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Item type:Publication, Intelligent water drops algorithm-based aggregation in heterogeneous wireless sensor network(Hindawi Limited, 2022-01-01)This paper provides a novel implementation of the intelligent water drops (IWD) method for resolving data aggregation issues in heterogeneous wireless sensor networks (WSN). When the aggregating node is utilized to transmit the data to the base station, the research attempts to show that the traffic situations of WSN may be modified appropriately by parameter tuning and algorithm modification. IWD is used to generate an optimum data aggregation tree in WSN as one of its applications. IWD assumes that all nodes in the environment are identical, resulting in identical parameter updates for all nodes. In practical scenarios, however, diverse nodes with variable beginning energy, communication range, and sensing range characteristics are deployed. In order to replicate the influence of heterogeneity in the environment, improved IID (IIWD) is offered as an enhancement to the original IID. The suggested enhancement is appropriate for scenarios in which the aggregation node is utilized to transmit data to the base station in heterogeneous configurations. In terms of residual energy, dead nodes, payload, and network lifespan, a series of simulation results demonstrates that the proposed IIWD significantly improves the accuracy and effectiveness of the IWD method in comparison. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An efficient outlier detection with deep learning-based financial crisis prediction model in big data environment(Hindawi Limited, 2022-01-01)As Big Data, Internet of Things (IoT), cloud computing (CC), and other ideas and technologies are combined for social interactions. Big data technologies improve the treatment of financial data for businesses. At present, an effective tool can be used to forecast the financial failures and crises of small and medium-sized enterprises. Financial crisis prediction (FCP) plays a major role in the country's economic phenomenon. Accurate forecasting of the number and probability of failure is an indication of the development and strength of national economies. Normally, distinct approaches are planned for an effective FCP. Conversely, classifier efficiency and predictive accuracy and data legality could not be optimal for practical application. In this view, this study develops an oppositional ant lion optimizer-based feature selection with a machine learning-enabled classification (OALOFS-MLC) model for FCP in a big data environment. For big data management in the financial sector, the Hadoop MapReduce tool is used. In addition, the presented OALOFS-MLC model designs a new OALOFS algorithm to choose an optimal subset of features which helps to achieve improved classification results. In addition, the deep random vector functional links network (DRVFLN) model is used to perform the grading process. Experimental validation of the OALOFS-MLC approach was conducted using a baseline dataset and the results demonstrated the supremacy of the OALOFS-MLC algorithm over recent approaches. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Application of cloud computing technology in computer secure storage(Hindawi Limited, 2022-01-01)To investigate the use of cloud computing technologies in safe computer storage, firstly, it is proposed to complete the central control function by building a cloud computing data center, collect multiple platforms and network safety technologies, and then connect computers in unlike sites to confirm computer information security. Then, based on the implementation advantages of cloud computing technique in computer network safe storage, specific applications are analyzed. Finally, a cloud computing secure modeling and analysis idea based on multiqueue and multiserver is proposed. The proposed cloud security approach ensures that both data and applications are easily accessible to authorized users. One always has a consistent way to access your cloud data and applications, allowing you to address any potential security issues as soon as they arise. It has greatly improved computer security storage convenience while also greatly improving computer network storage security. After verification, with the cloud computing technology platform to carry out relevant businesses at any time, the operation effectiveness has been meaningfully enhanced by 80%. At the same time, it promotes the construction of information sharing and gives full performance to the benefits of hardware, accelerates the process of resource integration, and provides information support for the formulation of enterprise strategic plans. Combined with the actual situation, the current study discusses the development and application direction of cloud computing, so as to add new impetus to the economic growth of enterprises. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Collective intelligence in digital marketing and business decision-making through artificial swarm intelligence(Taylor & Francis, 2024-05-15)Artificial swarm intelligence effectively connects specific human groups into different kinds of emergent systems operated by AI algorithms. It can be remarkably useful for getting a situational overview, searching for different objects, monitoring the productive environment, and establishing communication networks. AI enables marketers to personalize communications on an individual level. This definite technology works through the prediction of customer behavior depending on the intelligence achieved from previous interactions. In accordance with this, the current business environment is creatively progressing, technologically advanced, digitally empowered, immensely flexible, and forwardmoving. Due to this reason, a competitive business environment has been observed throughout the entire world. Globalization also encourages this competitive business world. Based on those reasons, it is important to implement AI in the fields of business decision-making and digital marketing. It is also necessary to identify significant customer segments, their product preferences, current demand, and valuable feedback. On the other hand, collective intelligence refers to a group of intelligence that emerges from collective efforts, efficient collaboration, and competition among various individuals. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Optimizing the Parameters of Spark Plasma Sintering to Enhance the Hardness of MgO/TiC Composites(Hindawi Limited, 2023-01-01)In this research, the first work was carried out to manufacture MgO-based metal matrix composite containing 3 wt%. Sintering parameters, such as temperature, pressure, and time were subjected to Taguchi analysis to identify the most significant effect on magnesium oxide physical and mechanical characteristics. The impact of each sintering parameter explores using the analysis of variance-structure and microstructure analysis using XRD and EDS-equipped FE-SEM. The mechanical properties of the composite are evaluated by testing its Rockwell hardness (HR) and Vickers hardness (HV). The results showed that sintering temperature was the most influential of the sintering factors on microhardness. Densification at its peak was 100%, while it peaked at 62.19 Rockwell hardness and 58.7 Vickers hardness. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Ant Colony Optimization-Enabled CNN Deep Learning Technique for Accurate Detection of Cervical Cancer(Hindawi Limited, 2023-01-01)Cancer is characterized by abnormal cell growth and proliferation, which are both diagnostic indicators of the disease. When cancerous cells enter one organ, there is a risk that they may spread to adjacent tissues and eventually to other organs. Cancer of the cervix of the uterus often initially manifests itself in the uterine cervix, which is located at the very bottom of the uterus. Both the growth and death of cervical cells are characteristic features of this condition. False-negative results provide a significant moral dilemma since they may cause women to get an incorrect diagnosis of cancer, which in turn can result in the woman's premature death from the disease. False-positive results do not raise any significant ethical concerns; but they do require a patient to go through an expensive and time-consuming treatment process, and they also cause the patient to experience tension and anxiety that is not warranted. In order to detect cervical cancer in its earliest stages in women, a screening procedure known as a Pap test is often performed. This article describes a technique for improving images using Brightness Preserving Dynamic Fuzzy Histogram Equalization. To individual components and find the right area of interest, the fuzzy c-means approach is applied. The images are segmented using the fuzzy c-means method to find the right area of interest. The feature selection algorithm is the ACO algorithm. Following that, categorization is carried out utilizing the CNN, MLP, and ANN algorithms.