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Latent lab: Large Language Models for Knowledge Exploration

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arXiv 2023年

作者： Dunnell, Kevin Painter, Trudy Stoddard, Andrew Lippman, Andy Department of Electrical Engineering and Computer Science MIT United States MIT Media Lab United States

This paper investigates the potential of AI models, particularly large language models (LLMs), to support knowledge exploration and augment human creativity during ideation. We present "Latent lab" an interactive tool for discovering connections among MIT Media lab research projects, emphasizing "exploration" over search. The work offers insights into collaborative AI systems by addressing the challenges of organizing, searching, and synthesizing content. In a user study, the tool's success was evaluated based on its ability to introduce users to an unfamiliar knowledge base, ultimately setting the groundwork for the ongoing advancement of human-AI knowledge exploration systems. © 2023, CC BY-NC-SA.

关键词： Knowledge based systems

The Trans-Canada Microwave System

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The Trans-Canada Microwave System

IEEE History of Telecommunications Conference, HISTELCON

作者： David G Michelson Department of Electrical and Computer Engineering Radio Science Lab The University of British Columbia Vancouver BC Canada

On 1 July 1958, the Trans-Canada Microwave System introduced live network television and direct-dialled long distance telephone service to Canadians from coast to coast. Comprising 139 towers spanning more than 6275 kilometres, it was, when completed, the world's longest such network. Later extended and upgraded, the system had an immense impact on Canada's society and economy. Although the achievement has been recognized as one of the most important in the history of Canada and is prominently mentioned in most histories of telecommunications in Canada, a detailed account of its design, construction, and impact has never been prepared. The passing of most of the participants and a lack of primary source material will make preparation of such an account a daunting task going forward.

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Predictive Chemistry Augmented with Text Retrieval

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arXiv 2023年

作者： Qian, Yujie Li, Zhening Tu, Zhengkai Coley, Connor W. Barzilay, Regina Computer Science and Artificial Intelligence Lab MIT United States Department of Electrical Engineering and Computer Science MIT United States Department of Chemical Engineering MIT United States

This paper focuses on using natural language descriptions to enhance predictive models in the chemistry field. Conventionally, chemoinformatics models are trained with extensive structured data manually extracted from the literature. In this paper, we introduce TextReact, a novel method that directly augments predictive chemistry with texts retrieved from the literature. TextReact retrieves text descriptions relevant for a given chemical reaction, and then aligns them with the molecular representation of the reaction. This alignment is enhanced via an auxiliary masked LM objective incorporated in the predictor training. We empirically validate the framework on two chemistry tasks: reaction condition recommendation and one-step retrosynthesis. By leveraging text retrieval, TextReact significantly outperforms state-of-the-art chemoinformatics models trained solely on molecular data. © 2023, CC BY.

关键词： Information retrieval

Multi Socket Network Transmission with Elliptic Curve Cryptography Encryption Algorithm 1

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Multi Socket Network Transmission with Elliptic Curve Crypto...

1st International Conference on Technology, engineering, and Computing Applications, ICTECA 2023

作者： Kawet, Hetly Brinner Yusak Heikhmakhtiar, Aulia Rahardjo, Budi Mantoro, Teddy The Republic of Indonesia Defence University Sains and Defence Technology Faculty Bogor Indonesia Institut Teknologi Bandung School of Electrical Engineering and Informatics Bandung Indonesia Sampoerna University Media-Tech Lab Department of Computer Science Jakarta Indonesia

ISBN: (纸本)9798350360554

Information systems play a crucial role in facilitating effective and efficient media sharing by enabling the exchange of information. However, the current technological landscape is plagued by numerous potential attacks that can compromise the security of exchanged information. Examples of such attacks include stealing user data through interception of user-server communication, spoofing, and sniffing. Robust security measures are essential to mitigate the risks of data leakage and ensure data confidentiality during network-based information exchange. This study proposes designing a communication system based on a multi-socket network, employing the elliptic curve cryptography (ECC) encryption algorithm. The system comprises a single server and multiple clients. This paper analyzes the security of ECC from the performance comparison of ECC and RSA when implemented in multi sochet server. This work uses cryptography library implementation using C programming language. The utilization of the ECC encryption algorithm in network transmission ensures a high level of security and data confidentiality during information exchange. Furthermore, the data transmission system implemented with the ECC algorithm exhibits a swift computation time, thereby expediting key processing and message transmission while maintaining a strong level of security. © 2023 IEEE.

关键词： Geometry

Artemis Removable-Canister Waste Accumulation System & Handler (ARC-WASH): A Portable Modular Space Lavatory

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Artemis Removable-Canister Waste Accumulation System & Handl...

2022 IEEE Aerospace Conference, AERO 2022

作者： Payra, Syamantak Paradiso, Joseph A. Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science United States Responsive Environments Group Massachusetts Institute of Technology Mit Media Lab United States

ISBN: (数字)9781665437608

ISBN: (纸本)9781665437608

The Artemis Removable-Canister Waste Accumulation System and Handler (ARC-WASH) is a portable, modular space lavatory designed for use onboard spacecraft in both microgravity and terrestrial/lunar gravity. In designing this translunar waste collection and storage system, a systems engineering approach is combined with product design principles and inspiration from everyday objects to create a toilet that prioritizes crew comfort, inclusivity, and ease of use by all astronauts, while maintaining cleanliness, efficiency, and functionality in the most demanding of environments. The flexible, modular design of the ARC-WASH accommodates astronauts of all genders, solves problems faced with previous generations of space toilets, and introduces an unprecedented degree of versatility for use in landers, rovers, and even future space habitats. © 2022 IEEE.

关键词： Manned space flight

Transferable and high-quality adversarial example generation leveraging diffusion model

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Transferable and high-quality adversarial example generation...

IEEE International Conference on Multimedia and Expo (ICME)

作者： Kangze Xu Ziqiang He Xiangui Kang Z. Jane Wang Guangdong Key Lab of Information Security School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Electrical and Computer Engineering Dept University of British Columbia Vancouver Canada

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

In recent years, adversarial example methods in deep learning have proliferated. Meanwhile diffusion models have gained wide applications across various tasks due to their superior distribution reconstruction capability. By leveraging the design experience from prior adversarial examples, combining it with the modeling proficiency of diffusion models, and employing a cost function to evaluate image smoothness for regulating the regional distribution of adversarial noise, we propose a novel adversarial example design method. Experiments demonstrate that our generated adversarial examples exhibit both high attack success rate and superior image quality. The controlled distribution region of adversarial noises significantly enhances the subjective visual quality of our generated images.

关键词： Image quality Deep learning Visualization Costs Design methodology Computational modeling Noise Diffusion models Cost function Image reconstruction

Permeable Skin Patch with Miniaturized Octopus-Like Suckers for Biosignal Monitoring

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Permeable Skin Patch with Miniaturized Octopus-Like Suckers ...

Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Aljawharah A. Alsharif Nazek El-Atab SAMA Lab Electrical Engineering Computer Electrical Mathematical Scienceand Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

Wearable electronics demand high adhesion properties through various skin conditions. Here, 3D-printed porous skin patches with octopus-like suckers of different geometries are presented. Experimental and theoretical studies are investigated to show an enhanced, low-cost 3D-printed bioinspired patches that successfully obtain biosignals comparable to commercial *** Relevance— This work establishes low-cost, highly-adhesive skin patches that are irritation- and contamination-free with effortless peel-off technique for biosignal measurement.

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Alioth: A Machine Learning Based Interference-Aware Performance Monitor for Multi-Tenancy Applications in Public cloud

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arXiv 2023年

作者： Shi, Tianyao Yang, Yingxuan Cheng, Yunlong Gao, Xiaofeng Fang, Zhen Yang, Yongqiang MoE Key Lab of Artificial Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Alibaba Cloud Hangzhou China

Multi-tenancy in public clouds may lead to colocation interference on shared resources, which possibly results in performance degradation of cloud applications. cloud providers want to know when such events happen and how serious the degradation is, to perform interference-aware migrations and alleviate the problem. However, virtual machines (VM) in Infrastructure-as-a-Service public clouds are black boxes to providers, where application-level performance information cannot be acquired. This makes performance monitoring intensely challenging as cloud providers can only rely on low-level metrics such as CPU usage and hardware counters. We propose a novel machine learning framework, Alioth, to monitor the performance degradation of cloud applications. To feed the data-hungry models, we first elaborate interference generators and conduct comprehensive co-location experiments on a testbed to build Alioth-dataset which reflects the complexity and dynamicity in real-world scenarios. Then we construct Alioth by (1) augmenting features via recovering low-level metrics under no interference using denoising auto-encoders, (2) devising a transfer learning model based on domain adaptation neural network to make models generalize on test cases unseen in offline training, and (3) developing a SHAP explainer to automate feature selection and enhance model interpretability. Experiments show that Alioth achieves an average mean absolute error of 5.29% offline and 10.8% when testing on applications unseen in the training stage, outperforming the baseline methods. Alioth is also robust in signaling quality-of-service violation under dynamicity. Finally, we demonstrate a possible application of Alioth's interpretability, providing insights to benefit the decision-making of cloud operators. The dataset and code of Alioth have been released on GitHub. Copyright © 2023, The Authors. All rights reserved.

关键词： Quality of service

MSNER: A Multilingual Speech Dataset for Named Entity Recognition

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arXiv 2024年

作者： Meeus, Quentin Moens, Marie-Francine Van Hamme, Hugo LIIR Lab Computer Science Dpt. KU Leuven Belgium PSI Electrical Engineering Dpt. KU Leuven Belgium

While extensively explored in text-based tasks, Named Entity Recognition (NER) remains largely neglected in spoken language understanding. Existing resources are limited to a single, English-only dataset. This paper addresses this gap by introducing MSNER, a freely available, multilingual speech corpus annotated with named entities. It provides annotations to the VoxPopuli dataset in four languages (Dutch, French, German, and Spanish). We have also releasing an efficient annotation tool that leverages automatic pre-annotations for faster manual refinement. This results in 590 and 15 hours of silver-annotated speech for training and validation, alongside a 17-hour, manually-annotated evaluation set. We further provide an analysis comparing silver and gold annotations. Finally, we present baseline NER models to stimulate further research on this newly available dataset. © 2024, CC BY.

关键词： Silver