Recognizing phishing site using Machine Learning- A Comparative Approach using MultinomialNB & Logistic Regression

Phishing is a method of trying to collect personal information like login credentials or credit card information using deceptive e-mails or websites. Phishing sites are made to hoodwink clueless clients into intuition they are on an authentic site. The lawbreakers will invest a great deal of energy causing the site to appear as valid as could really be expected and numerous locales will show up practically undefined from the genuine article. This paper proposes a methodology to detect boycotted URLs using machine learning algorithms so that people can be frightened while examining or getting to a particular site. In this project we have using machine learning algorithms such MultinomialNB and Logistic Regression. We used distinctive data and text pre-processing techniques to improve precision and accuracy. An app is developed as the end product of this research work

A Visual Computing Unified Application Using Deep Learning and Computer Vision Techniques

Vision Studio aims to utilize a diverse range of modern deep learning and computer vision principles and techniques to provide a broad array of functionalities in image and video processing. Deep learning is a distinct class of machine learning algorithms that utilize multiple layers to gradually extract more advanced features from raw input. This is beneficial when using a matrix as input for pixels in a photo or frames in a video. Computer vision is a field of artificial intelligence that teaches computers to interpret and comprehend the visual domain. The main functions implemented include deepfake creation, digital ageing (de-ageing), image animation, and deepfake detection. Deepfake creation allows users to utilize deep learning methods, particularly autoencoders, to overlay source images onto a target video. This creates a video of the source person imitating or saying things that the target person does. Digital aging utilizes generative adversarial networks (GANs) to digitally simulate the aging process of an individual. Image animation utilizes first-order motion models to create highly realistic animations from a source image and driving video. Deepfake detection is achieved by using advanced and highly efficient convolutional neural networks (CNNs), primarily employing the EfficientNet family of models

A Novel Approach and Implementation Concept For A Nanosatellite Backup on-Board Computer

STUDSAT-2 (STUDENT SATellite-2) is a one-of-a-kind satellite technology project undertaken by Indian undergraduate students. The aim of this project is to demonstrate the On-Board Computer's redundancy (OBC). The OBC subsystem is one of the many subsystems that make up the STUDSAT-2 satellite system. It is critical to the satellite's operation. Even a minor malfunction in this system could lead to the mission's complete failure. As a result, OBC redundancy management is required to overcome this. As a result, the proposed model of Backup On-Board Computer for STUDSAT-2 was planned and built by incorporating redundancy in both software and hardware, thus increasing the OBC's reliability

Experimental and CFD analysis of a gas-lubricated foil thrust bearing for various foil configurations

Thrust foil bearings operating at hydrodynamic conditions are self-acting (aerodynamic) bearings that support high-speed shafts at mild loading conditions with air as a lubricant and are generally used in low-power gas turbines. This paper presents an experimental study and a detailed computational analysis of dynamic characteristics of the foil thrust bearing (FTB) in terms of load-carrying capabilities as a function of thrust runner speed and gap between the bearing assembly and the runner by considering the effect of bearing parameters such as number of foils, shape of the foils, and assembly of foils on the bearing pad. The parametric study was conducted on a newly conceptualized bearing test rig capable of rotating up to 45,000 rpm speeds that measured the axial loads of the air foil thrust bearings (AFTB). The computational model of the foil thrust bearings for various configurations with top foils is simulated using multiphysics software for foil deflections and pressure distributions on the foil surface. The numerical results were compared with the experimental values, while the air foil thrust bearings with multilayered foils called cascaded foils (patented) had higher load capability in comparison to other conventional bearing models

Friction stir welding of SS 316 LN and Nitronic 50 jacket sections for application in superconducting fusion magnet systems

Article explores the possibility of using friction stir welding (FSW) to join jacket web sections of two nitrogen-containing stainless steels for housing internally cooled superconducting cables which are utilized to generate magnetic fields in tokamak type fusion reactor systems. It has been shown that the FSW fabricated SS 316 LN jackets possessed the required strength and magnetic properties critical to this application

Pharmacological hypogonadism impairs molecular transducers of exercise-induced muscle growth in humans

Background: The relative role of skeletal muscle mechano-transduction in comparison with systemic hormones, such as testosterone (T), in regulating hypertrophic responses to exercise is contentious. We investigated the mechanistic effects of chemical endogenous T depletion adjuvant to 6weeks of resistance exercise training (RET) on muscle mass, function, myogenic regulatory factors, and muscle anabolic signalling in younger men. Methods: Non-hypogonadal men (n=16; 18–30years) were randomized in a double-blinded fashion to receive placebo (P, saline n=8) or the GnRH analogue, Goserelin [Zoladex (Z), 3.6mg, n=8], injections, before 6weeks of supervised whole-body RET. Participants underwent dual-energy X-ray absorptiometry (DXA), ultrasound of m. vastus lateralis (VL), and VL biopsies for assessment of cumulative muscle protein synthesis (MPS), myogenic gene expression, and anabolic signalling pathway responses. Results: Zoladex suppressed endogenous T to within the hypogonadal range and was well tolerated; suppression was associated with blunted fat free mass [Z: 55.4±2.8 to 55.8±3.1kg, P=0.61 vs. P: 55.9±1.7 to 57.4±1.7kg, P=0.006, effect size (ES)=0.31], composite strength (Z: 40±2.3% vs. P: 49.8±3.3%, P=0.03, ES=1.4), and muscle thickness (Z: 2.7±0.4 to 2.69±0.36cm, P>0.99 vs. P: 2.74±0.32 to 2.91±0.32cm, P0.99 vs. P: 1.9 fold, P0.99 vs. P: 4.7 fold, P=0.0005, ES=0.68; myogenin: Z: 1.3 fold, P>0.99 vs. P: 2.7 fold, P=0.002, ES=0.72), RNA/DNA (Z: 0.47±0.03 to 0.53±0.03, P=0.31 vs. P: 0.50±0.01 to 0.64±0.04, P=0.003, ES=0.72), and RNA/ASP (Z: 5.8±0.4 to 6.8±0.5, P>0.99 vs. P: 6.5±0.2 to 8.9±1.1, P=0.008, ES=0.63) ratios, as well as acute RET-induced phosphorylation of growth signalling proteins (e.g. AKTser473: Z: 2.74±0.6, P=0.2 vs. P: 5.5±1.1 fold change, P0.99 vs. P: 3.6±1 fold change, P=0.002, ES=0.53). Both MPS (Z: 1.45±0.11 to 1.50±0.06%·day−1, P=0.99 vs. P: 1.5±0.12 to 2.0±0.15%·day−1, P=0.01, ES=0.97) and (extrapolated) muscle protein breakdown (Z: 93.16±7.8 vs. P: 129.1±13.8g·day−1, P=0.04, ES=0.92) were reduced with hypogonadism result in lower net protein turnover (3.9±1.1 vs. 1.2±1.1g·day−1, P=0.04, ES=0.95). Conclusions: We conclude that endogenous T sufficiency has a central role in the up-regulation of molecular transducers of RET-induced muscle hypertrophy in humans that cannot be overcome by muscle mechano-transduction alone

Testosterone therapy induces molecular programming augmenting physiological adaptations to resistance exercise in older men

Background: The andropause is associated with declines in serum testosterone (T), loss of muscle mass (sarcopenia) and frailty. Two major interventions purported to offset sarcopenia are anabolic steroid therapies and resistance exercise training (RET). Nonetheless, the efficacy, and physiological and molecular impacts of T therapy adjuvant to short-term RET remain poorly defined.Methods: Eighteen non-hypogonadal healthy older men, 65-75 y, were assigned in a random double-blinded fashion to receive, bi-weekly, either placebo (P, saline, n=9) or T (Sustanon 250 mg, n=9) injections over 6-weeks whole-body RET (3-sets of 8-10 reps at 80% 1-RM). Subjects underwent dual-energy x-ray absorptiometry, ultrasound of vastus lateralis (VL) muscle architecture, and knee-extensor isometric muscle force tests; VL muscle biopsies were taken to quantify myogenic/anabolic gene expression, anabolic signalling, muscle protein synthesis (D2O) and breakdown (extrapolated).Results: T adjuvant to RET, augmented total fat free mass (FFM) (P=0.007), legs fat free mass (P=0.02), and appendicular FFM (P=0.001) gains, while decreasing total fat mass (P=0.02). Augmentations in VL muscle thickness, fascicle length, and quadriceps cross-section area with RET occured to a greater extent in T (P less than 0.05).Total strength (P=0.0009) and maximal voluntary contract (e.g. knee extension at 70°) (P=0.002) increased significantly more in the T group. Mechanistically, both muscle protein synthesis rates (T: 2.13±0.21%·day−1 vs. P: 1.34±0.13%·day−1, P=0.0009) and absolute breakdown rates (T: 140.2±15.8 vs. P: 90.2±11.7g·day-1, P=0.02) were elevated with T therapy, which led to higher net turnover and protein accretion in the T group (T: 8.3±1.4g·day-1 vs. P: 1.9±1.2 g·day-1, P=0.004). Increases in ribosomal biogenesis (RNA:DNA ratio); mRNA expression relating to T metabolism (Androgen Receptor: 1.4-fold; Srd5a1: 1.6-fold; AKR1C3: 2.1-fold; HSD17β3: 2-fold); IGF-1-signalling (IGF-1Ea (3.5-fold), IGF-1Ec (3-fold) and myogenic regulatory factors (MRF); as well the activity of anabolic signalling (e.g. mTOR, AKT, RPS6; P less than 0.05) were all upregulated with T therapy. Only T up-regulated mitochondrial citrate synthase activity (P=0.03) and transcription factor A (Tfam) (1.41±0.2-fold, P=0.0002), in addition to PGC1-α mRNA (1.19±0.21-fold, P=0.037).Conclusions: Administration of T adjuvant to RET enhanced skeletal muscle mass and performance, while upregulating myogenic gene programming, myocellular translational efficiency and capacity - collectively resulting in higher protein turnover, and net protein accretion. T coupled with RET is an effective short-term intervention to improve muscle mass/ function in older non-hypogonadal men

Hybrid Genetic Algorithm and Modified-Particle Swarm Optimization Algorithm (GA-MPSO) for Predicting Scheduling Virtual Machines in Educational Cloud Platforms

Cloud computing is expanding gradually as the number of educational applications is rapidly increasing. To get Educational cloud services, internet connectivity is predominantly important and Cloud Environment uses one of the basic technology to manage the Physical servers effectively ie; Virtualization Technology. In Cloud Computing, the data centers host numerous Virtual Machines (VMs) on top of the Servers. Due to the rapid growth of Educational platforms, the workload of the VM is computationally getting increased. In the Cloud Educational platforms, to execute the jobs IT resources are provisioned over the network. Since the data generated from the client-side is dynamic in nature, it is difficult to allocate the computational resources efficiently. So to enhance the energy efficiency and to provide the resources in an optimized way, a VM Scheduling mechanism with Hybrid Genetic Algorithm-Modified Particle Swarm Optimization (GA-MPSO) is proposed in this work to achieve QoS parameters like reduced Energy consumption, SLA violation, and cost reduction over the heterogeneous environments. The Hybrid G-MPSO develops the optimal range and improves the best range of scheduling the Virtual resources to VMs from Physical Machines (PMs). The proposed approach, when compared to other VM scheduling algorithms, it intensifies the energy consumption to 105KWH, SLA violation rate of 0.08%, reduces the migrations count to 2122, and consumes the overall cost of 2567.68$. The different scheduling methods for VMs are evaluated against the results, which show that the Hybrid GA-MPSO method is far better than the existing algorithms