Predict the Effects of Forming Tool Characteristics on Surface Roughness of Aluminum Foil Components Formed by SPIF Using ANN and SVR

Sherwan Mohammed Najm,Imre Paniti 한국정밀공학회 2021 International Journal of Precision Engineering and Vol.22 No.1

In the present work, multiple forming tests were conducted under different forming conditions by Single Point Incremental Forming (SPIF). In which surface roughness, arithmetical mean roughness (Ra) and the ten-point mean roughness (Rz) of AlMn1Mg1 sheet were experimentally measured. Also, an Artificial Neural Network (ANN) was used to predict the (Ra) and (Rz) by adopting the data collected from 108 components that were formed by SPIF. Forming tool characteristics played a key role in all the predictions and their effect on the final product surface roughness. In the aim to explore the proper materials and geometry of forming tools, diff erent ANN structures, different training, and transfer functions have been applied to predict (Ra) and (Rz) as an output argument. Furthermore, Support Vector Regression (SVR) with different kernel types have been used for prediction, together with Gradient Boosting regression to sort the effective parameters on the surface roughness. The input arguments were tool materials, tool shape, tool end/corner radius, and tool surface roughness (Ra and Rz). The actual data subjected to a fi t regression model to generate prediction equations of Ra and Rz. The results showed that ANN with one output gives the best R-Square (R 2 ). Levenberg-Marquardt backpropagation (Trainlm) training function recorded the highest value of R 2 , 0.9628 for prediction Ra using Softmax transfer function whereas 0.9972 for Rz by Log- Sigmoid transfer function. Furthermore, tool materials, together with tool surface (Ra), are playing a significant importance role, affecting the sheet surface roughness (Ra). Whereas tool roughness Rz was the critical parameter effected on the Rz of the product. Also, there was a significant positive effect of tool geometry on the sheet surface roughness.

Public Sentiment Analysis and Topic Modeling Regarding COVID-19’s Three Waves of Total Lockdown: A Case Study on Movement Control Order in Malaysia

A.H. Alamoodi,Mohammed Rashad Baker,O.S. Albahri,B.B. Zaidan,A.A. Zaidan,Wing-Kwong Wong,Salem Garfan,A.S. Albahri,Miguel A. Alonso,Ali Najm Jasim,M. J. Baqer 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.7

The COVID-19 pandemic has affected many aspects of human life. The pandemic not only caused millions of fatalities and problems but also changed public sentiment and behavior. Owing to the magnitude of this pandemic, governments worldwide adopted full lockdown measures that attracted much discussion on social media platforms. To investigate the effects of these lockdown measures, this study performed sentiment analysis and latent Dirichlet allocation topic modeling on textual data from Twitter published during the three lockdown waves in Malaysia between 2020 and 2021. Three lockdown measures were identified, the related data for the first two weeks of each lockdown were collected and analysed to understand the public sentiment. The changes between these lockdowns were identified, and the latent topics were highlighted. Most of the public sentiment focused on the first lockdown as reflected in the large number of latent topics generated during this period. The overall sentiment for each lockdown was mostly positive, followed by neutral and then negative. Topic modelling results identified staying at home, quarantine and lockdown as the main aspects of discussion for the first lockdown, whilst importance of health measures and government efforts were the main aspects for the second and third lockdowns. Governments may utilise these findings to understand public sentiment and to formulate precautionary measures that can assure the safety of their citizens and tend to their most pressing problems. These results also highlight the importance of positive messaging during difficult times, establishing digital interventions and formulating new policies to improve the reaction of the public to emergency situations.

Impact of Multiphase Computed Tomography Angiography for Endovascular Treatment Decision- Making on Outcomes in Patients with Acute Ischemic Stroke

Johanna M. Ospel,Ondrej Volny,Wu Qiu,Mohamed Najm,Moiz Hafeez,Sarah Abdalrahman,Enrico Fainardi,Marta Rubiera,Alexander Khaw,Jai J. Shankar,Michael D. Hill,Mohammed A. Almekhlafi,Andrew M. Demchuk,May 대한뇌졸중학회 2021 Journal of stroke Vol.23 No.3

Background and Purpose Various imaging paradigms are used for endovascular treatment (EVT) decision-making and outcome estimation in acute ischemic stroke (AIS). We aim to compare how these imaging paradigms perform for EVT patient selection and outcome estimation. Methods Prospective multi-center cohort study of patients with AIS symptoms with multi-phase computed tomography angiography (mCTA) and computed tomography perfusion (CTP) baseline imaging. mCTA-based EVT-eligibility was defined as presence of large vessel occlusion (LVO) and moderate-to-good collaterals on mCTA. CTP-based eligibility was defined as presence of LVO, ischemic core (defined on relative cerebral blood flow, absolute cerebral blood flow, and cerebral blood volume maps) <70 mL, mismatch-ratio >1.8, absolute mismatch >15 mL. EVT-eligibility and adjusted rates of good outcome (modified Rankin Scale 0–2) based on these imaging paradigms were compared. Results Of 289/464 patients with LVO, 263 (91%) were EVT-eligible by mCTA-criteria versus 63 (22%), 19 (7%) and 103 (36%) by rCBF, aCBF, and CBV-CTP-criteria. CTP and mCTA-criteria were discordant in 40% to 53%. Estimated outcomes were best in patients who met both mCTA and CTP eligibility-criteria and were treated with EVT (62% to 87% good outcome). Patients eligible for EVT by mCTA-criteria and not by CTP-criteria receiving EVT achieved good outcome rates of 53% to 57%. Few patients met CTP-criteria and not mCTA-criteria for EVT. Conclusions Simpler imaging selection criteria that rely on little else than detection of the occluded blood vessel may be more sensitive and less specific, thus resulting in more patients being offered EVT and arguably benefiting from it.

Experimental and Numerical Investigations of the Fatigue Life of AA2024 Aluminium Alloy-Based Nanocomposite Reinforced by TiO2 Nanoparticles Under the Effect of Heat Treatment

Hamid M. Mahan,S. V. Konovalov,Sherwan Mohammed Najm,Oleksik Mihaela,Tomasz Trzepieciński 한국정밀공학회 2024 International Journal of Precision Engineering and Vol.25 No.1

Using aluminium metal matrix nanocomposites has recently gained increased attention in the industry due to their high strength and ductility. In this paper, TiO2 nanoparticles in volume percentages of 5 wt. % were added to the AA2024 alloy using the stir casting method. Using a novel powder injection system, TiO2 nanoparticles with an average particle size of 30 ± 5 nm was added to the matrix. The influence of TiO2 content on the fatigue life before and after heat treatment was studied. The results showed the fatigue properties of AA2024 with TiO2 nanoparticles increased after heat treatment. The optimum improvement in fatigue properties was obtained at 5 wt. % TiO2 after heat treatment, with an improving fatigue life in 14.71% compared with sample based. This is due to an increased number of fine precipitates besides its uniformly distributed after heat treatment. The fatigue life of the composite materials with added nanoparticles was investigated using a finite element-based ANSYS workbench. There was a good match between what happened in the experiments and what happened to the numerical fatigue strength. For the composite materials, the difference between the experimental and numerical values of fatigue strength was not greater than 4% for the matrix. The results also, indicated that, after ageing, the precipitate-free zone at the inter-dendritic zone disappeared or became smaller. However, after adding 5 wt. % of titanium and, also, performing heat treatment, it is not possible to precipitate the Al2CuMg precipitates, and, instead of it, the Al3TiCu and Al7TiCu phases precipitates have been formed.