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arXiv 2024年

作者： Liu, Jiao Sun, Zhu Feng, Shanshan Chen, Caishun Ong, Yew-Soon College of Computing & Data Science Nanyang Technological University Singapore Information Systems Technology and Design Singapore University of Technology and Design Singapore Centre for Frontier AI Research A*STAR The Institute of High Performance Computing A*STAR Singapore

In the evolutionary computing community, the remarkable language-handling capabilities and reasoning power of large language models (LLMs) have significantly enhanced the functionality of evolutionary algorithms (EAs), enabling them to tackle optimization problems involving structured language or program code. Although this field is still in its early stages, its impressive potential has led to the development of various LLM-based EAs. To effectively evaluate the performance and practical applicability of these LLM-based EAs, benchmarks with real-world relevance are essential. In this paper, we focus on LLM-based recommender systems (RSs) and introduce a benchmark problem set, named RSBench, specifically designed to assess the performance of LLM-based EAs in recommendation prompt optimization. RSBench emphasizes session-based recommendations, aiming to discover a set of Pareto optimal prompts that guide the recommendation process, providing accurate, diverse, and fair recommendations. We develop three LLM-based EAs based on established EA frameworks and experimentally evaluate their performance using RSBench. Our study offers valuable insights into the application of EAs in LLM-based RSs. Additionally, we explore key components that may influence the overall performance of the RS, providing meaningful guidance for future research on the development of LLM-based EAs in RSs. © 2024, CC BY.

关键词： Algorithmic languages

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CEER:Cooperative Energy-Efficient Routing Mechanism for Underwater Wireless Sensor Networks Using Clusters

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Computer Systems science & Engineering 2023年第6期45卷 2587-2602页

作者： Sayyed Mudassar Shah Tariq Hussain Babar Shah Farman Ali Khalid Zaman Kyung-Sup Kwak Institute of Computer Science&Information Technology the University of Agriculture Peshawar25000Pakistan High Performance Computing and Networking Institute National Research Council(ICAR-CNR)Naples80131Italy College of Technological Innovation Zayed UniversityDubai19282UAE Department of Software Sejong UniversitySeoul05006Korea Department of Information and Communication Engineering Inha UniversityIncheon22212Korea

Underwater acoustic sensor networks(UWASNs)aim to find varied offshore ocean monitoring and exploration *** most of these applications,the network is composed of several sensor nodes deployed at different depths in the *** nodes located at depth on the seafloor cannot invariably communicate with nodes close to the surface level;these nodes need multihop communication facilitated by a suitable routing *** this research work,a Cluster-based Cooperative Energy Efficient Routing(CEER)mechanism for UWSNs is proposed to overcome the shortcomings of the Co-UWSN and LEACH *** optimal role of clustering and cooperation provides load balancing and improves the network *** simulation results using MATLAB show better performance of CEER routing protocol in terms of various parameters as compared to Co-UWSN routing protocol,i.e.,the average end-to-end delay of CEER was 17.39,Co-UWSN was 55.819 and LEACH was *** addition,the average total energy consumption of CEER was 9.273,Co-UWSN was 12.198,and LEACH was *** packet delivery ratio of CEER was 53.955,CO-UWSN was 42.047,and LEACH was *** stability period CEER was 130.9,CO-UWSN was 129.3,and LEACH was *** obtained results maximized the lifetime and improved the overall performance of the CEER routing protocol.

关键词： Cluster head co-UWSN UWSN relay LEACH CEER

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Search-in-Memory (SiM): Reliable, Versatile, and Efficient data Matching in SSD's NAND Flash Memory Chip for data Indexing Acceleration

arXiv

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arXiv 2024年

作者： Chen, Yun-Chih Chang, Yuan-Hao Kuo, Tei-Wei The Department of Computer Science TU Dortmund Germany The Institute of Information Science Academia Sinica Taipei115 Taiwan Department of Computer Science and Information Engineering High Performance and Scientific Computing Center Center of Data Intelligence: Technologies Applications and Systems of National Taiwan University Taiwan

To index the increasing volume of data, modern data indexes are typically stored on SSDs and cached in DRAM. However, searching such an index has resulted in significant I/O traffic due to limited access locality and inefficient cache utilization. At the heart of index searching is the operation of filtering through vast data spans to isolate a small, relevant subset, which involves basic equality tests rather than the complex arithmetic provided by modern CPUs. We introduce the Search-in-Memory (SiM) chip, which demonstrates the feasibility of performing data filtering directly within a NAND flash memory chip, transmitting only relevant search results rather than complete pages. Instead of adding complex circuits, we propose repurposing existing circuitry for efficient and accurate bitwise parallel matching. We demonstrate how different data structures can use our flexible SIMD command interface to offload index searches. This strategy not only frees up the CPU for more computationally demanding tasks, but it also optimizes DRAM usage for write buffering, significantly lowering energy consumption associated with I/O transmission between the CPU and DRAM. Extensive testing across a wide range of workloads reveals up to a 9X speedup in write-heavy workloads and up to 45% energy savings due to reduced read and write I/O. Furthermore, we achieve significant reductions in median and tail read latencies of up to 89% and 85% respectively. Copyright © 2024, The Authors. All rights reserved.

关键词： Energy utilization

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Modulating Oxygen Affinity to Enhance Liquid Products for the Electrochemical Reduction of Carbon Monoxide

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SmartMat 2025年第2期6卷 214-223页

作者： Jiayi Chen Juan Manuel Arce-Ramos Ioannis Katsounaros Emiel de Smit Saifudin MAbubakar Yanwei Lum Jia Zhang Lei Wang State Key Laboratory of Photocatalysis on Energy and Environment College of ChemistryFuzhou UniversityFuzhouChina Department of Chemical and Biomolecular Engineering National University of SingaporeSingaporeSingapore Institute of High Performance Computing(IHPC) Agency for ScienceTechnology and Research(A*STAR)SingaporeSingapore ExxonMobil Chemical Europe LLC MachelenBelgium ExxonMobil Asia Pacific Pte.Ltd SingaporeSingapore Centre for Hydrogen Innovations National University of SingaporeSingaporeSingapore

Electrocatalytic CO reduction(COR)offers a promising alternative approach for synthesizing valuable chemicals,potentially at a lower carbon intensity as compared to conventional chemical ***-based catalysts have shown encouraging selectivity and activity toward multi-carbon(C^(2+))products,albeit typically in the form of a *** COR selectivity toward specific types of C2+products,such as liquid products with high energy density,remains a *** this study,we developed a Cu/Zn bimetallic catalyst composite and demonstrated enhanced selectivity toward liquid products as compared to reference CuO and Cu-based catalysts,approaching 60%at a high current density of 300 mA/cm^(2).Our investigation highlights that the introduction of Zn promoted the emergence of a Cu/Zn heterojunction interface during *** functional theory simulations were used to rationalize the observed differences in selectivity,revealing that interface plays a crucial role in diminishing the oxygen adsorption at the Cu-sites and modifying the adsorption energy of COR reaction intermediates,consequently leading to enhanced selectivity toward liquid products.

关键词： C_(2)liquid production CO_(2)/CO reduction copper/zinc electrocatalysts oxygen affinity

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Visualization and Analysis of Transformer Attention 1

Visualization and Analysis of Transformer Attention

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1st Workshop on Artificial Intelligence for Perception and Artificial Consciousness, AIxPAC 2023

作者： Calderaro, Salvatore Lo Bosco, Giosué Rizzo, Riccardo Vella, Filippo Department of Mathematics and Computer Science Università degli Studi di Palermo via Archirafi 34 Palermo Italy Institute of High Performance Computing and Networking National Research Council of Italy CNR via Ugo La Malfa 153 Palermo Italy

The capability to select the relevant portion of the input is a key feature to limit the sensory input and focus on the most informative collected part. The transformer architecture is among the most performing deep neural network architectures due to the attention mechanism. The attention allows us to spot relevant connections between portions of the images and highlight these connections. Since the model is complex, it is not easy to determine which are these connections and the important areas. We discuss a technique to show these areas and highlight the regions most relevant for label attribution. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Deep neural networks

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ASBase:The universal database for aggregate science

Aggregate

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Aggregate 2023年第1期4卷 148-157页

作者： Junyi Gong Wanjun Gong BoWu Haoran Wang Wei He Zhongyang Dai Yangzhong Li Yong Liu Zhiming Wang Xiaojun Tuo Jacky W.Y.Lam Zijie Qiu Zheng Zhao Ben Zhong Tang Shenzhen Institute of Aggregate Science and Technology School of Science and EngineeringThe Chinese University of Hong KongShenzhenGuangdongChina AIE-Institute State Key Laboratory of Luminescence Materials and DevicesCenter of Aggregation-induced EmissionKey Laboratory of Luminescence from Molecular Aggregates of Guangdong ProvinceSouth China University of Technology(SCUT)GuangzhouChina High Performance Computing Department National Supercomputing Center in ShenzhenShenzhenChina Department of Chemistry Hong Kong University of Science and TechnologyKowloonHong KongChina

This paper reports the first universal and versatile database on aggregate materials for the field of aggregate science *** the current stage,the database(http://119.91.135.188:8080/)contains over 1000 entries of organic aggregate material systems(mainly luminescent systems at the current stage)with a unique data structure which is designed particularly for aggregate materials and containing the photophysics and physicochemical properties of the compounds in different statuses of aggregation,including dilute solution form,pristine solid-state,stable crystalline,and nanoaggregates formed in *** web-based interface of the database provided functions to index,search,manipulate,fetch and deposit data *** addition,a background calculation service optimizes the chemical structure of new entries on different levels of *** database also provided background API for interactive developments of prediction or regression models based on machine-learning algorithms.

关键词： aggregate science aggregation-induced emission data-driven model database

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Boosting Meaningful Dependency Mining with Clustering and Covariance Analysis

Boosting Meaningful Dependency Mining with Clustering and Co...

引用

International Conference on data Engineering

作者： Xi Wang Ruochun Jin Wanrong Huang Yuhua Tang Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha China Department of Intelligent Data Science College of Computer Science and Technology National University of Defense Technology Changsha China

ISBN: (数字)9798350317152

ISBN: (纸本)9798350317169

Functional dependencies (FDs) form a valuable ingredient for various data management tasks. However, existing methods can hardly discover practical and interpretable FDs, especially in large noisy real-life datasets. This paper studies the problem of discovering meaningful functional dependencies (FDms) that utilize support and error parameters to capture interesting dependencies in such datasets and proposes an efficient discovery algorithm called FDMε. In order to scale with large datasets, FDM ε employs an efficient sampling method with accuracy guarantees to capture the differences between tuple pairs and to quantify the connection between support/error of dependencies on samples and those on the entire dataset. Moreover, it adopts a clustering-based correlated attributes extraction to divide the exponentially large search space into multiple small sub-spaces and proposes an easy-first traversal strategy with covariance-based guidance that quickly detects candidate dependencies and validates them. Additionally, we prove a covariance lower bound as an additional pruning criterion to reduce the search space. Extensive experiments on real-life and synthetic datasets demonstrate that FDM ε is 14 times faster than existing discovery algorithms on average, up to 31 times, and scales to larger datasets with the least memory cost.

关键词： Accuracy Costs Clustering algorithms Search problems data engineering Noise measurement Frequency division multiplexing

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NHC-mediated photocatalytic para-selective C–H acylation of aryl alcohols: regioselectivity control via remote radical spiro cyclization

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science China Chemistry 2025年

作者： Tinglei Zhang Lala Wang Xiaolin Peng Tianhui Liao Dongmei Chen Ting Tu Donghan Liu Ziye Cheng Shiqing Huang Shi-Chao Ren Xinglong Zhang Yonggui Robin Chi State Key Laboratory of Green Pesticide Key Laboratory of Green Pesticide and Agricultural Bioengineering Ministry of Education Guizhou University Qiannan Medical College for Nationalities School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Department of Chemistry The Chinese University of Hong Kong Institute of High Performance Computing Agency for Science Technology and Research

Friedel-Crafts reaction and transition-metal catalysis represent primary methodologies for arene acylation; however, suffer from certain limitations, such as electronic effect-dependent reactivity, regioselectivity issues, the necessity of directing group, and relatively exceptionally limited exploration in meta-and para-acylations. N-heterocyclic carbene(NHC) catalysis has recently emerged as a promising alternative strategy for arene acylation, offering distinct regioselectivity profiles that are challenging to achieve through known methods. Herein, an NHC-mediated photo-catalytic para-selective C–H acylation of aryl alcohols is disclosed. The reaction employs a remote radical-induced temporary spiro cyclization strategy, proceeding via tandem radical dearomatization, radical acylation, rearomatization processes. Combined experimental and computational mechanistic studies support the proposed reaction pathway and observe an exclusive para-selectivity regardless of the nature of the substituents on the substrates. Despite the less satisfactory yields, the current method exhibits non-electronic nature-based reactivity and regioselectivity, enabling quick access to acylated arenes that are difficult or impossible for reported methods.

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Cooperative Colorization: Exploring Latent Cross-Domain Priors for NIR Image Spectrum Translation

arXiv

引用

arXiv 2023年

作者： Yang, Xingxing Chen, Jie Yang, Zaifeng Department of Computer Science Hong Kong Baptist University Hong Kong Institute of High Performance Computing Astar Singapore

Near-infrared (NIR) image spectrum translation is a challenging problem with many promising applications. Existing methods struggle with the mapping ambiguity between the NIR and the RGB domains, and generalize poorly due to the limitations of models' learning capabilities and the unavailability of sufficient NIR-RGB image pairs for training. To address these challenges, we propose a cooperative learning paradigm that colorizes NIR images in parallel with another proxy grayscale colorization task by exploring latent cross-domain priors (i.e., latent spectrum context priors and task domain priors), dubbed CoColor. The complementary statistical and semantic spectrum information from these two task domains - in the forms of pre-trained colorization networks - are brought in as task domain priors. A bilateral domain translation module is subsequently designed, in which intermittent NIR images are generated from grayscale and colorized in parallel with authentic NIR images;and vice versa for the grayscale images. These intermittent transformations act as latent spectrum context priors for efficient domain knowledge exchange. We progressively fine-tune and fuse these modules with a series of pixel-level and feature-level consistency constraints. Experiments show that our proposed cooperative learning framework produces satisfactory spectrum translation outputs with diverse colors and rich textures, and outperforms state-of-the-art counterparts by 3.95dB and 4.66dB in terms of PNSR for the NIR and grayscale colorization tasks, respectively. Copyright © 2023, The Authors. All rights reserved.

关键词： Textures

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Improving the learning performance by exploiting multimedia in eXtreme apprenticeship

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Multimedia Tools and Applications 2024年 1-25页

作者： Persia, Fabio D’Auria, Daniela Ge, Mouzhi Pilato, Giovanni Department of Information Engineering Computer Science and Mathematics University of L’Aquila Via Vetoio L’Aquila67100 Italy Faculty of Computer Science Free University of Bozen-Bolzano Piazza Domenicani 3 Bozen-Bolzano39100 Italy Faculty of European Campus Rottal-Inn Deggendorf Institute of Technology Dieter-Görlitz-Platz 1 Deggendorf94469 Germany Institute for High Performance Computing and Networking National Research Council of Italy Via Ugo La Malfa 153 Palermo90146 Italy

From prior studies on eXtreme Apprenticeship (XA), it can be seen that XA has emerged as an innovative and effective educational approach. The technology in computer science evolves rapidly and XA tackles the gap between University education and industry development. Additionally, distance learning by multimedia is more and more important, sometimes even becoming necessary. As a result, this paper intends to study how to integrate XA and multimedia to improve the learning performance in computer science, with particular reference to the programming courses. Since computer science is mostly driven by the new applications, XA and multimedia are considered to be effective and efficient to reduce the cognitive efforts by practical demonstration. The experimental results, based on the case study of the operating systems course at the Bachelor’s level, show that exploiting multimedia in XA can significantly improve the learning performance in terms of grade distributions, reliability, knowledge transfer and student satisfaction with respect to more traditional approaches based on frontal lectures. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Distance education

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