The social media of X has become a focal point for discussions on sensitive issues, including the Israeli-Palestinian conflict. This research analyzes sentiment toward tweets expressing support for Palestine on X, com...
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Universities heavily depend on information technology to support their academic activities. Universitas Muhammadiyah Semarang (Unimus) currently operates with a total bandwidth of 1.3 Gbps. The primary issue is the cu...
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This paper presents a detailed study of the impact of temperature on the performance of a nonlinear electromagnetic vibration energy harvester, which is applied in autonomous power systems. The variability of material...
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The study of electrostatic precipitators (ESP) is of great importance in powder technology. Different physical and chemical processes occur during its operation. The objective of this investigation is to analyze and o...
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With the introduction of 5G networks, high-speed low-latency network connections became available for mobile and embedded devices without the limited range of WiFi networks. Although the source and the destination can...
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ISBN:
(数字)9798350378009
ISBN:
(纸本)9798350378016
With the introduction of 5G networks, high-speed low-latency network connections became available for mobile and embedded devices without the limited range of WiFi networks. Although the source and the destination can now be hundreds of kilometres away, the communication between them can be flawless. Our goal is to have a low cost, low power, lightweight device that is able to stream video for UAV (unmanned aerial vehicles), mobile robot teleoperation over 5G networks to AR/VR (augmented/virtual reality) applications, to large distances without the need for line of sight. In this paper we compare the latency of existing low cost video streamer solutions (UAV camera streaming, single board computer) and present a custom hardware-software solution optimized for low latency, while conducting measurements over different network types (wired, campus 5G, public 5G). We have shown that the custom device was able to achieve with significantly lower latency (50–80 ms direct over direct connection, about 100–150 ms over public 5G).
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...
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 information redundancy. This paper describes an integration of error correction and detection techniques into the interface of RISC-V processor to protect the data stored in the memory. We also provide a hardware-software interface for reporting errors and software routines for correcting data in memory. Our solution has a negligible impact (-3.9%) on the overall performance of the core with a small area and power consumption overhead.
This paper proposes an efficient method for calculating the eigenvalues of large-scale exponential correlation matrices by leveraging tridiagonal matrix theory. The approach explicitly factorizes the characteristic po...
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The Renewable Energy Sources (RES) penetration in the power system of Cyprus has dramatically increased over the last years. As a result, the system is already facing significant challenges limiting the RES hosting ca...
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In vitro dissolution prediction is a field of phar-maceutical research that aims to predict a tablet's dissolution profile using non-destructive methods based on the tablet's measured manufacturing parameters ...
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ISBN:
(数字)9798350329520
ISBN:
(纸本)9798350329537
In vitro dissolution prediction is a field of phar-maceutical research that aims to predict a tablet's dissolution profile using non-destructive methods based on the tablet's measured manufacturing parameters or composition. One of the most popular non-destructive measurements is Raman chemical imaging, which outputs a Raman map. However, because of the current development of the Raman imaging technique, obtaining large training datasets is very expensive and time-consuming. Still, training popular complex deep learning architectures that may achieve better accuracy is only possible with a large dataset. Therefore this article focuses on utilising pre-trained networks and the transfer learning technique to attempt to solve the problem of the small size of training samples. The results showed that deep neural networks with data augmentation and transfer learning could achieve better accuracy than simple convolutional neural networks. The presented strategies showed the need for an extensive dataset could be handled, and the accuracy could be enhanced, although there is room for further refinement.
This study presents an innovative method to improve the accuracy of indoor mapping by deploying and integrating a sensor that transmits two-dimensional data with a three-dimensional mesh created by another device. The...
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ISBN:
(数字)9798350385601
ISBN:
(纸本)9798350385618
This study presents an innovative method to improve the accuracy of indoor mapping by deploying and integrating a sensor that transmits two-dimensional data with a three-dimensional mesh created by another device. The Iterative Closest Point algorithm was used to coordinate the different data sets and transform their different coordinate systems into a common indoor map. Prior to this, rigorous image cleaning and matching processes are conducted to ensure the quality of the data used. The effectiveness of this methodology has been validated through multiple tests using a Lidar scanner and a HoloLens 2 Augmented Reality device. This method not only offers potential for enhancing indoor navigation and safety protocols like emergency evacuation but also presents opportunities for advancing asset tracking and other applications.
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