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9th International Conference on Web Research, ICWR 2023

作者： Khomami, Mohammad Mehdi Daliri Saghiri, Ali Mohammad Rezvanian, Alireza Meybodi, Mohammad Reza Computer Engineering Amirkabir University of Technology Soft Computing Laboratory Department Tehran Iran University of Science and Culture Department of Computer Engineering Tehran Iran

ISBN: (纸本)9798350399691

Nowadays, we are faced with a huge amount of private data generated in different ecosystems, including the Internet of Things, social networks, peer-to-peer networks, and e-commerce, to mention a few. The performance of traditional object storage and retrieval systems concerning response time is going to be degraded by a drastic increase in generated data. This problem becomes more challenging when a specific private object should be found. To address the mentioned problem, this paper suggests scalable object storage and retrieval. To do this, three well-known methods, content-addressable networks from peer-to-peer systems, vector space model from information retrieval systems, and siamese neural networks from neural networks theory, are involved in a framework to bring a scalable system to solve the mentioned problems. The suggested framework is unique to the best of our knowledge because there is no fusion among mentioned fields reported so far. A case study on signature detection is also conducted to evaluate the proposed framework. The results show that, compared to a centralized system, the proposed framework significantly decreases the response time for detecting a signature while maintaining the same accuracy. In addition, the proposed mechanism does not require the private objects to be sent to a central entity, which helps to alleviate privacy concerns. © 2023 IEEE.

关键词： Peer to peer networks

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A survey on graph neural network-based next POI recommendation for smart cities

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Journal of Reliable Intelligent Environments 2024年第3期10卷 299-318页

作者： Yu, Jian Guo, Lucas Zhang, Jiayu Wang, Guiling Department of Computer Science and Soft Engineering Auckland University of Technology Auckland New Zealand School of Information Science and Technology Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data North China University of Technology Beijing China

Amid the rise of mobile technologies and Location-Based Social Networks (LBSNs), there’s an escalating demand for personalized Point-of-Interest (POI) recommendations. Especially pivotal in smart cities, these systems aim to enhance user experiences by offering location recommendations tailored to past check-ins and visited POIs. Distinguishing itself from traditional POI recommendations, the next POI approach emphasizes predicting the immediate subsequent location, factoring in both geographical attributes and temporal patterns. This approach, while promising, faces with challenges like capturing evolving user preferences and navigating data biases. The introduction of Graph Neural Networks (GNNs) brings forth a transformative solution, particularly in their ability to capture high-order dependencies between POIs, understanding deeper relationships and patterns beyond immediate connections. This survey presents a comprehensive exploration of GNN-based next POI recommendation approaches, delving into their unique characteristics, inherent challenges, and potential avenues for future research. © The Author(s) 2024.

关键词： Location based services

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End-to-end differentiability and tensor processing unit computing to accelerate materials’ inverse design

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npj Computational Materials 2023年第1期9卷 1072-1083页

作者： Han Liu Yuhan Liu Kevin Li Zhangji Zhao Samuel S.Schoenholz Ekin D.Cubuk Puneet Gupta Mathieu Bauchy SOlids inFormaTics AI-Laboratory(SOFT-AI-Lab) College of Polymer Science and EngineeringSichuan UniversityChengdu 610065China AIMSOLID Research Wuhan 430223China Physics of AmoRphous and Inorganic Solids Laboratory(PARISlab) Department of Civil and Environmental EngineeringUniversity of CaliforniaLos AngelesCA 90095USA Department of Computer Science University of CaliforniaLos AngelesCA 90095USA Google Research Brain TeamMountain ViewCAUSA Department of Electrical and Computer Engineering University of CaliforniaLos AngelesCA 90095USA

Numerical simulations have revolutionized material ***,although simulations excel at mapping an input material to its output property,their direct application to inverse design has traditionally been limited by their high computing cost and lack of ***,taking the example of the inverse design of a porous matrix featuring targeted sorption isotherm,we introduce a computational inverse design framework that addresses these challenges,by programming differentiable simulation on TensorFlow platform that leverages automated end-to-end *** to its differentiability,the simulation is used to directly train a deep generative model,which outputs an optimal porous matrix based on an arbitrary input sorption isotherm ***,this inverse design pipeline leverages the power of tensor processing units(TPU)—an emerging family of dedicated chips,which,although they are specialized in deep learning,are flexible enough for intensive scientific *** approach holds promise to accelerate inverse materials design.

关键词： enough inverse isotherm

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A Comparative Analysis of Artificial Intelligence and Business Intelligence Using Big Data Analytics 1

A Comparative Analysis of Artificial Intelligence and Busine...

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1st International Conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Marella, Bhagath Chandra Chowdari Vegineni, Gopi Chand Addanki, Sireesha Ellahi, Ehsan Arun Kumar, K. Mandal, Rishabh Insights & Data Department of Financial Services Capgemini India Enrollment and Eligibility Team India System soft Technologies LLC India Cleveland State University Department of Information Systems OH United States Tula's Institute Department of Computer Science and Engineering UK Dehradun India India

ISBN: (纸本)9798331518578

Business intelligence (BI) encompasses the tools and uses to gather, combine, examine, and display data about a specific firm. Using historical and current efficiency comparisons, these structures assist in formulating plans and choices to achieve better outcomes in the future. Additionally, it helps firms determine which business issues and industry trends require attention. It has several benefits, such as increasing responsibility and efficiency, but it carries some disadvantages, such as being expensive, complicated, and time-consuming to adopt. Using big data-driven approaches to optimize talent recruitment is essential for improved decisions in the cutthroat world of BI. The efficacy of many machine learning algorithms to increase recruiting performance and accuracy is compared in this investigation. For optimizing, cross-validating, and hyperparameter modification were employed. The Random Forest (RF) algorithm has the greatest accuracy (92.9%), trailed by the Gradient Boosting Classifying system (92.6%) and the neural network (NNs) models (92.7%). These findings imply that sophisticated ML algorithms, in particular RF and NN, can greatly improve BI platforms' hiring procedures. Recruiters can benefit from this research's insightful recommendations for incorporating advanced ML methods into talent recruitment plans. © 2025 IEEE.

关键词： Data accuracy

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A Framework for Scalable Object Storage and Retrieval Considering Privacy Concerns: A Case Study on the Signature Detection

A Framework for Scalable Object Storage and Retrieval Consid...

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International Conference on Web Research (ICWR)

作者： Mohammad Mehdi Daliri Khomami Ali Mohammad Saghiri Alireza Rezvanian Mohammad Reza Meybodi Soft Computing Laboratory Department Computer Engineering Amirkabir University of Technology Tehran Iran Department of Computer Engineering University of Science and Culture Tehran Iran

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Process Mining Approach to Analyze Engagement in Campaign Activities 9

Process Mining Approach to Analyze Engagement in Campaign Ac...

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9th IEEE Information Technology International Seminar, ITIS 2023

作者： Nugroho, Aryo Ambarwati, Awalludiyah Faza, Arsi Raniah Falah, Ardi Ilham Putra, Oddy Virgantara Widiastuti, Ika Universitas Narotama Department of Information System Surabaya Indonesia UPN Veteran Jawa Timur Department of Accounting Surabaya Indonesia AONO Research Center Department of Soft Computing Surabaya Indonesia Universitas Darussalam Gontor Department of Informatics Ponorogo Indonesia Ewha Womans University Department of Computer Science & Engineering. Seoul Korea Republic of

ISBN: (纸本)9798350306835

Campaign strategies are evolving because of developments in communication technologies. Campaign activities have become more attractive to the younger generation with the existence of social media. There is much research related to campaigns, but it focuses on data collection and content. This research tries to look at it from the other side, namely from the perspective of the campaign team. How can teams improve performance and ensure that strategies are executed correctly? The analysis was carried out using process mining. The methodology used is the Project Mining Methodology, supported by data, identification, conformity checking, and quality improvement. The data used was taken from a Facebook group that was specifically created and operated during the 100 days of the official campaign. Interactions occurred with 2215 members with 975 active members, of which there were 357 posts, 8755 reactions, 1275 comments, and 280 shares. The results obtained from this process show weekly posting patterns and responses. Furthermore, we can see the involvement of key figures in the activities of the campaign group. © 2023 IEEE.

关键词： Social networking (online)

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Embracing Safe Contacts with Contact-aware Planning and Control

arXiv

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arXiv 2023年

作者： Li, Zhaoting Zamora, Miguel Zheng, Hehui Coros, Stelian Computational Robotics Lab Computer Science Department ETH Zurich Switzerland Soft Robotics Lab Department of Mechanical and Process Engineering ETH Zurich Switzerland

Unlike human beings that can employ the entire surface of their limbs as a means to establish contact with their environment, robots are typically programmed to interact with their environments via their end-effectors, in a collision-free fashion, to avoid damaging their environment. In a departure from such a traditional approach, this work presents a contact-aware controller for reference tracking that maintains interaction forces on the surface of the robot below a safety threshold in the presence of both rigid and soft contacts. Furthermore, we leveraged the proposed controller to extend the BiTRRT sample-based planning method to be contact-aware, using a simplified contact model. The effectiveness of our framework is demonstrated in hardware experiments using a Franka robot in a setup inspired by the Amazon stowing task. A demo video of our results can be seen here: https://***/2WeYytauhNg. © 2023, CC BY.

关键词： End effectors

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厚度变化不敏感的近红外量子点发光二极管

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science Bulletin 2023年第23期68卷 2954-2961,M0005页

作者：沈万姗刘洋 Luke Grater So Min Park Haoyue Wan 俞燕君潘嘉琳孔繁诚田起生周东营刘泽柯马万里孙宝全 Sjoerd Hoogland 王亚坤廖良生 Institute of Functional Nano&Soft Materials(FUNSOM) Jiangsu Key Laboratory for Carbon-Based Functional Materials&DevicesSoochow UniversitySuzhou 215123China Department of Electrical and Computer Engineering University of TorontoToronto M5S 3G4Canada Macao Institute of Materials Science and Engineering Macao University of Science and TechnologyMacao 999078China

近红外发光二极管在通信、传感和成像等领域的应用日益广泛.量子点作为一种有潜力的发光材料,在近红外发光范围内具有独特的优势.然而,现有的近红外量子点发光二极管存在一个严重的问题,即它们对发射层厚度非常敏感.为了解决这个问题,... 详细信息

近红外发光二极管在通信、传感和成像等领域的应用日益广泛.量子点作为一种有潜力的发光材料,在近红外发光范围内具有独特的优势.然而,现有的近红外量子点发光二极管存在一个严重的问题,即它们对发射层厚度非常敏感.为了解决这个问题,本文采用了一系列创新方法.通过引入核壳结构和表面处理,使光致发光量子效率达到80%,成功提高了载流子的传输性能并且增加了量子点的辐射复合速率,从而获得具有对发光层厚度不敏感的高效近红外量子点发光二极管.最终作者制备得到了在40-220 nm的范围内表现出性能稳定的近红外量子点发光二极管,该发光器件的发光峰波长位于1025 nm处,最高外量子效率达到11.5%.这项研究为近红外发光领域的发展提供了有力的支持,为未来光电子学和光通信技术的进步铺平了道路.

关键词： Quantum dots Near-infrared Light-emitting diodes Electroluminescence

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In Situ Iodide Passivation Toward Efficient CsPbI_(3) Perovskite Quantum Dot Solar Cells

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Nano-Micro Letters 2023年第10期15卷 28-39页

作者： Junwei Shi Ben Cohen‑Kleinstein Xuliang Zhang Chenyu Zhao Yong Zhang Xufeng Ling Junjun Guo Doo‑Hyun Ko Baomin Xu Jianyu Yuan Wanli Ma Department of Materials Science and Engineering Southern University of Science and TechnologyShenzhen 518055People’s Republic of China Institute of Functional Nano&Soft Materials(FUNSOM) Soochow University199 Ren‑Ai RoadSuzhou Industrial ParkSuzhou 215123People’s Republic of China Department of Electrical and Computer Engineering University of British Columbia2329 West MallVancouverBC V6T 1Z4Canada Department of Chemistry Sungkyunkwan UniversitySuwon 16419Republic of Korea Jiangsu Key Laboratory of Advanced Negative Carbon Technologies Soochow University199 Ren‑Ai RoadSuzhou Industrial ParkSuzhou 215123People’s Republic of China Jiangsu Key Laboratory for Carbon‑Based Functional Materials&Devices Soochow University199 Ren‑Ai RoadSuzhou Industrial ParkSuzhou 215123People’s Republic of China

All-inorganic CsPbI_3 quantum dots(QDs) have demonstrated promising potential in photovoltaic(PV) applications. However, these colloidal perovskites are vulnerable to the deterioration of surface trap states, leading to a degradation in efficiency and stability. To address these issues, a facile yet effective strategy of introducing hydroiodic acid(HI) into the synthesis procedure is established to achieve high-quality QDs and devices. Through an in-depth experimental analysis, the introduction of HI was found to convert PbI_2 into highly coordinated [PbI_m]~(2-m), enabling control of the nucleation numbers and growth kinetics. Combined optical and structural investigations illustrate that such a synthesis technique is beneficial for achieving enhanced crystallinity and a reduced density of crystallographic defects. Finally, the effect of HI is further reflected on the PV performance. The optimal device demonstrated a significantly improved power conversion efficiency of 15.72% along with enhanced storage stability. This technique illuminates a novel and simple methodology to regulate the formed species during synthesis, shedding light on ofurther understanding solar cell performance, and aiding the design of future novel synthesis protocols for high-performance optoelectronic devices.

关键词： CsPbI_(3)perovskite quantum dots In situ passivation Surface trap states Perovskite solar cell

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FM-FCN:A Neural Network with Filtering Modules for Accurate Vital Signs Extraction

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Research 2025年第1期2024卷 92-106页

作者： Fangfang Zhu Qichao Niu Xiang Li Qi Zhao Honghong Su Jianwei Shuai Department of Physics and Fujian Provincial Key Laboratory for Soft Functional Materials ResearchXiamen UniversityXiamen 361005China National Institute for Data Science in Health and Medicine and State Key Laboratory of Cellular Stress BiologyInnovation Center for Cell Signaling NetworkXiamen UniversityXiamen 361005China Vitalsilicon Technology Co.Ltd. JiaxingZhejiang 314006China School of Computer Science and Software Engineering University of Science and Technology LiaoningAnshan 114051China Yangtze Delta Region Institute of Tsinghua University ZhejiangJiaxing 314006China Wenzhou Institute University of Chinese Academy of SciencesWenzhou 325001China Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine Vision and Brain Health)Wenzhou 325001China

Neural networks excel at capturing local spatial patterns through convolutional modules,but they may struggle to identify and effectively utilize the morphological and amplitude periodic nature of physiological *** this work,we propose a novel network named filtering module fully convolutional network(FM-FCN),which fuses traditional filtering techniques with neural networks to amplify physiological signals and suppress ***,instead of using a fully connected layer,we use an FCN to preserve the time-dimensional correlation information of physiological signals,enabling multiple cycles of signals in the network and providing a basis for signal ***,we introduce the FM as a network module that adapts to eliminate unwanted interference,leveraging the structure of the *** approach builds a bridge between deep learning and signal processing ***,we evaluate the performance of FM-FCN using remote *** results demonstrate that FM-FCN outperforms the second-ranked method in terms of both blood volume pulse(BVP)signal and heart rate(HR)*** substantially improves the quality of BVP waveform reconstruction,with a decrease of 20.23%in mean absolute error(MAE)and an increase of 79.95%in signal-to-noise ratio(SNR).Regarding HR estimation accuracy,FM-FCN achieves a decrease of 35.85%in MAE,29.65%in error standard deviation,and 32.88%decrease in 95%limits of agreement width,meeting clinical standards for HR accuracy *** results highlight its potential in improving the accuracy and reliability of vital sign measurement through high-quality BVP signal *** codes and datasets are available online at https://***/zhaoqi106/FM-FCN.

关键词： physiological signalsin filtering module fully convolutional network fm fcn which vital signs extraction amplify physiological signals convolutional modulesbut neural networks filtering module capturing local spatial patterns

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