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Multidimensional Voronoi Constellations vs. Short Blocklength Probabilistic Shaping: A Comparison for Multilevel Coding Approach

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Multidimensional Voronoi Constellations vs. Short Blocklengt...

Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Yajie Sheng Bin Chen Yi Lei Jingxin Deng Jiwei Xu Mengfan Fu Qunbi Zhuge Shen Li Department of Computer Science and Information Engineering Hefei University of Technology Hefei China Department of Electronic Engineering State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong University Shanghai China Department of Electrical and Computer Engineering Centre of Optics Photonics and Lasers (COPL) Université Laval Québec Canada

Performance of concatenated multilevel coding with probabilistic shaping (PS) and Voronoi constellations (VCs) is analysed over AWGN channel. Numerical results show that VCs provide up to 1.3 dB SNR gains over PS-QAM ... 详细信息

ISBN: (数字)9798350379266

ISBN: (纸本)9798350379273

关键词： AWGN channels Wireless communication Optical fibers Probabilistic logic Optical fiber communication Encoding Complexity theory Gain Photonics Signal to noise ratio

How Do Hackathons Foster Creativity? Towards AI Collaborative Evaluation of Creativity at Scale

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arXiv 2025年

作者： Falk, Jeanette Chen, Yiyi Rafner, Janet Zhang, Mike Bjerva, Johannes Nolte, Alexander Aalborg University Copenhagen Department of Computer Science Copenhagen Denmark Center for Hybrid Intelligence Department of Management and Aarhus Institute for Advanced Studies Aarhus University Aarhus Denmark Aalborg University Copenhagen Department of Computer Science Pioneer Centre for Artificial Intelligence Copenhagen Denmark Software Engineering and Technology Eindhoven University of Technology Eindhoven Netherlands and Software and Societal Systems Carnegie Mellon University PittsburghPA United States

Hackathons have become popular collaborative events for accelerating the development of creative ideas and prototypes. There are several case studies showcasing creative outcomes across domains such as industry, education, and research. However, there are no large-scale studies on creativity in hackathons which can advance theory on how hackathon formats lead to creative outcomes. We conducted a computational analysis of 193,353 hackathon projects. By operationalizing creativity through usefulness and novelty, we refined our dataset to 10,363 projects, allowing us to analyze how participant characteristics, collaboration patterns, and hackathon setups influence the development of creative projects. The contribution of our paper is twofold: We identified means for organizers to foster creativity in hackathons. We also explore the use of large language models (LLMs) to augment the evaluation of creative outcomes and discuss challenges and opportunities of doing this, which has implications for creativity research at large. © 2025, CC BY.

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Feature and Performance Comparison of FaaS Platforms

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Feature and Performance Comparison of FaaS Platforms

IEEE International Conference on Software Engineering and Service Sciences (ICSESS)

作者： Penghui Ma Peichang Shi Guodong Yi National Key Laboratory of Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha China Key Laboratory of Software Engineering for Complex Systems College of Computer Science National University of Defense Technology Changsha China Xiangjiang Lab Changsha China School of Advanced Interdisciplinary Studies Hunan University Of Technology and Business Changsha China

With serverless computing offering more efficient and cost-effective application deployment, the diversity of serverless platforms presents challenges to users, including platform lock-in and costly migration. Moreover, due to the black box nature of function computing, traditional performance benchmarking methods are not applicable, necessitating new studies. This article presents a detailed comparison of six major public cloud function computing platforms and introduces a benchmarking framework for function computing performance. This framework aims to help users make comprehensive comparisons and select the most suitable platform for their specific needs.

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ST-KeyS: Self-Supervised Transformer for Keyword Spotting in Historical Handwritten Documents

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arXiv 2023年

作者： Jemni, Sana Khamekhem Ammar, Sourour Souibgui, Mohamed Ali Kessentini, Yousri Cheddad, Abbas Digital Research Center of Sfax B.P. 275 Sakiet Ezzit Sfax3021 Tunisia Laboratory of Signals systems Artificial Intelligence and networks Sfax Tunisia Multimedia Information systems and Advanced Computing Laboratory Tunisia Computer Vision Center Computer Science Department Universitat Autònoma de Barcelona Spain Department of Computer Science Blekinge Institute of Technology Karlskrona Sweden

Keyword spotting (KWS) in historical documents is an important tool for the initial exploration of digitized collections. Nowadays, the most efficient KWS methods are relying on machine learning techniques that require a large amount of annotated training data. However, in the case of historical manuscripts, there is a lack of annotated corpus for training. To handle the data scarcity issue, we investigate the merits of the self-supervised learning to extract useful representations of the input data without relying on human annotations and then using these representations in the downstream task. We propose ST-KeyS, a masked auto-encoder model based on vision transformers where the pretraining stage is based on the mask-and-predict paradigm, without the need of labeled data. In the fine-tuning stage, the pre-trained encoder is integrated into a siamese neural network model that is fine-tuned to improve feature embedding from the input images. We further improve the image representation using pyramidal histogram of characters (PHOC) embedding to create and exploit an intermediate representation of images based on text attributes. In an exhaustive experimental evaluation on three widely used benchmark datasets (Botany, Alvermann Konzilsprotokolle and George Washington), the proposed approach outperforms state-of-the-art methods trained on the same datasets. © 2023, CC BY.

关键词： Image enhancement

Performance assessment of vehicle interdiction strategies in a simulation based environment on a complex transportation network

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arXiv 2023年

作者： Samanta, Sukanya Uniyal, Jatin Sen, Goutam Ghosh, Soumya Kanti Advanced Technology Development Centre Indian Institute of Technology Kharagpur West Bengal Kharagpur721302 India Department of Industrial and Systems Engineering Indian Institute of Technology Kharagpur West Bengal Kharagpur721302 India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur West Bengal Kharagpur721302 India

We consider the escape interdiction problem in a transportation network. In the absence of traffic in the network, the criminal/attacker tries to escape from the city using any of the shortest paths from the crime scene to any randomly chosen exit point. In the presence of traffic, the attacker chooses the optimal path, which takes minimum time to reach his destination. On the contrary, police/defenders try to interdict the criminal on his escape route. This is a challenging task for police with limited resources. Again, a real city road network is also complex in nature. First, we develop a simulation-based model for the optimal allocation of resources using the SUMO simulator. Next, we focus on developing a more advanced search strategy like routing with optimal resource allocation. We develop a novel meta-heuristic approach in a simulation environment to interdict the attacker in a dynamic crime scenario. Like the previous approach, the attacker follows the path with optimal time to escape from the city. In contrast, defenders try to catch the attacker regardless of the path which the attacker takes. The defenders aim is to maximize the interdiction probability. As time plays a vital role, we choose a meta-heuristic approach to provide quality solutions in a time-efficient manner. We test the developed meta-heuristic with a case study on the IIT Kharagpur map, India. We analyze the performance of the mentioned approaches using the SUMO simulator both in the presence of traffic and without traffic. We develop a linear regression model to generate optimal path in the presence of traffic. Here traffic is generated randomly in the whole network using the SUMO simulator. Copyright © 2023, The Authors. All rights reserved.

关键词： Genetic algorithms

St-Keys: Self-Supervised Transformer for Keyword Spotting in Historical Handwritten Documents

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SSRN

SSRN 2023年

作者： Jemni, Sana Khamekhem Ammar, Sourour Souibgui, Mohamed Ali Kessentini, Yousri Cheddad, Abbas Digital Research Center of Sfax B.P. 275 Sakiet Ezzit Sfax3021 Tunisia SM@RTS: Laboratory of Signals systeMs aRtificial Intelligence and neTworkS MIR@CL: Multimedia InfoRmation systems and Advanced Computing Laboratory Computer Vision Center Computer Science Department Universitat Aut`onoma de Barcelona Spain Department of Computer Science Blekinge Institute of Technology Karlskrona Sweden

Keyword spotting (KWS) in historical documents is an important tool for the initial exploration of digitized collections. Nowadays, the most efficient KWS methods are relying on machine learning techniques that require a large amount of annotated training data. However, in the case of historical manuscripts, there is a lack of annotated corpus for training. To handle the data scarcity issue, we investigate the merits of the self-supervised learning to extract useful representations of the input data without relying on human annotations and then using these representations in the downstream task. We propose ST-KeyS, a masked auto-encoder model based on vision transformers where the pretraining stage is based on the mask-and-predict paradigm, without the need of labeled data. In the fine-tuning stage, the pre-trained encoder is integrated into a siamese neural network model that is fine-tuned to improve feature embedding from the input images. We further improve the image representation using pyramidal histogram of characters (PHOC) embedding to create and exploit an intermediate representation of images based on text attributes. In an exhaustive experimental evaluationon three widely used benchmark datasets (Botany, Alvermann Konzilsprotokolle and George Washington), the proposed approach outperforms state-of-the-art methods trained on the same datasets. © 2023, The Authors. All rights reserved.

关键词： Embeddings

Navigation-GPT: A Robust and Adaptive Framework Utilizing Large Language Models for Navigation Applications

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arXiv 2025年

作者： Ma, Feng Wang, Xiu-Min Chen, Chen Xu, Xiao-Bin Yan, Xin-Ping Wuhan University of Technology Wuhan China Intelligent Transportation Systems Research Center Wuhan University of Technology Wuhan China School of Computer Science & Engineering Wuhan Institute of Technology Wuhan China China-Austria Belt and Road Joint Laboratory on Artificial Intelligence and Advanced Manufacturing Hangzhou Dianzi University Hangzhou China Nanjing Smart Water Transport Technology Co. Ltd. Nanjing China

Existing navigation decision support systems often perform poorly when handling non-predefined navigation scenarios. Leveraging the generalization capabilities of large language model (LLM) in handling unknown scenarios, this research proposes a dual-core framework for LLM applications to address this issue. Firstly, through ReAct-based prompt engineering, a larger LLM core decomposes intricate navigation tasks into manageable sub-tasks, which autonomously invoke corresponding external tools to gather relevant information, using this feedback to mitigate the risk of LLM hallucinations. Subsequently, a fine-tuned and compact LLM core, acting like a first-mate is designed to process such information and unstructured external data, then to generates context-aware recommendations, ultimately delivering lookout insights and navigation hints that adhere to the International Regulations for Preventing Collisions at Sea (COLREGs) and other rules. Extensive experiments demonstrate the proposed framework not only excels in traditional ship collision avoidance tasks but also adapts effectively to unstructured, non-predefined, and unpredictable scenarios. A comparative analysis with DeepSeek-R1, GPT-4o and other SOTA models highlights the efficacy and rationality of the proposed framework. This research bridges the gap between conventional navigation systems and LLMs, offering a framework to enhance safety and operational efficiency across diverse navigation applications. © 2025, CC BY-SA.

关键词： Ships

Brownian motion simulation of SiO2 abrasive nanoparticle on SiC substrate surface 10

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Brownian motion simulation of SiO2 abrasive nanoparticle on ...

10th International Conference on Leading Edge Manufacturing Technologies in 21st Century, LEM 2021

作者： Saenna, Soraya Khajornrungruang, Panart Blattler, Aran Permpatdechakul, Thitipat Suzuki, Keisuke Bakier, Mohammed A. Graduate School of Computer Science and Systems Engineering Kyushu Institute Technology 680-4 Kawazu Iizuka-shi Fukuoka820-8502 Japan Dept. of Intelligent and Control Systems Advanced Mechanical Division Kyushu Institute of Technology 680-4 Kawazu Iizuka-shi Fukuoka820-8502 Japan

Chemical-Mechanical Polishing (CMP) process has emerged as the method of choice for planarization in the semiconductor industry. The interaction force between the surface being polished and the abrasive nanoparticles plays a significant role in flattening the substrate surface in the CMP process. For example, when the SiO2 nanoparticle is distant from the SiC substrate surface, the interaction force between the surface and the nanoparticles is presented. This force could be analysed using Derjaguin and Landau and Verwey and Overbeek (DLVO) theory and particle Brownian motion. According to the simulation results, we found that very fine abrasive nanoparticle such as smaller than approximately 10 nm is comparatively approach to the surface being polished more certainly. © 2021 The Japan Society of Mechanical Engineers.

关键词： Silicon carbide

A Context-Aware Exercise Facilitation System While Doing Other Tasks

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A Context-Aware Exercise Facilitation System While Doing Oth...

IEEE Global Conference on Consumer Electronics (GCCE)

作者： Mizuki Kobayashi Airi Tsuji Kaori Fujinami Grad. School of Bio-Functions and Systems Science Tokyo University of Agriculture and Technology Tokyo Japan Div. of Advanced Information Technology and Computer Science Tokyo University of Agriculture and Technology Tokyo Japan

We proposed a context-aware exercise-facilitation system that can be used in parallel with various tasks in daily life. The offline-evaluation results show that the proposed system can recommend appropriate exercises ... 详细信息

ISBN: (纸本)9781665492331

关键词： Task analysis Consumer electronics