithm for adjusting the timing of traffic lights inresponse to traffic volumes is also highlighted in an effort to make travel more efficient forpassengers and reduce pollution.

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MANAGINGS TOP AND GO TRAFFIC WITH AI

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With the increasing adoption of cloud computing, data security has become a significant concern for organizations and individuals. In this context, efficient and secure keyword search techniques are essential to retrieve relevant information from encrypted data stored in the cloud. This paper proposes an ensemble multiple-keyword search approach with enhanced data security in a cloud environment. The proposed system combines the strengths of multiple keyword search techniques to achieve better search accuracy and efficiency. The ensemble method leverages various algorithms, such as inverted index, bloom filters, and homomorphic encryption, to overcome the limitations of individual techniques and provide robust search capabilities. The proposed approach employs encryption mechanisms to protect sensitive information to ensure data security. The data is encrypted before being uploaded to the cloud, ensuring only authorized users can access and retrieve the information. Homomorphic encryption enables the cloud server to perform search operations on the encrypted data without decrypting it, preserving the privacy of the stored information.

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Cloud computing, Symmetric-key, homomorphic, and Attribute-based Encryption (ABE).

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Grecordingsoftenincludeseveralartifactsofvaryingtypes,magnitudes,anddurations,whichmakesaccurateautomatedorhumandiagnosischallenging, if not impossible. The real ECGsignal, which has been tainted by artifacts,cannotberestoredusingany oftheECGdenoising algorithms established by variousresearchers.WeofferanewmethodforblindECGrecoveryutilizingloopadversarialgenerativenetworks(Loop),where reliability of signals may be enhancedtothelevelofclinicalECGdespiteanumberofartifactsofvariedformsandintensities.Byusingagenerativebrainmodel to improve restoration performance,weprovidefullyoperational1DCycle-GANs. The suggested method (CPSC-2020)wasrigorouslytestedusingoneofthebiggestbaselineelectrocardiogram(ECG)dataset ever produced as a component of theChinesePhysiologyDataChallenge.Agroupofcardiologistsexaminedthepatient toensurethequalityanduseoftherecovered ECG, especially in establishing anaccurate arrhythmias diagnosis. This studyprovesthatdegradedECGsignalscanberestoredtoclinicallyacceptablelevels,making it a watershed moment in the field ofECGrestoration.

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Cycle-GANs for Blind Electrocardiogram Restoration

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Success in digital marketing, an online business, depends on solving cyberspace security issues. More people are choosing to work online and launch technology and digital businesses as the Digital Age develops. One well-known example is marketing. In recent years, a brand-new marketing genre called "digital marketing" has evolved. Given that it may help practically every organisation, digital marketing is a lucrative and important industry. They must be knowledgeable about how to safeguard their businesses against cybercrime as more people enter or develop in digital marketing. Cybercrime can involve the theft, misuse, and tampering of personal information and internet accounts. This article examines ways to protect a digital marketing company's success in light of the ongoing cyber threats. Data was gathered from people interested in digital marketing using online websites. There are opportunities to improve the efficiency and safety of financial transactions by integrating digital technology into the operation of national financial systems.

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Digital marketing, Cyber security, Digital fraud, digital economy, financial security

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E-commerce App with AI Voice Assistant

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E-commerce, AI Voice Assistant, Voice Search, Mobile application

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The nexus of legislative issues and wrongdoing has consistently made the genuine reason for legislative issues unessential. In the foundations of decentralization of governmental issues, fundamentally in the get together races, panchayat decisions, civil races, applicants with expanding criminal picture have clarified that governmental issues (battle for power) was accomplished by involving popularity based implies for the government assistance of its residents. It is known that, presently the rising number of up-and-comers and pioneers with criminal picture, even crook picture, utilize political power just for their futile advantages. Heads of any ideological group don't focus on foster incredible political qualities and standards of citizenship. They don't advance positive energy and country building responsibility. Legislative issues or the utilization of political power is the same old thing. The crazy circumstance is that the most common way of expanding criminalization of governmental issues in Bihar has prompted the politicization of wrongdoing instead of criminalization of legislative issues and has turned into a noticeable element of the legislative issues culture of the present decision class. Criminalization of governmental issues is an intense issue in Bihar, which has proactively arrived at perilous levels. This evil of criminalization of governmental issues draws in unique consideration of individuals as the subject spins around the personal stakes of all party legislators on the grounds that such individuals can never trust that lawmakers will show any drive to correct this fiendishness. In this exploration paper, an endeavor has been made to break down the rising predominance of hoodlums in Bihar governmental issues and its healing measures

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Criminal, Criminalisation, Politics, Winn ability, Bihar

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Many fuels are utilized in households for cooking. These fuels are categorized as solid and clean eco-friendly sources. Biogas generation is an example of waste-to-energy conversion. Biogas is generated through the conversion of organic waste such as kitchen waste, animal waste, and agricultural residue (rubber wash) generated in households/ small farms through the bio-methanation process. Different types of biogas plants are installed and adopted in households. There are 2 types that are widely adopted and installed, (i) Fixed dome and (ii) Floating drum. The study area was the Kanyakumari District of Tamil Nadu. The biogas beneficiaries list was collected from authentic sources such as District Rural Development Agencies, NGOs, and Turn-key agents (People/Organisations who help users adopt biogas at home). The census method was adopted to identify and interview 270 biogas users in the district with the help of a detailed questionnaire. Biogas is an excellent choice of fuel for cooking purposes. Results from the study are that, of three different raw materials-based biogas plants, agriculture residue (rubber wash) is more efficient in which quantity of gas generated is higher. Likewise, fixed dome type of biogas plant generates more gas in quantity. The study with a micro perspective recommends more rubber wash-based fixed dome-type biogas plants to be installed and adopted in higher numbers in the study area.

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Biogas, Waste to Energy Conversion (WTE), Raw Materials, Type of biogas plants, Households

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Modern agriculture faces the challenge of efficiently predicting crop yields to ensure food security and resource optimization. This research focuses on using machine learning and data analysis to improve the accuracy of crop yield prediction in modern agriculture. The study uses a comprehensive dataset containing geographical, climatic, and agronomic attributes. The objectives include data preprocessing, feature transformation, algorithm selection, and model evaluation. The dataset comprises 28,242 entries with crop yield, climate factors, and location details. Initial exploration reveals correlations and trends, and data cleaning procedures are implemented. The analysis provides insights into crop production by region and type. Various machine learning models, including Linear Regression, Lasso, Ridge, K-Nearest Neighbors, and Decision Tree Regression, are employed and evaluated. Decision Tree Regression performs well with a high R-squared score and low mean squared error. The model's practical application is demonstrated through a hypothetical yield prediction scenario, showcasing its potential for aiding agricultural decision-making. The study concludes that combining machine learning and data analysis can enhance crop yield prediction accuracy, enabling informed decisions and sustainable food production.

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Crop yield prediction, machine learning, data analysis, agricultural productivity, predictive modeling.

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Abstract : As we know that firewall are widely emplaced in security apparatus to ensure the security of private networks in most organizations. Basically effectiveness of firewall depends on the quality of policy and its configuration. Nevertheless, the designing and managing its policies are untrustworthy because of its complex nature of configuration as well as the lack of systematic analysis apparatus and tools. This paper represents an anomaly management framework and visualization approach of firewall. We signify the possibility and relevancy of framework by a proof of concept prototype of a visualization which is based on firewall policy analysis tool known as firewall Anomaly Management Environment (FAME). We also introduce FIREMAN, a immobile analysis toolkit for firewall modeling and analysis. By treating firewall configurations as specialized programs.

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Keywords: - firewall policies, anomaly management, visualization tool.

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For human existence as well as the health of our environment, water is a vital component. Without water, life cannot exist on earth; humans and other living things suffer and die; agricultural activities cannot be initiated; and industries cannot be maintained. All things depend on water, and it may be found in nature in a wide range of environments, including the fog, clouds, ocean, snow, rivers, rain, and lakes. The petrogenic PAHs are mainly Naphthalene , Fluorene , Phenanthrene , Dibenzothiophene and Acenaphthylene and pyrogenic PHAs are Anthracene, , Fluoranthene , Benzo(a)anthracene , Benzo(a)anthracene and , pyrene . The study of petrogenic and pyrogenic sources are carried out in Kolkata , Kanpur and Gazipur district

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PAHs , Ganga , petrogenic , pyrogenic , Kanpur , Gazipur , Kolkata , chrysene , India , Volumetric flasks etc

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THE HEALTH STATUS AND HEALTH-SEEKING BEHAVIOUR OF RURAL WOMEN IN COSTAL KARNATAKA

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THE HEALTH STATUS AND HEALTH-SEEKING BEHAVIOUR OF RURAL WOMEN IN COSTAL KARNATAKA

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Purpose: To measure service quality performance of public and private hospitals using extended HEALTHQUAL dimensions in the Surat region. Design: This research design is descriptive using a non-probability convenience sampling method. Survey was conducted on a sample of 200 consumers through structured questionnaire using extended HEALTHQUAL dimensions. Findings:Dimensions are found out in which particular type of hospital is doing well. Also the dimension in which both kinds if banks needs immediate focus are also found out and listed. Research limitations / implications: With this study, researchers tried to measure the performance of each type of hospital with different dimensions. Contribution and value-add: This study would help to understand customer perceptions towards performance of hospitals. Because of the intangibility of services, measurement and differentiation are very difficult. The research study attempts to develop appropriate dimensions and scales to measure the performance of the health care industry in India.

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HEALTHQUAL, Government and Private hospitals

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Child marriage persists globally, hindering SDG achievement. Target 5.3 under SDG 5 seeks to end harmful practices like child marriage by 2030. Despite laws, 1 in 5 girls marry before 18. Child Marriage Prevention Act (1929) reflects past struggles. Education empowers girls, breaking poverty cycles. Focus on under 18s aids family planning and society’s development.

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Awareness, Child Marriage, Child Abuse,Health and Well being, Gender Equality

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This research delves into the dynamic realm of online travel services, focusing on MakeMyTrip, a prominent online travel portal catering to a global audience. The study explores the platform's multifaceted services, its growing popularity, and its role as a preferred choice for modern travellers. This research methodology systematically addresses the research problem, involving data collection methods, analysis procedures, and tools such as simple percentage, weighted average, and chi-square analyses. The sample size of 123 respondents was obtained via Google Forms using convenient sampling, during the period of January 2023 to April 2023. The study's scope encompasses Coimbatore's customer base, aiming to comprehensively explore preferences for MakeMyTrip and contribute to a holistic understanding of the subject.

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Online travel portal, MakeMyTrip, Customer preferences, User experience, Travel industry.

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This paper consists of the work undertaken of the study of dielectric parameter of non-aqueous solution of Tropine-Chloroform for various concentrations. The time domain reflectometry technique is used for the study in the frequency range from 10 MHz to 30 GHz. The relaxation time (?), The static dielectric constant (??), dielectric constant at higher frequency (??) of mixture of Tropine with Chloroform have evaluated at 250 c

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Alkaloids, Dielectric constant, Relaxation time& TDR

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This paper focuses on the analysis of a first-order non-linear differential equation model for HIV infection in CD4+ T cells. The objective is to solve this model analytically using the Taylor series method (TSM). The TSM offers a straightforward way to determine the components of the series. As the order of approximation increases, the accuracy of the method also improves. By comparing the analytical expression with numerical simulations, we establish the superior accuracy and reliability of the Taylor series method's approximate solution. Additionally, we leverage Python's graphical capabilities to visually represent the HIV infection model.

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HIV infection of CD4+ T-cells, Taylor series method (TSM), First order non-linear differential equation, Mathematical modelling, Numerical simulation, Python-jupyter.

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