Low-capacity scenarios have become increasingly important in the technology of the Internet of Things (IoT) and the next generation of wireless networks. Such scenarios require efficient and reliable transmission over...
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Although attention weights have been commonly used as a means to provide explanations for deep learning models, the approach has been widely criticized due to its lack of faithfulness. In this work, we present a simpl...
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Smart grid (SG) will transform contemporary businesses by offering efficient solutions to improve existing power systems' efficiency, stability, and resilience. SG provides long-term power supply by interconnectin...
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We initiate a study of a new model of property testing that is a hybrid of testing properties of distributions and testing properties of strings. Specifically, the new model refers to testing properties of distributio...
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Effective data transmission plays a crucial role in federated learning (FL), which enables collaborative model training without centralizing data. This paper proposes a new coded transmission to enhance the communicat...
Urban traffic management faces significant challenges due to non-compliance with traffic rules, particularly among motorcycle riders. This study introduces an innovative approach employing the YOLOv9 object detection ...
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The development of indoor positioning systems is possible thanks to the availability of wireless network infrastructure. Thus, a wireless provider can determine an accurate indoor position taking into account the exis...
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Since years, forest fires are a significant concern globally, causing damage to ecosystems and human settlements. For effective prevention and mitigation predicting forest fires is important, different factors contrib...
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The course computer systems for VLSI, held in the fourth year of undergraduate studies at the School of electricalengineering, University of Belgrade, introduces students to the Verilog and SystemVerilog languages an...
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Federated learning (FL) provides a distributed learning framework for multiple participants to collaborate learning without sharing raw data. In many practical FL scenarios, participants have heterogeneous resources d...
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