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Data mining is a new technology with enormous potential to focus on important information and collected customer behaviour. Healthcare services used to have incredible potential for data mining because of this exponential development in the number of electronic health records. Medical data is health-related data related to regular patient care and clinical trial program. The feature selection process is choosing the relevant features for efficient disease diagnosis. With healthcare data, the classification and clustering methods had used for efficient disease diagnosis. In this paper, several researchers researched different disease diagnosis methods. However, time complexity had not reduced, and existing disease diagnosis methods did not enhance the accuracy. To address the proposed methods and different disease diagnosis schemes appraised.

Pistachios are a tremendous source of fiber, protein, antioxidants, healthy fats, and other minerals like thiamine and vitamin B6. They may help people lose weight, lower cholesterol, and blood sugar levels, lead to better gut, eye, and blood vessel health. The two main varieties farmed and exported in Turkey are kirmizi and siirt pistachios. Understanding how to detect the type of pistachio is essential as it plays an important role in trade. In this study, it is aimed to classify these two types of pistachios and analyze the performance of the various small-scale machine learning algorithms. 2148 sample images for these two kinds of pistachios were considered for this study which includes 1232 of Kirmizi type and 916 of Siirt type. In order to evaluate the model fairly, stratified random sampling is applied on the dataset. For feature extraction, we used deep neural network-based embeddings to acquire the vector representation of images. The classification of pistachio species is then performed using a variety of small-scale machine learning algorithms29,31 that have been trained using these feature vectors. As a result of this study, the success rate obtained from Logistic Regression through features extracted from the penultimate layer of Painters network is 97.20%. The performance of the models was evaluated through Class Accuracy, Precision, Recall, F1 Score, and values of Area under the curve (AUC). The outcomes show that the method suggested in this study may quickly and precisely identify different varieties of pistachios while also meeting agricultural production needs.

Formation of oil-suspended sediment aggregates (OSAs) is believed to be one of the natural cleaning processes in the marine environment. In this study, we have investigated the formation processes of OSAs under different mixing periods (continuous mixing and with the addition of sediments in between), oil-sediment ratios (1:1, 1:2 and 2:1) and crude oils (Arabian Light (AL), Kuwait (KW) and Murban (MB)). The results revealed that size of OSAs significantly increased (up to ≈ 1.41 mm) with the addition of sediments. Aggregates (total 36) were extracted for n-alkanes and polycyclic aromatic hydrocarbons to quantify and assess their weathering and toxic levels. The maximum n-alkane depletion was 84% (111-02), 94% (212-02) and 84% (321-02) and PAH depletion was ≈ 72% (111-02), 79% (212-02) and 81% (311-03) for the OSAs of AL, KW and MB crude oils, respectively, for the different samples considered, indicating that n-alkanes were depleted relatively higher than the PAHs. The highest depletion of both n-alkane and PAHs has occurred in OSAs of 10-h continuous mixing. The depletion of both n-alkane and PAHs reduced after the addition of sediments, however, escalated the growth of OSAs, resulting in bigger size OSAs. The concentration of PAHs of all 36 OSAs is greater than 5000 ng/g, indicating very high PAH pollution. Though the formation of OSAs helps in cleaning the spill sites, the carcinogenic threat to the marine ecosystem caused by these OSAs cannot be ignored. This study is funded by the Department of Science and Technology through Climate Change Programme to VS.

The present study reports the ability of the medicinal plant Abutilon indicum (AI) stem extract active fractions to induce apoptosis in Human U87 glioblastoma cells. Cytotoxicity guided extraction and fractionation of AI stem extracts aided in identifying and isolating the polyphenolic compound, Gallic acid (GA). Isobologram analysis revealed that, cytotoxic activity of FrF was due to synergistic effect between GA and the other components of FrF. FrF induced apoptosis correlated with increased intracellular ROS expression and DNA damage. The study for the first time proves the synergetic effect between GA and phytoconstituents of enriched AI stem fractions.

Head injuries are highly impactable for motorized two wheeler users causing injury, disabilities and sometimes leading to death. Helmets are manufactured using different materials especially it depends on applications in which it is utilized. In this work, initially the helmet is modelled with the similar dimensions as per the available manufacturing data. The main objective of this work is to analyse the performance of helmet with five different materials such as ACRYLONITRILE BUTADIENE STYRENE (ABS), POLYCARBONATE (PC), POLYSTYRENE, ABS + PC PLASTIC and Epoxy E-Glass. The modelled helmet is subjected to static and dynamic analyses for choosing the best material by evaluating its mechanical strength such as total deformation, strain energy and equivalent stress using ANSYS. In static analysis, helmet model is subjected with different loads with different conditions to calculate total deformation, strain energy and equivalent energy. While considering dynamic analysis, the helmet model is subjected to loading by covering with two rectangular plates. One side is fixed and other is dropped from a height of 3 m. ABS and Polycarbonate produces more or less same deformation when compared with other materials which results in high strain energy.

Internet Gateway(IGW) main role is detecting availability nodes and providing internet to Mobile Ad Hoc Network(MANET) have whenever connected to internet. Discovery time of gateway is changed based on the throughput and packet delay. Many of the situations the mobile nodes are have fixed host connection to the internet using minimum hop path, it is not good for waiting packets because of that packets are have longer path interface queue. This research paper object is avoided above the problem mentioning using a novel approach of SPAHN (Solving Problem of Ad-Hoc Network). This paper mainly focus is classify the routing protocols of load-aware in MANET and from this classify discover the proactive load-aware gateway (PL-AG) from a device into interface queue size and min-hop-metric. This novel approach has been allowing and gives better handoff between two internet gateways for fixed host seamless connectivity. We justify the performance of the SPAHN approach using two metrics like average end-to-end delay and throughput based on this examination the SPAHN system yield good simulation results comparably existing systems.

Photovoltaic power generation is a potential alternative energy source that offers several benefits over other alternative energy sources such as wind, sun, ocean, biomass, geothermal, and so on. Multilevel inverters are essential for power conversion in solar power generation. These multilevel inverters employ three distinct topologies: diode-clamped (neutral-point clamped) inverter, capacitor-clamped (flying capacitor) inverter, and cascaded H-bridge multilevel inverter. The cascaded H-bridge multilevel inverter is more appropriate for photovoltaic applications than the other two topologies. The proposed system asymmetrical cascaded multilevel inverter (ACMLI) is energized using a photovoltaic system (PV). A three-phase cascaded H-bridge fifteen-level inverter for grid-connected solar systems is given in this study utilizing a proportional integral controller. The harmonic distortion was removed using a multicarrier pulse width modulation method. The MATLAB/Simulink is used to simulate the performance of a three-phase cascaded H-bridge fifteen-level inverter in terms of harmonic content and number of switches. To test the performance of the designed system, a hardware prototype was created. From the obtained results, the proposed method reduces the switch count, harmonic distortion, and rejects the external disturbances of input and output variables.

Plants image preprocessing is a challenge as it is emerging area in the research for various disease detections and diagnoses which aids for the agriculturist for easy diagnosis of disease in percentage and applies appropriate fertilizers to get the disease-free crop. Preprocessing is being major operation with respect to image data at lowest level of abstraction. The aim of the preprocessing is to enhance the image features to avoid the distortion. Image preprocessing is very necessary aspect as the image should not have any impurities, and it is accomplished to be better for the further process such as segmentation, feature extraction, and classification. Collection of data is challenging because of the type of device the image captured and factors like climatic condition, etc. The factors like noise and other aspects need to be eliminated. It is necessary for the preprocessing to remove noise. Preprocessing is the process which is used to enhance the evaluation and interpretation of an image. Image preprocessing is executed systematically; then, the further detection of disease in plants will be successful.

It additionally can distinguish if bugs or bugs are inside a 10 m distance of the plant. We will handle our info picture by utilizing PC programming; the picture will be gathered from the rancher. Illness location includes the means like taking image of influenced territory and gives greater lucidity on the photos. The photos are edge to specific qualities after that identified picture limit is covered over the first image. The picture is bunched dependent on the highlights utilizing k-implies grouping, GLCM calculation would produce the highlights from the pictures.