In this paper, we share our experience in teaching parallel algorithms with the binary-forking model. With hardware advances, multicore computers are now ubiquitous. This has created a substantial demand in both resea...
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ISBN:
(纸本)9798350364613;9798350364606
In this paper, we share our experience in teaching parallel algorithms with the binary-forking model. With hardware advances, multicore computers are now ubiquitous. This has created a substantial demand in both research and industry to harness the capabilities of parallel computing. It is thus important to incorporate parallelism in computer science education, especially in the early stages of the curriculum. However, it is commonly believed that understanding and using parallelism requires a deep understanding of computersystems and architecture, which complicates introducing parallelism to young students and non-experts. We propose to use the binary-forking model in teaching parallel algorithms, proposed by our previous research work. This model is meant to capture the performance of algorithms on modern multicore shared-memory machines, which is a simple abstraction to isolate algorithm design ideas with system-level details. The abstraction allows for simple analysis based on the work-span model in theory, and can be directly implemented as parallel programs in practice. In this paper, we briefly overview some basic primitives in this model, and provide a list of algorithms that we believe are well-suited in parallel algorithm courses.
This study examines the intersection of quantum computing with machine learning, focusing on the potential, difficulties, and present progress in this emerging topic. The study explores the theoretical foundations of ...
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ISBN:
(数字)9783031746826
ISBN:
(纸本)9783031746819;9783031746826
This study examines the intersection of quantum computing with machine learning, focusing on the potential, difficulties, and present progress in this emerging topic. The study explores the theoretical foundations of quantum machine learning algorithms, explaining the core ideas that utilize quantum mechanics to improve computing skills. The text explores many quanta computing paradigms, including quantum annealing, quantum circuits, and quantum-inspired algorithms. It evaluates their suitability and effectiveness in addressing intricate machine learning challenges. The study provides a thorough examination of current literature and recent advancements to explain the changing field of quantum machine learning frameworks. It emphasizes their potential to transform data analysis, optimization, and pattern identification. Furthermore, it discusses the practical factors and technological challenges related to the implementation of quantum machine learning algorithms on current quantum hardware, highlighting the need of reliable error correction, qubit coherence, and scalable architectures. The study offers valuable insights into the significant influence of quantum machine learning on diverse fields such as banking, healthcare, and cybersecurity by connecting theoretical principles with real-world applications. Furthermore, it delineates prospective areas of study and possible methods for fully utilizing quantum computing in machine learning applications, thus promoting cooperation among researchers, practitioners, and stakeholders in shaping the future of this dynamic and interdisciplinary domain.
In recent years, many scholars and experts have discovered that mobile communication systems and techniques are susceptible to a wide range of cyberattacks. These assaults not only inflict pain and damage to private f...
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Exoplanets are the planets orbiting stars out of our solar system. The exploration of such planets has become a growing field in astronomy but the analysis of the data related to such planets involves many challenges ...
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This article presents a versatile model of failure prediction in control systems of objects with large time constants. The basic model of a control unit consists of deterministic finite automaton (DFA) which states co...
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The proceedings contain 48 papers. The special focus in this conference is on Intelligent Computing and Big Data Analytics. The topics include: Road Mishap Prevention Using Driver state Detection;optic Disc Segmentati...
ISBN:
(纸本)9783031747007
The proceedings contain 48 papers. The special focus in this conference is on Intelligent Computing and Big Data Analytics. The topics include: Road Mishap Prevention Using Driver state Detection;optic Disc Segmentation Using Disc-Centered Patch Augmentation;Neural stress Mapping with Machine Learning from EEG Data;early Detection and Diagnosis of Brain Related Diseases;quantum Machine Learning: Bridging the Gap Between theory and practice;quantum-Inspired Machine Learning Models for Cyber Threat Intelligence;quantum-Enhanced Secure Multi-party Computation for Cyber Security Applications;quantum Machine Learning algorithms for Big Data Analytics in Cyber Security;advancements in Machine Learning for Anomaly Detection in Cyber Security;Phishing URL Detection: Leveraging Machine Learning for Improved Security Measures;web Of Synonyms: An Enhanced Keyword Extraction Model For Recommendation systems;Enhancing Road Safety: Reckless Driver Detection via OpenCV in Simulated Environments;Comparative Analysis of CNN Models For Insect Detection System;Deep Learning for ECG-Based Arrhythmia Classification: A 1D-CNN with Optimization Techniques;Hybrid Feature Coupled BiLstM to Predict the Trajectories and Motion of the Autonomous Vehicles;intelligent Medical Assistance: Generic Medications Recommender System;osteoarthritis Classification Using Knee X-Ray Images Based on Hybrid Feature Fusion Framework;ARMA-Welch HRV Features: Predicting Ventricular Tachycardia with ML;cross-Language Question-Answering System Using Hugging-Face Transformers;smileScan - Predictive Dental Detection;optimizing Flood Preparedness: A Comprehensive to Refine Rainfall Predict with Ensemble Machine Learning Models;veriFace: Deepfake Detector Using Deep Learning.
Skin cancer, particularly malignant melanoma, presents major diagnostic challenges due to similarities with benign tumors. Automatic detection systems based on deep learning algorithms provide intriguing answers, but ...
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Organisational rules, which guide and constrain enterprise agents' actions, are essential to maintaining structure and coherence in dynamic environments. However, these rules often exist in complex and interconnec...
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It aims to inspire domestic and foreign alumni to participate in the construction of the Second Centenary National Demonstration Zone of the Communist Party of China by reviewing the cognitive computing and system ana...
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The field of computing known as quantum computing is devoted to creating computer technology that is based on the ideas of quantum theory (which makes sense of the way of behaving of energy and material on the nuclear...
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