Dynamic application partitioning and task-scheduling secure schemes for biosensor healthcare workload in mobile edge cloud

Currently, the use of biosensor-enabled mobile healthcare workflow applications in mobile edge-cloud-enabled systems is increasing progressively. These applications are heavyweight and divided between a thin client mobile device and a thick server edge cloud for execution. Application partitioning is a mechanism in which applications are divided based on resource and energy parameters. However, existing application-partitioning schemes widely ignore security aspects for healthcare applications. This study devises a dynamic application-partitioning workload task-scheduling-secure (DAPWTS) algorithm framework that consists of different schemes, such as min-cut algorithm, searching node, energy-enabled scheduling, failure scheduling, and security schemes. The goal is to minimize the energy consumption of nodes and divide the application between local nodes and edge nodes by applying the secure min-cut algorithm. Furthermore, the study devises the secure-min-cut algorithm, which aims to migrate data between nodes in a secure form during application partitioning in the system. After partitioning the applications, the node-search algorithm searches optimally to run applications under their deadlines. The energy and failure schemes maintain the energy consumption of the nodes and the failure of the system. Simulation results show that DAPWTS outperforms existing baseline approaches by 30% in terms of energy consumption, deadline, and failure of applications in the system.publishedVersio

Hyperspectral vision methods for automatic recognition of emergency plant pests

The objective of this research work is to develop the computational techniques in computer vision and machine learning to detect and identify Emergency Plant Pests (EPPs) in hyperspectral images and the ability to apply in a real-time basis for the plant biosecurity surveillance application. There are three problems that will be addressed regarding hyperspectral imagery classification for EPPs; feature extraction, object detection and classification problems. Therefore, the development of computational methods for the three problems have been proposed. The first one, extraction of descriptive features, is to relate EPPs to their spectral imaging representations as necessary for representing information of the pest for reliable classification. This involves the development of texture based image descriptors that are both, invariant to changes in the viewing conditions and robust to in-field conditions. The second one is the object detection related problem in hyperspectral images. For any development of automatic surveillance systems, rapid object detection is one of essentials for success. The proposed method rapidly finds potential areas of locations of suspected objects and operates effectively on large-scale clustering and high dimensionality problems like the hyperspectral data. The last major problem of the research is to develop a classification method appropriate for the application. The method requires the capability to operate under a real-time setting with desirable discrimination performance for satisfying with a high margin of confidence. The development of these methods is further explained based on mathematic formulations. The experimental results show the utility and performance of the proposed methods. Finally, an attempt of further investigation of possible applications for these computational techniques has been carried out. -- provided by Candidate

Non-Prescription Medicine Mobile Healthcare Application: Smartphone-Based Software Design and Development Review

The challenge of this research is to answer the question of what the real need of users regarding the development of a smartphone-based software for healthcare application. This study aimed to develop the non-prescription drugs mobile health application (NMMHA) to support users in the initial medication. The application has been released to evaluate tested its usability and acceptance. To ensure the NMMHA is going to perform well, a survey has been conducted to collect data about the opinions of two groups of responders (pharmacists and general people). An attitude test and statistical analysis have also been accomplished for both groups to determine the differentiation between the two groups. The impressive results indicate that the group of general peoples tend to use the application more than the group of pharmacists, whereas the overall attitude test results of the two groups are not different.

An affine Invariant Hyperspectral Texture Descriptor Based Upon Heavy-tailed Distributions and Fourier Analysis

In this paper, we address the problem of recovering a hyperspectral texture descriptor. We do this by viewing the wavelength-indexed bands corresponding to the texture in the image as those arising from a stochastic process whose statistics can be captured making use of the relationships between moment generating functions and Fourier kernels. In this manner, we can interpret the probability distribution of the hyperspectral texture as a heavy-tailed one which can be rendered invariant to affine geometric transformations on the texture plane making use of the spectral power of its Fourier cosine transform. We do this by recovering the affine geometric distortion matrices corresponding to the probability density function for the texture under study. This treatment permits the development of a robust descriptor which has a high information compaction property and can capture the space and wavelength correlation for the spectra in the hyperspectral images. We illustrate the utility of our descriptor for purposes of recognition and provide results on real-world dataseis. We also compare our results to those yielded by a number of alternatives

Pharmacy Assistant Mobile Application (PAMA): Development and Reviews

Nowadays, pharmaceutical mobile applications are widely used. Several features and functionality play an important role to support the real needs of users especially in primary medication. Users’ behaviors in the modern world have changed where users may prefer to access drug information using search engines via the Internet rather than consulting with professionals like pharmacists, doctors or experts. However, the drug information that users retrieve from the internet sources may provide inaccurate, incomplete or unreliable information.The questions are: can we decrease this phenomenon? Suppose that we are applying an application to a content provider, which application functionalities are suitable for users and support their real needs? Can the application encourage users to gather drug information via the application instead of searching via the internet sites? The proposed study aimed to develop a Pharmacy Assistant Mobile Application (PAMA) based on necessarily required features and functionalities which are designed and operate on the iOS operation system. The application performance has been tested and measured regarding the graphic user interface and the system acceptance level.The experimental results have been reviewed and an issue has been found which needs to be considered as an important factor when developing a healthcare mobile application for the real uses