Results 11 to 20 of about 14,768 (170)
LoRa in a haystack: a study of the LORA signal behavior [PDF]
2019 International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 2019 Over the years, LoRa has been raising a lot of interest, both from the academia and the industry. LoRa is indeed a promising technology that enables long range and low power communications to connect IoT devices to the Internet. LoRa is often envisioned for several applications such as regular reporting but it is also aimed to be exploited for other ...
Amadou, Ibrahim +2 more
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Proceedings of the 1st Workshop on Experiences with the Design and Implementation of Frugal Smart Objects, 2020 With the growth of LoRa deployments there are plenty of anecdotal reports of very long wireless links, well beyond the line of sight. Most reports suggest that these links are related to anomalous tropospheric propagation. We developed a platform to study tropospheric links based on TheThingsNetwork, a popular LoRaWAN-based infrastructure.
Zennaro M. +5 more
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Long-Lived LoRa: Prolonging the Lifetime of a LoRa Network [PDF]
2020 IEEE 28th International Conference on Network Protocols (ICNP), 2020 Prolonging the network lifetime is a major consideration in many Internet of Things applications. In this paper, we study maximizing the network lifetime of an energy-harvesting LoRa network. Such a network is characterized by heterogeneous recharging capabilities across the nodes that is not taken into account in existing work. We propose a link-layer
Sezana Fahmida +4 more
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Analysis of the reliability of LoRa [PDF]
IEEE Communications Letters, 2020 This letter studies the performance of a single gateway LoRa system in the presence of different interference considering the imperfect orthogonality effect. It utilizes concepts of stochastic geometry to present a low-complexity approximate closed-form model for computing the success and coverage probabilities under these challenging conditions. Monte
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S-LoRA: Serving Thousands of Concurrent LoRA Adapters
CoRR, 2023 The "pretrain-then-finetune" paradigm is commonly adopted in the deployment of large language models. Low-Rank Adaptation (LoRA), a parameter-efficient fine-tuning method, is often employed to adapt a base model to a multitude of tasks, resulting in a substantial collection of LoRA adapters derived from one base model.
Ying Sheng 0007 +11 more
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Simulation of LoRa in NS-3: Improving LoRa Performance with CSMA [PDF]
2018 IEEE International Conference on Communications (ICC), 2018 In this paper, we consider two research issues. First, we present a NS-3 module that simulates the behavior of LoRa in an accurate way. To validate the module, we compare its results with measurements on a real-world testbed and with measured values reported by other work. We also show that the module correctly represents the capture effect that lowers
Duda, Andrzej, To, Thanh-Hai
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Journal of ICT Standardization, 2021 LoRaWAN® Certification of devices is critical for effective and efficient mass deployment of LoRaWAN Networks, as it ensures devices will work on any network, under all conditions. Certified Devices significantly reduce the support costs as any product failures detected later when the device is deployed is far more expensive to repair and poor RF ...
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Implementation of a LoRa Mesh Library
IEEE Access, 2022 This work was supported by the Ministry of Science and Innovation of the Spanish Government through the State Research Agency (AEI) under Project PID2019-106774RB-C21, Project PCI2019-111851-2 (LeadingEdge CHIST-ERA), and Project PCI2019-111850-2 (DiPET CHIST-ERA).
Miquel Solé, Joan +3 more
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CoRRBackdoored and privacy-leaking deep neural networks pose a serious threat to the deployment of machine learning systems in security-critical settings. Existing defenses for backdoor detection and membership inference typically require access to clean reference models, extensive retraining, or strong assumptions about the attack mechanism. In this work,
Marco Arazzi, Antonino Nocera
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CoRRWe introduce Vision as LoRA (VoRA), a novel paradigm for transforming an LLM into an MLLM. Unlike prevalent MLLM architectures that rely on external vision modules for vision encoding, VoRA internalizes visual capabilities by integrating vision-specific LoRA layers directly into the LLM.
Han Wang +7 more
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