At the time of this writing more than 60 (sixty) companies in the world are building quantum computers. These computers, based on quantum physics principles, are radically different from those that operate according t...
ISBN:
(纸本)9798350336429
At the time of this writing more than 60 (sixty) companies in the world are building quantum computers. These computers, based on quantum physics principles, are radically different from those that operate according to the more familiar principles of classical physics. A quantum algorithm takes a number of classical bits as its input, manipulates them so as to create a superposition of all their possible states, further manipulates this exponentially large superposition to obtain the final quantum result, and then measures the result to get (with the appropriate probability distribution) the same number of output bits as in its input. For the middle phase, there are elementary operations which count as one step and yet manipulate all the exponentially many amplitudes of the superposition. The natural language of these quantum gates is that of linear algebra in a complex (Hilbert) vector space. Since 2017 it is known that it is possible to replace the linear algebra with some string-rewriting rules which are no more complicated than the basic rules of arithmetic. The original system was introduced by Terry Rudolph and has been promoted and disseminated in large-scale outreach projects (among others) by Diana Franklin (University of Chicago) and Sofia Economou and Ed Barnes (Virginia Tech) as well as several other educators at the high-school level. In this paper we show how a slightly modified (though still very elementary) system can be used to communicate a visual and entirely operational understanding of key quantum computation concepts such as: superposition, probability, entanglement, phase, interference and unitary state evolution, as they occur in well-known quantum algorithms. We give concrete examples of proving properties for quantum gates and quantum circuits without resorting at all to complex numbers or matrix multiplication. Only simple, abacus-like operations are used-hence the title of the paper. The system we present allows a novice learner to actual
Developers regularly rely on third party code obtained from collaborative software platforms and code management systems. Despite the benefits and efficiency, this introduces potential security and privacy risks. The ...
详细信息
Developers regularly rely on third party code obtained from collaborative software platforms and code management systems. Despite the benefits and efficiency, this introduces potential security and privacy risks. The identification of security vulnerabilities and security risks in dependencies has received more attention than the identification of privacy risks, which we address here. Specifically, we focus on the privacy risks created with the inclusion of data which has been identified as private or personally identifiable. The challenge of identifying privacy risk is amplified by the overlapping but disjoint definitions of privacy across jurisdictions, so that that code developed in one region or for one use context may inadvertently result in compliance and privacy risks in another regulatory context. We describe the feasibility of using a range of approaches, from string matching through different types of Natural Language Processing (NLP), to automate the detection of privacy sensitive source code references. We leverage the categorical definitions in the General Data Privacy Regulation (GDPR) and California Consumer Privacy Act (CCPA) to define sensitivity. We argue that current commercial methods are insufficient to capture the nuanced nature of privacy risks in code. To test the potential of NLP approaches, we developed a modest labeled corpus of 97 code snippets from GitHub, encompassing both sensitive and non-sensitive control data. We report on the effectiveness of different NLP-based models, including fine-tuned BERT-based models such as CodeBERT and GraphCodeBERT, and large language models such as ChatGPT and Google BARD. Our analysis reveals that advanced systems do not necessarily offer superior accuracy, with fine-tuned models reaching 86% accuracy, and larger language models not exceeding 72%. These findings provide insights into potential areas for enhancing the automation of privacy-sensitive information detection in code, given the challenges un
This study benchmarks Kalman, Savitzky-Golay, and Gaussian filters to improve eye landmark detection crucial for online proctoring systems. Using eye-tracking video data, we evaluated filters on Mean Squared Error (MS...
详细信息
Due to the recent developments in communications technology,cognitive computations have been used in smart healthcare techniques that can combine massive medical data,artificial intelligence,federated learning,bio-ins...
详细信息
Due to the recent developments in communications technology,cognitive computations have been used in smart healthcare techniques that can combine massive medical data,artificial intelligence,federated learning,bio-inspired computation,and the Internet of Medical *** has helped in knowledge sharing and scaling ability between patients,doctors,and clinics for effective treatment of ***-based respiratory disease detection and monitoring are crucial in this direction and have shown several promising *** the subject’s speech can be remotely recorded and submitted for further examination,it offers a quick,economical,dependable,and noninvasive prospective alternative detection ***,the two main requirements of this are higher accuracy and lower computational complexity and,in many cases,these two requirements do not correlate with each *** problem has been taken up in this paper to develop a low computational complexity-based neural network with higher accuracy.A cascaded perceptual functional link artificial neural network(PFLANN)is used to capture the nonlinearity in the data for better classification performance with low computational *** proposed model is being tested for multiple respiratory diseases,and the analysis of various performance matrices demonstrates the superior performance of the proposed model both in terms of accuracy and complexity.
The analysis of particle sizes in seabed sediments plays an important role in various fields. However, acquiring digital sediment images has been challenging due to the characteristics of sediment particles and the co...
详细信息
The accuracy of deep neural networks is significantly influenced by the effectiveness of mini-batch construction during training. In single-label scenarios, such as binary and multi-class classification tasks, it has ...
详细信息
With the emergence of deep learning, Convolutional Neural Network (CNN) models have been proposed to advance the progress of various applications, including face recognition, object detection, pattern recognition, and...
详细信息
This panel explores the evolving relationship between technology and society through the lens of Social informatics (SI) research, with a specific focus on the integration of Artificial Intelligence (AI) into social a...
详细信息
This panel explores the evolving relationship between technology and society through the lens of Social informatics (SI) research, with a specific focus on the integration of Artificial Intelligence (AI) into social and organizational settings. Experts will discuss how AI adoption across various sectors influences social dynamics, cultural norms, and ethical considerations for a range of stakeholders. Key themes include responsible AI development, user privacy concerns, and addressing biases in AI algorithms. Through interdisciplinary insights, the panel aims to engage the audience in a lively discussion of AI's impact on society, exploring current challenges and opportunities at the intersection of SI and AI research. 87 Annual Meeting of the Association for Information Science & Technology | Oct. 25 – 29, 2024 | Calgary, AB, Canada.
Multi-Task Learning (MTL) is a framework, where multiple related tasks are learned jointly and benefit from a shared representation space, or parameter transfer. To provide sufficient learning support, modern MTL uses...
详细信息
Graph embedding has become an increasingly important technique for analyzing graph-structured data. By representing nodes in a graph as vectors in a low-dimensional space, graph embedding enables efficient graph proce...
详细信息
暂无评论