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Ibrahim Almarashdeh

Imam Abdulrahman Bin Faisal University

Author-ID : 2376386

Computer Science & IT Electrical & Electronics Engineering

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Articles

Robust features extraction for general fish classification Mutasem K. Alsmadi; Mohammed Tayfour; Raed A. Alkhasawneh; Usama Badawi; Ibrahim Almarashdeh; Firas Haddad
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

Image recognition process could be plagued by many problems including noise, overlap, distortion, errors in the outcomes of segmentation, and impediment of objects within the image. Based on feature selection and combination theory between major extracted features, this study attempts to establish a system that could recognize fish object within the image utilizing texture, anchor points, and statistical measurements. Then, a generic fish classification is executed with the application of an innovative classification evaluation through a meta-heuristic algorithm known as Memetic Algorithm (Genetic Algorithm with Simulated Annealing) with back-propagation algorithm (MA-B Classifier). Here, images of dangerous and non-dangerous fish are recognized. Images of dangerous fish are further recognized as Predatory or Poison fish family, whereas families of non-dangerous fish are classified into garden and food family. A total of 24 fish families were used in testing the proposed prototype, whereby each family encompasses different number of species. The process of classification was successfully undertaken by the proposed prototype, whereby 400 distinct fish images were used in the experimental tests. Of these fish images, 250 were used for training phase while 150 were used for testing phase. The back-propagation algorithm and the proposed MA-B Classifier produced a general accuracy recognition rate of 82.25 and 90% respectively.

The effect of recovery satisfaction on citizens loyalty perception: a case study of mobile government services Ibrahim Almarashdeh
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Use of mobile services is an integral part of today’s life. Organizations, government agencies as well as service providers in the market employ mobile services or application in reaching their citizens or users worldwide. Notably, service failure issues might frustrate users in using mobile service, but usually, service providers would employ the strategy of recovery as solution. Recovery strategy aims to sustain the relationship with users following service failure. Somehow, the factors that might impact recovery process are unclear. It is also unclear if users will use the service again following the completion of recovery process. Hence, in this study, a survey on 743 adults was carried out, and the data were analyzed using SEM to determine the factors that impact users’ recovery satisfaction the most and the impact of recovery satisfaction on citizens loyalty to use mobile government in the future. The finding of this study illustrated that expect of self-efficacy, all factors proposed in the research model found to has a significant impact on recovery satisfaction. Among all the supported hypothesis, the highest impact on recovery satisfaction comes from perceived trust in government as the initial predictor to use the service

Bivariate modified hotelling’s T2 charts using bootstrap data Firas Haddad; Mutasem K. Alsmadi; Usama Badawi; Tamer Farag; Raed Alkhasawneh; Ibrahim Almarashdeh; Walaa Hassan
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

The conventional Hotelling’s charts are evidently inefficient as it has resulted in disorganized data with outliers, and therefore, this study proposed the application of a novel alternative robust Hotelling’s charts approach. For the robust scale estimator , this approach encompasses the use of the Hodges-Lehmann vector and the covariance matrix in place of the arithmetic mean vector and the covariance matrix, respectively. The proposed chart was examined performance wise. For the purpose, simulated bivariate bootstrap datasets were used in two conditions, namely independent variables and dependent variables. Then, assessment was made to the modified chart in terms of its robustness. For the purpose, the likelihood of outliers’ detection and false alarms were computed. From the outcomes from the computations made, the proposed charts demonstrated superiority over the conventional ones for all the cases tested.

Applying the big bang-big crunch metaheuristic to large-sized operational problems Yousef K. Qawqzeh; Ghaith Jaradat; Ali Al-Yousef; Anmar Abu-Hamdah; Ibrahim Almarashdeh; Mutasem Alsmadi; Mohammed Tayfour; Khalid Shaker; Firas Haddad
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

In this study, we present an investigation of comparing the capability of a big bang-big crunch metaheuristic (BBBC) for managing operational problems including combinatorial optimization problems. The BBBC is a product of the evolution theory of the universe in physics and astronomy. Two main phases of BBBC are the big bang and the big crunch. The big bang phase involves the creation of a population of random initial solutions, while in the big crunch phase these solutions are shrunk into one elite solution exhibited by a mass center. This study looks into the BBBC’s effectiveness in assignment and scheduling problems. Where it was enhanced by incorporating an elite pool of diverse and high quality solutions; a simple descent heuristic as a local search method; implicit recombination; Euclidean distance; dynamic population size; and elitism strategies. Those strategies provide a balanced search of diverse and good quality population. The investigation is conducted by comparing the proposed BBBC with similar metaheuristics. The BBBC is tested on three different classes of combinatorial optimization problems; namely, quadratic assignment, bin packing, and job shop scheduling problems. Where the incorporated strategies have a greater impact on the BBBC's performance. Experiments showed that the BBBC maintains a good balance between diversity and quality which produces high-quality solutions, and outperforms other identical metaheuristics (e.g. swarm intelligence and evolutionary algorithms) reported in the literature.

The adoption of bitcoins technology: The difference between perceived future expectation and intention to use bitcoins: Does social influence matter? Ibrahim Almarashdeh; Kamal Eldin Eldaw; Mutasem Alsmadi; Fahad Alghamdi; Ghaith Jaradat; Ahmad Althunibat; Malek Alzaqebah; Rami Mustafa A. Mohammad
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5351-5366

Bitcoin is a decentralized system that tries to become a solution to the shortcomings of fiat and gold-based currencies. Considering its newness, the adoption level of bitcoin is yet understood. Hence, several variables are proposed in this work in examining user perceptions regarding performance expectancy, effort expectancy, trust, adoption risk, decentralization and social influence interplay, with the context of user’s future expectation and behavioral intentions to use bitcoins. Data were gathered from 293 completed questionnaire and analised using AMOS 18. The outcomes prove the sound predictability of the proposed model regarding user’s future expectations and intentions toward bitcoins. All hypotheses were supported, they were significantly affecting the dependent variables. Social influence was found as the highest predictor of behavioral intention to negatively utilize bitcoins. The significant impact of social influence, adoption risk and effort expectancy which affect behavioral intention to use bitcoins the most, are demonstrated in this study. Bitcoins should thus, present an effective, feasible and personalized program which will assist efficient usage among users. Additionally, the impacts of social influence, adoption risk and perceived trust on behavioral intention to utilize new technology were compared, and their direct path was tested together, for the first time in this context.

Emergent situations for smart cities: A survey Ahmad Mohamad Al-Smadi; Mutasem K. Alsmadi; Abdel Karim Baareh; Ibrahim Almarashdeh; Hayam Abouelmagd; Osman Saad Shidwan Ahmed
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

A smart city is a community that uses communication and information technology to improve sustainability, livability, and feasibility. As any community, there are always unexpected emergencies, which must be treated to preserve the regular order. However, a smart system is needed to be able to respond effectively to these emergent situations. The contribution made in this survey is twofold. Firstly, it provides a comprehensive exhaustive and categorized overview of the existing surveys for smart cities. The categorization is based on several criteria such as structures, benefits, advantages, applications, challenges, issues, and future directions. Secondly, it aims to analyze several studies with respect to emergent situations and management to smart cities. The analysis is based on several factors such as the challenges and issues discussed, the solutions proposed, and opportunities for future research. The challenges include security, privacy, reliability, performance, scalability, heterogeneity, scheduling, resource management, and latency. Few studies have investigated the emergent situations of smart cities and despite the importance of latency factor for smart city applications, it is rarely discussed.

Comparison of specific segmentation methods used for copy move detection Eman Abdulazeem Ahmed; Malek Alzaqebah; Sana Jawarneh; Jehad Saad Alqurni; Fahad A. Alghamdi; Hayat Alfagham; Lubna Mahmoud Abdel Jawad; Usama A. Badawi; Mutasem K. Alsmadi; Ibrahim Almarashdeh
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp2363-2374

In this digital age, the widespread use of digital images and the availability of image editors have made the credibility of images controversial. To confirm the credibility of digital images many image forgery detection types are arises, copy-move forgery is consisting of transforming any image by duplicating a part of the image, to add or hide existing objects. Several methods have been proposed in the literature to detect copy-move forgery, these methods use the key point-based and block-based to find the duplicated areas. However, the key point-based and block-based have a drawback of the ability to handle the smooth region. In addition, image segmentation plays a vital role in changing the representation of the image in a meaningful form for analysis. Hence, we execute a comparison study for segmentation based on two clustering algorithms (i.e., k-means and super pixel segmentation with density-based spatial clustering of applications with noise (DBSCAN)), the paper compares methods in term of the accuracy of detecting the forgery regions of digital images. K-means shows better performance compared with DBSCAN and with other techniques in the literature.

Co-Authors Abdel Karim Baareh Ahmad Althunibat Ahmad Mohamad Al-Smadi Ali Al-Yousef Anmar Abu-Hamdah Eman Abdulazeem Ahmed Fahad A. Alghamdi Fahad Alghamdi Firas Haddad Ghaith Jaradat Hayam Abouelmagd Hayat Alfagham Jehad Saad Alqurni Kamal Eldin Eldaw Khalid Shaker Lubna Mahmoud Abdel Jawad Malek Alzaqebah Mohammed Tayfour Mutasem Alsmadi Mutasem K. Alsmadi Osman Saad Shidwan Ahmed Raed A. Alkhasawneh Raed Alkhasawneh Rami Mustafa A. Mohammad Sana Jawarneh Tamer Farag Usama A. Badawi Usama Badawi Walaa Hassan Yousef K. Qawqzeh

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