Traditional perception systems for TJA (Traffic Jam Assistance) are mostly implemented by fusing images with radar or lidar. As computer vision techniques become more powerful, cameras can almost replace the need for ...
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Not only common issues on object detection task need to be deal with, for Unmanned Aerial Vehicle (UAV) applications, small object is one of the critical problems that needs to be solved. YOLOv7 is a powerful network ...
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Presently,customer retention is essential for reducing customer churn in telecommunication *** churn prediction(CCP)is important to predict the possibility of customer retention in the quality of *** risks of customer...
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Presently,customer retention is essential for reducing customer churn in telecommunication *** churn prediction(CCP)is important to predict the possibility of customer retention in the quality of *** risks of customer churn also get essential,the rise of machine learning(ML)models can be employed to investigate the characteristics of customer ***,deep learning(DL)models help in prediction of the customer behavior based characteristic *** the DL models necessitate hyperparameter modelling and effort,the process is difficult for research communities and business *** this view,this study designs an optimal deep canonically correlated autoencoder based prediction(ODCCAEP)model for competitive customer dependent application *** addition,the O-DCCAEP method purposes for determining the churning nature of the *** O-DCCAEP technique encompasses preprocessing,classification,and hyperparameter ***,the DCCAE model is employed to classify the churners or ***,the hyperparameter optimization of the DCCAE technique occurs utilizing the deer hunting optimization algorithm(DHOA).The experimental evaluation of the O-DCCAEP technique is carried out against an own dataset and the outcomes highlighted the betterment of the presented O-DCCAEP approach on existing approaches.
The role of influencers, especially on social media platforms, has grown significantly. A commonly used feature among business professionals today is follower grouping. However, this feature is limited to identifying ...
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ISBN:
(数字)9798331508616
ISBN:
(纸本)9798331508623
The role of influencers, especially on social media platforms, has grown significantly. A commonly used feature among business professionals today is follower grouping. However, this feature is limited to identifying influencers based solely on mutual followership, underscoring the need for a more sophisticated approach to influencer *** study proposes a new method for influencer detection that integrates the Leiden Coloring Algorithm and Matrix Centrality. This approach leverages network analysis to identify patterns and relationships in large-scale datasets. First, the Leiden Coloring Algorithm partitions the network into various communities, which are considered potential influencer groups. Furthermore, Eigenvector and Degree Centrality augment this process by identifying nodes with high connectivity, representing potential *** proposed method is validated using crawled data from the Twitter (X) social media platform with the keyword "GarudaIndonesia." The results of the Leiden Coloring Algorithm recommend 10 accounts as influencers. Based on Eigenvector Centrality and Degree Centrality for a dataset of 1,000 rows, it is observed that the first and second ranks consistently identify the same influencers, namely IndonesiaGaruda and GarudaCares. However, the third to tenth ranks suggest different influencers. For a dataset of 5,000 rows, both methods again identify IndonesiaGaruda as the top-ranked influencer, while the second to tenth ranks differ between the two *** modularity value for the first test scenario is 0.9396, while for the second test scenario, it is 0.9381. The processing time for the first test scenario is 29.5493 seconds, compared to 434.1838 seconds for the second test scenario. Additionally, the number of communities identified by the Leiden Coloring Algorithm increases with dataset size, with 505 communities for the first test scenario and 1,969 communities for the second. This demonstrates that larger datasets res
In today's digital era, the influence of social media influencers has grown significantly. A commonly used feature by business professionals today is follower grouping. However, this feature is limited to identify...
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ISBN:
(数字)9798331508616
ISBN:
(纸本)9798331508623
In today's digital era, the influence of social media influencers has grown significantly. A commonly used feature by business professionals today is follower grouping. However, this feature is limited to identifying influencers based solely on mutual followership, highlighting the need for a more sophisticated approach to influencer detection. This study proposes a novel method for influencer detection that integrates the Leiden coloring algorithm and Degree centrality. This approach leverages network analysis to identify patterns and relationships within large-scale datasets. First, the Leiden coloring algorithm is employed to partition the network into distinct communities, identifying potential influencer clusters. Subsequently, Degree centrality is utilized to identify nodes within these communities exhibiting high connectivity, indicating individuals with significant influence. The proposed method was validated using data crawled from Twitter (X) social media, employing the keyword "GarudaIndonesia." The data was collected using Tweet-Harvest between January 1, 2020, and October 16, 2024, resulting in a dataset of 22,623 rows. The proposed method was compared to the Louvain coloring method, demonstrating an increase in the modularity value of the Leiden coloring algorithm by 0.0195, a reduction in processing time by 13.93 seconds, and a decrease in the number of communities by 649.
Diagnosability is an important parameter to measure the fault tolerance of a multiprocessor system. If we only care about the state of a node, instead of doing the global diagnosis, Hsu and Tan proposed the idea of lo...
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In this article, we propose to study a novel research problem to boost group performance, that is, social-aware diversity-optimized group extraction (SDGE), which takes into consideration the two important factors: 1)...
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This paper applies ant colony optimization (ACO) algorithm for the dual-pin flying probe circuit board inspection optimal path searching problem. First, the proposed approach creates a representation for circuit inspe...
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In general, public or private organizations or companies have used information-based technology as a support to improve business performance to be more effective and efficient in order to achieve a company's busin...
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A vehicle has a license plate and can be identified by the license number attached to the vehicle plate. For detection and recognition, multimedia sensors can be used so that it requires a vehicle tracking application...
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