Fulfilling increasing performance demands of space and automotive applications can be problematic as high dependability is required. Memory is one of the most radiationsensitive parts, so it is often protected with in...
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Despite investing heavily in data-related technology and human resources, enterprises are still struggling to derive value from data. To foster data value creation and move toward a data-driven enterprise, adequa...
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A rheological model is proposed that captures the performance loss and properties of a potential subsequent recovery of socio-technical systems subject to arbitrary disruptions. The model facilitates the quantitative ...
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The accurate identification of smart meter(SM)fault types is crucial for enhancing the efficiency of operationand maintenance(O&M)and the reliability of power ***,the intelligent classification of SM fault typesfa...
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The accurate identification of smart meter(SM)fault types is crucial for enhancing the efficiency of operationand maintenance(O&M)and the reliability of power ***,the intelligent classification of SM fault typesfaces significant challenges owing to the complexity of featuresand the imbalance between fault *** address these issues,this study presents a fault diagnosis method for SM incorporatingthree distinct *** first module employs acombination of standardization,data imputation,and featureextraction to enhance the data quality,thereby facilitating improvedtraining and learning by the *** enhance theclassification performance,the data imputation method considersfeature correlation measurement and sequential imputation,and the feature extractor utilizes the discriminative enhancedsparse *** tackle the interclass imbalance of datawith discrete and continuous features,the second module introducesan assisted classifier generative adversarial network,which includes a discrete feature generation ***,anovel Stacking ensemble classifier for SM fault diagnosis is *** contrast to previous studies,we construct a two-layerheuristic optimization framework to address the synchronousdynamic optimization problem of the combinations and hyperparametersof the Stacking ensemble classifier,enabling betterhandling of complex classification tasks using SM *** proposedfault diagnosis method for SM via two-layer stacking ensembleoptimization and data augmentation is trained and validatedusing SM fault data collected from 2010 to 2018 in Zhejiang Province,*** results demonstrate the effectivenessof the proposed method in improving the accuracyof SM fault diagnosis,particularly for minority classes.
Digitalization and sustainability are two central fields of action in the company that are of crucial importance for future business success. The necessary transformation represents a strategically relevant and time-c...
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Several newly developed techniques and tools for manipulating images, audio, and videos have been introduced as an outcome of the recent and rapid breakthroughs in AI, machine learning, and deep learning. While most a...
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Traditional data monetization approaches face challenges related to data protection and logistics. In response, digital data marketplaces have emerged as intermediaries simplifying data transactions. Despite the growi...
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The extensive spread of DeepFake images on the internet has emerged as a significant challenge, with applications ranging from harmless entertainment to harmful acts like blackmail, misinformation, and spreading false...
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Introduction Plant phenotyping describes the result of the interaction of genotype with the environment[1].This is performed with high throughput in greenhouses by automated screening systems using different types of ...
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Introduction Plant phenotyping describes the result of the interaction of genotype with the environment[1].This is performed with high throughput in greenhouses by automated screening systems using different types of imaging and non-imaging sensors[2].The high-throughput imaging routines result in large amounts of data,which require sophisticated processing *** and reusing phenotype-related data are not common,because its acquisition and processing are resource costly and technically intensive[3].
Background: Recently, e-learning has become a very basic, integral part of technology-based learning. Wide trends are increasing day by day because of the demands and its usage based on working remotely due to highly ...
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Background: Recently, e-learning has become a very basic, integral part of technology-based learning. Wide trends are increasing day by day because of the demands and its usage based on working remotely due to highly penetrated mobile handheld devices and digital media. The smart campus infrastructure has played a vital role to its full extent towards Z millennium students in the 20th century. The teaching and learning accessibility depends on terms of various cost-based afforda-ble platforms, either with synchronous learning or asynchronous mode of learning. Methods: The current patent research explores the changeling leading to infrastructural reforms as per the need for digital media for e-learning during and after COVID-19 spreads. The perspectives in 2 forms of research study are: 1st working on infrastructural needs and demands for the smart campuses and online learning challenges and 2nd is working on platforms technology utilization for better accessible resources for all learners. This work studied different aspects during and after COVID-19, leading to the importance of uninterrupted internet access, phone, hardware and relia-bility, etc. In this work, the importance of gamification study and flipped classrooms for enhancing learner performance to highly engage them in learning environments focused research model on learner engagement on Gamified perceiving study with Smart PLS-SEM was investigated. Promoting sustainability in its entirety through knowledge transfer and contributions to address various challenges in the redesign of learners' syllabi to meet educational needs, emphasizing online learning to integrate various modes of learner platforms, personalized teaching and learn-ing, peer-to-peer communication for learner enhancement, and student engagement through gami-fication are studied. Results: Learners who are enrolled at the school, college, and university levels of education increased exponentially post-COVID-19. More than 90% responded to sch
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