Road extraction is a sub-domain of remote sensing applications; it is a subject of extensive and ongoing research. The procedure of automatically extracting roads from satellite imagery encounters significant challenges due to the multi-scale and diverse structures of roads; improvement in this field is needed. Convolutional neural networks (CNNs), especially the DeepLab series known for its proficiency in semantic segmentation due to its efficiency in interpreting multi-scale objects’ features, address some of these challenges caused by the varying nature of roads. The present work proposes the utilization of DeepLabV3+, the latest version of the DeepLab series, by introducing an innovative Dense Depthwise Dilated Separable Spatial Pyramid Pooling (DenseDDSSPP) module and integrating it in the place of the conventional Atrous Spatial Pyramid Pooling (ASPP) module. This modification enhances the extraction of complex road structures from satellite images. This study hypothesizes that the integration of DenseDDSSPP with a CNN backbone network and a Squeeze-and-Excitation block will generate an efficient dense feature map by focusing on relevant features, leading to more precise and accurate road extraction from remote sensing images. The Results Section presents a comparison of our model’s performance against state-of-the-art models, demonstrating better results that highlight the effectiveness and success of the proposed approach.

Background: Globally, high rates of maternal and infant mortality call for interventions during the perinatal period to engage pregnant people as well as their loved ones in care. Mobile health technologies have become ubiquitous in our lives and in health care settings. However, there is a need to further explore their safety and effectiveness to support and improve health outcomes locally and globally. Objective: The aim of this study was to review and synthesize published literature that described the development process or effectiveness evaluations of maternal and infant apps. Methods: We applied a methodological framework for scoping reviews as well as the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines; in addition, the systematic review platform Covidence (Veritas Health Innovation Ltd) was used to facilitate the review of included studies. Search terms were developed collaboratively, and health sciences–associated databases were searched for studies conducted between January 1, 2000, and February 4, 2022. We excluded studies about apps that only gathered or tracked data or targeted care providers. Results: A total of 1027 articles were included for title and abstract screening, of which 87 (8.47%) were chosen for full-text screening. Of these 87 articles, 74 (85%) were excluded with reasons, and 19 (22%) were included. Four articles were added at data extraction from hand searching and 2 others were excluded. Thus, we reviewed and synthesized data from 11 unique studies reported in 21 articles published between 2017 and 2021. The included studies represented 8 different countries. Most of the apps (8/11, 73%) were in English, although apps were also developed in Arabic, Bahasa Indonesia, and Nepali. The articles reviewed revealed the early stage of development of the field of maternal and infant health apps, with modest evidence of app use and achievement of study outcomes. Only 1 (9%) of the 11 apps was endorsed by an independent health care provider society. App development and evaluation processes emerged, and specific app features were identified as vital for well-functioning apps. End-user engagement occurred in some, but not all, parts of app research and development. Conclusions: Apps to improve maternal and infant health are being developed and launched in enormous numbers, with many of them not developed with mothers’ needs in mind. There are concerns about privacy, safety, and the standardization of current apps as well as a need for professional or institution-specific guidelines or best practices. Despite challenges inherent in currently available apps and their design processes, maternal and infant app technology holds promise for achieving health equity goals and improving maternal and child health outcomes. Finally, we propose recommendations for advancing the knowledge base for maternal and infant apps.

Snacks contribute to the diet quality in youth, which is often poor. Although the US Department of Agriculture (USDA) has guidelines for healthy snacks, this is lost in translation when youth are choosing snacks. To develop a user-friendly app to help identify healthy snacks based on the US Department of Agriculture guidelines and evaluate the app's feasibility, usability, satisfaction, and acceptability. The 'Snackability' app was developed following the ADDIE (analysis, design, development, implementation, and evaluation) model. The app was pilot tested for 2 weeks among college-age students (18-24 years) using questionnaires and focus groups. Based on the feedback received, the app was improved, and pilot-tested again. The app had a simple score (-1 to 11) and feedback (the higher the score, the healthier the snack is). The 1st pilot test among 12 students showed that the app's feasibility and usability were >50% (p < 0.05). Participants reported that the app was a good way to help individuals select and consume healthy snacks and suggested improving the search process and including average score reports, a 'consumed history' tab, gamification, notifications, and the option to add snacks not found. These were incorporated into the 2nd version of the app, which was pilot tested among 8 students. Feasibility, usability, and acceptability of the 2nd version were >50% (p < 0.05). Additional suggestions were to include images for serving size, snack alternatives, and barcode scanning, which were incorporated into the 3rd version. Snackability app was feasible, usable, satisfactory, and acceptable, and several features were improved as suggested by participants.

Multimedia communication services today are conceived, designed, and developed in isolation, following a stovepipe approach. This has resulted in a fragmented and incompatible set of technologies and products. Building new communication services requires a lengthy and costly development cycle, which severely limits the pace of innovation. In this paper, we address the fundamental problem of automating the development of multimedia communication services. We propose a new paradigm for creating such services through declarative specification and generation, rather than through traditional design and development. Further, the proposed paradigm pays special attention to how the end-user specifies his/her communication needs, an important requirement largely ignored in existing approaches.