Development of a real-time web-based employee abuse reporting system

Author(s):  
Nanwin ◽  
Domaka Nuka ◽  
Williams ◽  
Daniel Ofor
2021 ◽  
Vol 3 (2) ◽  
pp. 77-86
Author(s):  
Rifky Lutfi Datau ◽  
Lillyan Hadjaratie

Sistem pelaporan pengaduan yang saat ini masih secara konvensional seringkali mengalami permasalahan seperti kehilangan berkas aduan dan pelapor yang tidak mengetahui mengenai laporan yang telah diadukan. Hal ini terjadi disebabkan sistem yang belum real time. Untuk mengatasi masalah tersebut diperlukan pemanfaatan sistem dalam mekanisme pengelolaan laporan pengaduan dan meminimalkan resiko masalah yang terjadi. Penelitian ini bertujuan untuk mengembangkan sistem pengelolaan laporan pengaduan berbasis web mobile di pemerintah Provinsi Gorontalo. Penelitian ini menggunakan metode Prototype. Penelitian ini menghasilkan sistem untuk mengelola laporan pengaduan yang memberikan hak akses bagi admin, pelapor, pengelola, dan pimpinan. Sistem ini juga dapat mempermudah pembuatan laporan pengaduan sehingga dapat di akses dimanapun dan kapanpun. Selain itu, pelapor dapat dengan mudah mengajukan pengaduan, pengelola dapat dengan mudah mencari data mengenai laporan pengaduan dan pimpinan dapat dengan mudah memonitor laporan pengaduan yang masuk. The conventional complaint reporting system often experiences problems; one of them is losing the complaint file. It is worsened by the condition in which informants might not know about the report that has been filed. This condition happens due to the non-real-time system. Based on this problem, it is necessary to use the system in the complaint report management mechanism and minimize the risk of the occurred problems. This study aimed to develop a mobile web-based complaint report management system for the government of Gorontalo Province. This research uses the Prototype method. This research designed a system for managing complaint reports that provide access rights for admins, informants, managers, and leaders. Further, this system provided easier access to make complaint reports to be accessed anywhere and anytime. Moreover, it would be easier for informants to file complaints, managers to find the data regarding complaints reports, and leaders to monitor the incoming complaints reports.


2018 ◽  
Vol 68 (suppl 1) ◽  
pp. bjgp18X697205
Author(s):  
Elise Tessier ◽  
Richard Pebody ◽  
Nicki Boddington ◽  
Michael Edelstein ◽  
Joanne White ◽  
...  

BackgroundVaccine uptake data is automatically extracted from all GP practices in England via the web-based reporting system, ImmForm, on behalf of Public Health England. In 2016/17, an Uptake Summary Tool was introduced on ImmForm for practice managers, clinical commissioning groups (CCGs) and screening and immunisation teams (SCRIMMS) to help facilitate local and regional management of the influenza programme. The tool allows practices to view and evaluate influenza uptake rates by target cohorts, comparing them against the previous season and CCG average/overall national uptake each week.AimTo assess how many practices use the Uptake Summary Tool and whether there is a difference in vaccine uptake among practices that use the tool compared with those that don’t during the 2016/17 and 2017/18 influenza seasons.MethodPractice level use of the Uptake Summary Tool was examined for the 2016/17 influenza season and vaccine uptake compared between practices that used the tool and those that did not.ResultsAn average of 1272 practices used the tool each week during the 2016/17. Vaccine uptake was on average 2.9% greater for targeted cohorts in practices that used the tool than practices that did not during the 2016/17 season.ConclusionWhen used on a regular basis the Uptake Summary Tool can help GP practices, CCGs and SCRIMMS monitor vaccine and may be associated with increased vaccine uptake. Uptake for the 2017/18 season will be monitored and assessed throughout the current season. We aim to expand the tool to other vaccine collections in the near future.


2019 ◽  
Vol 152 (Supplement_1) ◽  
pp. S131-S132
Author(s):  
Kathryn Hogan ◽  
Beena Umar ◽  
Mohamed Alhamar ◽  
Kathleen Callahan ◽  
Linoj Samuel

Abstract Objectives There are few papers that characterize types of errors in microbiology laboratories and scant research demonstrating the effects of interventions on microbiology lab errors. This study aims to categorize types of culture reporting errors found in microbiology labs and to document the error rates before and after interventions designed to reduce errors and improve overall laboratory quality. Methods To improve documentation of error incidence, a self-reporting system was changed to an automatic reporting system. Errors were categorized into five types Gram stain (misinterpretations), identification (incorrect analysis), set up labeling (incorrect patient labels), procedures (not followed), and miscellaneous. Error rates were tracked according to technologist, and technologists were given real-time feedback by a manager. Error rates were also monitored in the daily quality meeting and frequently detected errors were discussed at staff meetings. Technologists attended a year-end review with a manager to improve their performance. To maintain these changes, policies were developed to monitor technologist error rate and to define corrective measures. If a certain number of errors per month was reached, technologists were required to undergo retraining by a manager. If a technologist failed to correct any error according to protocol, they were also potentially subject to corrective measures. Results In 2013, we recorded 0.5 errors per 1,000 tests. By 2018, we recorded only 0.1 errors per 1,000 tests, an 80% decrease. The yearly culture volume from 2013 to 2018 increased by 32%, while the yearly error rate went from 0.05% per year to 0.01% per year, a statistically significant decrease (P = .0007). Conclusion This study supports the effectiveness of the changes implemented to decrease errors in culture reporting. By tracking errors in real time and using a standardized process that involved timely follow-up, technologists were educated on error prevention. This practice increased safety awareness in our micro lab.


2013 ◽  
Vol 718-720 ◽  
pp. 1740-1745
Author(s):  
Tulu Muluneh Mekonnen ◽  
De Ning Jiang ◽  
Yong Xin Feng

Vehicle collision sensor system and reporting accident to police is an electronic device installed in a vehicle to inform police man in case of accident to track the vehicles location. This system works using pressure sensor, GPS and GSM technology. These technology embedded together to sense the vehicle collision and indicate the position of the vehicle or locate the place of accident in order to solve the problem immediately (as soon as possible).For doing so AT89S52 microcontroller is interfaced serially to a GSM modem, GPS receiver, and pressure sensor. A GSM modem is used to send the position (Latitude and Longitude) of the vehicle, the plate of the vehicle and the SMS text from the accident place. The GPS modem will continuously give the data (longitude and latitude) and Load sensor senses the collision of the vehicle against obstacles and input to microcontroller. As load sensor senses the collision, the GSM start to send the plate of the vehicle, text message and the position of the vehicle in terms of latitude and longitude in real time.


Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4045
Author(s):  
Alessandro Sassu ◽  
Jose Francisco Saenz-Cogollo ◽  
Maurizio Agelli

Edge computing is the best approach for meeting the exponential demand and the real-time requirements of many video analytics applications. Since most of the recent advances regarding the extraction of information from images and video rely on computation heavy deep learning algorithms, there is a growing need for solutions that allow the deployment and use of new models on scalable and flexible edge architectures. In this work, we present Deep-Framework, a novel open source framework for developing edge-oriented real-time video analytics applications based on deep learning. Deep-Framework has a scalable multi-stream architecture based on Docker and abstracts away from the user the complexity of cluster configuration, orchestration of services, and GPU resources allocation. It provides Python interfaces for integrating deep learning models developed with the most popular frameworks and also provides high-level APIs based on standard HTTP and WebRTC interfaces for consuming the extracted video data on clients running on browsers or any other web-based platform.


2015 ◽  
Vol 51 (32) ◽  
pp. 6948-6951 ◽  
Author(s):  
Yanfeng Zhang ◽  
Qian Yin ◽  
Jonathan Yen ◽  
Joanne Li ◽  
Hanze Ying ◽  
...  

Anin vitroandin vivodrug-reporting system is developed for real-time monitoring of drug release via the analysis of the concurrently released near-infrared fluorescence dye.


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