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https://dabi.temple.edu/external/zoran/papers/Rafaa_Complex_Net_2025.pdf
The HMN-RTS model improves 3 h ahead outage severity prediction, resulting in a 0.76 macro F1-score vs 0 .51 for the best alternative for a five-class problem formulation. The HMN-RTS model provides useful predictions of outage duration 6 h ahead, enabling grid operators to implement outage mitigation strategies promptly.
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https://cis.temple.edu/~tug29203/18spring-3329/reading/hw4a.pdf
c. Suppose that different VC numbers are permitted in each link along a VC’s path. During connection setup, after an end-to-end path is determined, describe how the links can choose their VC numbers and configure their for-warding tables in a decentralized manner, without reliance on a central node. P3. A bare-bones forwarding table in a VC network has four columns. What is the meaning of ...
https://cis.temple.edu/~jiewu/research/publications/Publication_files/1-s2.0-S0957417424018475-main.pdf
However, due to the diversity and complexity, modeling human actions as general graphs and capturing discriminative spatial–temporal motion patterns is challenging. Besides, the inevitable interference, especially occlusion, impairs the robustness of existing methods that depend on complete skeletons. To solve these problems, we propose a Multi-Granular Spatial-Temporal Synchronous Graph ...
https://cis.temple.edu/~jiewu/research/publications/Publication_files/Paper%206750%20Camera%20Ready%20Version.pdf
1 Introduction Federated learning (FL) [Koneˇcn ́y et al., 2017], a widely-used framework for distributed machine learning, is a signif-icant research focus. Most FL algorithms, such as the clas-sic FedAvg, fall into Synchronous Federated Learning (SFL). They require the server to wait for all selected clients’ lo-cal training and uploads before aggregating updates, and as-sume uniform ...
https://cis.temple.edu/~wu/research/publications/Publication_files/Joint%20Dynamic%20Grouping%20and%20Gradient%20Coding%20for%20Time-critical%20Distributed%20Machine%20Learning%20in%20Heterogeneous%20Edge%20Networks-FINAL-VERSION.pdf
Abstract—In edge networks, distributed computing resources have been widely utilized to collaboratively perform a machine learning task by multiple nodes. However, the model training time in heterogeneous edge networks is becoming longer because of excessive computation and delay caused by slow nodes, namely stragglers. The parameter server even abandons stragglers which fail to return ...
https://sites.temple.edu/ticlj/files/2017/02/28.2.Hessebon-TICLJ.pdf
Section II of this paper discusses the metaphor of constitution-making waves and its applicability in Sub-Saharan Africa. Discussions of the distinguishing features of constitutions 4.0 and the problems of incumbency abuse and politicized ethnicity in Kenya prior to the adoption of the Kenyan Constitution in 2010 follow. The purpose of these discussions is to show the problems the new Kenyan ...
https://cis.temple.edu/~latecki/Papers/Quan_DRBANET_ICIP_2022.pdf
ABSTRACT Due to the powerful ability to encode image details and semantics, many lightweight dual-resolution networks have been proposed in recent years. However, most of them ignore the benefit of boundary information. This paper introduces a lightweight dual-resolution network, called DRBANet, aim-ing to refine semantic segmentation results with the aid of boundary information. DRBANet also ...
https://sites.temple.edu/trail/files/2021/11/XieXinDamesIROS2021.pdf
Zhanteng Xie, Pujie Xin, and Philip Dames Abstract—This paper proposes a novel neural network-based control policy to enable a mobile robot to navigate safety through environments filled with both static obstacles, such as tables and chairs, and dense crowds of pedestrians. The network architecture uses early fusion to combine a short history of lidar data with kinematic data about nearby ...