https://rajpub.com/index.php/ijct/issue/feed INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 2020-01-15T08:52:24+00:00 Editorial Office editor@rajpub.com Open Journal Systems https://rajpub.com/index.php/ijct/article/view/8533 Model-Based Parallelization for Simulink Models on Multicore CPUs and GPUs 2020-01-15T08:52:24+00:00 Zhaoqian Zhong zhaoqian@ertl.jp Masato Edahiro zhaoqian@ertl.jp <p>In this paper we propose a model-based approach to parallelize Simulink models of image processing algorithms on homogeneous multicore CPUs and NVIDIA GPUs at the block level and generate CUDA C codes for parallel execution on the target hardware. In the proposed approach, the Simulink models are converted to directed acyclic graphs (DAGs) based on their block diagrams, wherein the nodes represent tasks of grouped blocks or subsystems in the model and the edges represent the communication behaviors between blocks. Next, a path analysis is conducted on the DAGs to extract all execution paths and calculate their respective lengths, which comprises the execution times of tasks and the communication times of edges on the path. Then, an integer linear programming (ILP) formulation is used to minimize the length of the critical path of the DAG, which represents the execution time of the Simulink model. The ILP formulation also balances workloads on each CPU core for optimized hardware utilization. We parallelized image processing models on a platform of two homogeneous CPU cores and two GPUs with our approach and observed a speedup performance between 8.78x and 15.71x.</p> 2020-01-04T10:50:21+00:00 Copyright (c) 2020 Zhaoqian Zhong, Masato Edahiro https://rajpub.com/index.php/ijct/article/view/8480 Medical Device Integration with Electronic Health Records: A Case Study of University of Nairobi Health Services, Kenya 2020-01-15T08:43:12+00:00 David Muchangi Mugo davemugo2005@gmail.com Benard Mutisya Nzyoka Nzyoka mnmutisya@gmail.com Stephen Mburu Ng’ang’a smburu@uonbi.ac.ke <p>In this study, we describe a demonstration in which available electronic medical records system (EMR) was successfully integrated with a wireless blood pressure monitor (BPM). This was implemented by adopting the use of RESTful Application Programming Interface (API) technologies and commonly established standards designed for medical devices interoperability. Before deploying the prototype, we conducted pilot tests at the University of Nairobi, nursing station to get feedback on the time spent using the conventional blood pressure data capture methods and the newly integrated application. Clinical data from the device was exchanged adhering to the HL7/XML standard communication protocol. The findings indicate a positive outcome was availed on the time taken for the blood pressure readings, time spent by the patient at the nursing station, doctor’s time to search the patients’ blood pressure readings as well as the data accuracy fed in the EMR system.</p> <p>&nbsp;</p> 2020-01-06T10:54:38+00:00 Copyright (c) 2020 David Muchangi Mugo, Benard Mutisya Nzyoka Nzyoka, Stephen Mburu Ng’ang’a https://rajpub.com/index.php/ijct/article/view/8563 Twitter Privacy Concern: The Effect of Twitter Profile 2020-01-15T08:43:14+00:00 Jehad Al Amri j.alamri@tu.edu.sa <p>Privacy concern vary from one to another. Sensitive information related to finance and health are most of the concern. The vast spread of using social media/ micro-blogging platforms, i.e. Twitter, as a desirable channel of online communication, has changed the peoples' understanding of what is private communication and whether they should or should not be concerned about their privacy. This paper examines the relationship between the level of privacy concern of Twitter users and their gender, experience on Twitter, type of their Twitter account and type of their username. A survey in the form of a questionnaire has been conducted in Saudi Arabia. The research compares privacy concern from the perspective of male and female, old and new Twitter users, private and public account holders and nickname and real name username holders. Determining the Chi square and using T-test and ANOVA, this research shows that the individual’s privacy concerns are affected by the Twitter users’ profile; gender, number of the years on Twitter, the type of Twitter account and username.</p> 2020-01-06T10:53:36+00:00 Copyright (c) 2020 Jehad Al Amri