scholarly journals A Mobile Application to Follow Up the Management of Broiler Flocks

2021 ◽  
Vol 3 (4) ◽  
pp. 990-1000
Author(s):  
Angel Antonio Gonzalez Martinez ◽  
Irenilza de Alencar Nääs ◽  
Jair Minoro Abe ◽  
Danilo Florentino Pereira
Keyword(s):  
Performance Index ◽  
Mobile Application ◽  
Graphical Interface ◽  
Application Development ◽  
Broiler Meat ◽  
Rearing Conditions ◽  
Commercial Broiler ◽  
On Farm ◽  
A Performance

Broiler meat is one of the most consumed meats worldwide. The broiler production system poses several challenges for the producer, including maintaining environmental conditions for rearing. The popularization of mobile devices (smartphones) among people, including those with lower incomes, makes it possible for specialist systems to be developed and used for diverse purposes through Apps (mobile application). The present study proposed the development of a mobile application to help farmers follow up on-farm flock management. We retrieved rearing environment and flock data from commercial broiler farms that complied with broiler-producing standards and followed the breeders’ recommendations. Data were organized and normalized to serve as the basis for the software. We specified a performance index based on the average environment and flock-based data. The language used for the application development was Python compatible with the GNU GPL (General Public License), which has a vast library of ready-made functions. For the graphical interface, we selected Kivy and KivyMD framework. The developed mobile application might help farmers evaluate broiler rearing conditions on-farm during the flock’s growth and grade the flock using a performance index.

A Tracer Study of ICT Graduate Students at Mzuzu University, Malawi

Mousaion ◽  
2019 ◽  
Vol 36 (3) ◽  
Author(s):  
Chimango Nyasulu ◽  
Winner Chawinga ◽  
George Chipeta
Keyword(s):  
Language Processing ◽  
Mobile Application ◽  
First Century ◽  
Application Development ◽  
Job Requirements ◽  
Level Of Satisfaction ◽  
Information And Communication ◽  
Quantitative Design ◽  
The Right ◽  
The University

Governments the world over are increasingly challenging universities to produce human resources with the right skills sets and knowledge required to drive their economies in this twenty-first century. It therefore becomes important for universities to produce graduates that bring tangible and meaningful contributions to the economies. Graduate tracer studies are hailed to be one of the ways in which universities can respond and reposition themselves to the actual needs of the industry. It is against this background that this study was conducted to establish the relevance of the Department of Information and Communication Technology at Mzuzu University to the Malawian economy by systematically investigating occupations of its former students after graduating from the University. The study adopted a quantitative design by distributing an online-based questionnaire with predominantly closed-ended questions. The study focused on three key objectives: to identify key employing sectors of ICT graduates, to gauge the relevance of the ICT programme to its former students’ jobs and businesses, and to establish the level of satisfaction of the ICT curriculum from the perspectives of former ICT graduates. The key findings from the study are that the ICT programme is relevant to the industry. However, some respondents were of the view that the curriculum should be strengthened by revising it through an addition of courses such as Mobile Application Development, Machine Learning, Natural Language Processing, Data Mining, and LINUX Administration to keep abreast with the ever-changing ICT trends and job requirements. The study strongly recommends the need for regular reviews of the curriculum so that it is continually responding to and matches the needs of the industry.

Prediction of Future Market Price for Agricultural Commodities

2015 ◽  
Vol 3 (1) ◽  
Author(s):  
Sagar Pathane ◽  
Uttam Patil ◽  
Nandini Sidnal
Keyword(s):  
Mobile Application ◽  
Market Price ◽  
Commodity Prices ◽  
Future Price ◽  
Future Market ◽  
Graphical Interface ◽  
Agricultural Commodities ◽  
Agricultural Commodity ◽  
Web Based ◽  
Agriculture Products

The agricultural commodity prices have a volatile nature which may increase or decrease inconsistently causing an adverse effect on the economy. The work carried out here for predicting prices of agricultural commodities is useful for the farmers because of which they can sow appropriate crop depending on its future price. Agriculture products have seasonal rates, these rates are spread over the entire year. If these rates are known/alerted to the farmers in advance, then it will be promising on ROI (Return on Investments). It requires that the rates of the agricultural products updated into the dataset of each state and each crop, in this application five crops are considered. The predictions are done based on neural networks Neuroph framework in java platform and also the previous years data. The results are produced on mobile application using android. Web based interface is also provided for displaying processed commodity rates in graphical interface. Agricultural experts can follow these graphs and predict market rates which can be informed to the farmers. The results will be provided based on the location of the users of this application.

Development of “My Retainers” mobile application: Triangulation of two qualitative methods (Preprint)

2019 ◽  
Author(s):  
Dalya Al-Moghrabi ◽  
Fiorella Beatriz Colonio-Salazar ◽  
Ama Johal ◽  
Padhraig Seamus Fleming
Keyword(s):  
Behaviour Change ◽  
Mobile Applications ◽  
Visual Information ◽  
Mobile Application ◽  
Behavioural Change ◽  
Patient Experiences ◽  
Application Development ◽  
Participant Preferences ◽  
Orthodontic Retainers ◽  
Purposive Sample

BACKGROUND Diligent wear of removable orthodontic retainers requires prolonged compliance and is invariably necessary to preserve optimal results. Patient-informed behaviour-change interventions represent a promising and novel means of enhancing compliance with retainer wear. OBJECTIVE To describe the development of a patient-informed mobile application aimed to enhance retainer wear. METHODS Four aspects were considered during mobile application development: participant preferences; analysis of publicly-available retainer-related posts on Twitter; available interventions; and behaviour-change theories. Audio-recorded one-to-one interviews were conducted with a subset of participants to account for patient preferences in terms of features, design and content. A criterion-based purposive sample of participants wearing vacuum-formed retainers for at least 4 years was used. Thematic analysis of transcribed data was undertaken. RESULTS The need to facilitate communication with the treating clinician, responsive reminder and tracking systems, and access to useful and engaging written and visual information, in addition to other personalised and interactive features were considered important. Concerns related to retainer wear shared on Twitter informed an exhaustive list of frequently-asked questions. Application features were mapped to relevant theoretical constructs. Determinants of existing behavioural change theories were used to link application features to expected outcomes. CONCLUSIONS A holistic process involving both patient and professional input can be useful in informing the development of mobile applications. The orthodontic application (“My Retainers”) will undergo further scrutiny in relation to its effectiveness in inducing behavioural change and concerning patient experiences prior to finalisation.

Stochastic and Deterministic Petri Networks Model for Joint Management Model for Spare Parts and Maintenance: Simulation Study

2020 ◽  
Vol 46 ◽  
pp. 180-188 ◽  
Author(s):  
Oumaima Bounou ◽  
Abdellah El Barkany ◽  
Ahmed El Biyaali
Keyword(s):  
Simulation Study ◽  
Monitoring And Evaluation ◽  
Spare Parts ◽  
Maintenance Management ◽  
Graphical Interface ◽  
Efficient Tool ◽  
Joint Management ◽  
And Storage ◽  
Evaluation Techniques

Maintenance management is an orderly procedure to address the planning, organization, monitoring and evaluation of maintenance activities and associated costs. The maintenance management allows to have an efficient tool either to the management of the preventive or curative activity, an optimization of the production tool, and finally a follow-up of the costs and the performances. A good maintenance management system can help prevent problems and damages to the operating and storage environment, extend the life of assets, and reduce operating costs.In this paper, we will first present our model on the joint management of spare parts and maintenance. We will do a simulation study of our model, presented in the first section of this paper. The results of this study are presented in the second section through the presentation of the influence of certain parameters of the model on the operation of the system under consideration. This study carried out on the graphical interface of Matlab, which is one of the performance evaluation techniques. It allows to visualize the variations and anomalies which can be reached in the system considered as an overcoming of the repair of the machines by the unforeseen breakdowns.

scholarly journals Google Play Content Scraping and Knowledge Engineering using Natural Language Processing Techniques with the Analysis of User Reviews

2020 ◽  
Vol 30 (1) ◽  
pp. 192-208 ◽  
Author(s):  
Hamza Aldabbas ◽  
Abdullah Bajahzar ◽  
Meshrif Alruily ◽  
Ali Adil Qureshi ◽  
Rana M. Amir Latif ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Language Processing ◽  
Mobile Application ◽  
Knowledge Engineering ◽  
Machine Learning Algorithms ◽  
Application Development ◽  
User Reviews ◽  
N Gram ◽  
Logistic Regression Algorithm ◽  
Google Play

Abstract To maintain the competitive edge and evaluating the needs of the quality app is in the mobile application market. The user’s feedback on these applications plays an essential role in the mobile application development industry. The rapid growth of web technology gave people an opportunity to interact and express their review, rate and share their feedback about applications. In this paper we have scrapped 506259 of user reviews and applications rate from Google Play Store from 14 different categories. The statistical information was measured in the results using different of common machine learning algorithms such as the Logistic Regression, Random Forest Classifier, and Multinomial Naïve Bayes. Different parameters including the accuracy, precision, recall, and F1 score were used to evaluate Bigram, Trigram, and N-gram, and the statistical result of these algorithms was compared. The analysis of each algorithm, one by one, is performed, and the result has been evaluated. It is concluded that logistic regression is the best algorithm for review analysis of the Google Play Store applications. The results have been checked scientifically, and it is found that the accuracy of the logistic regression algorithm for analyzing different reviews based on three classes, i.e., positive, negative, and neutral.

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