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531.
Faizan Ahmed Khan Farooq Ahmad Arfat Ahmad Khan Chitapong Wechtaisong 《计算机系统科学与工程》2023,44(3):2019-2032
The need for the analysis of modern businesses is rapidly increasing as the supporting enterprise systems generate more and more data. This data can be extremely valuable for executing organizations because the data allows constant monitoring, analyzing, and improving the underlying processes, which leads to the reduction of cost and the improvement of the quality. Process mining is a useful technique for analyzing enterprise systems by using an event log that contains behaviours. This research focuses on the process discovery and refinement using real-life event log data collected from a large multinational organization that deals with coatings and paints. By investigating and analyzing their order handling processes, this study aims at learning a model that gives insight inspection of the processes and performance analysis. Furthermore, the animation is also performed for the better inspection, diagnostics, and compliance-related questions to specify the system. The configuration of the system and the conformance checking for further enhancement is also addressed in this research. To achieve the objectives, this research uses process mining techniques, i.e. process discovery in the form of formal Petri nets models with the help of process maps, and process refinement through conformance checking and enhancement. Initially, the identified executed process is reconstructed by using the process discovery techniques. Following the reconstruction, we perform a deep analysis for the underlying process to ensure the process improvement and redesigning. Finally, some recommendations are made to improve the enterprise management system processes. 相似文献
532.
Niharika Gupta Baijnath Kaushik Mohammad Khalid Imam Rahmani Saima Anwar Lashari 《计算机、材料和连续体(英文)》2023,76(1):347-366
Diabetes is one of the fastest-growing human diseases worldwide and poses a significant threat to the population’s longer lives. Early prediction of diabetes is crucial to taking precautionary steps to avoid or delay its onset. In this study, we proposed a Deep Dense Layer Neural Network (DDLNN) for diabetes prediction using a dataset with 768 instances and nine variables. We also applied a combination of classical machine learning (ML) algorithms and ensemble learning algorithms for the effective prediction of the disease. The classical ML algorithms used were Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbor (KNN), and Naïve Bayes (NB). We also constructed ensemble models such as bagging (Random Forest) and boosting like AdaBoost and Extreme Gradient Boosting (XGBoost) to evaluate the performance of prediction models. The proposed DDLNN model and ensemble learning models were trained and tested using hyperparameter tuning and K-Fold cross-validation to determine the best parameters for predicting the disease. The combined ML models used majority voting to select the best outcomes among the models. The efficacy of the proposed and other models was evaluated for effective diabetes prediction. The investigation concluded that the proposed model, after hyperparameter tuning, outperformed other learning models with an accuracy of 84.42%, a precision of 85.12%, a recall rate of 65.40%, and a specificity of 94.11%. 相似文献
533.
Saima Ashraf Yanyan Liu Huijuan Wei Ruofan Shen Huanhuan Zhang Xianli Wu Sehrish Mehdi Tao Liu Baojun Li 《Small (Weinheim an der Bergstrasse, Germany)》2023,19(43):2303031
Bimetallic Nanoalloy catalysts have diverse uses in clean energy, sensing, catalysis, biomedicine, and energy storage, with some supported and unsupported catalysts. Conventional synthetic methods for producing bimetallic alloy nanoparticles often produce unalloyed and bulky particles that do not exhibit desired characteristics. Alloys, when prepared with advanced nanoscale methods, give higher surface area, activity, and selectivity than individual metals due to changes in their electronic properties and reduced size. This review demonstrates the synthesis methods and principles to produce and characterize highly dispersed, well-alloyed bimetallic nanoalloy particles in relatively simple, effective, and generalized approaches and the overall existence of conventional synthetic methods with modifications to prepare bimetallic alloy catalysts. The basic concepts and mechanistic understanding are represented with purposely selected examples. Herein, the enthralling properties with widespread applications of nanoalloy catalysts in heterogeneous catalysis are also presented, especially for Hydrogen Evolution Reaction (HER), Oxidation Reduction Reaction (ORR), Oxygen Evolution Reaction (OER), and alcohol oxidation with a particular focus on Pt and Pd-based bimetallic nanoalloys and their numerous fields of applications. The high entropy alloy is described as a complicated subject with an emphasis on laser-based green synthesis of nanoparticles and, in conclusion, the forecasts and contemporary challenges for the controlled synthesis of nanoalloys are addressed. 相似文献
534.
Lala S. Roohan Farooq Srivastava Chandan 《Metallurgical and Materials Transactions A》2023,54(2):634-645
Metallurgical and Materials Transactions A - Effect of graphene oxide on the corrosion behavior of electrodeposited Cu–Cr coatings on mild steel substrate was studied and the results were... 相似文献
535.
Saima Batool Muhammad Idrees Su-Ting Han Vellaisamy A. L. Roy Ye Zhou 《Small (Weinheim an der Bergstrasse, Germany)》2023,19(12):2206550
Current electrical contact models are occasionally insufficient at the nanoscale owing to the wide variations in outcomes between 2D mono and multi-layered and bulk materials that result from their distinctive electrostatics and geometries. Contrarily, devices based on 2D semiconductors present a significant challenge due to the requirement for electrical contact with resistances close to the quantum limit. The next generation of low-power devices is already hindered by the lack of high-quality and low-contact-resistance contacts on 2D materials. The physics and materials science of electrical contact resistance in 2D materials-based nanoelectronics, interface configurations, charge injection mechanisms, and numerical modeling of electrical contacts, as well as the most pressing issues that need to be resolved in the field of research and development, will all be covered in this review. 相似文献
536.
Arshad Hasna Shaheen Saima Khan Javed Ali Anwar Muhammad Shahid Aurangzeb Khursheed Alhussein Musaed 《Cognition, Technology & Work》2023,25(2-3):305-324
Cognition, Technology & Work - Requirements prioritization is essential for development of quality software products. Requirements prioritization helps focus on the most important requirements... 相似文献
537.
Farooq Salma Dar Aamir Hussain Dash Kshirod Kumar Srivastava Shivangi Pandey Vinay Kumar Ayoub Wani Suhana Pandiselvam R. Manzoor Sobiya Kaur Mandeep 《Food science and biotechnology》2023,32(5):621-638
Food Science and Biotechnology - Cold plasma processing is a nonthermal approach that maintains food quality while minimizing the effects of heat on its nutritious qualities. Utilizing activated,... 相似文献
538.
Silicon - This work presents the design and simulation of a novel double-gate L-shaped Schottky barrier MOSFET (DG-LS-SB-MOSFET). The device uses a low work function metal near source-channel... 相似文献