The purpose of this study was to describe prevalence of technology use among adults ages 65 and older, particularly for those with disability and activity-limiting symptoms and impairments.
Data from ...the 2011 National Health and Aging Trends Study, a nationally representative sample of community-dwelling Medicare beneficiaries (N = 7,609), were analyzed. Analysis consisted of technology use (use of e-mail/text messages and the internet) by sociodemographic and health characteristics and prevalence ratios for technology usage by disability status.
Forty percent of older adults used e-mail or text messaging and 42.7% used the internet. Higher prevalence of technology use was associated with younger age, male sex, white race, higher education level, and being married (all p values <.001). After adjustment for sociodemographic and health characteristics, technology use decreased significantly with greater limitations in physical capacity and greater disability. Vision impairment and memory limitations were also associated with lower likelihood of technology use.
Technology usage in U.S. older adults varied significantly by sociodemographic and health status. Prevalence of technology use differed by the type of disability and activity-limiting impairments. The internet, e-mail, and text messaging might be viable mediums for health promotion and communication, particularly for younger cohorts of older adults and those with certain types of impairment and less severe disability.
To solve the information explosion problem and enhance user experience in various online applications, recommender systems have been developed to model users' preferences. Although numerous efforts ...have been made toward more personalized recommendations, recommender systems still suffer from several challenges, such as data sparsity and cold-start problems. In recent years, generating recommendations with the knowledge graph as side information has attracted considerable interest. Such an approach can not only alleviate the above mentioned issues for a more accurate recommendation, but also provide explanations for recommended items. In this paper, we conduct a systematical survey of knowledge graph-based recommender systems. We collect recently published papers in this field, and group them into three categories, i.e., embedding-based methods, connection-based methods, and propagation-based methods. Also, we further subdivide each category according to the characteristics of these approaches. Moreover, we investigate the proposed algorithms by focusing on how the papers utilize the knowledge graph for accurate and explainable recommendation. Finally, we propose several potential research directions in this field.
Object detection has recently experienced substantial progress. Yet, the widely adopted horizontal bounding box representation is not appropriate for ubiquitous oriented objects such as objects in ...aerial images and scene texts. In this paper, we propose a simple yet effective framework to detect multi-oriented objects. Instead of directly regressing the four vertices, we glide the vertex of the horizontal bounding box on each corresponding side to accurately describe a multi-oriented object. Specifically, We regress four length ratios characterizing the relative gliding offset on each corresponding side. This may facilitate the offset learning and avoid the confusion issue of sequential label points for oriented objects. To further remedy the confusion issue for nearly horizontal objects, we also introduce an obliquity factor based on area ratio between the object and its horizontal bounding box, guiding the selection of horizontal or oriented detection for each object. We add these five extra target variables to the regression head of faster R-CNN, which requires ignorable extra computation time. Extensive experimental results demonstrate that without bells and whistles, the proposed method achieves superior performances on multiple multi-oriented object detection benchmarks including object detection in aerial images, scene text detection, pedestrian detection in fisheye images.
All papers published in this volume of IOP Conference Series: Earth and Environmental Science have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert ...referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Double-blind • Conference submission management system: (1) Authors send their papers to the email address of the conference. (2) All submissions go through a preliminary review to check the scope, length and plagiarism. (3) Problematic papers sent back to the authors. (4) The rest papers assigned to relevant reviewers. The email address used for the management system is emceme@126.com and the person in charge is Professor Huayuan Wu. • Number of submissions received: 478 • Number of submissions sent for review: 418 • Number of submissions accepted: 378 Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 79.08% • Average number of reviews per paper: 2 • Total number of reviewers involved: 35 • Any additional info on review process: (1) Papers divided into several sections according to the scopes. (2) Authors’ names, affiliations and emails removed from papers. (3) Papers assigned to relevant reviewers for peer review. (4) Papers rejected if two reviewers give a poor rating to the same paper. (5) Papers sent for publication if two reviewers accept the same paper. (6) Papers sent to editors for final decision if two reviewers disagree on the same paper. (7) Authors revise papers according to the reviewers’ comments. • Contact person for queries (please include: name, affiliation, institutional email address) Liyun Guo, China University of Geosciences, 120040787@cug.edu.cn
All papers published in this volume of IOP Conference Series: Materials Science and Engineering have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert ...referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Double-blind • Conference submission management system: no, articles were sent directly to editor on conference e-mail icmtmt@gmail.com • Number of submissions received: 512 • Number of submissions sent for review: 455 • Number of submissions accepted: 416 • Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 81,25 • Average number of reviews per paper: 2 • Total number of reviewers involved: 910 The main criteria for the review were: 1. Is the topic in the conference scope? 2. Is subject is worthy the publication? 3. Is information new? 4. Is paper written in acceptable English? For each question, the reviewer used scale from 1 to 5 to answer. The reviewer also checked that article was formatted according the Template, that all references, figures and tables were cited in the text and provided other comments. • Contact person for queries: Dr. Stanislav Roshchupkin, icmtmte@gmail.com, Tel. +79787040395
All papers published in this volume of IOP Conference Series: Materials Science and Engineering have been peer-reviewed through processes administered by the proceedings Editors. Reviews were ...conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.• Type of peer review: Single Anonymous• Conference submission management system: The CVENT submission management system and Morressier• Number of full paper submissions received: 59• Number of full paper submissions sent for review: 59• Number of submissions accepted: 52• Acceptance Rate (Submissions Accepted / Submissions Received × 100): 88.13%• Average number of reviews per paper: 2• Total number of reviewers involved: 37Contact persons for queries:Name: Bernard RolfeEmail: Bernard.Rolfe@deakin.edu.auAffiliation: Deakin University, AustraliaName: Matthias WeissEmail: Matthias.Weiss@deakin.edu.auAffiliation: Deakin University, AustraliaName: Peng (Neo) ZhangEmail: Peng.Neo.Zhang@deakin.edu.auAffiliation: Deakin University, AustraliaName: Jeong Whan YoonEmail: j.yoon@kaist.ac.krAffiliation: KAIST, South Korea / Deakin University, Australia
All papers published in this volume of IOP Conference Series: Earth and Environmental Science have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert ...referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Double-review and non-blind. There were two rounds of reviews conducted by ICEEG 2020. The first round is the preliminary examination, which checks the quality and the scope of the submissions. The second round is professional review. Two experts in related research fields gave professional review on the submissions and put forward suggestions for revision. At last, the accepted submissions received the acceptance notice. • Conference submission management system: All submissions are required to send by email to iceeg2020@163.com, oversaw by Zhuo Wang (wangzhuo18@mail.jlu.edu.cn) Jing Li (inter_lijing@jlu.edu.cn) • Number of submissions received: 213 • Number of submissions sent for review: 165 • Number of submissions accepted: 159 • Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 74.6% • Average number of reviews per paper: 2 • Total number of reviewers involved: 38 • Any additional info on review process: • Contact person for queries: (please include name, affiliation and email address) Professor Qi Lu College of Geo-Exploration Science and Technology, Jilin University luqi@jlu.edu.cn
Scene text detection and recognition have been well explored in the past few years. Despite the progress, efficient and accurate end-to-end spotting of arbitrarily-shaped text remains challenging. In ...this work, we propose an end-to-end text spotting framework, termed PAN++, which can efficiently detect and recognize text of arbitrary shapes in natural scenes. PAN++ is based on the kernel representation that reformulates a text line as a text kernel (central region) surrounded by peripheral pixels. By systematically comparing with existing scene text representations, we show that our kernel representation can not only describe arbitrarily-shaped text but also well distinguish adjacent text. Moreover, as a pixel-based representation, the kernel representation can be predicted by a single fully convolutional network, which is very friendly to real-time applications. Taking the advantages of the kernel representation, we design a series of components as follows: 1) a computationally efficient feature enhancement network composed of stacked Feature Pyramid Enhancement Modules (FPEMs); 2) a lightweight detection head cooperating with Pixel Aggregation (PA); and 3) an efficient attention-based recognition head with Masked RoI. Benefiting from the kernel representation and the tailored components, our method achieves high inference speed while maintaining competitive accuracy. Extensive experiments show the superiority of our method. For example, the proposed PAN++ achieves an end-to-end text spotting F-measure of 64.9 at 29.2 FPS on the Total-Text dataset, which significantly outperforms the previous best method. Code will be available at: git.io/PAN .
All conference organisers/editors are required to declare details about their peer review. Therefore, please provide the following information:
•
Type of peer review:
Single blind
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Conference ...submission management system:
By email received from the organizing and editorial committee of the conference. The correspondence authors make the submission by email.
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Number of submissions received:
17
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Number of submissions sent for review:
17
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Number of submissions accepted:
11
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Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received × 100):
64.71%
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Average number of reviews per paper:
2 reviews per paper
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Total number of reviewers involved:
8
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Any additional info on review process:
All papers are plagiarism checked by Turnitin software
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Contact person for queries:
Ely Dannier V. Niño
Foundation of Researchers in Science and Technology of Materials (FORISTOM)
Email:info@foristom.org
All conference organisers/editors are required to declare details about their peer review. Therefore, please provide the following information:• Type of peer review: Single blind• Conference ...submission management system:By email received from the organizing and editorial committee of the conference. The correspondence authors make the submission by email.• Number of submissions received:24• Number of submissions sent for review:24• Number of submissions accepted:20• Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100):83.33%• Average number of reviews per paper:2 reviews per paper• Total number of reviewers involved:12• Any additional info on review process:All papers are plagiarism checked by Turnitin software• Contact person for queries:Ely Dannier V. NiñoFoundation of Researchers in Science and Technology of Materials (FORISTOM)Email: info@foristom.org
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