Artificial intelligence together with its applications are advancing in all fields, particularly medical science. A considerable quantity of clinical data is available, yet the vast majority of it is wasted. It will b...
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Evolutionary machine learning has drawn much attentions on solving data-driven learning problem in the past decades, where classification is a major branch of data-driven learning problem. To improve the quality of ob...
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Evolutionary machine learning has drawn much attentions on solving data-driven learning problem in the past decades, where classification is a major branch of data-driven learning problem. To improve the quality of obtained classifier, ensemble is a simple yet powerful strategy. However, gathering classifiers for ensemble requires multiple runs of learning process which bring additional cost at evaluation on the data. This study proposes an innovative framework for ensemble learning through evolutionary multitasking, i.e., the evolutionary multitasking for ensemble learning (EMTEL). There are four main features in the EMTEL. First, the EMTEL formulates a classification problem as a dynamic multitask optimization problem. Second, the EMTEL utilizes evolutionary multitasking to resolve the dynamic multitask optimization problem for better convergence through the synergy of common properties hidden in the tasks. Third, the EMTEL incorporates evolutionary instance selection for saving the cost at evaluation. Finally, the EMTEL formulates the ensemble learning problem as a numerical optimization problem and proposes an online ensemble aggregation approach to simultaneously select appropriate ensemble candidates from learning history and optimize ensemble weights for aggregating predictions. A case study is investigated by integrating two state-of-the-art methods for evolutionary multitasking and evolutionary instance selection respectively, i.e., the symbiosis in biocoenosis optimization and cooperative evolutionary learning and instance selection. For online ensemble aggregation, this study adopts the well-known covariance matrix adaptation evolution strategy. Experiments validate the effectiveness of the EMTEL over conventional and advanced evolutionary machine learning algorithms, including genetic programming, self-learning gene expression programming, and multi-dimensional genetic programming. Experimental results show that the proposed framework ameliorates state-o
In today's Internet routing infrastructure,designers have addressed scal-ing concerns in routing constrained multiobjective optimization problems examining latency and mobility concerns as a secondary *** tactical...
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In today's Internet routing infrastructure,designers have addressed scal-ing concerns in routing constrained multiobjective optimization problems examining latency and mobility concerns as a secondary *** tactical Mobile Ad-hoc Network(MANET),hubs can function based on the work plan in various social affairs and the internally connected hubs are almost having the related moving standards where the topology between one and the other are tightly coupled in steady support by considering the touchstone of hubs such as a self-sorted out,self-mending and *** in the routing process is one of the key aspects to increase MANET performance by coordinat-ing the pathways using multiple criteria and *** present a Group Adaptive Hybrid Routing Algorithm(GAHRA)for gathering portability,which pursues table-driven directing methodology in stable accumulations and on-request steering strategy for versatile *** on this aspect,the research demonstrates an adjustable framework for commuting between the table-driven approach and the on-request approach,with the objectives of enhancing the out-put of MANET routing computation in each *** analysis and replication results reveal that the proposed method is promising than a single well-known existing routing approach and is well-suited for sensitive MANET applications.
Representation of compound information in a truthful, coarse way forms the layout of the granular computing paradigm. In granular computing, the continuous variables are mapped into intervals to be utilized in the ext...
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The increasing demand for effective retrieval from image datasets has been driven by the rapid growth of digital images. Image retrieval is a method for creating a structured database based on searching for similar im...
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During the COVID-19 crisis, the need to stay at home has increased dramatically. In addition, the number of sickpeople, especially elderly persons, has increased exponentially. In such a scenario, home monitoring of p...
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During the COVID-19 crisis, the need to stay at home has increased dramatically. In addition, the number of sickpeople, especially elderly persons, has increased exponentially. In such a scenario, home monitoring of patientscan ensure remote healthcare at home using advanced technologies such as the Internet of Medical Things (IoMT).The IoMT can monitor and transmit sensitive health data;however, it may be vulnerable to various attacks. In thispaper, an efficient healthcare security system is proposed for IoMT applications. In the proposed system, themedical sensors can transmit sensed encrypted health data via a mobile application to the doctor for ***, three consortium blockchains are constructed for load balancing of transactions and reducing transactionlatency. They store the credentials of system entities, doctors' prescriptions and recommendations according to thedata transmitted via mobile applications, and the medical treatment process. Besides, cancelable biometrics areused for providing authentication and increasing the security of the proposed medical system. The investigationalresults show that the proposed system outperforms existing work where the proposed model consumed lessprocessing time by values of 18%, 22%, and 40%, and less energy for processing a 200 KB file by values of 9%,13%, and 17%. Finally, the proposed model consumed less memory usage by values of 7%, 7%, and 18.75%. Fromthese results, it is clear that the proposed system gives a very reliable and secure performance for efficientlysecuring medical applications.
Wireless Sensor Networks (WSNs) play an important role in the modern era and security has become an important research area. Intrusion Detection System (IDS) improve network security by monitoring the network state so...
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Alzheimer’s dementia (AD) poses a significant global health challenge, characterized by progressive cognitive decline, memory impairment, and behavioral changes. The critical need for early detection to enable timely...
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A quickening transformation in the agriculture sector is being driven by the growth of Internet of Things (IoT) technology. The need for food production is growing quickly because it is predicted that by 2050 there wi...
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Fog computing is an emerging paradigm that provides services near the end-user. The tremendous increase in IoT devices and big data leads to complexity in fog resource allocation. Inefficient resource allocation can l...
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