PesTrapp mobile app: A trap setting application for real-time entomological field and laboratory study

2021 ◽  
Vol 38 (2) ◽  
pp. 171-179
Author(s):  
Cheong Y.L.
2017 ◽  
Vol 248 ◽  
pp. 217-225 ◽  
Author(s):  
Frank Schurr ◽  
Nicolas Cougoule ◽  
Marie-Pierre Rivière ◽  
Magali Ribière-Chabert ◽  
Hamid Achour ◽  
...  

2018 ◽  
Vol 4 (1) ◽  
Author(s):  
Dwi Swasono Rachmad ◽  
Gabriel Firsta Adnyana

ABSTRACT One of strategic that has been carried out by several universities in Indonesia to achieve quality academic and governance services is through the use of Information and Communication Technology (ICT) in the form of the use of academic information systems that contribute to improving the reputation of universities, as well as increasing user satisfaction. Lecture activities such as teaching and learning activities (KBM), the implementation of the semester exam, lecturer meeting is a daily operational activities. Teaching and learning activities are things that have become routine, but still often happens that students forget the academic activities that become obligations either because of a schedule change or other reasons. Regular schedule changes are usually distributed by the Administration to students or lecturers manually through a notice board The use of media boards raises difficulties for students, especially for students who have off-campus activities so the use of bulletin boards to convey information about lectures and academic activities among students became less effective. Therefore, an application is needed to help the delivery of information in realtime to remind students to carry out academic activities on schedule. Target to be achieved is to provide an e-reminder application of academic activities. This application consists of 3 users, the admin to enter the information mading, user (lecturer) to determine the schedule of guidance and user (student) to display the schedule of lectures, and the payment of the lecture along with notification of the schedule reminder so it can help and provide convenience for the administration in preparing and reminding activities to be carried out so that students can see about academic information and tuition payment information in real time both to students who are inside and outside the campus. Keywords : e-reminder, academic activities, mobile app<br />ABSTRAK<br />Beberapa perguruan tinggi di Indonesia untuk mencapai pelayanan akademik dan tata kelola yang berkualitas adalah melalui pemanfaatan Teknologi Informasi dan Komunikasi (TIK) berupa penggunaan sistem informasi akademik yang berperan untuk meningkatkan reputasi perguruan tinggi, serta meningkatkan kepuasan pengguna Kegiatan belajar mengajar merupakan hal yang sudah menjadi rutinitas, namun masih seringkali terjadi mahasiswa yang lupa dengan aktifitas akademik yang menjadi kewajibannya karena adanya perubahan jadwal, ataupun hal lainnya. Perubahan jadwal regular biasanya didistribusikan oleh pihak Tata Usaha ke mahasiswa atau dosen secara manual melalui papan pengumuman. Penggunaan media papan pengumuman menimbulkan kesulitan bagi mahasiswa, terutama bagi mahasiswa yang mempunyai aktifitas di luar kampus sehingga penggunaan papan pengumuman untuk menyampaikan seputar informasi perkuliahan dan kegiatan akademik di kalangan mahasiswa menjadi kurang efektif. Aplikasi ini terdiri dari 3 pengguna, yaitu admin untuk memasukan informasi mading, user (dosen) untuk menentukan jadwal bimbingan dan user (mahasiswa) untuk menampilkan jadwal kuliah, dan pembayaran kuliah beserta notifikasi pengingat jadwal tersebut sehingga dapat membantu dan memberikan kemudahan bagi pihak tata usaha dalam menyusun serta mengingatkan kegiatan yang akan dilakukan sehingga mahasiswa dapat melihat seputar informasi akademik dan informasi pembayaran uang kuliah secara real time baik kepada mahasiswa yang berada didalam maupun diluar kampus.<br />Kata kunci : e-reminder, aktifitas akademik, aplikasi mobile


Author(s):  
Karen L. Celedonia ◽  
Michael Valenti ◽  
Amy Strickler ◽  
April Wall-Parker
Keyword(s):  

2018 ◽  
Vol 14 (03) ◽  
pp. 66 ◽  
Author(s):  
Lin Cheng ◽  
Wenshan Hu ◽  
Zhengyang Liu ◽  
Wei Cai

The maintenance of substations is crucial for the safety of the electrical grid and power industry.<strong> </strong>However, for long time, the maintenance teams in the field and the experts in the power companies are divided. The data and expertise exchanges between the on-site maintenance teams and data center are delayed due to the lack of effective communication. This paper introduces an on-site smart operation maintenance system for substation equipment based on mobile network. It is able to establish real-time communication and data exchange channels between the maintenance teams and data center. It consists of an operation and maintenance system platform located on the data center side and smart operation and maintenance boxes with mobile APP which are carried to the field side by the maintenance teams. As the kernel of the system, the smart boxes are bridges between the data center and operation sites. On one hand, it is able to formally upload data to the data center in real-time. One the other hand, the operation and maintenance personnel are able to call for help from the resource on the data center anytime. Using the system proposed in the paper, both efficiency of the operation and maintenance and the normalization of the data can be improved.


2016 ◽  
Vol 139 (4) ◽  
pp. 2037-2037
Author(s):  
Sumi Sinha ◽  
Elliott D. Kozin ◽  
Matthew R. Naunheim ◽  
Samuel R. Barber ◽  
Kevin Wong ◽  
...  

2020 ◽  
Vol 12 (22) ◽  
pp. 9541 ◽  
Author(s):  
Wei Chiang Chan ◽  
Wan Hashim Wan Ibrahim ◽  
May Chiun Lo ◽  
Mohamad Kadim Suaidi ◽  
Shiaw Tong Ha

Public transportation is an effective method of mobility that promotes cost-saving and is environmentally friendly. Poor public transport ridership in Malaysia is due to the unsatisfactory attitude of public transport users and inaccurate information on departure and arrivals. Sarawak, a state of Malaysia, is especially poor in ridership of public transport. A real-time Global Positioning System (GPS) tracking application (app) was found to be an effective tool to increase the ridership of public transport. Hence, a mobile app named UniBus was developed to enhance the ridership of public transport in Sarawak. The determinants that affect satisfaction and customer loyalty such as accessibility, reliability, comfort, safety, and security were all examined before and after the use of real-time GPS tracking app. The data was collected in Kuching, and targeted public transport users who used the UniBus app. The result indicated that all the mentioned variables were improved after using a real-time GPS tracking app. It is suggested that future studies can consider other factors such as service quality, availability, and perceived value as well as cover other states of Malaysia.


2020 ◽  
Vol 24 (5) ◽  
pp. 709-722
Author(s):  
Kieran Woodward ◽  
Eiman Kanjo ◽  
Andreas Oikonomou ◽  
Alan Chamberlain

Abstract In recent years, machine learning has developed rapidly, enabling the development of applications with high levels of recognition accuracy relating to the use of speech and images. However, other types of data to which these models can be applied have not yet been explored as thoroughly. Labelling is an indispensable stage of data pre-processing that can be particularly challenging, especially when applied to single or multi-model real-time sensor data collection approaches. Currently, real-time sensor data labelling is an unwieldy process, with a limited range of tools available and poor performance characteristics, which can lead to the performance of the machine learning models being compromised. In this paper, we introduce new techniques for labelling at the point of collection coupled with a pilot study and a systematic performance comparison of two popular types of deep neural networks running on five custom built devices and a comparative mobile app (68.5–89% accuracy within-device GRU model, 92.8% highest LSTM model accuracy). These devices are designed to enable real-time labelling with various buttons, slide potentiometer and force sensors. This exploratory work illustrates several key features that inform the design of data collection tools that can help researchers select and apply appropriate labelling techniques to their work. We also identify common bottlenecks in each architecture and provide field tested guidelines to assist in building adaptive, high-performance edge solutions.


2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 1310-1310
Author(s):  
Lu Hu ◽  
Chan Wang ◽  
Huilin Li ◽  
Margaret Curran ◽  
Collin J Popp ◽  
...  

Abstract Objectives We examined whether a diet personalized to reduce postprandial glycemic response (PPGR) to foods increases weight loss self-efficacy. Methods The Personal Diet Study is an ongoing clinical trial that aims to compare two weight loss diets: a one-size-fits-all, calorie-restricted, low-fat diet (Standardized) versus a diet having the same calorie restriction but utilizing a machine learning algorithm to predict and reduce PPGR (Personalized). Both groups receive the same behavioral counseling to enhance weight loss self-efficacy. Both groups self-monitor dietary intake using a mobile app, with Standardized receiving real-time feedback on calories and macronutrient distribution, and Personalized receiving real time feedback on calories, macronutrient distribution, and predicted PPGR. We examined changes in self-efficacy between baseline and 3 mos, using the 20-item Weight Efficacy Lifestyle questionnaire (WEL). Linear mixed models were used to analyze differences, adjusting for age, gender, and race. Results The analyses included the first 75 participants to complete 3-mos assessments (41 Personalized and 34 Standardized). The majority of the participants were white (69.3%), female (61.3%), with a mean age of 61.7 years (SD = 9.9) and BMI of 33.4 kg/m2 (SD = 4.8). At baseline, WEL scores were similar between the 2 groups [Standardized WEL: 118.8 (SD = 27.6); Personalized WEL: 124.9 (SD = 29.5), P = 0.47]. At 3 mos, the WEL score was significantly improved in both groups [16.0 (SD = 4.1) in the Standardized group (P &lt; 0.001) and 7.4 (SD = 3.7) in the Personalized group (P = 0.048)], but the between group difference was not significant (P = 0.12). Conclusions Personalized feedback on predicted PPGRs does not appear to enhance weight loss self-efficacy at 3 mos. The lack of significance may be related to the short follow-up period in these preliminary analyses, the small sample accrued to date, or the fact that WEL is designed to assess confidence in various situations (e.g., depressed, anxious) that may not be impacted by personalization. These analyses will be replicated with a larger sample using data obtained through the 6-mos follow-up. New self-efficacy measures may be required to assess the impact of personalized dietary counseling. Funding Sources This research was supported by the American Heart Association.


2017 ◽  
Vol 23 (6) ◽  
pp. 350-358
Author(s):  
Seokhwan Choi ◽  
Junho Kwon ◽  
Yoon-Ho Choi

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