Hasil untuk "Information technology"

J. Sweller

R. Baeza-Yates, B. Ribeiro-Neto

Contents Preface Acknowledgements 1 Introduction 2 User Interfaces for Search by Marti Hearst 3 Modeling 4 Retrieval Evaluation 5 Relevance Feedback and Query Expansion 6 Documents: Languages & Properties with Gonzalo Navarro and Nivio Ziviani 7 Queries: Languages & Properties with Gonzalo Navarro 8 Text Classification with Marcos Gonccalves 9 Indexing and Searching with Gonzalo Navarro 10 Parallel and Distributed IR with Eric Brown 11 Web Retrieval with Yoelle Maarek 12 Web Crawling with Carlos Castillo 13 Structured Text Retrieval with Mounia Lalmas 14 Multimedia Information Retrieval by Dulce Poncele'on and Malcolm Slaney 15 Enterprise Search by David Hawking 16 Library Systems by Edie Rasmussen 17 Digital Libraries by Marcos Gonccalves A Open Source Search Engines with Christian Middleton B Biographies Bibliography Index

S. Mumtaz

M. L. Laucks

H. Heijden

G. DeSanctis, M. S. Poole

B. Logan, B. Hamelers, R. Rozendal et al.

H. Chesbrough

A. Dennis, J. George, L. M. Jessup et al.

Jess Gaspar, E. Glaeser

Will improvements in information technology eliminate face-to- face interactions and make cities obsolete? In this paper, we present a model where individuals make contacts and choose whether to use electronic or face-to-face meetings in their interactions. Cities are modeled as a means of reducing the fixed travel costs involved in face-to-face interactions. When telecommunications technology improves, there are two opposing effects on cities and face-to-face interactions: some relationships that used to be face-to-face will be done electronically (an intuitive substitution effect), and some individuals will choose to make more contacts, many of which result in face-to-face interactions. Our empirical work suggests that telecommunications may be a complement, or at least not a strong substitute for cities and face-to-face interactions. We also present simple models of learning in person, from a written source, or over the phone, and find that interactive communication dominates other forms of learning when ideas are complicated.

N. Levina, J. Ross

Soonhee Kim, H. Lee

Hua Xu, Shane P. Stenner, S. Doan et al.

V. Pipek, Volker Wulf

Anol Bhattacherjee, Johan L. Perols, C. Sanford

Jianjun Chen, Liyuan Zheng, Huilai Zou et al.

Precise segmentation of individual teeth from digital three-dimensional (3D) tooth models is critical in computer-assisted orthodontic surgery. This study explores the application of Point Multi-Layer Perceptron (PointMLP) in processing 3D tooth models and introduces an innovative integration of the Graph Attentional Convolution (GAC) Layer with a graph attention mechanism. By incorporating the GAC Layer into PointMLP, the model can focus on key local regions in the 3D tooth model and dynamically adjust the attention applied to these areas. This enhanced attention mechanism allows the model to better capture subtle surface structures, facilitating the accurate extraction of valuable local features. Compared to other traditional segmentation algorithms, the proposed method shows improvements of 1.1, 2.04, 1.06, 2.2, and 1.8 percentage points in Overall Accuracy (OA), Sensitivity (SEN), Positive Predictive Value (PPV), and Intersection Over Union (IoU), respectively. At the same number of training epochs, our method outperforms both GAC and PointMLP in segmentation performance.

Yuxi Liu, Yanlin Cao, Yugang Li et al.

Focusing on vaccines available to adults and not in the immunization schedule, this study investigates the preferences and factors influencing adults in selecting vaccination clinic locations. It aims to provide strategic insights for boosting vaccination rates by analyzing adults’ decision-making factors. This contributes to developing more efficient, patient-focused vaccination strategies that tackle vaccine hesitancy and improve access to vaccination sites. We conducted a cross-sectional study through the “YueMiao” platform from November 1 to December 10, 2023, using convenience and purposive sampling to engage 2014 participants. We collected data via online surveys that included questions about sociodemographic characteristics, sources of vaccination clinic information, clinic satisfaction, and the impact of site selection on vaccination decisions. Our findings reveal that adults’ site preferences for vaccination are influenced by gender, age, income, and vaccination history. Participants showed a strong preference for locations that offer convenience, efficiency, transparent pricing, and a comfortable environment. Analysis of service satisfaction at these clinics indicates that vaccinated individuals report higher satisfaction with appointment systems, wait times, and service hours than those unvaccinated. Furthermore, the preference for vaccination sites consistently aligns with the vaccine type, with a majority opting for community health service centers. Our results suggest that public health strategies should concentrate on enhancing site convenience, service quality, and information transparency to elevate adult vaccination rates. Future initiatives should aim to increase public trust in vaccines, improve the selection and quality of vaccination sites, and effectively utilize digital technology for spreading vaccination information.

Junzhe Hu, Chuanwen Luo, Yi Hong et al.

Recently, the Internet of Things (IoT) has played an important role in many fields. Nevertheless, the fast and uneven energy consumption of IoT Devices (IoTDs) significantly limits the lifetime of IoT networks. One of the effective solutions is to deploy Laser Static Chargers (LSCs) to power IoTDs. However, deploying LSCs to cover all IoTDs will consume enormous costs. To prolong the lifetime of IoT and reduce the deployment costs of LSCs, in this paper, we first propose a novel IoT network named Self-organizing Power Transfer IoT with Laser Static Chargers (SPTIoT-LSC), where IoTDs are equipped with laser transmission and reception modules allowing energy transfer between IoTDs, and several LSCs are deployed into the network to charge IoTDs. Based on SPTIoT-LSC, we study the Minimizing Laser Chargers Coverage(MLCC) problem, which aims to minimize the number of LSCs deployed in SPTIoT-LSC while enabling all IoTDs to work continuously. Then we prove its NP-hardness. To solve the problem, we propose two sub-algorithms: the Layered Charging Scheduling Strategy (LCSS) algorithm and Deploy Chargers based on the Multi-agent deep deterministic policy gradient (DCM) algorithm to maximize the working time of IoTDs with given LSCs and corresponding positions and deploy given LSCs in SPTIoT-LSC, respectively. Based on the above sub-algorithms, we propose an approximation algorithm to solve the MLCC problem. Finally, extensive experiments are proposed to verify the efficiency of the proposed algorithm and the superiority of SPTIoT-LSC.

Akhil Premkumar

Diffusion models transform noise into data by injecting information that was captured in their neural network during the training phase. In this paper, we ask: \textit{what} is this information? We find that, in pixel-space diffusion models, (1) a large fraction of the total information in the neural network is committed to reconstructing small-scale perceptual details of the image, and (2) the correlations between images and their class labels are informed by the semantic content of the images, and are largely agnostic to the low-level details. We argue that these properties are intrinsically tied to the manifold structure of the data itself. Finally, we show that these facts explain the efficacy of classifier-free guidance: the guidance vector amplifies the mutual information between images and conditioning signals early in the generative process, influencing semantic structure, but tapers out as perceptual details are filled in.

Alexander Yu. Nikiforov, Nikolai A. Usachev, Alexander V. Ermakov