Public Apps Research Articles

정부24 앱 사용자 리뷰 분석을 통한 문제 파악 및 개선방안

Fourth Industrial Revolution and COVID-19 pandemic have boosted the use of Government 24 app for public service complaints in the era of non-face-to-face interactions. there has been a growing influx of complaints and improvement demands from users of public apps. Furthermore, systematic management of public apps is deemed necessary. The aim of this study is to analyze the grievances of Government 24 app users, understand the current dissatisfaction among citizens, and propose potential improvements. Data were collected from the Google Play Store from May 2, 2013, to June 30, 2023, comprising a total of 6,344 records. Among these, 1,199 records with a rating of 1 and at least one 'thumbs-up' were used for topic modeling analysis. The analysis revealed seven topics: 'Issues with certificate issuance,' 'Website functionality and UI problems,' 'User ID-related issues,' 'Update problems,' 'Government employee app management issues,' 'Budget wastage concerns ((It's not worth even a single star) or (It's a waste of taxpayers' money)),' and 'Password-related problems.' Furthermore, the overall trend of these topics showed an increase until 2021, a slight decrease in 2022, but a resurgence in 2023, underscoring the urgency of updates and management. We hope that the results of this study will contribute to the development and management of public apps that satisfy citizens in the future.

Interface Design of "Qingge" Public Welfare APP

In this rapidly developing era of big data, people access to the information on the Internet, now this is especially true of college students, aiming at the condition of the college students, they are increasingly pay attention to the realization of its value, and volunteering is a very good way, but the volunteer activity is a single, volunteer organizations in the public class, College students do not have access to more information platforms to get more types of volunteers. Now most of the public class APP on the market in the region is highly targeted, but activity is very limited, the kinds of voluntary organizations where there is little role in public welfare type of APP, can't meet the needs of college students for a variety of volunteers to yearn for, cause the APP downloads is not high, and there is no substantive role, will not develop good habits of users, Therefore, according to this situation, the improvement of the demand for college students' volunteers will also help to enhance the public welfare activities of college students. Through an in-depth study of the use and investigation of public service APPS, this paper designed a multi-type volunteer platform for college students to do public service based on the needs of college students for public service platforms. Meanwhile, the visual design style of the APP interface was in line with the preferences of college students with the "green pigeon" public service APP interface, so that college students could find more colorful volunteer projects on this platform, meet their needs for different types of volunteers, and better realize their own value. Meanwhile, they could see the experience sharing of college students' volunteering on this APP, and enhance their enthusiasm. Establish their own sense of responsibility at the same time to develop the public welfare undertakings of our country.

Abstract 6394: The SB Image Processing Toolkit: Machine learning for cancer research on the CGC

Abstract Applying machine learning algorithms to analysis of multi-omics datasets has provided a wealth of analysis and interpretations of data not easily achievable by conventional methods. The Cancer Genomics Cloud (CGC), powered by Seven Bridges, offers many helpful features to simplify and streamline the performance of machine learning (ML) tasks on the platform. The CGC platform contains features and tools for all of the steps of a ML project, from data exploration, to model generation, to production, so that all key steps occur on the platform. The Data Cruncher interactive analysis tool enables users to perform data exploration, modeling, training, and visualization using familiar frameworks like Jupyterlab and RStudio. We applied this ML methodology to imaging tools, to create The SB Image Processing Toolkit. Here we demonstrate the use of this toolkit with specific cancer datasets, including training and analysis, with all steps taking place on the cloud. The SB Image Processing Toolkit is a collection of various deep-learning, preprocessing, and utility tools and workflows created with the purpose of performing image class prediction on any type of image data. The toolkit supports a variety of images used in cancer research, such as histopathology and radiology images, and common formats like JPG or PNG. There are nine distinct tools within the toolkit, including methods for quality control, normalization, preprocessing for histopathology or radiology images, classification, and deep learning. Together, these tools create an easy-to-use infrastructure to enable various stages of ML and Image Processing. Most importantly, it was designed to enable users to create and use ML image classifiers on the CGC without any coding experience. All workflows can be searched for and implemented via the Public Apps Gallery on the CGC. Users can import image data, run analysis, and compare results all in one environment. By harnessing the scale and flexibility of cloud computing, the SB Image Processing Toolkit brings massive speed and price improvements compared to manual writing and running model training scripts. In conjunction with the access to data and ease of use, the CGC makes complex machine learning methods accessible to any researcher. Citation Format: Soner Koc, Jovana Babic, Nevena Nikolic, Ana Stankovic, Daniel Ventre, Manisha Ray, Zelia F. Worman, Sai Lakshmi Subramanian, Dennis A. Dean, Jack DiGiovanna, Brandi Davis Dusenbery. The SB Image Processing Toolkit: Machine learning for cancer research on the CGC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6394.

Mobile Resources for the Public Health Workforce

Health science librarians, whether in academic or medical libraries, are increasingly becoming aware of mobile applications (apps) that offer the medical practitioner point-of-care access to current medical information. One can find hundreds of free apps or apps for purchase in the subjects of nursing, pharmacy, and medicine, as well as general consumer health and wellness apps for the iOS (Apple Mobile Device Operating System) and Android platforms. Yet, apps that provide information for public health practice have been to slow to come. This column will explore the barriers to public health information access for the public health workforce, the need for public health apps, and current initiatives for open government data and web app development.