In recent years, deceptive content such as fake news and fake reviews, also known as opinion spams, have increasingly become a dangerous prospect for online users. Fake reviews have affected consumers and stores alike...
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ISBN:
(数字)9798350370096
ISBN:
(纸本)9798350370102
In recent years, deceptive content such as fake news and fake reviews, also known as opinion spams, have increasingly become a dangerous prospect for online users. Fake reviews have affected consumers and stores alike. Furthermore, the problem of fake news has gained attention in 2016, especially in the aftermath of the last U.S. presidential elections. Fake reviews and fake news are a closely related phenomenon as both consist of writing and spreading false information or beliefs. The opinion spam problem was formulated for the first time a few years ago, but it has quickly become a growing research area due to the abundance of user‐generated content. It is now easy for anyone to either write fake reviews or write fake news on the web. The biggest challenge is the lack of an efficient way to tell the difference between a real review and a fake one; even humans are often unable to tell the difference. In this paper, we introduce a new n‐gram model to detect automatically fake contents with a particular focus on fake reviews and fake news.
The recent COVID-19 pandemic highlighted that there is a lot of work to do regarding the integration of digital technologies in healthcare. Actual trending offers the possibility to patients to have permanent knowledg...
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Personal computers and the Internet are used in different areas and are easier to use. Most data is easy to transmit and duplicate in digital format, and being tampered with and stolen easily leads to issues for conte...
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Mobile access innovation is experiencing a progressive change. Every mobile generation witnessed fast and huge execution upgrades. These are proportional with the requests of the massive data increasing over the last ...
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Many real-world problems are notoriously multi-objective and NP-hard. Hence, there is a constant striving for optimizers capable of solving such problems effectively. In this paper, we examine the Multi-Objective Para...
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the design decisions made in the architecture of a software system are essential to its maintainability, and thus its quality is of great importance. architecture smells (ASs) can be used to identify any quality issue...
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ISBN:
(数字)9798350372632
ISBN:
(纸本)9798350372649
the design decisions made in the architecture of a software system are essential to its maintainability, and thus its quality is of great importance. architecture smells (ASs) can be used to identify any quality issues within the system. To further explore the relationships between ASs, stability, and reusability, Spearman correlation coefficients will be calculated. This paper seeks to examine the connection between architecture smells, software stability, and reusability. To do this, we utilized a dataset created by other researchers and conducted an empirical study of the associations between five types of architecture smells and software stability and reusability. This research is necessary as there is a lack of in-dep.h research on architecture smells and their relationship to software stability and reusability. We found a relationship between the presence of Feature Concentration in package and the stability and reusability of the package. Also, package's stability is affected by both Cyclic dep.ndency and Unstable dep.ndency. A slight positive correlation has been found between God Class and stability, as well as a very weak negative correlation between Unstable dep.ndency and reusability. Finally, we found a slight negative correlation between package stability and reusability.
In this study, we proposed a transfer-learning based variational autoencoder model for predicting the electrical characteristics in the parameter tuning process of a-IGZO TFT structure design. The result achieve a hig...
In this study, we proposed a transfer-learning based variational autoencoder model for predicting the electrical characteristics in the parameter tuning process of a-IGZO TFT structure design. The result achieve a high R2 score of 0.9704 with a low-computing-power hardware-friendly method that reduced time consumption significantly compared to prior approaches. The findings have practical implications for mitigating the time-consuming nature of TCAD simulations, and the method can expand to various types of input data while ensuring high performance and generalization. We demonstrated significant improvement in generalization and accuracy through a k-fold validation.
In the realm of cloud native environments, Ku-bernetes has emerged as the de facto orchestration system for containers, and the service mesh architecture, with its interconnected microservices, has become increasingly...
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ISBN:
(数字)9781728190549
ISBN:
(纸本)9781728190556
In the realm of cloud native environments, Ku-bernetes has emerged as the de facto orchestration system for containers, and the service mesh architecture, with its interconnected microservices, has become increasingly prominent. Efficient scheduling and resource allocation for these microservices play a pivotal role in achieving high performance and maintaining system reliability. In this paper, we introduce a novel approach for container scheduling within Kubernetes clusters, leveraging Graph Attention Networks (GATs) for representation learning. Our proposed method captures the intricate dep.ndencies among containers and services by constructing a representation graph. The deep Q-learning algorithm is then employed to optimize scheduling decisions, focusing on container-to-node placements, CPU request-response allocation, and adherence to node affinity and anti-affinity rules. Our experiments demonstrate that our GATs-based method outperforms traditional scheduling strategies, leading to enhanced resource utilization, reduced service latency, and improved overall system throughput. The insights gleaned from this study pave the way for a new frontier in cloud native performance optimization and offer tangible benefits to industries adopting microservice-based architectures.
The purpose of this research is to help save electricity within organizations and workplaces that use computers. Due to the behavior of general users today, they do not give importance to saving electricity. This work...
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The purpose of this research is to help save electricity within organizations and workplaces that use computers. Due to the behavior of general users today, they do not give importance to saving electricity. This work has developed an automatic computer shutdown system. with image processing via a webcam by using image processing techniques (image processing) applied to a webcam by using a webcam to capture the user on the computer screen. Then the images are analyzed and examined with the principles of image processing with the face detection technique using the algorithm of Haar -like features to detect human faces and ROI. define a specific area of interest. The system will then check the amount of inactivity on the screen. or does not show the face image within 10 minutes, the system will automatically turn off the computer. with image processing. This work can make it easier to turn off computers when not in use. and helps to save electricity for the organization or agencies as well.
The suggested remedy for saturated pixels in digital camera photos introduces a brand-new learning-based method for reconstructing images with high dynamic range (HDR). While current techniques concentrate on increasi...
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