Simulations are indispensable to reduce costs and risks when developing and testing algorithms for unmanned aerial vehicles (UAV) especially for applications in high risk scenarios like search and rescue (SAR) operati...
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ISBN:
(纸本)9781665412520
Simulations are indispensable to reduce costs and risks when developing and testing algorithms for unmanned aerial vehicles (UAV) especially for applications in high risk scenarios like search and rescue (SAR) operations and post-disaster damage assessment. Many UAV applications require real-time tasks for which the timeliness of computations is fundamental. However, standard simulation tools are not guaranteed to run in sync with real-time events, leading to unreliable assessments of the ability of the target hardware to perform specific tasks. In this work we present a simulation and test system able to run UAV tasks on resource-constrained target hardware possibly adopted in these applications. the system allows for hardware-in-the-loop simulations in which a virtual UAV provided with virtual sensors is controlled by the software under test (SUT) running on the target hardware, while simulated and real time are kept in sync. We provide experimental results from the execution of several increasingly difficult tasks in the system.
the current work proposes an exploration over the topical relevance of five extractive micro-blog summary techniques i.e. LexRank, LSA, T5, ALBERT & DistilBERT in crisis timeline for situational tweets of Turkey E...
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ISBN:
(数字)9798350370249
ISBN:
(纸本)9798350370270
the current work proposes an exploration over the topical relevance of five extractive micro-blog summary techniques i.e. LexRank, LSA, T5, ALBERT & DistilBERT in crisis timeline for situational tweets of Turkey Earthquake 2023. Here, the topic model i.e. LDA is utilized to extract the crisis topics from generated summary using each technique in crisis timeline. then a topical relevance has been formulated a) between incoming corpus (situational tweets) and generated summaries and b) among the summary techniques at distinct time frames t in crisis timeline. the behavioral patterns of each technique at distinct time frame in terms of topical correlation are observed for $6 \boldsymbol \& 7$ February, 2023 to interpret the utility of single or multiple summary algorithms in terms of capturing crisis topics at various time frames t of the crisis. Finally, the summaries of the most suitable techniques are provided as a prompt at every time frame t to Google’s LLM i.e. Gemini AI for re-summarizing at crisis timeline. It is evident from the results that the selection of multiple summaries as a prompt and providing it to LLM has improved the lexical & syntactic relevance of crisis summaries at crisis timeline.
the proceedings contain 29 papers. the special focus in this conference is on Networked systems. the topics include: Efficient means of achieving composability using object based semantics in transactional memory syst...
ISBN:
(纸本)9783030055288
the proceedings contain 29 papers. the special focus in this conference is on Networked systems. the topics include: Efficient means of achieving composability using object based semantics in transactional memory systems;unleashing and speeding up readers in atomic object implementations;Optimal recoverable mutual exclusion using only FASAS;declarative parameterized verification of topology-sensitive distributed protocols;On verifying TSO robustness for event-driven asynchronous programs;model checking dynamic pushdown networks with locks and priorities;OSM-GKM optimal shared multicast-based solution for group key management in mobile IPv6;a game-theoretic approach for the internet content distribution chain;New competition-based approach for caching popular content in ICN;formalizing and implementing distributed ledger objects;churn possibilities and impossibilities;practically-self-stabilizing vector clocks in the absence of execution fairness;short paper: Tight bounds for universal and cautious self-stabilizing 1-maximal matching;automata-based bottom-up design of conflict-free security policies specified as policy expressions;Short paper: Stress-SGX: Load and stress your enclaves for fun and profit;short paper: Application of noisy attacks on image steganography;a measure for quantifying the topological structure of some networks;short paper: Maintenance of strongly connected component in shared-memory graph;Comparative analysis of our association rules based approach and a genetic approach for OLAP partitioning;short paper: IoT context-driven architecture: characterization of the behavioral aspect;on the unfairness of blockchain;weak failures: Definitions, algorithms and impossibility results;complete visibility for oblivious robots in O(N) Time;gathering of mobile agents in asynchronous byzantine environments with authenticated whiteboards;on helping and stacks.
Today, in Uzbekistan, the number of retail store chains is increasing. In their work, the latest technological achievements are used in order to satisfy the demands and needs of our people. Especially in the condition...
ISBN:
(纸本)9781450399050
Today, in Uzbekistan, the number of retail store chains is increasing. In their work, the latest technological achievements are used in order to satisfy the demands and needs of our people. Especially in the conditions of the COVID-19 pandemic, it has been highlighted that retail enterprises operating on the basis of network marketing, based on the needs and demands of the population, are operating in the form of large supermarkets and small stores. In this article, based on the latest information, we analyzed the brands "Korzinka", "Makro", "Havas", "Carrefour" operating in Uzbekistan.
this paper explores machine learning algorithmsthat can be used to predict student results in an assignment of a Software Engineering course, based on weekly cumulative average source code submissions to GitLab. GitL...
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ISBN:
(纸本)9783030681982;9783030681975
this paper explores machine learning algorithmsthat can be used to predict student results in an assignment of a Software Engineering course, based on weekly cumulative average source code submissions to GitLab. GitLab is a source code version control system, commonly used in Software Engineering courses in Higher Education. the aim of this work is to create models that can be used to predict if a group of students in a team will pass or fail an assignment. In this paper, we present results from Decision Tree, Random Forest, Extra Trees, Ada Boost and Gradient Boosting machine learning models. these models were evaluated using cross-validation, with Ada Boost achieving the highest average score.
Detecting Bangla traffic signs in Bangladesh is crucial for road safety as it ensures effective communication with drivers who primarily understand Bengali. Accurate recognition of these signs can significantly reduce...
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ISBN:
(数字)9798350385779
ISBN:
(纸本)9798350385786
Detecting Bangla traffic signs in Bangladesh is crucial for road safety as it ensures effective communication with drivers who primarily understand Bengali. Accurate recognition of these signs can significantly reduce accidents and enhance compliance with traffic regulations, ultimately saving lives on the country's roads. this study delves into the development of a multi-layer Convolutional Neural Network (CNN) architecture specifically designed for precise Bangla traffic sign detection. the dataset was collected from Dhaka by us and aims to accurately represent the road systems in *** used a range of powerful deep learning algorithms, such as DenseNet201, ResNet50, VGG19, Xception, CNN01, and CNN02, to tackle the traffic sign detection task. these algorithms were selected for their impressive track record in image classification tasksthe models were improved to increase reliability after being trained on a well-rounded dataset collected directly from *** a careful examination, DenseNet201 stood out as the best model, achieving an impressive accuracy of 99.65%. this impressive accomplishment highlights the ability of the DenseNet201 architecture to recognize complex features found in Bangla traffic *** there is not much research paper about bangla traffic sign *** it is hard to compare. there is one paper of Uddin, Md Mahatab et al about bangla traffic sign identification. His CNN model achieved 98% accuracy. Our study addresses a significant gap in the field of Bangla traffic sign detection, especially considering the lack of existing research papers on the subject. In addition, it highlights the significance of choosing CNN architectures that are customized for specific datasets and tasks, thus enhancing the accuracy and effectiveness of machine learning models in real-world scenarios.
the proceedings contain 77 papers. the topics discussed include: ELS: an hard real-time scheduler for homogeneous multi-core platforms;MC-RPL: a new routing approach based on multi-criteria RPL for the Internet of thi...
ISBN:
(纸本)9781728150758
the proceedings contain 77 papers. the topics discussed include: ELS: an hard real-time scheduler for homogeneous multi-core platforms;MC-RPL: a new routing approach based on multi-criteria RPL for the Internet of things;Persian sentiment lexicon expansion using unsupervised learning methods;a case study for presenting bank recommender systems based on bon card transaction data;performance evaluation of classification data mining algorithms on coronary artery disease dataset;DMap: a distributed blockchain-based framework for online mapping in smart city;and a novel parallel jobs scheduling algorithm in the cloud computing.
the proceedings contain 8 papers. the topics discussed include: scalable hyperparameter optimization with lazy Gaussian processes;understanding scalability and fine-grain parallelism of synchronous data parallel train...
ISBN:
(纸本)9781728159850
the proceedings contain 8 papers. the topics discussed include: scalable hyperparameter optimization with lazy Gaussian processes;understanding scalability and fine-grain parallelism of synchronous data parallel training;DisCo: physics-based unsupervised discovery of coherent structures in spatiotemporal systems;GradVis: visualization and second order analysis of optimization surfaces during the training of deep neural networks;metaoptimization on a distributed system for deep reinforcement learning;scheduling optimization of parallel linear algebra algorithms using supervised learning;parallel data-local training for optimizing Word2Vec embeddings for word and graph embeddings;and fine-grained exploitation of mixed precision for faster CNN training.
the proceedings contain 18 papers. the special focus in this conference is on High Performance computing in Computational Science. the topics include: A Scheduling theory Framework for GPU Tasks Efficient Execution;A ...
ISBN:
(纸本)9783030159955
the proceedings contain 18 papers. the special focus in this conference is on High Performance computing in Computational Science. the topics include: A Scheduling theory Framework for GPU Tasks Efficient Execution;A Timer-Augmented Cost Function for Load Balanced DSMC;Accelerating Scientific Applications on Heterogeneous systems with HybridOMP;a New Parallel Benchmark for Performance Evaluation and Energy Consumption;bigger Buffer k-d Trees on Multi-Many-Core systems;a Parallel Generator of Non-Hermitian Matrices Computed from Given Spectra;LRMalloc: A Modern and Competitive Lock-Free Dynamic Memory Allocator;towards a Strategy for Performance Prediction on Heterogeneous Architectures;Dynamic Configuration of CUDA Runtime Variables for CDP-Based Divide-and-Conquer algorithms;Design, Implementation and Performance Analysis of a CFD Task-Based Application for Heterogeneous CPU/GPU Resources;Optimizing Packed String Matching on AVX2 Platform;A GPU-Based Metaheuristic for Workflow Scheduling on Clouds;a Systematic Mapping on High-Performance computing for Protein Structure Prediction;performance Evaluation of Deep Learning Frameworks over Different Architectures;non-uniform Domain Decomposition for Heterogeneous Accelerated Processing Units;performance Evaluation of Two Load Balancing algorithms for Hybrid Clusters.
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