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The drone industry has been steadily expanding in the past ten years. According to analysts, India will have the third-largest drone market in the world by 2025. If this forecast comes true, India will become a centre for drone technology by 2030, within the fiscal year 2024 turnover is estimated to be between 60 and 80 billion to 900 billion Indian Rupees. Compared to the conventional modes, UAVs are an enhanced variation of the photogrammetric method. To convert the pictures taken by drones into 3D models, there is a variety of software available, including Agisoft Metashape, Pix 4D Photogrammetry, Drone deploy, and Context capture software. Among these, Context Capture Software has been user-friendly in obtaining the results such as the length from end to end of the footpath inside the educational institution, the area of the rooftop of a building on campus, and the area of the open-air auditorium inside the educational institution. [ABSTRACT FROM AUTHOR]

There are a number of current uses for aluminium network composites. When it comes to coordinating qualities, no modern solid material can match aluminium framework composites. The properties of aluminium lattice composites are greatly affected by the support concept, which may take the form of a continuous or fractured fibre structure. Focusing on composite-coated aluminium materials, this paper examines their microstructure and hardness. Because of its low density and great strength, aluminium finds widespread use in aerospace, marine, and automotive applications; nevertheless, protective coatings are often required to prolong the material's life since it oxidises at a higher rate than steel. The mechanical conductivity of PVD-coated aluminium is affected by the covering material. Composite materials and designs abound for use on aluminium plates. The primary goal of covering is to increase the material's solidity and prevent its breakdown. We use a PVD method to coat the aluminium plate with the composite material. Some of the tests used to determine the material's resilience when coated include the scratch test, the Rockwell hardness, the nano-space test, and the rebounce test. The adhesion test determines how well the coated material adheres to the aluminium plates. [ABSTRACT FROM AUTHOR]

The study focuses on implementing value engineering concepts in an Industrial project with the goal of achieving better quality at a lower cost. The construction industry is known for its challenges in balancing factors such as money, time, and quality. However, by adapting modern techniques and tools, such as value engineering, these factors can be effectively balanced. Value engineering is an efficient tool that aims to enhance construction quality while minimizing costs. It involves analyzing the basic functions of a project and scrutinizing and eliminating any unnecessary elements. In this thesis, the value engineering study is conducted using the Function Analysis System Technique (FAST) tool, which aids in functional analysis. The project study follows a step-by-step process to achieve the desired results. By implementing value engineering concepts in the construction of Industrial projects, the thesis aims to optimize the use of available resources and eliminate any unnecessary expenses. This approach helps in identifying alternative solutions and design modifications that can enhance quality and reduce costs. Ultimately, the goal is to construct an industrial building that meets high-quality standards while maintaining affordability. [ABSTRACT FROM AUTHOR]

The concept of harnessing Internet of Everything (IoE) technology in higher education has the potential to revolutionize teaching and learning processes. This paper explores the role of IoE in higher education by investigating its impact on student engagement, teaching methodologies, and campus management. Using a quantitative approach, an online survey was conducted to gather data from professors and students. The results indicate high satisfaction levels with technology use and highlight the transformative impact of IoE in higher education. The findings contribute to the existing body of knowledge and provide insights for creating more connected and collaborative learning environments. Ensuring data security and addressing challenges associated with IoE implementation are crucial for its successful integration in higher education. [ABSTRACT FROM AUTHOR]

This research examines the influence of bagasse ash and terrazyme (Bio-enzyme) on the geotechnical characteristics of soil of black cotton through compaction tests, unconfined compression strength (UCC) tests, and California bearing ratio (CBR) tests. The results reveal that adding bagasse ash and terrazyme alters the soil optimum moisture content (OMC) and maximum dry density (MDD). Increasing percentages of bagasse ash and terrazyme lead to an increase in OMC and a decrease in MDD; however, beyond certain percentages, further increases result in an increase in MDD and a decline in OMC. Moreover, including bagasse ash and terrazyme significantly enhances the UCC of the Soil. The optimal stabilization percentages are determined as 6% bagasse ash and 1.2 ml of terrazyme per 2 kg of Soil, with the UCC reaching 4250.15 kPa after 21 21-day curing period. Additionally, the bagasse ash and terrazyme content have a notable impact on the CBR of the Soil, with treated Soil showing improved CBR values compared to untreated Soil. Overall, the findings demonstrate the positive effects of bagasse ash and terrazyme in enhancing the geotechnical properties of black cotton soil, making them promising additives for soil stabilization applications. [ABSTRACT FROM AUTHOR]

In present numerical study the double lid-driven cavity (LDC) flow having a power law fluid in it is analyzed. Finite volume method is adopted for discretizing unsteady two-dimensional incompressible Navier – Stokes equations, which are then solved using open source software package OpenFOAM. The power law index (n) values are varied from 0.25 to 2 at Reynolds (Re) = 100. The flow behavior is analyzed with the aid of streamline contours and profiles of pressure and velocity. The spreading of velocity gradients is found to be decreased as the value of n increases. The symmetric streamline pattern which is observed at the lower values of n is found to be lost at higher values. [ABSTRACT FROM AUTHOR]

Data-driven methods have proven to be a competent tool for investigating various physical phenomena. A large amount of fluid mechanics problems are not easy to solve if their dynamics do not adhere to the available characteristic equations. Such flow problems can only be analyzed with the help of data driven techniques. Here Dynamic Mode Decomposition is applied to a regular flow over cylinder problem with various cases having different Reynolds and Richardson numbers. The fluid flow data required for the algorithm is obtained from CFD analysis using OpenFOAM. The output data obtained from the algorithm includes the dynamic modes corresponding to vortex shedding patterns observed on all cases. These patterns are plotted to show the capabilities of the algorithm. [ABSTRACT FROM AUTHOR]

Parking is a very common problem observed in today's world with everyone using vehicles. Conventional parking systems are generally manual and requires human intervention for the whole parking process. New trends in technology related to smart parking systems are emerging, but they generally have a cubic structure and occupies a lot of space. We aim to solve these problems by reducing the amount of space by changing the structure while also reducing the recovery time of the vehicle to make the parking process faster. The rudimentary idea for the cylindrical tower-like structure was brainstormed in 2D and then modelled in 3D using various tools like extrude, extruded cut, linear and circular pattern and many other features to create a model using Solid Works. Also, it covers detailed calculations about the motor used and the power consumed to lift the load. [ABSTRACT FROM AUTHOR]

The aim of this research work is to improve the accuracy of currency more efficiently using Region based Image segmentation compared with Edge based segmentation. Materials and Methods:The accuracy and sensitivity of Region based image segmentation (n=20) was compared with accuracy and sensitivity of Edge based segmentation(n=20) with p value 0.8 by varying different currency images in Matlab simulation tool. The extraction rate is to be improved in terms of accuracy and sensitivity using Region based image segmentation and it is compared with Edge based segmentation for different currency images. Result : According to results obtained Region based image segmentation method has accuracy 96.91% and edge based segmentation accuracy 89.33% and the sensitivity of Region based image segmentation is 96.37% and also sensitivity of edge based segmentation is 89.09%. Region based image segmentation has results significantly 0.00 compared with Edge based segmentation 0.00. Conclusion :Within the limits of study, the accuracy and sensitivity of currency images using Region based Image segmentation provides significant results. [ABSTRACT FROM AUTHOR]

Predicting the onset of cardiovascular disease is the goal. Images are separated into labelled and unlabeled categories using two machine learning algorithms: Decision Tree and Logistic regression. In order to efficiently and accurately analyse labelled pictures with G power in 80% and threshold 0.05 percent, CI 95% mean and standard deviation, the sample size was iterated 10 times from n =5 in Decision Tree and n = 5 in Logistic Regression. Accurate predictions and classifications of values from cardiac patient data have been generated in this study by comparing the predictive and classifying abilities of Decision Tree and Logistic Regression. The accuracy of Decision Tree (72.40%) is statistically significant (p0.05) greater than that of Logistic Regression (67.59%). Decision Tree outperforms Logistic Regression in predicting cardiovascular disease. [ABSTRACT FROM AUTHOR]

The goal is to anticipate cardiac arrest in heart disease patients. Machine learning methods like SVM and decision tree categorise photos (DT). To effectively and reliably analyse labelled pictures with G power of 80%, threshold 0.05 percent, CI 95 percent mean and standard deviation, SVM and Decision Tree sample sizes of n=5 were iterated 10 times. The Support Vector Machine (SVM) outperformed the Decision Tree (DT) in predicting and categorising cardiac patients' data with a p-value of 0.05. Support Vector Machine predicts cardiomyopathy risk better than Decision Tree. [ABSTRACT FROM AUTHOR]

In this study, we compare Novel Finger Vein Recognition Method to Message Digest 5 (MD5) to determine which algorithm provides better accuracy for creating a secure digital register. This article makes use of the freely accessible PolyU fingerprint database for its data set. 170 individuals were used in the study to determine the efficacy of the anti-scamming strategy for fingerprint identification (Group 1=85, Group 2=85), and the numbers were crunched using G-power 0.8, alpha qualities of 0.05, and beta qualities of 0.2, and a 95% confidence interval. Finger vein recognition method where number of samples (N=10) and Message digest 5 algorithm where number of samples (N=10) are used to provide a secure digital registry for fingerprint identification with an increased accuracy rate. The accuracy rate of the Message digest 5 method is 93.64, while the accuracy rate of the Finger vein identification algorithm is 98.56. There is statistical significance in the research (p0.05; p=0.0218). When compared to the Message digest 5 technique, which is used to generate a secure digital registry, the accuracy rate of the finger vein identification algorithm is much higher. [ABSTRACT FROM AUTHOR]

The goal of this study is to use Support Vector Machines (SVMs) to recognise handwritten characters and compare their predictive accuracy to that of Logistic Regression. In this paper, we explore the application of machine learning algorithms like Support Vector Machine and Logistic Regression to the problem of character recognition. For a 0.05 level of statistical significance, we need 15 samples out of a total of 30. The SVM algorithm achieves a higher recognition rate (96.58 percent) than the Logistic Regression algorithm (87.43 percent) when both are used for character recognition. A p-value of 0.005 indicates a statistically significant difference between the study groups. Support Vector Machine was found to have better prediction accuracy than the Logistic Regression algorithm in this study of character recognition. [ABSTRACT FROM AUTHOR]

The project's ultimate goal is into action a sophisticated method of weather monitoring that makes use of the Internet of Things to make its real-time data widely available. In real time appliances, the ESP8266 microprocessor monitors temperature and humidity with a sample size of 10 measurements and a g power of 80%. When comparing the accuracy and loss of a raspberry pi and an ESP8266 microprocessor at measuring temperature and humidity, the latter achieves a 91.987 percent success rate while the former achieves only an 8.013 percent success rate. The significance value is 0.874 (P>0.05), indicating that there is a statistically significant difference between the study groups. Putting sensors out into the world is essential for gathering information for this purpose. Sensors placed around the world will gather and log data in near-real time. [ABSTRACT FROM AUTHOR]

The main objective of this research is to compare the performance of pulse coupled neural networks (PCNN) and convolutional neural networks in detecting changes in densely populated coastal areas using the shift feature (CNN). The primary purpose of this research is to analyse the performance of pulse coupled neural networks (PCNN) and convolutional neural networks in identifying changes in densely populated coastal regions utilising the shift feature (CNN). Using a g-power analysis with an alpha error of 0.95, an edge worth of 0.05, a confidence interval from 80 to 95 percent, and a pre-test g-power of 80 percent, this study analysed ten samples using two sets of computations. Multiple images of an alien landscape were taken by satellites after the command. This study recommends a simple CNN structure with a thick component finder for the organisation of images. With a 95.7 percent success rate, PCNN outperforms the 93.7 percent success rate of Shift Feature. The results showed that Shift Feature outperformed PCNN with a p-value of less than 0.05. When it comes to identifying Robust Coastal Area Changes, the normal precision of Shift Feature is noticeably higher than the mean accuracy of PCNN. [ABSTRACT FROM AUTHOR]

In India almost 40 million liters of wastewater enters rivers and other water bodies each day without any proper monitoring or analysis methodology. The aim of the study is to design a low cost IoT based water quality monitoring and analysis system which will effectively analyze TDS (Total Dissolved Solids), turbidity, temperature parameters of water. These parameters, namely, temperature, TDS (Total Dissolved Solids), turbidity will determine the type of water, type of water treatment required and the level of fitness for consumption. The analyzed parameters are sent to the programmed mail. Different samples of water were taken during the study and the results for type of water, type of water treatment required, level of fitness for consumption were determined. The results were sent to a deployed webapp over Wi-Fi and the results are also stored in a SD card to prevent loss of analysis data. This study will enable an efficient and effective way of water quality monitoring and analysis. [ABSTRACT FROM AUTHOR]

In the sphere of automobile, aircraft, and other diverse engineering applications, composite material has a large stipulation in order to enhance the requirement in those fields. But, aside from aluminium, this technological advancement requires something new. Metal Matrix Composite (MMC) could be a solution to this problem. The base matrix material in this study is Aluminum LM24 alloy, with silicon carbide and graphite particles as reinforcement. The MMCs are made using the Stir casting technique, which is a liquid state process. The samples for the different MMC specimens were 5 percent SIC and 5 percent graphite, 6.5 percent SIC and 3.5 percent graphite, and 7.5 percent SIC and 2.5 percent graphite. On the produced composite specimens, mechanical parameters such as tensile strength and hardness are investigated. Microstructure studies are also carried out on the samples that have been analysed. Microstructure characterization was explored experimentally using an inverted metallurgical microscope to assure the distribution of reinforcement in the matrix. To express those materials' features, the findings were plotted and visually presented. According to the tensile data, the strength improved as the reinforcement percent increased, resulting in a drop in elongation percent. The percentage of reinforcement in the composite sample enhanced the hardness as well. [ABSTRACT FROM AUTHOR]

Power systems are prone to failures such as power quality tripping, resonance, and CMV failures. These failures are infinite and dynamic because of the fluctuations in the power system impedance together with its load demand and harmonic dis-tortions. To have stability and control over the power system together with a quality power supply, it is imperative to monitor the fundamental frequency. Motivated by this, a data-driven approach based on dynamic mode decomposition (DMD) is proposed which is essential to observe parameters such as frequency and amplitude. This methodology works well for extracting fundamen-tal frequency under harmonics, sub-harmonics, and inter-harmonics scenarios in the signal which causes considerable damage to end-user equipment if not monitored properly. In this methodology, appended time-shifted power signals stacked into a measure-ment matrix are used for extracting the parameters from the signal. DMD relies on dynamics to capture information and predict frequencies. Measurement matrices play a crucial role in identifying the underlying dynamics of the system. Thus it creates a suitable measurement matrix and gives us input to the data-driven system which is vital for the system to perform well. This study investigates the importance of different special matrices such as Hankel, Toeplitz, and Circulant to create the measurement matrices in DMD to extract the signal parameters. DMD can replace conventional Fourier-based techniques by reducing the estimation error percentage. Various experiments are conducted to confirm the potentiality of the proposed methodology. [ABSTRACT FROM AUTHOR]

Power line interference (PLI), which is in the range of 50 Hz or 60 Hz, is one of the unavoidable noise present in the electrocardiogram signal (ECG). An ECG signal corrupted with PLI noise may end up with poor diagnosis of unhealthy heart conditions. We propose a methodology employing Variational mode decomposition (VMD) In this work, we explore the boundless potential of Variational Mode Decomposition (VMD) for removing the PLI noise from various types of numerically simulated ECG signals obtained from healthy as well as different abnormal heart conditions. An existing mathematical model developed using a discretized reaction diffusion model is used to numerically simulate normal as well as various abnormal ECG signals. The model consists of a set of mutually coupled non-linear oscillators which is represented as a four component ordinary differential equation (ODE) system. The PLI noise is manually added to the numerically simulated ECG signals represent different arrythmia heart conditions. The corrupted abnormal ECG signal is decomposed into intrinsic mode functions (IMFs) employing VMD. Further, the frequency spectrum analysis is performed and the IMFs corresponding to the PLI noise is determined and removed to get back the original ECG signal. From the result analysis, it is observed that the proposed methodology employing VMD can remove power line noise very effectively from healthy as well as various abnormal ECG signals. [ABSTRACT FROM AUTHOR]

In this work, it was selected to focus on the development of multi-element organometallic precursors in the Si/C/Zr system. In addition, various polymer structures have been considered to anticipate the shape controls of these precursors and to modify the chemical composition of the final ceramics. Furthermore, the laser pyrolysis spray process was selected to integrate the micro phase sequence powders to gain access to the microstructure of the final compound material. In order to evaluate the compatibility of the original precursors with this formulation process, this work will take up the spray pyrolysis tests. [ABSTRACT FROM AUTHOR]

The goal of the 10T memory cell's design is to allow it to bounce back from failure at any of the weak nodes. High stability, low power consumption, and a minimal environmental impact are important design priorities. The paper begins by proposing a 10T memory cell with appropriate transistor size and an upset physical mechanism to increase reliability in an aeronautical radiation environment. To show the efficacy of RHBD, we use Tanner Tool to stimulate the suggested idea in a TSMC 65nm CMOS process. The 10T memory cell architecture is more resilient to 0->1 and 1->0 single node upsets due to the longer read/write access time. [ABSTRACT FROM AUTHOR]

As the ratio of machine masters per chip increases, system performance becomes more dependent on the arbitration procedure. The arbitrator circuit, which regulates the entitlement for colourful requestors, has an impact on the system's results. Typically, an arbitration plan is selected based on the operation. For each cycle, a memory arbitrator chooses which CPU will haveaccess. An arbitrator is used by a packet switch to select which input packet will be added to the conversation. The Round-Robin arbitration with adjustable weight of resource access time is introduced in this paper. When subvention hunger is prohibited, the round-robin arbitrator method is helpful. Each requestor's permitted time shares are quantified by the arbitrator. Giving requests in a round-robin fashion ensures at least some fairness. By weight, the requestors might order their time shares. Requestor B will get a time slice that is twice as long as Requestor A's if their respective weights are two and four, respectively. The process of verifying designs is carried out with the aid of System Verilog. Arbitrator inputs are shuffled, labour projections are calculated using an algorithm, and verification data is collected. This article includes the effort necessary to construct and verify a weighted Round-Robin arbitrator. [ABSTRACT FROM AUTHOR]

Microfluidic devices build benefits such as capacity to manipulate 10-9 to 10-18 L sample volume, fast analysis and on-spot detection are required for separation and analysis of biomolecules for earlier clinical assays. This paper presents the electrophoresis based separation of platelets from whole blood for the early diagnosis of illness such as thrombocytophenia and thrombocytosis. Simple cross flow microfluidic channel, utilizing focusing and filtration channels, is designed for separation based on electrophoresis and electro-osmosis principle. Blood and analyte solution is introduced into the device using the capillary forceand the separation is achieved by applying the electric potential. The concentration of different molecules along the channels is analyzed for the designed structure. [ABSTRACT FROM AUTHOR]

Recently, inertial-based microfluidic systems for cell separation have gained popularity owing to their ease of use and ultra-high throughput. Hydrodynamic forces prevail at the microchannel's top and bottom, creating two counter-rotating vortices that power these devices. The vortices form due to the centrifugal force acting as a secondary force inside the spiral form of the microchannel. This study employs COMSOL Multiphysics for a numerical simulation of dean flow dynamics based on the Navier-Stokes equation. Changing the flow rate inside a spiral microchannel allows for more efficient separation of RBCs, WBCs, and platelets, the three primary cell types found in human blood. The influence of channel Reynolds number and radius of curvature on dean flow velocity is investigated. PDMS (Poly Dimethyl Siloxane) is chosen as a material because of its flexibility and biocompatibility nature. The optimized spiral microchannel can be used for effective cell focusing and separation corresponding to their size depends on lateral hydrodynamic forces. [ABSTRACT FROM AUTHOR]

This initiative seeks to reduce the number of fatalities caused by terrorist attacks Therefore, this issue can be resolved by creating an RF-based spy robot with a wireless camera, making it simpler to research rivals as required. This robot can covertly infiltrate hostile terrain and transmit data to us using a wireless camera. The movement of the moving robot is controlled by commands sent from a handheld RF transmitter to an RF receiver mounted on the robot. These robots are utilized to take the place of soldiers in war areas because human life is always regarded highly. Additionally, this spy robot can be used in luxury hotels, shopping centers, and jewelry showrooms. where threats from terrorists or trespassers could exist, it can be used to learn about hostile terrain during conflict, keep track of that information from a safe distance, and securely plan a counterattack and tracking the sites of terrorist officialdoms and then scheduling an attack for the right moment and it can be used for surveillance of any area affected by a disaster that people are unable to access. [ABSTRACT FROM AUTHOR]

Generating forecast is without doubt one of the most important zones in any industry. Consumers-oriented merchandise encounter undetermined demands, insufficiency of historical information and brief life cycle, these elements challenges the forecasting techniques to provide precise result. In this paper, the instance of Big Mart has been discussed to predict the sales of different items and for understanding the effects of different factors which effect the item‟s sales. We performed the statistical analysis on the dataset using statistical tool "SPSS". Predictive model is built using CatBoost which is applied for sales prediction. The proposed model achieved high level of accuracy as compared to other machine learning algorithms. [ABSTRACT FROM AUTHOR]

Magnetically Impelled Arc Butt (MIAB) welding is a solid-state pressure welding for joining tubes and pipes that uses electromagnetic force to produce heat and the upsetting of joining the components. The magnetic flux density is a critical influencing parameter in this welding process since it governs arc rotation and improves the weld quality of the material. Other MIAB welding variables, including the exciting coil current, coil position, and the gap size between the tubes, also influence the magnetic flux density. This work aims to analyze the magnetic flux density distribution in MIAB welding with the different thicknesses (such as 2, 3, 4 and 5 mm) of T11 and T91 tubes with an outer diameter of 45 mm. The finite element method (FEM) utilized for simulating the distribution of magnetic flux density in MIAB welding with the constant input parameters are coil position from the weld region is 20 mm, the air gap distance between the tube is 2 mm, and exciting current on the coil is 2A. From the analysis, the higher magnetic flux density value of 1.9377 T is obtained for the lower thickness of 2 mm. The magnetic flux density values are 1.5166 T, 1.1834 T and 1.0091 T for the tube thickness of 3, 4 and 5 mm, respectively. It is found that the magnetic flux density increases with the lower tube thickness, which leads to improved arc rotation. [ABSTRACT FROM AUTHOR]

Optical transmission characterization has been done in the vacuum evaporated thin films of Ge25S75-xSbx (x = 0, 10) chalcogenides in the wavelength range 300 to 3100 nm. Swanepoel's method is used for the analysis of various linear optical parameters. Tauc's relation is used for the estimation of optical band gap (Eg). Recent optical applications of present glassy materials have been discussed on the basis of linear optical parameters. [ABSTRACT FROM AUTHOR]

The passive and active drying capabilities of okra (Abelmoschus Esculentus) were examined in the current study using heat pump drying, open sun drying, and greenhouse drying with two distinct glazing materials (Drip Lock sheet and UV Polyethylene sheet). The fastest drying method is heat pump drying, which has a drying rate of 4.63 g/h. While UV polyethylene sheet active mode and drip lock sheet passive mode have drying rates of 4.07 g/h, drip lock greenhouse active mode had a drying rate of 4.12 g/h. Open sun drying had a lower drying rate of 2.68 g/h compared to other drying modes. According to the statistical analysis, the Prakash and Kumar model is the most effective model for drying okra among all drying methods from the chosen twelve mathematical models. [ABSTRACT FROM AUTHOR]

Studies on the thin layer drying kinetics of okra (Abelmoschus esculentus) in passive and active methods with open, heat pump dry, and greenhouse dry using various film materials, including UV Polyethylene sheet and drip lock film, have been conducted. Food products are dried to lower their moisture content, increase shelf life, and decrease post-harvest waste. In total, it took 16 hours for the okra to dry under open sun drying (OSD), 14 hours in an UV poly-ethylene sheet greenhouse dryer operating in passive method (UVPM), 13 hours in a drip lock sheet greenhouse dryer operating in passive method (DLPM), and 12 hours in an UV polyethylene sheet greenhouse dryer operating in active mode. HPD achieved the highest dryer efficiency of 38.78% whereas Drip Lock Sheet Active Mode (DLAM) greenhouse drying had the lowest efficiency of 14.15%. When drying okra, HPD produced a lower effective moisture diffusivity of 1.04 x 10−10 m2/s compared to other modes, which produced a higher effective moisture diffusivity of 2.09 x 10−10 m2/s. The Heat Pump dryer (HPD) exhibited a higher Specific Moisture Extraction Rate (SMER) of 2.60 kg/kWh when compared to conventional drying methods. It was discovered that HPD dried materials more quickly than greenhouse drying, yet greenhouse drying is more economical from an economic standpoint. [ABSTRACT FROM AUTHOR]

The analysis of rotor dynamic aspects of a gas turbine is very much essential before the start of manufacturing. For better accuracy often designers look for 3D representations of the rotor models, however, these models have its advantages as well as disadvantages. The major disadvantages are the model size increases significantly. However, this issue can be addressed by model reduction techniques such as the use of external superelement (SE) which is obtained by component mode synthesis (CMS) or similar approaches for model reduction. The major limitation of this technique is that: Analysis needs a detailed 3D CAD model before the start of analysis. So, when we do not have the detailed 3D models of compressors and turbines or we want to study the effect of many design modifications on the performance of a rotor shaft system, while keeping the complexity low an equivalent mass representation for turbine and compressor systems are very useful. In this paper we have used an equivalent mass representation of a small gas turbine rotor and studied different performance performances like stability, unbalance response and modal frequencies while using different values for support systems of a rotor shaft system. Using parametric study, we could successfully propose the design modification for changing peak amplitudes as well as natural frequencies of the rotor dynamic system supported with a foil bearing. [ABSTRACT FROM AUTHOR]

Organic/inorganic nanocomposites (NC'S) are exceedingly promising materials for the development of opto-electronic devices. The production of NC'S based materials has many advantages mainly economical, development of foldable and huge area device fabrication. Poly Vinyl Alcohol (PVA) is a possible material possessing high dielectric potency, better charge holding capacity along with variable opto-electronic properties with dopant. Herein, we report the development of PVA-Cu2Se NC'S via thought focus integration of copper selenide (Cu2Se) Nano Particle (NP) in to PVA host matrix using aqueous solvent casting. The effect of NP concentration on structure, optical and opto-electronic properties have also been valued and considerably presented. The doped PVA films display increased light absorption in the near visible region and change in the position in the absorption edge. The energy band gap of PVA is reduced upon doping. The obtained outcome indicates that small bandgap PVA with better film-making capability and structural stability will address the concerns of conjugated polymers. The developed composite is of organized structure, which offers new functional hybrids for various opto-electronic applications. [ABSTRACT FROM AUTHOR]

Neem wood used many structural applications due to its coarse grain with interlocking fibers leads to excellent mechanical properties with a very good life. However, wood structures are exposed to various environmental conditions, so it is necessary to investigate the effect of time and temperature for different stacking sequences. This paper aims to explore the importance of time and temperature of neem wood veneer epoxy composites at various stacking sequence and interfacial bonding. The Dynamic Mechanical Analyzer used to study short term creep at a nitrogen environment using a three-point bending condition. The result shows neat neem wood veneer exhibit a higher percentage of strain as compared to neem wood epoxy composites. On the other hand, the stacking sequence having significant changes in dynamic mechanical and creep studies, storage modulus (G') & loss modulus (G") increases along the wood fiber direction with minor load-bearing capacity in lateral direction. By varying the orientation of the wood veneer mechanical and thermo-mechanical properties improved in both longitudinal and lateral direction. [ABSTRACT FROM AUTHOR]

The aim of the work is to predict the credit card approval using XGBoost algorithm in comparison with logistic regression to improve accuracy. Accuracy is performed with the dataset size of 48678. Prediction of credit card approval using XGboost Classifier where the number of samples (N = 10) and logistic regression where the number of samples (N = 10) algorithms. The dataset contains 19 attributes that help in whether the person gets the approval of a credit card or not. The Accuracy of XGboost Classifier is 87.97% and loss is 12.04% which appears to be better than Logistic Regression accuracy is 65.16 % and loss is 34.84 %. There is a significant difference in Accuracy (P = 0.487). Conclusion: The results show that the Novel XGboost Classifier is significantly better than Logistic Regression (LR) for Credit Card Approval Prediction in terms of accuracy. [ABSTRACT FROM AUTHOR]

In recent times, Aluminum Matrix Composites (AMCs) are most commonly used in many industrial works. For Al6063, easiest technique for the fabrication will be the stir casting method. The stir casting techniqueimporves the homogenity of reinforcement at final stage of the casting which enhances the intended properties of composite materials. However, the stirring effect affects the homogeneity of the particle distribution in the composite is not well studied. Even though Aluminium has been a game changer in creating light weight aircraft durable material. It can further be enhanced for creating a rigid, durable long lasting, light weight compounds. The purpose of this Matrix is to create a better source for light weight exo-skeleton. Exo-skeleton will be a pocket rocket for a military during battles. They will relieve the stress in carring the equipment and weaponry of a soldier for a period of time. The mechanical part of the exoskeleton ie the frame must be durable to with harsh battle conditions and must be wear resistant. By reinforcement with suitable compound the strength and wear resistant properties are enhanced. [ABSTRACT FROM AUTHOR]

Today's trend in fiber composite research is widely increasing and by which natural fiber is also an alternative way to overcome artificial fiber. When sisal and ramie fibers are combined with a matrix polyester material can be created that is more competitive with the glass fiber. A fiber composite is made up of two phases one is a matrix and another one is reinforcement. Epoxy hardener Hy 951+Epoxy resin Ly 556 is employed with matrix phases. Natural fibers have the following advantages: greater obtainable, long durability, and specific resistance. The major function of a fiber matrix is to prevent the fiber from physical damage or external damage and to transfer stress between the reinforcing matrix, whereas the presence of fibers in a composite improves mechanical properties such as stiffness, strength, and so on. Due to their environmentally favorable features, sisal and ramie fiber composites are gaining popularity these days. Artificial fibers could be replaced with natural fibers. Natural fibers are alternatives to glass fiber and polymers. The sisal and ramie fiber reinforcement phase has not continuously been in shape. When differentiate to the phase of the matrix, it usually has high strength. The features of composites are determined by factors such as fiber extraction, surface modification, and composite synthesis. To attain the needed strength, fiber length, orientation, concentration, dispersion, aspect ratios, matrix selection, and matrix chemistry must all be considered during synthesis. [ABSTRACT FROM AUTHOR]

The aim of this paper is mining serendipitous drug usage to validate and generate drug repositioning hypotheses from social media. Materials and Methods: Two machine learning algorithms svm with sample size=12 and adaboost algorithm with sample size=12. Results: The support vector machine algorithm has shown more accuracy of (96. 66%) in reducing the false positive rates when compared with Adaboost algorithm accuracy(84.6%). The pre-test was calculated with a g-power value = 80% and threshold 0. 05% confidence interval of 95% mean and standard deviation by using the G-power tool. t is found that the svm algorithm has more accuracy percentage when compared with the Adaboost algorithm. [ABSTRACT FROM AUTHOR]

The project's goal is to identify vehicles, measure count and provide results as the vehicle count. Materials and methods: The performance measure for highest accuracy rate in novel vehicle detection using back propagation neural network (N=10)over Oriented fast and rotated brief which identifies and counts distance. identification can be done using an image set to distinguish vehicles. The Gpower test used in about 85% (g power setting parameters: α=0.05 and power=0.85) Result: Back propagation neural network (94.32%) identifies vehicle and measures the count accurately over Oriented fast and rotated brief (91.16%) with a level of significance as 0.506 (Two tailed,p>0.05). Conclusion: The accuracy rate of Back propagation neural network is higher compared with that of oriented fast and rotated brief. [ABSTRACT FROM AUTHOR]

The primary goal of this work is to build a novel sequential multiplier and mixed type multiplier to examine power consumption. Material and Methods:The ISE Design suite was used to simulate and verify the multiplier's design. The power values were acquired by altering the input values of a circuit. In this experiment, 20 distinct values are used. For the analysis of the power used by the multiplier with a g power of 80%, 20 samples from each group were collected. Result:Compared to the minimum power consumption of sequential multipliers, which is 37.9226 mW, mixed style multipliers consume 21.969 mW. The significance value of two groups is (p < 0.05). Conclusion: From the analysis it was observed that a mixed style multiplier is significantly better than the sequential multiplier in the ISE design suite VLSI. [ABSTRACT FROM AUTHOR]

The impartial of this research article is to employ an efficient anti-scamming strategy for fingerprint identification with improved accuracy rate by using Enhanced Patch Based Deep Learning method in comparison with Semantic Segmentation method. The data set in this paper utilizes the publicly available PolyU fingerprint database. The anti-scamming technique for fingerprint recognition had a sample size of 170 (Groups 1 and 2 each had 85 participants), and the computation was done using G-power 0.8 with alpha and beta values of 0.05 and 0.2 and a confidence interval of 95%. Enhanced Patch Based Deep Learning method with number of samples (N=10) and Semantic Segmentation method with number of samples (N=10) both conduct an anti-scamming strategy for fingerprint identification with enhanced accuracy rate. When compared to Semantic Segmentation technique, which is 94.382, the Enhanced Patch Based Deep Learning approach classifier has a greater accuracy rate of 97.245. The significance value for the study is 0.05, i.e., p=0.0268. Enhanced Patch Based Deep Learning method affords improved outcomes in accuracy rate when compared to Semantic Segmentation method for anti-scamming strategy for fingerprint identification [ABSTRACT FROM AUTHOR]

The work's goal is to use Gradient Boosting Machines Algorithm to more accurately anticipate stock prices regarding the stock values when compared to the Random Forest Algorithm. Materials and Methods For the purpose of accurately forecasting stock values, iterations of the Gradient Boosting Machines (GBM) and Random Forest algorithms with sample sizes of 20 and 20 were performed, respectively. The Gradient Boosting Machines Algorithm's Novel Loss Function, which is based on prior stock values, helps to reduce the total prediction error. Results: When compared to the accuracy of the Random Forest Method (83.6%), the GBM algorithm has a much higher accuracy (92.3%). With a significance score of 0.000 (p<0.05, 2-tailed), the study groups differ statistically significantly from one another. Conclusion: GBM method with novel loss function aids in forecasting stock values with a higher degree of accuracy. [ABSTRACT FROM AUTHOR]

The main aim of our research is to design the dedicated hydraulic power pack for the wiper system in sendzimir mill. The sendzimir mill is the mother unit of CRM (cold rolling mill) which is used to roll the metal sheets (stainless steel). The wiper system is used to wipe out the excess coolants from the strips. If wiping is not done efficiently it will be hazardous to the environment and to workers when subjected to annealing. The formation of a thin coolant layer on cold-rolled metal sheets leads to an improper metal finish with oil patches. So, each drop of coolant should be wiped out before the coiling of cold-rolled strips. The present hydraulic system for the wiper was installed in the auxiliary hydraulic unit of the sendzimir mill. Since the entire rolling system of the sendzimir mill is carried out using the auxiliary hydraulic unit there will be pressure drops in the pumps which lead to poor performance of the wiping system. Hence in order to increase the performance of the wiper system a new dedicated hydraulic circuit is designed. [ABSTRACT FROM AUTHOR]

The effect of multiple dimples on an aerofoil are manifold. The aerofoil under study was a NACA 0015 aerofoil designed as the blade of a vertical axis wind turbine. In theory, the dimples, as seen in golf balls help smoothen the flow over the surface of the blades and in turn makes the flow adhere to the surface of the blade for longer. This leads to decrease in the drag forces and turbulence over the blade. This leads to there being less resistance from air to the rotation of the blades and hence, theoretically, the blade should be able to spin at a faster pace, hence generating more power at a lower wind speed. In order to test this theory, the dimpled blade was tested against a smooth blade under the same conditions and the results were achieved both computationally and practically. In both the cases, the dimpled blade was shown to have more benefits and produce more power. Under the testing conditions of wind speed 15m/s, it was noted that the blade velocity increased to 7m/s for the dimpled blade as compared to the blade velocity of 6m/s of the smooth blade. The theory that the dimples assists the blade to move faster was substantiated with practical results. [ABSTRACT FROM AUTHOR]

The objective of this study was to pick the qualities of an AA2024 and silicon nitride-upheld composite that might be used in various present-day applications. Individual and different strongholds were used to construct the hardness and impact characteristics of aluminum 2024 framework using the high impactable projecting strategy. The made aluminum metal systems, microstructure, thickness, hardness, and impact strength properties, Corrosion resistance were investigated. The extension of silicon nitride assembles the hardness and impact toughness, according to the disclosures for morphological assessment. It was revealed the two strongholds were added to the nano powder particles in structure materials, the composites hardness and impact strength extended, while the metal organization composite's thickness reduced, making it fitting for low weight and high strength applications. HCl, NaCl and regular water were utilized in the utilization test. The eventual outcomes of the test were stood out from the potential gains of various courses of action. [ABSTRACT FROM AUTHOR]

In modern manufacturing industries, Internet of Things (IoT) has become vital for improved data communication, productivity and profitability. An IoT system adopted in most of the industries across the world varies due to usage of different IoT platforms, which emphasize the need for standard IoT platform. An attempt was made to empower Return of Investment (ROI) from Gravity Die Casting (GDC) system by financial assessment of real time production process. Industry 4.0 was preferred as the standard platform for remote monitoring of GDC system. In this study, vertical integration of data across an industry was promoted and factors associated between financial Key Performance Indicators (KPI) such as Overall Equipment Effectiveness (OEE), die preheat temperature, solidification time, energy consumption and real time data has been established. The system for remote monitoring of GDC machine was developed in PTC ThingWorx. Machine data and fixed data are integrated to determine break-even cost and quantity for manufacturing a product in GDC machine. Standard user interfaces for top, middle and bottom level management are developed and validated for GDC machine. The proposed and developed system for remote monitoring of GDC machine covers the financial assessment of production process and also showed improved communication and productivity. As a result, implementation of IoT system for GDC machine improved quality of products, reduce set up time and maintenance time losses. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) increases the visibility and awareness of utility consumption and remote monitoring system for individual machine. IoT supports for proper predictive maintenance by collecting and analyzing real time consumption data for every individual machine unit through various sensors. IoT was used to replace the preventive maintenance system by predictive maintenance system of factory and it is being installed by most of the leading companies. Analysis on real time data improves energy efficiency and competitiveness of the leading manufacturing companies. An attempt was performed by directly connecting IoT system with individual machine as well as with the control panel of the system to retrieve data. A framework was developed to support the integration of real-time energy data into a factory information tools and platforms. In this study, real time remote monitoring system was developed to monitor the electrical energy parameters of the Computer Numerical Control (CNC) machine. ThingWorx user interface was adopted for smart and remote real time energy monitoring. Practical model of IoT based energy monitoring system accurately determined the energy consumption of the industry and reduced the wastage of energy. [ABSTRACT FROM AUTHOR]

Product Life cycle Management (PLM) is an effective business strategy which is used to integrate data, processes, human resources and business systems by extending business across the product life cycle. In recent days, products get smarter where most of the products are embedded with electronics and its associated software. Products are made smarter by implementing the concepts of Internet of Things (IoT). Monitoring the product data from ideation to disposal stage is important for further analysis of a product. Data management of a product with dynamic and individual customer requirement information is the major challenge in a manufacturing industry. Implementation of PLM is one of the suggested method for recording the information about the product throughout its life cycle. In this present study, PLM implemented in an IoT enabled product with the use of Aras Innovator software to retrieve data of the product for further process. With predominant knowledge about the activities of the industry, a work environment can be incorporated within the PLM system. Implementation of PLM system in an enterprise for IoT products were resulted in improved control of the systems in a manufacturing industry. [ABSTRACT FROM AUTHOR]