Analiza različitih NVH izvora motora s unutarnjim izgaranjem

The powertrain is the “heart” of a vehicle. It is the singular most expensive and most complex part of every vehicle. The powertrain consists of the engine, intake, and exhaust subsystems, and the transmission and drivetrain systems. The powertrain is one of the major sources of vehicle sounds and vibrations. In general, powertrain vibration and sound sources consist of the following: 1. Engine, including combustion-related sounds and vibrations, reciprocating unbalance, rotating unbalance, crankshaft torsional oscillations, etc; 2. Valve Train system, including valves, cam system, timing belt, or chain; 3. Accessories, including their unbalance and resonance; 4. Intake system and exhaust system vibrations; 5. Driveshaft first-order resonance; 6. Universal joint second-order bending vibrations and torsional vibrations; and 7. Axle vibrations due to gear tooth conjugation error, transmission error, pinion par eccentricity, slip-stick between pinion and ring gear, etc.In this work various sources of noise in an engine have been analyzed.Pogonski sklop je \u27srce\u27 vozila. To je najskuplji i najsloženiji dio svakog vozila. Pogonski sklop sastoji se od motora, unosa i ispušnih podsustava te prijenosnih i pogonskih sustava. Pogonski sklop jedan je od glavnih izvora zvukova vozila i vibracija. Općenito, izvori vibracije i zvukova pogonskog sklopa sastoje se od sljedećeg: 1. motora, uključujući zvukove vezane uz izgaranje i vibracije, klipne neravnoteže, rotirajuće neravnoteže, torzijskih oscilacija koljenastog vratila…; 2. sustava razvodnog mehanizma, uključujući ventile, CAM sustav, razvodni remen ili lanac; 3. dodatnu opremu, uključujući i njezinu neravnotežu i rezonanciju; 4. vibracije usisnog sustava i ispušnog sustava; 5. rezonancija prvog reda vratila; 6. vibracija savijanja drugog reda kardanskog zgloba i torzijskih vibracija; i 7. vibracije osovine uslijed pogreške konjugacije zupčanika, pogreške u prijenosu, zupčanik prema ekscentričnosti, slip-stick gibanje između zupčanika i prstenastog zupčanika… U radu su analizirani različiti izvori buke u motoru

Prikaz rada motora zrakoplova

Engines used in aircrafts are propulsion type which work on the basis of thrust force acting on them. In this paper working of various engines has been reviewed. Various problems associated with these engines have been discussed with future remedies to rectify these faults.Motori koji se koriste u zrakoplovima pogonskog su tipa koji rade na osnovi potisne sile koja djeluje na njih. U ovom članku prikazan je rad različitih motora. Raspravljeni su razni problemi koji se povezuju s tim motorima s budućim mjerama za uklanjanje tih grešaka

Biologically Inspired Oscillating Activation Functions Can Bridge the Performance Gap between Biological and Artificial Neurons

Nonlinear activation functions endow neural networks with the ability to learn complex high-dimensional functions. The choice of activation function is a crucial hyperparameter that determines the performance of deep neural networks. It significantly affects the gradient flow, speed of training and ultimately the representation power of the neural network. Saturating activation functions like sigmoids suffer from the vanishing gradient problem and cannot be used in deep neural networks. Universal approximation theorems guarantee that multilayer networks of sigmoids and ReLU can learn arbitrarily complex continuous functions to any accuracy. Despite the ability of multilayer neural networks to learn arbitrarily complex activation functions, each neuron in a conventional neural network (networks using sigmoids and ReLU like activations) has a single hyperplane as its decision boundary and hence makes a linear classification. Thus single neurons with sigmoidal, ReLU, Swish, and Mish activation functions cannot learn the XOR function. Recent research has discovered biological neurons in layers two and three of the human cortex having oscillating activation functions and capable of individually learning the XOR function. The presence of oscillating activation functions in biological neural neurons might partially explain the performance gap between biological and artificial neural networks. This paper proposes 4 new oscillating activation functions which enable individual neurons to learn the XOR function without manual feature engineering. The paper explores the possibility of using oscillating activation functions to solve classification problems with fewer neurons and reduce training time

IOT based advanced medicine dispenser integrated with an interactive web application

Internet of Things (IOT) is a development of the internet which plays a major role in integrating human-machine interaction by allowing everyday objects to send and receive data in a variety of applications. Using IOT in healthcare monitoring provides an avenue for doctors and patients to interact and to track the dosage of medication administered. The paper presents an interactive, user friendly network integrated with an automated medicine dispenser which uses IOT, cloud computing and machine learning. The network was built on a python tornado framework with a front end developed using materialise CSS. The feasibility of this approach was validated by building a prototype and conducting a survey.Intelligent Electrical Power Grid

In-Hospital Characteristics and 30-Day Readmissions for Acute Myocardial Infarction and Major Bleeding in Patients With Active Cancer

There are limited data on readmission with ischemic and major bleeding events in patients with acute myocardial infarction (AMI) with active cancer. The purpose of our study was to evaluate in-hospital characteristics and 30-day readmission rates for recurrent AMI and major bleeding by cancer type in patients with AMI and active cancer. From 2016 through 2018, patients in the Nationwide Readmission Database admitted with AMI and underlying active colon, lung, breast, prostate, and hematological cancers were included. Thirty-day readmission for recurrent AMI and major bleeding were reported. Of 1,524,677 index hospitalizations for AMI, 35,790 patients (2.2%) had cancer (0.9% hematological; 0.5% lung; 0.4% prostate; 0.2% breast; and 0.1% colon). Compared with patients without cancer, patients with cancer were about 6 to 10 years older and had a higher proportion of atrial fibrillation, valvular heart disease, previous stroke, and a greater co-morbidity burden. Of all cancer types, only active breast cancer (adjusted odds ratios 1.82, 95% CI 1.11 to 2.98) was found to be significantly associated with elevated odds of readmission for major bleeding; no such association was observed for recurrent AMI. In conclusion, AMI in patients with breast cancer is associated with significantly greater odds of readmission for major bleeding within 30 days after discharge. Management of patients with concomitant AMI and cancer is challenging but should be based on a multidisciplinary approach and estimation of an individual patient\u27s risk of major coronary thrombotic and bleeding events

Abstracts of National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020

This book presents the abstracts of the papers presented to the Online National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020 (RDMPMC-2020) held on 26th and 27th August 2020 organized by the Department of Metallurgical and Materials Science in Association with the Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, India. Conference Title: National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020Conference Acronym: RDMPMC-2020Conference Date: 26–27 August 2020Conference Location: Online (Virtual Mode)Conference Organizer: Department of Metallurgical and Materials Engineering, National Institute of Technology JamshedpurCo-organizer: Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, IndiaConference Sponsor: TEQIP-

Measurement of the double-differential inclusive jet cross section in proton-proton collisions at s\sqrt{s} = 5.02 TeV

International audienceThe inclusive jet cross section is measured as a function of jet transverse momentum $p_\mathrm{T}$ and rapidity $y$. The measurement is performed using proton-proton collision data at $\sqrt{s}$ = 5.02 TeV, recorded by the CMS experiment at the LHC, corresponding to an integrated luminosity of 27.4 pb$^{-1}$. The jets are reconstructed with the anti-$k_\mathrm{T}$ algorithm using a distance parameter of $R$ = 0.4, within the rapidity interval $\lvert y\rvert$$\lt$ 2, and across the kinematic range 0.06 $\lt$$p_\mathrm{T}$$\lt$ 1 TeV. The jet cross section is unfolded from detector to particle level using the determined jet response and resolution. The results are compared to predictions of perturbative quantum chromodynamics, calculated at both next-to-leading order and next-to-next-to-leading order. The predictions are corrected for nonperturbative effects, and presented for a variety of parton distribution functions and choices of the renormalization/factorization scales and the strong coupling $\alpha_\mathrm{S}$