Mobile application development framework to support farming as a business via benchmarking: the case of Tanzania

This research article published by the International Journal of Advanced Computer Research (IJACR), Volume-9 Issue-45 -2019Contributions from various researchers and scholars have made major advances relevant to a wide range of mobile applications at various scales. Although current agricultural and rural development (ARD) systems have features that are needed for farming as a business (FAAB). It is established that all of them have limitations in realising benchmarking as their basic principle. Common limitations across all systems, include 1) scarcity of data for modelling, evaluating, and applying benchmarking and 2) inadequate knowledge systems that effectively communicate benchmarking results to farmers. These two limitations are greater obstacles to developing useful mobile applications than gaps in conceptual theory or available methods for using “Farming as a Business via Benchmarking (FAABB)”. This paper presents reviews of the current state of mobile application development frameworks, focusing on their capabilities and limitations to support FAABB. The paper presents a new framework to support FAABB in the Tanzanian context, which is implemented through a FAABB cyber studio hosted at the Nelson Mandela –African Institution of Science and Technology (NM-AIST) in Tanzania. The framework promises to address not only the knowledge codification problem, but also the need for a cultural change among agricultural researchers to ensure that data for addressing the range of use-cases are available for future mobile application development. The FAABB framework has been tested in the Southern Agricultural Growth Corridor of Tanzania (SAGCOT) and its initial results provides a useful starting point for developing m-apps for addressing ARD challenges in developing countries

An Advanced Conceptual Diagnostic Healthcare Framework for Diabetes and Cardiovascular Disorders

The data mining along with emerging computing techniques have astonishingly influenced the healthcare industry. Researchers have used different Data Mining and Internet of Things (IoT) for enrooting a programmed solution for diabetes and heart patients. However, still, more advanced and united solution is needed that can offer a therapeutic opinion to individual diabetic and cardio patients. Therefore, here, a smart data mining and IoT (SMDIoT) based advanced healthcare system for proficient diabetes and cardiovascular diseases have been proposed. The hybridization of data mining and IoT with other emerging computing techniques is supposed to give an effective and economical solution to diabetes and cardio patients. SMDIoT hybridized the ideas of data mining, Internet of Things, chatbots, contextual entity search (CES), bio-sensors, semantic analysis and granular computing (GC). The bio-sensors of the proposed system assist in getting the current and precise status of the concerned patients so that in case of an emergency, the needful medical assistance can be provided. The novelty lies in the hybrid framework and the adequate support of chatbots, granular computing, context entity search and semantic analysis. The practical implementation of this system is very challenging and costly. However, it appears to be more operative and economical solution for diabetes and cardio patients.Comment: 11 PAGE

Abstract State Machines 1988-1998: Commented ASM Bibliography

An annotated bibliography of papers which deal with or use Abstract State Machines (ASMs), as of January 1998.Comment: Also maintained as a BibTeX file at http://www.eecs.umich.edu/gasm