This research develops and optimizes an optical character recognition (OCR) system for goat weighing scales using intelligent computer vision and distributed computing to enhance accuracy and efficiency in real-world ...
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Federated learning (FL) is a distributed paradigm that enables multiple clients or edge devices to collaboratively train a model without sharing their local data. The FL system has to tackle a significant challenge du...
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The efficiency and accuracy of machine learning algorithms in embedded systems are paramount for real-Time processing tasks such as identifying an intended speaker out of potential sound sources. This paper presents a...
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This paper presents a secure and flexible process integration approach enabling distributed data fusion in military IoT applications. It seamlessly combines two recently developed technologies, the Dynamic Process Int...
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In shared memory programming, there is a need for synchronization primitives that are suitable for modern hardware to achieve high performance and reduce contention. This paper introduces a novel lock with a standard ...
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Effective communication and the capacity to express oneself precisely are central to English as a Foreign Language (EFL) courses. Successful language acquisition is now often measured by the ability to communicate eff...
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The proceedings contain 12 papers. The special focus in this conference is on Modelling and Mining networks. The topics include: A Simple Model of Influence: Details and Variants of Dynamics;impact of&#...
ISBN:
(纸本)9783031592041
The proceedings contain 12 papers. The special focus in this conference is on Modelling and Mining networks. The topics include: A Simple Model of Influence: Details and Variants of Dynamics;impact of Market Design and Trading Network Structure on Market Efficiency;Network Embedding Exploration Tool (NEExT);efficient Computation of K-Edge Connected Components: An Empirical Analysis;the Directed Age-Dependent Random Connection Model with Arc Reciprocity;how to Cool a Graph;distributed Averaging for Accuracy Prediction in Networked systems;towards Graph Clustering for distributed Computing Environments;hypergraphRepository: A Community-Driven and Interactive Hypernetwork Data Collection;clique Counts for Network Similarity.
PDC at UM, is a series of "codeless" modules consisting of visualizations, simulations, and demonstrations which introduce Parallel and distributed Computing (PDC) concepts in early computing courses. These ...
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ISBN:
(纸本)9798350364613;9798350364606
PDC at UM, is a series of "codeless" modules consisting of visualizations, simulations, and demonstrations which introduce Parallel and distributed Computing (PDC) concepts in early computing courses. These materials are codeless because they do not require students to write or understand code. Instead, students read a short introduction to a PDC concept and Then engage with a web-based visualization and/or (code-based) demonstration reinforcing the concept. The codeless nature of these modules makes them suitable for computing and non computing majors. To test the effectiveness of our modules we introduced them into two CSI courses and designed and administered a pre/posttest. Our results show statistically significant results: those who engaged with our modules substantially improved their knowledge and understanding of PDC concepts. Our modules also improved student attitudes, confidence and self-efficacy with respect to PDC topics. We also provide some qualitative observations of our study and identify common misconceptions students have about PDC.
A Minus Dominating (MD) Function of a graph G = (V, E) (vertical bar V vertical bar = n) is a function that assigns a value from {-1, 0, 1} to each node i. V such that the sum of the values of node i and all its neigh...
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ISBN:
(纸本)9783031744976;9783031744983
A Minus Dominating (MD) Function of a graph G = (V, E) (vertical bar V vertical bar = n) is a function that assigns a value from {-1, 0, 1} to each node i. V such that the sum of the values of node i and all its neighboring nodes is positive (i.e., equal to or greater than 1). An MD function is minimal if decreasing the value of any node by 1 causes a violation of the conditions of the MD function. As an extension of the MD function, we introduce the k-Minimal Minus Dominating (MMD) Function (k >= 0), which is a minimal MD function such that no other MD function can be obtained by increasing the values for some nodes by k in total and decreasing the values for some nodes by at least k + 1 in total. Note that any minimal MD function can be referred to as a 0-MMD function. In this paper, we propose a silent self-stabilizing algorithm to solve the 1-Minimal Minus Domination Problem on an arbitrary graph, using a composition technique that repeatedly applies several self-stabilizing algorithms in order, known as loop composition. It converges within O(n(Delta(2) + D)) rounds, where D is the diameter and Delta is the maximum degree of a graph, and each node requires O(Delta(4) log n) bits of memory.
Pneumonia is a major respiratory infection causing significant global morbidity and mortality, especially in developing nations with poor living conditions and inadequate medical infrastructure. Early diagnosis throug...
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