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The work aims to develop and comprehensively analyze an advanced overcurrent relay system for protecting power transmission networks. Overcurrent relays are critical components used either as main protection relays or as backup protection relays in the power transmission protection system. The primary function of these relays is to trip and disconnect the faulty circuit whenever the current exceeds a pre-defined threshold limit or pre-set current value. Ensuring the safety and reliability of electrical power systems heavily relies on the accuracy and performance evaluation of overcurrent relays. As a result, the design and simulation evaluation are conducted using the powerful MATLAB/Simulink platform. This paper presents an in-depth investigation into the design and performance assessment of an overcurrent relay, utilizing the MATLAB/Simulink simulation environment. By evaluating its effectiveness under various fault scenarios, including L-G (Line-to-Ground), L-L-G (Line-to-Line-Ground), and L-L-L-G (Line-to-Line-to-Line-Ground) faults with varying fault locations, the relay’s accuracy, selectivity, and response speed are comprehensively examined.

Our reliance on electronics, a cornerstone of modern life, comes at a cost. The relentless pace of technological advancement generates mountains of discarded devices, creating the growing problem of electronic waste. This E-waste, if improperly disposed of, can contaminate landfills and release harmful materials into the environment. This study investigates a potential solution: using a portion of e-waste in place of fine aggregate. To improve overall performance, we also incorporate mineral admixtures. Our research aims to understand how both the amount of e-waste and the specific mineral admixtures used influence the final properties of the concrete. We systematically replaced the fine aggregate with e-waste at varying percentages (0%, 10%, 20%, and 30%) and meticulously analyzed the resulting effects. The study identifies 10% e-waste replacement as the optimal level for achieving desirable properties in M20 grade concrete, a commonly used strength classification. This approach offers a two-fold benefit. It tackles the e- waste crisis by providing a sustainable disposal option, and it potentially reduces the construction industry's reliance on virgin resources like natural sand, contributing to a more sustainable future.

Every year, trade winds periodically transport Saharan-Sahelian dust westwards across the Atlantic Ocean towards North America during the months of May-September. These intercontinental events episodically increase airborne particulate matter (PM) concentrations in parts of Texas potentially endangering public health and compliance with National Ambient Air Quality Standards. This article reviews unique methods we developed to identify and quantify African dust episodes when superposed on industrial emissions in Houston, Texas. We measured ~50 elements in PM2.5 and PM10 including trace metals and used them as inputs to a receptor model. This approach accurately tracked foreign-born aeolian aerosols demonstrating the validity of our procedure, which uses rare earth elements and transition metals to discriminate local and distal sources of dust. Our procedures can be directly extended to discriminate and quantify Asian dust mixed with anthropogenic PM in population centres without loss of generality if unique geochemical signatures for source and sink regions can be established.

During the design phase of engineering networks, a critical issue remains the selection of pipe diameters that minimize capital investments for transporting the heat carrier from the heat source to the consumers. Object of study: a pressurized pipeline of circular cross-section with a moving heat carrier. Subject of study: total monetary costs for transporting the heat carrier as a function of the chosen pipeline diameter. Objective of study: to determine the pipe diameter that achieves maximum cost savings for transporting the heat carrier under given design conditions. Research methods: theory of hydraulic calculation for circular cross-section pipelines and theory of heat transfer through a single-layer cylindrical wall under steady-state conditions. Research results: using an example from a centralized heating system pipeline section, it was established that for a mass flow rate of the heat carrier equal to 32.9 t/h, the optimal pipe size would be 76×3 mm (nominal diameter 70 mm). Under current tariffs for thermal energy (24.82 USD/Gcal) and electrical energy (6.65 USD/(MW⋅h)), the total monetary costs for transporting the heat carrier over a heating season would be 56.28 USD per 1 running meter of pipeline. In comparison, with a nominal diameter of 50 mm, the total costs amounted to 90.37 USD; with a diameter of 80 mm, the costs were 63.29 USD. The developed method for hydraulic design calculations is universal and can be applied in the design of engineering networks where the working medium is a moving heat carrier (steam or hot water).

This research investigates the efficacy of integrated Pest management (IPM) techniques in cucumber cultivation, focusing at the utilization of natural control strategies to reduce pest-associated losses and improve crop productivity. No matter the growing emphasis on biological strategies, their adoption remains limited because of several challenges, including market pressures, regulatory hurdles, and pest resistance. But, through promoting awareness, expertise, and collaboration among organic and IPM communities, barriers to adoption may be overcome. The study underscores the importance of monetary useful resource for natural control and advocates for its integration into sustainable crop protection practices. Through a comparative evaluation of IPM and non-IPM farming processes, the studies highlight the fee implications and profitability of implementing biological control measures in cucumber production. Findings reveal that even as IPM farmers incur higher initial expenses, they reap advanced internet returns and benefit-cost ratios in comparison to non-IPM counterparts, demonstrating the monetary viability and sustainability of IPM strategies in cucumber farming.

This research delves into the multifaceted repercussions of climate change on ecosystems and communities, employing a comprehensive assessment of empirical statistics and scholarly literature. Through meticulous analysis, it reveals that biodiversity loss, changes in hydrological patterns, and shifts in species distribution are resulting in huge ecological transformations. Considerably, the study finds that global warming has led to a amazing 8,532-unit reduction in deciduous forests and a remarkable 12,052-unit increase in shrublands from 1985 to 2019. Moreover, the increament in open water bodies by means of 1,151 units underscores the dynamic nature of environmental shifts. Those modifications have profound implications for human health and well-being, with the capacity to disrupt livelihoods and socio-economic systems.

This study focuses on fabrication of SAF2507 similar joints with modified microwave hybrid heating (MHH) method and optimization of the elemental constitution based on energy dispersive spectroscopy (EDS) results. Major input parameters were in this work were filler powder (P), number of graphite rods (R) and process time (T). Each input parameter was varied to three different levels; such as P1, P2 and P3 being no powder, nickel powder and SS304 powder respectively; R1, R2 and R3 being 6, 8 and 10 number of graphite rods respectively; T1, T2 and T3 being 480, 540 and 600 seconds respectively. Experiments were performed as per L9 array based experimental design. EDS based elemental constitution results were used during optimization purpose. Weight percent of Cr, C and Ni have been considered for optimization. Additionally, the mechanical characterization of joints has also been carried out using micro-hardness tests.

Internet of Things isn’t always approximately about the things themselves; it’s approximately being clever. IoT is real and helpful because of its ability to apply intelligence to sense facts, especially in the context of construction engineering. A smart building’s architecture is a great place to start as IoT is reshaping every aspect of a building, from design to occupancy to maintenance. The experience of workers, control, and tenants is being optimized through the use of IoT data to inform decision-making. Better facilities may simplify corporate processes and increase revenue in smarter homes. The goal of intelligent houses is sustainability. There are several methods for automating tasks with the Internet of Things. It is necessary to address every single facet of the building architecture. This article discusses the problems and technologies of IoT-based smart building architecture. The Internet of Things (IoT) and embedded systems provide the foundation of the “Smart Building” idea. Together with smart lighting in smart buildings and seismic detection, the model that is being shown has several features. When the smart lighting system turns on and off, it is determined by the amount of natural light available and the presence of people within the building. In order to reduce the amount of maintenance needed, smart dustbins that open up when they sense a person are available. Watering systems that are designed to measure the moisture content of the soil are extremely useful for the maintenance of lawns. A seismic activity detection module allows for early warnings of earthquakes and other seismic activity that may occur in the future. It has been successfully developed a smart building concept that uses Arduino and a cloud server to analyze the data gathered from the smart building.

The discharge of wastewater into the ecosystem has an impact on fish and human health, therefore the toxins needs to be removed. It is sustainable to remove pollutants from wastewater by utilizing biochar made from lignocellulosic biomass (LCB) that has undergone thermal degradation. Because of it's large surface area, hollow structure, the oxygen groupings, and relatively low cost, bio Char is now known as a change rival in catalytic processes. Biochar was used in conjunction with a number of cutting-edge, creative technologies to treat wastewater efficiently. Details collected soil sampling, such as facts about the toxins current, the nature of the soil, its surrounding circumstances, and the efficacy of various rehabilitation methods, can be used to training machine learning methods. Through data analysis, machine learning models are able to spot relationships and trends which human beings might miss, which improves the accuracy of projections regarding the results of soil cleanup. The review paper outlines the challenges facing biochar-based enzymes using immediate and new technologies, along with emphasizes the application of algorithmic learning in pollution removal. Limitations and likelihoods for additional investigation are examined.

During a few extremely distressing earthquakes in India, R.C.C. elevated water tanks suffered significant damage or collapsed. This may have been brought on by incorrect staging geometry as well as ignorance of how the tank's supporting system should behave in the event of an earthquake. The elevated water tank is made up of structural components such as footings, beams, columns, and slabs. Subjected loads are passed between these components and ultimately to the soil's sub-grade. When an overhead tank is advantageously analysed, the elevated water tank behaves differently for distinct types of loadings (Dead, Live, and Seismic). Various combinations of loads that support the possibility of occurrence are indicated by the codes for Indian standards. The primary goal of this research is to improve performance during earthquakes and complement conventional staging by better understanding the behaviour of various bracing systems. Equivalent static analysis of various bracing system types applied to the elevated circular water tank staging in the seismic zone are carried out using STAAD Pro. The axial force and maximum bending moment of the circular water tank are examined in the X, Y, and Z axes. Several models are used to calculate the axial force and maximum bending moment for staging with cross bracing, diagonal bracing, and alternating diagonal bracing.

Climate change is widely acknowledged as a prominent obstacle that significantly impacts agricultural productivity and the wellbeing of individuals. Farmers bear the brunt of the impact since they must consistently adapt to changes in climate. Questionnaire surveys were conducted in Bhopal, India to ascertain farmers' perspectives of climate change and its implications. The research was conducted out in Bhopal, Madhya Pradesh. M.P. possesses a range of meteorological conditions, soils, and a variable cropping pattern. This study utilises cross-sectional household survey data collected from farmers residing in Bhopal. The study employed a multi-stage sampling process to choose respondent houses for the sample. Ultimately, the study's sample size was established at 97 household heads. The study employed quantitative data. Data collection was conducted using household surveys. The researchers employed both structured and unstructured questionnaires to examine the farmers' impression of climate change. Given the nature of their work, researchers asked the farmers who took part in it what they thought about climate change. The findings imply that a variety of factors, including age, level of learning, and prior agrarian expertise, influence farmers’ perceptions of global warming.

Navigating towards a sustainable future, this paper meticulously reviews diverse studies, exploring the intricate dynamics of transitioning to 100% solar energy in smart cities, whilst particularly scrutinising land requirements. The studies, set against varied geographical and socioeconomic backdrops, delve into the technical and economic feasibility, alongside environmental repercussions of a wholesale shift towards renewable energy in urban environments. For example, a detailed exploration of Delhi’s multi-sectoral energy transition pathway unveils potential in slashing primary energy and costs, mitigating greenhouse gas emissions, and bolstering the energy job sector. Another study elucidates a methodology for crafting Smart Energy Cities, exemplified by Aalborg’s transition within Denmark’s 100% renewable energy framework. Additionally, an examination of the economic and environmental performance of renewable energy systems in diverse Chinese residential communities highlights the predominance of solar energy and biomass, revealing disparities in investment recovery and emission reductions. Collectively, these studies illuminate the multifaceted aspects of renewable energy transitions in urban contexts, steering towards a globally sustainable, efficient, and secure energy future.

Power electronics pertains to a category of devices that convert electrical power from one form to another. Semiconductor devices act as switches in power electronics circuits, serving as the central components responsible for voltage regulation. Power electronics circuits strive to convert electrical energy from one form to another, from source to load, while minimizing cost, size, and weight as much as possible. The term “rectification” refers to the power circuit which alters the ac characteristic of the line electric power in order to supply “rectified” ac power with a dc value at the load side. The rectifier is utilized to convert alternating current (AC) voltage into direct current (DC) or low-frequency AC in order to power different load configurations. The AC mains are subjected to the injection of low order current harmonics by the Conventional Phase Controlled Rectifier. These harmonics necessitate the use of filtering components of considerable size for effective attenuation. The paper explores the simulation of the Converter through various PWM techniques, including space vector pulse width modulation and sinusoidal pulse width modulation.

Hybrid standalone power supply system’s especially operating with renewable energy sources are becoming popular and establishing in many places worldwide. Two major renewable energy sources for electricity generation are solar and wind. Usually Photovoltaic modules (PVMs) are using for producing electricity from solar energy and in the similar way, PMSG based wind power conversion systems are becoming popular for medium power ranges. Therefore, a standalone hybrid system consisting of PVMs, wind, and battery can ensure a reliable power supply to various loads. The combination of these energy sources, along with the battery storage system, offers a flexible and dependable power supply to consumers at all times. This innovative approach involves the implementation of a novel control technique in a microgrid setup to uphold power quality at the PCC. The system integrates devices for maximizing power point to improve energy utilization efficiency. A DC to DC bidirectional circuit connects the battery bank unit (BBU) to the system to efficiently regulate energy. The bidirectional DC to DC circuit controls the dc-link voltage by accurately managing the discharging and charging of the battery. The three-phase inverter is situated between the AC loads and dclink, designed with a control system that ensures a constant RMS voltage at the PCC, regardless of changes in load and energy sources. MATLAB platform is used to present the results under various case studies in this paper.

The hybrid photovoltaic (PV)- wind based power generation systems are installing on many rooftops of individual houses, apartments, institutions, hospitals and small scale industries worldwide. Even though it is connected to single phase utility grid, a battery is used for backup power supply during power cuts. The diesel generators also can be integrated to this system for supplying continuous power long term. This configuration can establish a nanogrid under low power systems. Many loads are operated under this nanogrid system, hence a proper control technique is required to maintain power quality as well as to compensate reactive power. Compensating reactive power demanded in nanogrid through the inverter can reduce the reactive power demand on the main utility grid. Individual maximum power point tracker (MPPT) circuits are employed for both PV and wind to harvest maximum power. The system is synchronized with single phase utility grid through the control of the inverter. The proposed control method can able to regulate the phase voltage t its reference signal for improving the power quality. MATLAB Simulink platform is used to present the results for testing the performance of the proposed method.

This paper presents a simple 3 level DC-DC boost converter for fuel cell applications to boost voltage from 48 V DC to 210 V DC. The main advantages of this converter are its simple design, presence of a single switching element for easy controllability, compact size, low cost and high power density. It is basically a simple boost converter with 3 stage voltage multiplier connected to the output side. Simulation and Hardware results for a power level of 250 W are provided in this paper.

The process of changing a soil’s physical characteristics to provide it long-term, permanent improvements in strength is known as soil stabilisation. Increasing a soil’s overall bearing capacity and shear strength is how stabilisation is achieved. After stabilisation, a solid monolith forms, reducing permeability and hence the possibility for shrinkage and swelling as well as the damaging impacts of freeze-thaw cycles. The goal of this study is to improve the physical characteristics of soils for better building results by investigating the potential of cement and rice husk ash (RHA) as soil stabilizing materials. Using RHA, a byproduct of milling rice, this study investigates alternate, environmentally friendly stabilization techniques with respect to the limits of traditional cement-based stabilization. The study assesses the impacts of different RHA and cement mixtures on soil’s Liquid Limit, Plastic Limit, and Plasticity Index using a thorough experimental approach. The factorial experiment provides important insights into changes in soil plasticity over a 3x3 matrix under nine distinct settings. The results show that while larger RHA percentages considerably lower the Plasticity Index, indicating improved soil stability, increasing cement concentration generally rises the Liquid and Plastic Limits. The satisfactory combination, determined to be 15% RHA and 8% cement, presents a possible path closer to producing soil that is less plastic and more durable. This obseravtion helps to broaden sustainable, low-cost techniques of stabilizing soil at the same time as also shedding light on the synergistic impacts of cement and RHA on soil parameters.

Engineered soil qualities can be modified mechanically, chemically, or biologically to achieve soil stabilisation. Soil stabilisation is a method used in civil engineering to enhance and enhance a soil’s structural qualities. Mechanical strength, permeation, compressibility, resilience, and plasticity are some of these attributes. The systematic investigation of soil stabilization with fly ash and ground granulated blast furnace slag (GGBS) as binders is presented in this work. The goal of using geopolymer technology is to enhance the mechanical qualities of clay soils for the building of road pavement by substituting conventional cementitious materials. The ideal ratio of Fly Ash to GGBS is found using a Taguchi experimental design technique, more precisely a L9 Orthogonal Array, with the goal of improving soil liquid limit, plastic limit, and plasticity index. The effectiveness of various Fly Ash and GGBS ratios is assessed, as well as their influence on soil behavior. In order to develop models for predicting soil parameters, regression analysis is used. Diagnostic plots show a reasonable fit but also highlight small amounts of unexplained variability. These discoveries have important ramifications for sustainable construction methods and are essential for improving soil stabilizing procedures, especially when it comes to road pavement engineering.

This paper presents an impressive design of a convergent divergent (C-D) nozzle using the method of characteristics for a Mach number 2 test section. The nozzle’s geometry was meticulously crafted in SolidWorks, and its performance was evaluated through a CFD simulation in Ansys Fluent R22 software. Results showed excellent agreement between the simulation and analytical data, with the Mach number ranging from 1.78 to 2. The study also compared turbulence modeling techniques, concluding that the k-omega model produced superior results. The supersonic wind tunnel achieved remarkable efficiency, completing a run at 1.8 Mach number in just 6 seconds. Overall, the study showcased exceptional accuracy and meticulousness.

Equivalent lateral forces are used in earthquake engineering to build structures that can survive seismic shocks. Considering seismic waves affect how the Earth moves, buildings in India’s seismically active areas must be built to withstand earthquakes. This study examines how multistorey reinforced concrete building frames function seismically while taking into account different soil types, loading scenarios, and seismic Zones IV. For a twelve-storey skyscraper, the analysis includes earthquake reaction storey displacement. This study looks into how soil changes in seismic zone IV affect buildings’ responses, as well as how seismic zones themselves affect them. The building’s natural time periods were evaluated using both response spectrum analysis and time history analysis methods. These results provide insightful information about the complex interaction between soil type and seismic zone, Member stresses and maximum displacement are calculated using static and dynamic analysis. In India’s seismically active region, the necessity for earthquake-resistant structures is highlighted by seismic waves that alter the motion of the earth. Response spectrum analysis combines modal responses via techniques including SRSS, CQC, and ABS, taking into account a variety of response modes. This study compares earthquake loads using various soil types in Zone IV to evaluate building performance during earthquakes. This project’s primary goal is to analyse a multistorey building’s seismic response. Staad Pro Software does load calculations in order to analyse the entire structure. Staad-Pro analysis employs the Limit State create approach, which complies with the Indian Standard Code of Practice.

The properties and compressive strength of hardened concrete are examined by destructive and non-destructive testing methods. There was no direct relationship between non-destructive testing results for existing concrete structures. This article describes the comparison between rebound and compression hammer tests of hardened concrete. It also describes the comparison of strength and cube compressive strength as well as the comparison of modulus of elasticity according to different standards.Destructive and non-destructive techniques were used in an experimental programme on various concrete mixtures, including M20, M25, and M30. A comprehensive technique was used for evaluating the compressive strength properties of concrete grades M20, M25, and M30, using both destructive and non-destructive testing methods. The impact strength, maximum load, Schmidt hammer, and uniaxial compression test findings have been also reviewed within the examination. The study’s primary purpose was to clarify the connections between specific evaluations technique and actual grades. Similarly, those connections were subjected to an in-depth validation technique using previously advanced formulation from previous research, which produced precious statistics about the assessment of concrete strength. These findings increase our understanding of concrete’s behaviour and provide essential path for destiny packages inside the engineering and construction industries, enabling properly-informed decision-making in those domains.

In India’s seismically active region, the necessity for earthquake-resistant structures is highlighted by seismic waves that alter the motion of the earth. Response spectrum analysis combines modal responses via techniques including CQC, and ABS, taking into account a variety of response modes. This study compares earthquake loads using various soil types in Zone III and evaluates building performance during seismic events. The primary goal of the entire project is to analyse the seismic response of multistory buildings. Staad Pro Software does load calculations in order to analyse the entire structure. The outcomes turned out to be incredibly exact and precise. A G+7 and G+10 storey building was examined for every potential load combination (seismic, live, and dead loads) during my analysis and design process. The highly interactive and user-friendly user interface of Staad. Pro allows. Numerous factors that may impact earthquake ground movements and associated reaction spectra are included in analytical approaches for site response analysis. To ensure that assessments of earthquake ground motons at the site are reliable, it is crucial to look into how these parameters affect site reaction analysis. The parametric study presented in this work looks into how site factors affect ground motion during earthquakes. We calculated the response reduction of the common moment-resisting body case and the unique moment-resisting frame values Tall Construction’s seismic reaction using the Staad Pro programme.

In the current study, the investigation of heat transfer and fluid flow Characteristics of Pure water when pass through a double tube heat exchanger (DTHX). this investigation has been conducted across various Reynolds Number to gain insights into their performance also conducted a computational fluid dynamics (CFD) simulation using the ANSYS-FLUENT 22 R1 software. Result obtained was validated by comparing to empirical correlation data found in the existing literature. The investigation considered various operating variable as Reynolds Number and temperature across the inner, and outer tubes. Specifically, the Reynolds Number of a range of 2500 to 5500 at 333 K, and 2500 at 303 K for the respective tubes. Key findings are that friction factor is increase by 6.38% as compared to correlation (Blasius) in existing literature. And Nusselt number (Nu) increase by 40.84% as compared to correlation at the Reynolds Number (Re) of 2500. The heat transfer coefficients (hi) were increased by 8.30% as compared to existing literature.

The subject of airfare is examined in this paper. As a result, a collection of factors that characterize a typical flight are selected under the presumption that they have an impact on airline ticket costs. The price of a plane ticket is influenced by the length of the trip, the location, the schedule, and several other factors, like holidays or vacations. Therefore, many people will surely save time and effort by having a basic awareness of airline expenses prior to making trip arrangements. The performance of the seven different machine learning (ML) models used to anticipate the price of airline tickets is compared after three datasets were analysed to acquire insight into airline fares. The objective is to investigate the factors that influence flight prices. The data can then be used to build a system that can predict how much a flight will cost.

The Brain Tumor (BT), which forms in the brain cells and spreads to the whole brain, may lead to death. Hence, early diagnosis of BT is significant. Still, the detection of BT between the skull and brain region is not concentrated, which results in misclassification outcomes. Thus, this article proposes Magnetic Resonance Imaging (MRI)-based BT detection and types’ classification utilizing Carlitz Exponential Hamilton Jacobi Bellman-based Reinforcement Learning (CEHJB-RL) and JenSorensen similarity-based Minimum Spanning Tree (JMST). Primarily, raw MRI images are taken and then pre-processed. Then, with skull and without skull regions are extracted from the pre-processed image and are subjected to the graph construction. Conversely, the edges are detected from the pre-processed image that can be patch-extracted and subjected to graph construction. By utilizing JMST and Morphological Operations (MO), the graphs are constructed. Thereafter, the features are extracted and fed to the classifier. Then, the type of BT is classified by the classifier using CEHJB-RL. Concerning the performance metrics, the outcomes illustrated that the proposed technique attained a higher accuracy (99.27%), which is better than other existing techniques.

Natural fibers are appealing due to its inexpensive price, small weight, and high specific modulus, renewable nature, as well as biodegradability. Bamboo fibers is one of the most promising natural fibers (along with jute, sisal, bamboo, coir, banana, and others) owing to its low cost, light weight, quick growing cycle, and wide availability. The goal of this paper is to look into fibers orientation reinforced hybrid polymer nano composites that combine BAMBOO/E-GLASS and epoxy polymer in the ratios of E-glass fibre80 percent +bamboo 20 percent, E-glass Fibre70 percent +bamboo 30 percent, and E-glass Fibre60 percent +bamboo 40 percent of volume. The mechanical characteristics will be calculated by performing tests on the specimen's tension, hardness, and flexural qualities in line with ASTM standards. Finally, the values are verified when the testing results have been obtained.

When bodily cells transform and proliferate out of control, it is called cancer. Cells are the minuscule building blocks that make up your body. Normal cells develop as required by the organism and degenerate when no longer required. The aberrant cells that make up cancer develop even if your body doesn't require them to. The aberrant cells in the majority of malignancies develop into a bump or mass known as a tumor. Long enough for cancer cells to exist in the body, they can spread (invade) into surrounding regions. They may even spread to various body regions (metastasis). Two key turning points for the practical application of targeted therapy in lung cancer patients were the sequencing of the malignant tumors genome and the development of medicines that target driver mutations. Understanding euplastic cells and mutational mechanisms, along with how they change as tumors form and how different cancer cells differ genetically, are all necessary for this. It is hoped that ongoing global initiatives to systematically identify the most pertinent genetic alterations for each subgroup of pulmonary cancer will raise the proportion of tumors that always respond better to novel medications targeting different genetic profiles. Oral medicines with significantly higher responder rates and lower toxicity than chemotherapy can be used to target many genetic changes. Methology: Alternative: Brain, Bone, Liver, Contra lateral lung, Adrenal gland. Evaluation Preference: Squamous cell carcinoma, denocarcinoma, Small cell lung carcinoma, undifferentiated carcinoma Result: As a result, Adrenal gland and top ranking, whereas the Brain rating received a low ranking received Conclusion: The value of the dataset for Lung cancer in EDAS method shows that it results in Adrenal gland and top ranking.

The name “cryptography” comes from a Greek word that refers to the art of securing data by organizing it in a disorganized and unintelligible way. It combines software engineering with math. The explosive expansion of the Internet has led to a greater awareness of intriguing uncertainty concerns. Although security is the biggest concern when it comes to the internet, many apps have been developed and designed without taking confidentiality, authentication, and protection—the three essential components of data security—into account. Knowing these kinds of security problems and challenges is going to be more important as our daily activities rely more and more on data networks. Cryptography is necessary to prevent some unwanted customers or persons from gaining access to the data. This study presents a novel hybrid security cipher that combines the three most significant ciphers, such as the Caesar, Rail Fence and Vigenère ciphers. When compared to traditional ciphers, this hybrid encryption cipher offers more security.

Cloud enterprises face challenges in managing large amounts of data and resources due to the fast expansion of the cloud computing atmosphere, serving a wide range of customers, from individuals to large corporations. Poor resource management reduces the efficiency of cloud computing. This research proposes an integrated resource allocation security with effective task planning in cloud computing utilizing a Machine Learning (ML) approach to address these issues. The suggested ML-based Multi-Objective Optimization Technique (ML-MOOT) is outlined below: An enhanced task planning, based on the optimization method, aims to reduce make-span time and increase throughput. An ML-based optimization is developed for optimal resource allocation considering various design limitations such as capacity and resource demand. A lightweight authentication system is suggested for encrypting data to enhance data storage safety. The proposed ML-MOOT approach is tested using a separate simulation setting and compared with state-of-the-art techniques to demonstrate its usefulness. The findings indicate that the ML-MOOT approach outperforms the present regarding resource use, energy utilization, reaction time, and other factors.

Parking spots have become a prevalent concern in urban growth. The number of automobiles is increasing faster than accessible parking spaces. This problem is addressed by implementing an Internet of Things (IoT)-based Parking Surveillance Scheme (IoT-PSS) for the smart campus. The system aims to efficiently match vehicles with available parking spaces, resulting in time savings, improved parking space usage, reduced management expenses, and decreased traffic congestion. Edge computing provides a new answer to data processing in monitoring systems by using advancements in IoT, artificial intelligence, and transmission technologies to analyze data regionally at the edge. This research explores the viability of using edge computing for smart parking monitoring, focusing on detecting parking occupancy via a real-time video stream. The structure operating pipeline to prioritize adaptability, online surveillance, data transfer, detection precision, and system dependability. The experimental findings show that the final detection approach achieves more than 95% accuracy in real-world situations with outstanding effectiveness and reliability. The IoT-PSS system is essential for smart cities and is a strong basis for future use in smart transportation networks.

The management of marine waste is an increasingly complex issue facing the world today. Our study provides an interesting take on the issue of marine waste by examining how Indonesian indigenous communities can deal with plastic marine pollution. While there is an obvious need for mitigating plastic use, for effective legislative policies regulating plastic waste management, and to do more to develop sustainable waste management practices; there are also opportunities for indigenous communities to take an innovative approach by using plastic waste in a manner that drives economic development from both non-market and neoliberal theoretical ideologies. As part of this assessment, alongside Indonesian examples we include examples of plastic re-use by indigenous communities of the Philippines and Australia. Moreover, our study highlights some of the areas in which this is being done in the fields of art and infrastructure development.

The current study focuses on the impact of firecrackers emission on particulate matter (PM2.5 and PM10), carbon monoxide (CO), carbon dioxide (CO2), and total volatile organic compounds (TVOC) and the noise was analyzed on pre, during, and post-Diwali 2022 period (5 days) in a residential area of Tamil Nadu state of India. The findings demonstrated that, for 24-hour mean values of PM2.5 and PM10 concentrations over the study period were consistently higher than the NAAQS (National Ambient Air Quality Standard) permitted limit. On the day of Diwali, the mean CO concentration reaches 2.5 mg/m3, exceeding the NAAQSrecommended allowable limit of 2 mg/m3. The CO2 concentration during Diwali day is 1.8 times higher than the pre-Diwali day. In addition, the 24-hour mean concentration of TVOC during pre-Diwali, Diwali, and post-Diwali was found to be 915.21 µg/m³, 1513.52 µg/m³ and 1617.12 µg/m³ respectively which is quite higher than normal days. Furthermore, the average noise level in the study site during pre, during, and post-Diwali was found to be 57.71 dB (A), 75.5 dB (A), and 63.66 dB (A) respectively which were higher than the safer limit on the residential zone. As a result of the widespread usage of firecrackers during Diwali festivities, these pollutants are significantly increased, which may have a negative influence on the general public’s health.

The primary goal of this paper is to develop a robot capable of efficiently climbing teak wood trees and performing bud pruning tasks, thereby addressing the challenges posed by labor scarcity in farming. Teak wood cultivation has been significantly affected by the lack of skilled labor, necessitating a minimum of five tree climbs per year for successful cultivation. The proposed robot design features an ‘X’ frame structure with conical-shaped rollers positioned at the bottom, connected to two DC motors. These motors can be controlled remotely to enable vertical movement along the tree. To ensure secure attachment, springs are utilized to fasten the robot model to the tree. At the top of the robot, an appropriately arranged motor-driven chainsaw is installed to execute high-speed bud pruning. Overall, this robot will be helpful to automate the pruning process through sustainable development.The bud pruning robot described consists of an ‘X’ frame design with two conical-shaped rollers at the bottom.These rollers are connected to two DC motors, which are controlled by a remote, allowing the robot to move up and down the tree.To ensure stability and secure attachment to the tree, springs are utilized to firmly fasten the robot in place. The top of the frame is equipped with a high-speed DC motor to which a chainsaw is attached for the purpose of pruning buds.

The Automatic UPS Battery Maintenance System is an innovative and technologically advanced solution developed to optimize the upkeep of Uninterruptible Power Supply (UPS) battery cells. Utilizing precision sensors and real-time data analysis, the system intelligently assesses the electrolyte levels and triggers automated distilled water replenishment when necessary. By eliminating the need for manual water level checks and refilling, the system minimizes the risk of under filled batteries, which can lead to decreased battery lifespan and compromised performance. User-friendliness is a cornerstone of the system’s design. It features an intuitive interface that provides users with a comprehensive view of battery health, water levels, and system status. In the event of anomalies, the system promptly issues notifications and alerts, ensuring timely response and minimizing potential disruptions during power outages. Key advantages of the Automatic UPS Battery Maintenance System include prolonged battery lifespan through reduced plate corrosion and sulfation, consistent and uninterrupted power supply, reduced labor and time overhead, datadriven insights for informed decision-making, and environmentally responsible water usage.In conclusion, this project introduces an intelligent and efficient solution to enhance UPS battery maintenance practices. By automating the critical process of water level management, the Automatic UPS Battery Maintenance System contributes to the overall reliability and longevity of UPS batteries, making it a valuable asset for businesses and individuals reliant on continuous and dependable power supply.

Rescue operations for people trapped in deep borewells provide a serious problem needing both advanced robotic technology and human expertise. This abstract focuses on the creation of a revolutionary machine-human rescuing robot that is specifically designed to respond to emergencies in deep borewells. the complicated nature of deep borewell rescues, which includes technical challenges, time-sensitive situations, and the requirement for swift and accurate action. It draws attention to the drawbacks of conventional rescue techniques and promotes the creation of a flexible robotic system that can work in tandem with human rescuers. The suggested robot is built as a hybrid system that combines human control with autonomous functionality. To deliver real-time data and visual feedback from the borewell inside, it integrates specialized sensors, cameras, and communication tools. The borewell rescue robot’s, structural frame work consists of two cylindrical pipes fastened vertically with the help of T shaped square rod, these cylindrical pipes acts as a holding platform for children hands. Lower end of the pipes are provided with mechanical straps which in turn are actuated by BLCD motors with human rescuers is a crucial component of its functionality. Skilled operators can control the robot’s movements in real time thanks to remote operating interfaces and haptic feedback systems. The significance of the robot-human rescue team in deep borewell crises is emphasized in the abstract.

Image deblurring is a challenging task that aims to restore a sharp and clear image from a blurred one. This problem is usually caused by camera motion or defocus blur. The objective of this paper is to develop a model that can effectively remove Gaussian blur from an image and improve its quality using deep learning techniques. Automated image deblurring is achieved using deep learning, this approach involves implementing a combination of convolutional neural networks (CNN) and simple auto encoders to train the model on a dataset of blurred and corresponding sharp images. The model is then used to deblur the test images and improve their quality. The paper uses a dataset of blurred and corresponding sharp images to train the model, and the performance of the model is evaluated based on metrics such as PSNR and SSIM. The results and discussions focus on the effectiveness of the model in removing Gaussian blur and improving the quality of the images. In conclusion, the paper demonstrates the effectiveness of using deep learning techniques for image deblurring and provides scope for future enhancements such as incorporating more complex models and exploring other types of blur removal techniques.

Sentiment analysis plays a significant role in understanding public opinion, trends, and sentiments expressed on social media platforms. In this paper, we focus on performing sentiment analysis on real-time Twitter data to gain insights into the sentiments related to specific topics or events, we collect a stream of tweets based on predefined keywords or hashtags. The collected tweets undergo pre-processing steps to clean and standardize the text for sentiment analysis. We employ machine learning classify the sentiments expressed in tweets, utilizing sentiment lexicons and training data as references. Real-time sentiment analysis is performed as new tweets are collected, enabling continuous monitoring and analysis of public sentiment. The sentiment analysis results are visualized through informative visualizations such as sentiment distribution charts and sentiment trends over time. Additionally, we focus on topic-specific analysis by filtering tweets based on relevant keywords or hashtags, providing deeper insights into sentiments related to specific subjects. The paper faces challenges such as noisy and informal text, ambiguity in sentiment expression, and handling large volumes of real-time data. Addressing these challenges, we aim to develop an effective sentiment analysis system that provides valuable insights into public sentiment and supports decision-making processes in various domains.

Data clustering is frequently utilized in the early stages of analyzing big data. It enables the examination of massive datasets encompassing diverse types of data, with the aim of revealing undiscovered correlations, concealed patterns, and other valuable information that can be leveraged. The assessment of algorithms designed for handling large-scale data poses a significant research challenge across various fields. Evaluating the performance of different algorithms in processing massive data can yield diverse or even contradictory results, a phenomenon that remains insufficiently explored. This paper seeks to address this issue by proposing a solution framework for evaluating clustering algorithms, with the objective of reconciling divergent or conflicting evaluation outcomes. “The multicriteria decision making (MCDM) method” is used to assess the clustering algorithms. Using the EDAS rating system, the report examines six alternative clustering algorithms “the KM algorithm, EM algorithm, filtered clustering (FC), farthest-first (FF) algorithm, make density-based clustering (MD), and hierarchical clustering (HC)”—against, six clustering external measures. The Expectation Maximization (EM) algorithm has an ASi value of 0.048021 and is ranked 5th among the clustering algorithms. The Farthest-First (FF) Algorithm has an ASi value of 0.753745 and is ranked 2nd. The Filtered Clustering (FC) algorithm has an ASi value of 0.055173 and is ranked 4th. The Hierarchical Clustering (HC) algorithm has the highest ASi value of 0.929506 and is ranked 1st. The Make Density-Based Clustering (MD) algorithm has an ASi value of 0.011219 and is ranked 6th. Lastly, the K-Means Algorithm has an ASi value of 0.055376 and is ranked 3rd. These ASi values provide an assessment of each algorithm’s overall performance, and the rankings offer a comparative analysis of their performance. Based on the result, we observe that the Hierarchical Clustering algorithm achieves the highest ASi value and is ranked first, indicating its superior performance compared to the other algorithms.

The pipeline at the thermal power station is now being used to conveying fly ash in the form of slurry. The objective of this research is to investigate the rheological behaviour of slurry suspensions of finer particles (FA) with and without coarser particles added (BA). In terms of weight, the ratios of fly ash to bottom ash (BA) are as follows: 9:1, 8:1, 7:3, and 6:4 respectively. Experiments on the rheology of each and every sample of slurry are carried out at shear rates ranging from 100 to 250 seconds-1. The temperature of the slurry suspension might range anywhere from 25 to 35 °C when it has a solid concentration of 30% (by weight). When finer fly ash slurry particles are combined with coarser bottom ash particles, the rheological properties of the resulting slurry suspension are significantly improved in terms of sustainable flow. The exhaustive assessments also investigate whether or not it is possible to conveying ash slurry by pipeline through sustainability.

Les caractéristiques environnementales des écosystèmes aquatiques continentaux sont en grande partie héritées le long du réseau hydrographique. Leur estimation automatisée nécessite l'utilisation d'un réseau hydrographique jointif et orienté. Le réseau orienté actuellement disponible en France (drain principal naturel) a permis entre autres la modélisation de l'écoulement naturel, la mise en place de différentes typologies de cours d'eau et l'application de modèles écologiques à l'échelle nationale. Cependant ce réseau apparaît limité du fait de son manque de représentativité des cours d'eau de tête de bassin. Pour couvrir de manière plus complète les cours d'eau de moindre taille, nous présentons ici un réseau hydrographique étendu (RHE) complétant le réseau existant. Le RHE comporte 2,5 fois plus d'arcs que le drain principal naturel, et permet une meilleure représentation des têtes de bassin (petits cours d'eau, faibles distances à la source, pentes fortes).