Management of Wireless Communication Systems Using Artificial Intelligence-Based Software Defined Radio
The wireless communication system was investigated by novel methods, which produce an optimized data link, especially the software-based methods. Software-Defined Radio (SDR) is a common method for developing and implementing wireless communication protocols. In this paper, SDR and artificial intelligence (AI) are used to design a self-management communication system with variable node locations. Three affected parameters for the wireless signal are considered: channel frequency, bandwidth, and modulation type. On one hand, SDR collects and analyzes the signal components while on the other hand, AI processes the situation in real-time sequence after detecting unwanted data during the monitoring stage. The decision was integrated into the system by AI with respect to the instantaneous data read then passed to the communication nodes to take its correct location. The connectivity ratio and coverage area are optimized nearly double by the proposed method, which means the variable node location, according to the peak time, increases the attached subscriber by a while ratio
International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 13 (2020); pp. 107-133
International Association of Online Engineering (IAOE), Vienna, Austria
Copyright (c) 2020 Faiq A. Mohammed Bargarai, Adnan Mohsin Abdulazeez, Volkan Müjdat Tiryaki, Diyar Qader Zeebaree
Anomaly Detection in Wireless Sensor Networks: A Proposed Framework
With the rise of IOT devices and the systems connected to the internet, there was, accordingly, an ever-increasing number of network attacks (e.g. in DOS, DDOS attacks). A very significant research problem related to identifying Wireless Sensor Networks (WSN) attacks and the analysis of the sensor data is the detection of the relevant anomalies. In this paper, we propose a framework for intrusion detection system in WSN. The first two levels are located inside the WSN, one of them is between sensor nodes and the second is between the cluster heads. While the third level located on the cloud, and represented by the base stations. In the first level, which we called light mode, we simulated an intrusion traffic by generating data packets based on TCPDUMP data, which contain intrusion packets, our work, is done by using WSN technology. We used OPNET simulation for generating the traffic because it allows us to collect intrusion detection data in order to measure the network performance and efficiency of the simulated network scenarios. Finally, we report the experimental results by mimicking a Denial-of-Service (DOS) attack.
International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 10 (2020); pp. 150-158
Developing an Android-Based Game for Chemistry Learners and Its Usability Assessment
Nowadays, smartphones are not only used for communication purposes but also for gaming and studying. Gaming is trendy among adolescents in daily activity. The gamification of chemistry concepts, therefore, becomes very interesting and promising to enhance students’ intention of learning and promoting ICT literacy among university students. In this article, we reported the development of an Android-based game on the concept of colloids. Volunteered students (N=100) from the Faculty of Education and Teacher Training took part in the implementation phase. Need assessment suggested that the concept colloids should be a specific topic to be developed as chosen by a significant number of respondents. The validity of the app in terms of the instructional design, software design, and the visual aspects scored above average (between 90 and 99 %). The developed app was found to be very easy to use, practical, and straightforward, with an overall usability score of 85.1%.
International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 15 (2020); pp. 111-124
Copyright (c) 2020 Muhammad Nazar, Rusman Rusman, Isfin Cahyani Putri, Kana Puspita
From Paper to Screen: Encouraging Theory of Sociology through Sosiopedia by Heutagogy Approach
The advance of increasingly sophisticated technology, in the era of the industrial revolution 4.0, led to the patterns of digital economy, artificial intelligence, big data, and robotic, known as the phenomenon of disruptive innovation. This change was addressed by the University in how the learning process was carried out and how students learned. The purpose of this study is to develop a mobile learning application “Sociopedia”, which tries to offer a fundamental change in the process of learning paper to the screen, smart phones. The heutagogy approach was chosen to provide easy access to various information indirectly (asynchronous). This approach offers freedom for learners to determine by themselves the way how they learn. Meanwhile, for the development method, this study used research and development (R&D) with the 4D model consisting of Define, Design, Develop, and Disseminate. Furthermore, sociological theory was chosen as the material in this development. This research found that the media and material validation showed that the product developed was very good and worth testing. In addition, sociopedia developed encourage student to motivate in learning sociology rather than in conventional approach.
International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 01 (2021); pp. 155-167
Copyright (c) 2021 Luhung Ahmad Perguna, Idris Idris, Ahmad Arif Widianto
How Big Data Collected Via Point of Sale Devices in Textile Stores in Spain Resulted in Effective Online Advertising Targeting
— In these days of online commerce, we need to know the real behavior of consumers in physical stores: the points of sale must anticipate the purchasing decisions of consumers in order to be able to offer the best buying experience as well as tailor the marketing variables to the specific needs of each consumer. This is where retail intelligence emerges, especially in the textile industry, as a potential technology that makes use of extremely large data sets (“big data”) to engage potential customers better in order to increase company sales. The objective of this study is to show how big data can be effectively leveraged for direct and clear commercial purposes in textile stores. The development of research is based on the analysis of the application of systematic observation of consumer behavior in three main streets in Spain known for textile retail stores and interpreting their differences. The results show that data collected through various point-of-sale devices have a significant influence on retail revenue. The differences between commercial areas and the relative attractiveness of the textile trade in different cities are also borne out by the results. The main conclusions point to the need to improve the profitability of textile fashion stores on the back of promotional tactics that focus on the number of estimated customers and the possibilities of selling to them. All of the aforesaid have a significant influence on how advertising planning is carried out for retail stores.
International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 13 (2020); pp. 65-77
Copyright (c) 2020 Gloria Jiménez Marín, Paloma Sanz Marcos, Irene Garcia Medina, Patricia Margarida Farias Coelho
A Study on the Usability of Moodle and Blackboard – Saudi Students Perspectives
Nowadays, e-learning management systems are used in many universities around the world. In Saudi Arabia, universities use several systems such as Moodle and Blackboard. However, only little empirical research has been conducted on Saudi students’ preference for such systems. This study compared the usability of Moodle and Blackboard systems among Saudi university students. Specifically, three comparison metrics have been considered: user interface, download and upload service and materials organization. The results showed that the students preferred Moodle and believed that it is more usable than Blackboard in all studied metrics.
International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 10 (2020); pp. 159-165
Energy Consumption Prediction Using Deep Learning Technique
In the present era, due to technological advances, the problem of energy consumption has become one of the most important problems for its environmental and economic impact. Educational buildings are one of the highest energy consuming institutions. Therefore, one has to direct the individual and society to reach the ideal usage of energy. One of the possible methods to do that is to prediction energy consumption. This study proposes an energy consumption prediction model using deep learning algorithm. To evaluate its performance, College of Computer (CoC) at Qassim University was selected to analyze the elements in the college that affect high energy consumption and data were collected from the Saudi Electricity Company of daily for 13 years. This research applied Long short term memory (LSTM) technique for medium-term prediction of energy consumption. The performance of the proposed model has been measured by evaluation metrics and achieved low Root mean square error (RMSE) which means higher accuracy of the model compared to relative studies. Consequently, this research provides a recommendation for educational organizations to reach optimal energy consumption.
International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 10 (2020); pp. 166-177
Finding a Parked Car Location in a Multi-Storey Building without GPS Service
This paper introduces a new approach named ‘Find My Parked Car’ to provide the user with the return way for his parked car location in the indoor garage of a multi-storey building where GPS is denied using the acquisition data obtained from the inertial sensors on smart devices such as smartphones. We build up a system that employs Pedestrian Dead-Reckoning Technique (PDR) to track the user inside the building. This approach harness the environment landmarks for floors separation and the PDR paths’ landmarks to enhance them by applying the Kalman Filter. Then we prunes the paths to remove the redundant parts of paths. Finally, we display the paths that guide the user back to his car via an android application. The feature of our approach is to help users returning back to parked car location based only on the available ubiquitous sensors in the new smartphones without any need to have any map or any additional infrastructure support.
International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 10 (2020); pp. 7-21
Modified Proportional Fair Scheduling Algorithm for Heterogeneous LTE-A Networks
Growing of time-sensitive applications such as streaming multimedia, voice over IP and online gaming required strongly support from mobile communication technology. So, the persistent need for wireless broadband technologies such as LTE-A is essential. LTE-A can achieve QoS in an efficient manner by using a reliable packet scheduling algorithm. It also supports good cell coverage by using heterogeneous capability. In this paper, modifications of proportional fair (PF) algorithm are proposed with different methods to compute the average throughput, which is the main and important parameter in the PF cost function. These methods are geometric mean, root mean square and arithmetic mean. Vienna simulator is used to study the performance of the proposed algorithms. A comparison between PF modifications and the most famous algorithms (the original PF and Best CQI algorithms) with various UE velocities is introduced. Average UE throughput, spectral efficiency, energy per bit, cell throughput and fairness are used as performance indicators. The results expose that QPF has best improved values for spectral efficiency, energy per bit and fairness by 8.4%, 14%, and 9.3%, respectively than original PF. However, Best CQI has a better value of average UE and cell throughput than all algorithms of 2% and 1.8% in low and medium UE velocity, respectively, but the best value of all types of throughput at high speed is gained by QPF. QPF and GMPF has the same performance in fairness with all UEs speeds.
International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 10 (2020); pp. 22-34
Implementing Web Services using PHP Soap Approach
Recently, the utilization of IT in the Higher Education institutions has expanded, thus e-Learning must to turn out to be completely embedded into e-Learning and showing practice rather than the traditional approaches to e-Learning. However, this development inside e-Learning frameworks isn't yet completely realized, and the most significant difficulties to this objective are holding students inside instruction and attracting them to take part in Higher Education. One of the methodologies that have been taken to address these difficulties is to utilize the Web services approach to encourage working and participation between Higher Education institutions. Taking account that XML documents are the most commonly applied and successful type of Web services. Being PHP is the best choice for web developers, especially for Web services. This paper will present the proposed approach which aims to expand the current architecture of Web services to meet the technical requirements of the e-Learning framework. It will give an outline of certain strategies that help designers to create SOAP with PHP language. It will portray how to expand PHP Sakai and Moodle to help Web services by utilizing the PHP SOAP method. Besides, it will delineate that this utilization of Web services is a direct advancement of Web programming models, and it will exhibit how PHP can be utilized as a fast and easy development tool for creating them. The spotlight of this paper is to research the expansion of Web services to support PHP Sakai and Moodle by utilizing the PHP SOAP strategy.
International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 10 (2020); pp. 35-45