Bassem Abdullah

ICPMD: Integrated cross-platform mobile development solution

In these days, smartphones become much more used than the personal computers because of the various categories of applications downloadable from the store. The vendors of smartphones support different platforms hence to reach as many users as possible, the developer has to develop the same application for all these platforms using the different tools and programming languages provided by each platform vendor. Therefore the cross-platform mobile applications development solutions were introduced to develop the application once and run it everywhere. The cross-platform solutions use different approaches for native development such as cross-compilation, Model-Driven Development ...etc. None of these approaches claim that it provides a complete solution as they are still under research and development. This paper introduces a new integrated cross-platform mobile development solution that merges between different approaches to benefit from the advantages and minimize the drawbacks of each approach. The main contributions include: explore the approaches used in designing the new solution, explain the research methodology and the new solution architecture along with the implementation, and evaluate the limitations of the new proposed architecture and implementation compared to known solutions. The results show substantial improvement over existing solutions.

A Kalman-based encoder for electrical stimulation modulation in a thalamic network model

Restoring vision is no longer impossible as a result of recent advances in neural interfaces. Successful demonstrations of retinal implants motivate the development of more effective visual prostheses. The thalamic Lateral Geniculate Nucleus (LGN) is one potential deep-brain interfacing site for visual prostheses. A main challenge in developing thalamic as well as other visual prostheses is optimizing the parameters of electrical stimulation. This paper introduces a Kalman-based optimal encoder whose function is to determine the optimal electrical stimulation parameters required to induce a certain visual sensation. The performance of the proposed approach is demonstrated using a probabilistic model of LGN neurons. Results demonstrate a significant similarity between neuronal responses obtained using electrical stimulation and the responses obtained using the corresponding visual stimuli with a mean correlation of 0.62 (P <; 0.01, n = 54). These results indicate the efficacy of the proposed optimal encoder in driving LGN neurons to induce visual sensations.

Tuning electrical stimulation for thalamic visual prosthesis: An autoencoder-based approach

Visual prosthesis holds hope of vision restoration for millions with retinal degenerative diseases. Machine learning techniques such as artificial neural networks could help in improving prosthetic devices as they could learn how the brain encodes information and imitate that code. This paper introduces an autoencoder-based approach for tuning thalamic visual prostheses. The objective of the proposed approach is to estimate electrical stimuli that are equivalent to a given natural visual stimulus, in a way such that they both elicit responses that are as similar as possible when introduced to a Lateral Geniculate Nucleus (LGN) population. Applying the proposed method to a probabilistic model of LGN neurons, results demonstrate a significant similarity between both responses with a mean correlation of 0.672 for optimal electrodes placement and 0.354 for random electrodes placement. The results indicate the efficacy of the proposed approach in estimating an electrical stimulus equivalent to a specific visual stimulus.

Moving object detection and background enhancement for thalamic visual prostheses

Visual prostheses open the door of hope to restore functional vision for the blind. One of the main challenges facing their development is the limited number of electrodes used in the stimulation process which limits the resolution of the perceived images. To improve the perception, the useful features in the scene need to be enhanced while the other features should be suppressed to achieve better resolution. This paper introduces an image processing method to enhance three main features detectable by the natural visual pathway; namely the contrast, the motion and the edges. It then reduces the size of the image into an activity matrix used to generate the electric stimulation for the electrodes array. We compared the proposed method to four other image processing strategies in terms of the quality of the resulting image in addition to the perceived image using a simulation of prosthetic vision. Results demonstrate that the proposed method outperforms the other techniques in both aspects.

BNEL_VP: An image processing toolbox for visual prostheses

Visual prosthesis opens new perspectives in the field of restoring vision for blind people. It aims to bypass the defective stages of the natural visual pathway and to provide proper inputs to the later stages. The starting point of any visual prosthesis is an image processing model which is typically performed in two phases: Feature extraction to highlight the important information of visual scene, followed by a visual pathway stimulation which replaces the functionality of the defective stages of the visual pathway. This paper introduces a MATLAB toolbox for visual prostheses to handle all the required image processing. This toolbox supports the most common image processing techniques needed for both static and dynamic scenes recognition. In addition, it supports different kinds of visual prostheses like retinal and thalamic visual prostheses depending on how deep the visual stimulation phase will go. The paper demonstrates the value of the toolbox through a case study in which it was used for a simulated thalamic visual prosthesis.

Enhanced Code Conversion Approach for the Integrated Cross-Platform Mobile Development (ICPMD)

Mobile development companies aim to maximize the return on investments by making their mobile applications (Apps) available on different mobile platforms. Consequently, the same App is developed several times; each time the developer uses the programming languages and development tools of a specific platform. Therefore, there is a need to have cross-platform mobile applications development solutions that enable the developers to develop the App once and run it everywhere. The Integrated Cross-Platform Mobile Applications Development (ICPMD) solution is one of the attempts that enables the developers to use the most popular programming languages like Java for Android and C# for Windows Phone 8 (WP8). ICPMD is used to transform both the source code and user interface to another language to generate full Apps on the target platform. This paper extends ICPMD by proposing a new code conversion approach based on XSLT and Regular Expressions to ease the conversion process. In addition, it provides the assessment method to compare the ICPMD efficiency with competing approaches. Several Apps are converted from WP8 to Android and vice versa. The ICPMD evaluation results show reasonable improvement over commercial cross-platform mobile development tools (Titanium and Xamarin).

SystemC based simulation of AUTOSAR software components

AUTOSAR is a software methodology commonly used in automotive software system design and implementation. It provides high level of abstraction for the designer through the concept of software components (SWC) and virtual function bus (VFB). Unfortunately, no mature simulation tool is available to simulate the system at the VFB level which disables evaluating the model before system integration. On the other hand, SystemC provides a framework to simulate, analyze, and verify software. Besides, it considers the timing behavior of hardware and communication buses. The similarities and analogies between SystemC modeling components and AUTOSAR software component (SWC) modeling encourages us to rely on SystemC to propose a flow to the designer of AUTOSAR system for timing simulation purpose. In this paper, we present a tool that uses SystemC simulation kernel to provide quick simulation for the designer of Automotive based systems.