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Ahmed Alsanad
STC’s Artificial Intelligent Chair, Department of Information Systems, College of Computer and Information Sciences, King Saud University, Riyadh 11451, Saudi Arabia

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Short Biography

Ahmed Alsanad, is an Associate Professor of Information System Department and chair member of Pervasive and Mobile Computing, CCIS, at the King Saud University, Riyadh, KSA. He received his Ph.D. degree in Computer Science from De Montfort University, United Kingdom in 2013. His research interests include Cloud Computing, Health Informatics, ERP and CRM. He has authored and co-authored more than 12 publications including refereed IEEE/ACM/ Springer journals, conference papers, and book chapters.

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Journal article
Published: 03 August 2021 in Information Fusion
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The conventional diagnostic process and tools of cardiovascular autonomic neuropathy (CAN) can easily identify the two main categories of the condition: severe/definite CAN and normal/healthy without CAN. Conventional techniques encounter significant challenges when identifying CAN in its early or atypical stages due to the inherent imbalanced and incompleteness condition in the collected clinical multimodal data, including electrocardiogram (ECG) data from ECG sensors, blood chemistry, podiatry, and endocrinology features. Therefore, most detection tools and techniques are limited to binary CAN classification. However, early diagnosis of CAN or diagnosis of the atypical stages of CAN is more important than the diagnosis of severe CAN, which, in fact, is easily identifiable with a few diagnostic reports. In this paper, we propose a novel multi-class classification approach for timely CAN detection. The proposed classification algorithm develops a multistage fusion model by combining feature selection and multimodal feature fusion techniques. The proposed method develops a performance criterion-based feature selection technique to guarantee highly significant features. A multimodal feature fusion technique was developed using deep learning feature fusion and selected original features. The experimental results obtained from testing with a large CAN dataset indicate that the proposed algorithm significantly improved the diagnostic accuracy of CAN compared to conventional Ewing battery features. The algorithm also identified the early or atypical stages of CAN with an AUC score of 0.931 using leave-one-out cross-validation.

ACS Style

Rafiul Hassan; Shamsul Huda; Mohammad Mehedi Hassan; Jemal Abawajy; Ahmed Alsanad; Giancarlo Fortino. Early detection of cardiovascular autonomic neuropathy: A multi-class classification model based on feature selection and deep learning feature fusion. Information Fusion 2021, 77, 70 -80.

AMA Style

Rafiul Hassan, Shamsul Huda, Mohammad Mehedi Hassan, Jemal Abawajy, Ahmed Alsanad, Giancarlo Fortino. Early detection of cardiovascular autonomic neuropathy: A multi-class classification model based on feature selection and deep learning feature fusion. Information Fusion. 2021; 77 ():70-80.

Chicago/Turabian Style

Rafiul Hassan; Shamsul Huda; Mohammad Mehedi Hassan; Jemal Abawajy; Ahmed Alsanad; Giancarlo Fortino. 2021. "Early detection of cardiovascular autonomic neuropathy: A multi-class classification model based on feature selection and deep learning feature fusion." Information Fusion 77, no. : 70-80.

Research article
Published: 22 July 2021 in Journal of Healthcare Engineering
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Biosensor is a means to transmit some physical phenomena, like body temperature, pulse, respiratory rate, electroencephalogram (EEG), electrocardiogram (ECG), and blood pressure. Such transmission is performed via Wireless Medical Sensor Network (WMSN) while diagnosing patients remotely through Internet-of-Medical-Things (IoMT). The sensitive data transmitted through WMSN from IoMT over an insecure channel is vulnerable to several threats and needs proper attention to be secured from adversaries. In contrast to addressing the security of all associated entities involving patient monitoring in the healthcare system or ensuring the integrity, authorization, and nonrepudiation of information over the communication line, no one can guarantee its security without a robust authentication protocol. Therefore, we have proposed a lightweight and robust authentication scheme for the network-enabled healthcare devices (IoMT) that mitigate all the identified weaknesses posed in the recent literature. The proposed protocol’s security has been analyzed formally using BAN logic and ProVerif2.02 and informally using pragmatic illustration. Simultaneously, at the end of the paper, the performance analysis result shows a delicate balance of security with performance that is often missing in the current protocols.

ACS Style

Saeed Ullah Jan; Sikandar Ali; Irshad Ahmed Abbasi; Mogeeb A. A. Mosleh; Ahmed Alsanad; Hizbullah Khattak. Secure Patient Authentication Framework in the Healthcare System Using Wireless Medical Sensor Networks. Journal of Healthcare Engineering 2021, 2021, 1 -20.

AMA Style

Saeed Ullah Jan, Sikandar Ali, Irshad Ahmed Abbasi, Mogeeb A. A. Mosleh, Ahmed Alsanad, Hizbullah Khattak. Secure Patient Authentication Framework in the Healthcare System Using Wireless Medical Sensor Networks. Journal of Healthcare Engineering. 2021; 2021 ():1-20.

Chicago/Turabian Style

Saeed Ullah Jan; Sikandar Ali; Irshad Ahmed Abbasi; Mogeeb A. A. Mosleh; Ahmed Alsanad; Hizbullah Khattak. 2021. "Secure Patient Authentication Framework in the Healthcare System Using Wireless Medical Sensor Networks." Journal of Healthcare Engineering 2021, no. : 1-20.

Journal article
Published: 21 July 2021 in Complexity
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This paper aims to implement an analytical method, known as the Laplace homotopy perturbation transform technique, for the result of fractional-order Whitham–Broer–Kaup equations. The technique is a mixture of the Laplace transformation and homotopy perturbation technique. Fractional derivatives with Mittag-Leffler and exponential laws in sense of Caputo are considered. Moreover, this paper aims to show the Whitham–Broer–Kaup equations with both derivatives to see their difference in a real-world problem. The efficiency of both operators is confirmed by the outcome of the actual results of the Whitham–Broer–Kaup equations. Some problems have been presented to compare the solutions achieved with both fractional-order derivatives.

ACS Style

Kamsing Nonlaopon; Muhammad Naeem; Ahmed M. Zidan; Rasool Shah; Ahmed Alsanad; Abdu Gumaei. Numerical Investigation of the Time-Fractional Whitham–Broer–Kaup Equation Involving without Singular Kernel Operators. Complexity 2021, 2021, 1 -21.

AMA Style

Kamsing Nonlaopon, Muhammad Naeem, Ahmed M. Zidan, Rasool Shah, Ahmed Alsanad, Abdu Gumaei. Numerical Investigation of the Time-Fractional Whitham–Broer–Kaup Equation Involving without Singular Kernel Operators. Complexity. 2021; 2021 ():1-21.

Chicago/Turabian Style

Kamsing Nonlaopon; Muhammad Naeem; Ahmed M. Zidan; Rasool Shah; Ahmed Alsanad; Abdu Gumaei. 2021. "Numerical Investigation of the Time-Fractional Whitham–Broer–Kaup Equation Involving without Singular Kernel Operators." Complexity 2021, no. : 1-21.

Journal article
Published: 25 June 2021 in Mathematical Problems in Engineering
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This paper aims to propose a new methodology for spherical cubic fuzzy (SCF) multicriteria decision-making (MCDM) utilizing the TOPSIS method that uses incomplete weight information. At first, the maximum deviation model is suggested to determine the criteria of weight values. An MCDM methodology is introduced using SCF information, based on the proposed method. Also, to validate the effectiveness of the proposed information, a numerical example is given. Finally, a comprehensive and structured analysis of existing work in comparison with previous work is given.

ACS Style

Tehreem; Amjad Hussain; Ahmed Alsanad; Mogeeb A. A. Mosleh. Spherical Cubic Fuzzy Extended TOPSIS Method and Its Application in Multicriteria Decision-Making. Mathematical Problems in Engineering 2021, 2021, 1 -14.

AMA Style

Tehreem, Amjad Hussain, Ahmed Alsanad, Mogeeb A. A. Mosleh. Spherical Cubic Fuzzy Extended TOPSIS Method and Its Application in Multicriteria Decision-Making. Mathematical Problems in Engineering. 2021; 2021 ():1-14.

Chicago/Turabian Style

Tehreem; Amjad Hussain; Ahmed Alsanad; Mogeeb A. A. Mosleh. 2021. "Spherical Cubic Fuzzy Extended TOPSIS Method and Its Application in Multicriteria Decision-Making." Mathematical Problems in Engineering 2021, no. : 1-14.

Journal article
Published: 25 June 2021 in Mathematical Problems in Engineering
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The notion of spherical fuzzy sets (SFSs) is one of the most effective ways to model the fuzzy information in decision-making processes. The sum of squares of membership, neutral, and nonmembership degrees in SFSs lies in the interval [0, 1] and accommodates more uncertainties. Henceforth, in this article, the idea of spherical cubic fuzzy sets (SCFSs) is introduced, which is the generalization of SFSs. Spherical cubic fuzzy set is the combination of spherical fuzzy sets and interval-valued spherical fuzzy sets. The membership, neutral, and nonmembership degrees in an SCFS are cubic fuzzy numbers (CFNs). Consequently, this set outperforms the pre-existing structures of fuzzy set theory. Moreover, some fundamental operations for the comparison of two spherical CFNs are defined such as score function and accuracy function. Further, several new operations through Dombi t-norm and Dombi t-conorms are characterized to get the best results during the decision criteria. Furthermore, spherical cubic fuzzy Dombi weighted averaging (SCFDWA), SCFD ordered weighted averaging (SCFDOWA), SCFD hybrid weighted averaging (SCFDHWA), SCFD weighted geometric (SCFDWG), SCFD ordered weighted geometric (SCFDOWG), and the SCFD hybrid weighted geometric (SCFDHWG) aggregated operators are discussed, and their characteristics are examined. In addition, some of the operational laws of these operators are defined. Also, a decision-making approach based on these operators is proposed. Since the proposed methods and operators are the generalizations of the existing methods and operators, therefore, these techniques produce more general, accurate, and precise results as compared with existing ones. Finally, a descriptive example is given in order to describe the validity, practicality, and effectiveness of the proposed methods.

ACS Style

Tehreem; Amjad Hussain; Ahmed Alsanad. Novel Dombi Aggregation Operators in Spherical Cubic Fuzzy Information with Applications in Multiple Attribute Decision-Making. Mathematical Problems in Engineering 2021, 2021, 1 -25.

AMA Style

Tehreem, Amjad Hussain, Ahmed Alsanad. Novel Dombi Aggregation Operators in Spherical Cubic Fuzzy Information with Applications in Multiple Attribute Decision-Making. Mathematical Problems in Engineering. 2021; 2021 ():1-25.

Chicago/Turabian Style

Tehreem; Amjad Hussain; Ahmed Alsanad. 2021. "Novel Dombi Aggregation Operators in Spherical Cubic Fuzzy Information with Applications in Multiple Attribute Decision-Making." Mathematical Problems in Engineering 2021, no. : 1-25.

Research article
Published: 14 June 2021 in Mathematical Problems in Engineering
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The structure of q-rung orthopair fuzzy sets (q-ROFSs) is a generalization of fuzzy sets (FSs), intuitionistic FSs (IFSs), and Pythagorean FSs (PFSs). The notion of q-ROFSs has the proficiency of coping with uncertainty without any restrictions. In addition, the structure of q-ROFSs can effectively cope with the situations involving dual opinions without any restrictions, instead of dealing with only single opinion or dual opinions under certain restrictions. In clustering problems, the correlation coefficients are worthwhile because they provide the degree of similarity or correlation between two elements or sets. The theme of this study is to formulate the correlation coefficients for q-ROFSs that are basically the generalization of correlation coefficients of IFSs and PFSs. Moreover, an application of these correlation coefficients to a clustering problem is proposed. Also, an analysis of the outcomes is carried out. Furthermore, a comparison is carried out among the correlation coefficients for q-ROFSs and the existing ones. Finally, the downsides of the existing works and benefits of the correlation coefficients for q-ROFSs are discussed.

ACS Style

Huma Bashir; Syed Inayatullah; Ahmed Alsanad; Rukhshanda Anjum; Mogeeb Mosleh; Pakeeza Ashraf. Some Improved Correlation Coefficients for q-Rung Orthopair Fuzzy Sets and Their Applications in Cluster Analysis. Mathematical Problems in Engineering 2021, 2021, 1 -11.

AMA Style

Huma Bashir, Syed Inayatullah, Ahmed Alsanad, Rukhshanda Anjum, Mogeeb Mosleh, Pakeeza Ashraf. Some Improved Correlation Coefficients for q-Rung Orthopair Fuzzy Sets and Their Applications in Cluster Analysis. Mathematical Problems in Engineering. 2021; 2021 ():1-11.

Chicago/Turabian Style

Huma Bashir; Syed Inayatullah; Ahmed Alsanad; Rukhshanda Anjum; Mogeeb Mosleh; Pakeeza Ashraf. 2021. "Some Improved Correlation Coefficients for q-Rung Orthopair Fuzzy Sets and Their Applications in Cluster Analysis." Mathematical Problems in Engineering 2021, no. : 1-11.

Journal article
Published: 31 May 2021 in Electronics
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The study proposed the classification and recognition of hand gestures using electromyography (EMG) signals for controlling the upper limb prosthesis. In this research, the EMG signals were measured through an embedded system by wearing a band of MYO gesture control. In order to observe the behavior of these change movements, the EMG data was acquired from 10 healthy subjects (five male and five females) performing four upper limb movements. After extracting EMG data from MYO, the supervised classification approach was applied to recognize the different hand movements. The classification was performed with a 5-fold cross-validation technique under the supervision of Quadratic discriminant analysis (QDA), support vector machine (SVM), random forest, gradient boosted, ensemble (bagged tree), and ensemble (subspace K-Nearest Neighbors) classifier. The execution of these classifiers shows the overall accuracy of 83.9% in the case of ensemble (bagged tree) which is higher than other classifiers. Additionally, in this research an embedded system-based classification approach of hand movement was used for designing an upper limb prosthesis. This approach is different than previous techniques as MYO is used with an external Bluetooth module and different libraries that make its movement and performance boundless. The results of this study also inferred the operations which were easy for hand recognition and can be used for developing a powerful, efficient, and flexible prosthetic design in the future.

ACS Style

Haider Javaid; Mohsin Tiwana; Ahmed Alsanad; Javaid Iqbal; Muhammad Riaz; Saeed Ahmad; Faisal Almisned. Classification of Hand Movements Using MYO Armband on an Embedded Platform. Electronics 2021, 10, 1322 .

AMA Style

Haider Javaid, Mohsin Tiwana, Ahmed Alsanad, Javaid Iqbal, Muhammad Riaz, Saeed Ahmad, Faisal Almisned. Classification of Hand Movements Using MYO Armband on an Embedded Platform. Electronics. 2021; 10 (11):1322.

Chicago/Turabian Style

Haider Javaid; Mohsin Tiwana; Ahmed Alsanad; Javaid Iqbal; Muhammad Riaz; Saeed Ahmad; Faisal Almisned. 2021. "Classification of Hand Movements Using MYO Armband on an Embedded Platform." Electronics 10, no. 11: 1322.

Journal article
Published: 28 April 2021 in Applied Soft Computing
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Recently, brain–computer interface (BCI) based systems have become an emerging technology facilitating smart living. Accurate identification of eye states (open or closed) via an EEG-based BCI interface has many applications in a smart living environment, such as controlling devices and monitoring health status. Artificial neural networks (ANNs), including deep neural networks, are currently quite popular in many applications. In this study, a robust and unique ANN-based ensemble method is developed in which multiple ANNs are trained individually using different parts of the training data. The outcomes of each ANN are then combined using another ANN to enhance the predictive intelligence. The outcome of this ANN is considered the ultimate prediction of the user’s eye state. The proposed ensemble method requires minimal training time and yields highly accurate eye state classification. An extensive analysis of bias and variance was used to assess the generalization ability of the proposed model while applying it to a real BCI environment and dataset. The proposed model outperforms traditional ANNs and other machine learning tools for eye state classification.

ACS Style

Mohammad Mehedi Hassan; Rafiul Hassan; Shamsul Huda; Zia Uddin; Abdu Gumaei; Ahmed Alsanad. A predictive intelligence approach to classify brain–computer interface based eye state for smart living. Applied Soft Computing 2021, 108, 107453 .

AMA Style

Mohammad Mehedi Hassan, Rafiul Hassan, Shamsul Huda, Zia Uddin, Abdu Gumaei, Ahmed Alsanad. A predictive intelligence approach to classify brain–computer interface based eye state for smart living. Applied Soft Computing. 2021; 108 ():107453.

Chicago/Turabian Style

Mohammad Mehedi Hassan; Rafiul Hassan; Shamsul Huda; Zia Uddin; Abdu Gumaei; Ahmed Alsanad. 2021. "A predictive intelligence approach to classify brain–computer interface based eye state for smart living." Applied Soft Computing 108, no. : 107453.

Journal article
Published: 02 March 2021 in IEEE Access
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Global Software Development (GSD) continues to receive interest from software industry due to potential economic benefits. Management of GSD projects is not straightforward due to involvement of different geographically distributed teams who collaborate to produce a software. The objective of this study is to prioritize the challenges faced by practitioners during management of a GSD project. A questionnaire survey was developed to collect feedback from GSD practitioners about relative importance of 20 challenges reported in literature. Next, the Fuzzy Analytical Hierarchy Process (FAHP) was used to rank the challenges associated with management of GSD projects. The study provides a prioritization-based taxonomy of challenges associated with management of GSD projects. We believe software organizations can use the taxonomy to better plan and manage GSD projects.

ACS Style

Muhammad Azeem Akbar; Ahmed Alsanad; Sajjad Mahmood; Abdulrahman Alothaim. Prioritization-Based Taxonomy of Global Software Development Challenges: A FAHP Based Analysis. IEEE Access 2021, 9, 37961 -37974.

AMA Style

Muhammad Azeem Akbar, Ahmed Alsanad, Sajjad Mahmood, Abdulrahman Alothaim. Prioritization-Based Taxonomy of Global Software Development Challenges: A FAHP Based Analysis. IEEE Access. 2021; 9 ():37961-37974.

Chicago/Turabian Style

Muhammad Azeem Akbar; Ahmed Alsanad; Sajjad Mahmood; Abdulrahman Alothaim. 2021. "Prioritization-Based Taxonomy of Global Software Development Challenges: A FAHP Based Analysis." IEEE Access 9, no. : 37961-37974.

Journal article
Published: 21 December 2020 in IEEE Access
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Internet of Things (IoT) is made up of various smart devices for the exchange of sensed data through online services. Direct contact with people through smart devices to define parameters for healthcare and send them to a centralized repository. At the time of data exchange, messages need to be secure between a source (sender) and target (receiver) in order to confront human malicious attacks. Various signature-based schemes are presented in the literature to provide secure communication. Smart apps, however, require lightweight activities by maintaining critical security strengths. The key challenge in signature-based methods is more incurred computational expense for signing and checking process involving large numbers. In this article, a new lightweight provably secure partial discrete logarithm (DL) based subtree-based short signature with fuzzy user data sharing for human-centered IoT systems is introduced and it’s security analysis is demonstrated on random oracle (RO) model. The presented scheme provides assurance of better security than other standing short-signature schemes. For low-storage, low-computation environments and low-bandwidth communication, the presented new provably secure and lightweight subtree-based short-signature scheme is needed. The results demonstrate the strength of proposed scheme, as opposed to existing works.

ACS Style

Chandrashekhar Meshram; Ahmed AlSanad; Jitendra V. Tembhurne; Shailendra W. Shende; Kailash Wamanrao Kalare; Sarita Gajbhiye Meshram; Muhammad Azeem Akbar; Abdu Gumaei. A Provably Secure Lightweight Subtree-Based Short Signature Scheme With Fuzzy User Data Sharing for Human-Centered IoT. IEEE Access 2020, 9, 3649 -3659.

AMA Style

Chandrashekhar Meshram, Ahmed AlSanad, Jitendra V. Tembhurne, Shailendra W. Shende, Kailash Wamanrao Kalare, Sarita Gajbhiye Meshram, Muhammad Azeem Akbar, Abdu Gumaei. A Provably Secure Lightweight Subtree-Based Short Signature Scheme With Fuzzy User Data Sharing for Human-Centered IoT. IEEE Access. 2020; 9 ():3649-3659.

Chicago/Turabian Style

Chandrashekhar Meshram; Ahmed AlSanad; Jitendra V. Tembhurne; Shailendra W. Shende; Kailash Wamanrao Kalare; Sarita Gajbhiye Meshram; Muhammad Azeem Akbar; Abdu Gumaei. 2020. "A Provably Secure Lightweight Subtree-Based Short Signature Scheme With Fuzzy User Data Sharing for Human-Centered IoT." IEEE Access 9, no. : 3649-3659.

Journal article
Published: 04 November 2020 in IEEE Access
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The DevOps (development and operations) is a collaborative software development environment which offers the continues development and deployment of quality software project within short time. The DevOps practices are not yet mature enough, and the software organizations hesitate to adopt it. This study aims: (1) to explore the DevOps challenges by conducting systematic literature review (SLR) and to get the insight of industry experts via questionnaire survey study; (2) to prioritize the investigated challenges using fuzzy analytical hierarchy process (FAHP). The study findings provide the set of critical challenges faced by the software organizations while adopting DevOps and a prioritization-based taxonomy of the DevOps challenges. The application of FAHP is novel in this research area as it assists in addressing the vagueness of practitioners concerning the influencing factors of DevOps. We believe that the finding of this study will serve as a body of knowledge for real world practitioners and researchers to revise and develop the new strategies for the successful implementation of DevOps practices in the software industry.

ACS Style

Muhammad Azeem Akbar; Wishal Naveed; Sajjad Mahmood; Abeer Abdulaziz Alsanad; Ahmed Alsanad; Abdu Gumaei; Ahmed Mateen. Prioritization Based Taxonomy of DevOps Challenges Using Fuzzy AHP Analysis. IEEE Access 2020, 8, 202487 -202507.

AMA Style

Muhammad Azeem Akbar, Wishal Naveed, Sajjad Mahmood, Abeer Abdulaziz Alsanad, Ahmed Alsanad, Abdu Gumaei, Ahmed Mateen. Prioritization Based Taxonomy of DevOps Challenges Using Fuzzy AHP Analysis. IEEE Access. 2020; 8 (99):202487-202507.

Chicago/Turabian Style

Muhammad Azeem Akbar; Wishal Naveed; Sajjad Mahmood; Abeer Abdulaziz Alsanad; Ahmed Alsanad; Abdu Gumaei; Ahmed Mateen. 2020. "Prioritization Based Taxonomy of DevOps Challenges Using Fuzzy AHP Analysis." IEEE Access 8, no. 99: 202487-202507.

Journal article
Published: 04 November 2020 in IEEE Access
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The software organizations rapidly adopting global software development (GSD) to gain the economic and strategic benefits. Besides, GSD faces many challenges that mainly concerned with the requirements change management (RCM). This study aims to identify and empirically validate the factors that can negatively influence the RCM process in GSD. To this end, literature review and questionnaire survey were conducted for the investigation and validation of RCM challenges. A total of 31 RCM challenges were identified. We have further classified the identified challenges in organization types, organization size and based on experts’ opinions with the aim to provide a clear understanding of the RCM process and its challenges to the practitioners. Based on these identified challenges, we believe that this study can provide a framework for tackling problems associated with RCM activities in GSD environment, which is significant to success and progression of GSD organizations.

ACS Style

Muhammad Azeem Akbar; Wishal Naveed; Abeer Abdulaziz Alsanad; Lulwah Alsuwaidan; Ahmed Alsanad; Abdu Gumaei; Muhammad Shafiq; Muhammad Tanveer Riaz. Requirements Change Management Challenges of Global Software Development: An Empirical Investigation. IEEE Access 2020, 8, 203070 -203085.

AMA Style

Muhammad Azeem Akbar, Wishal Naveed, Abeer Abdulaziz Alsanad, Lulwah Alsuwaidan, Ahmed Alsanad, Abdu Gumaei, Muhammad Shafiq, Muhammad Tanveer Riaz. Requirements Change Management Challenges of Global Software Development: An Empirical Investigation. IEEE Access. 2020; 8 (99):203070-203085.

Chicago/Turabian Style

Muhammad Azeem Akbar; Wishal Naveed; Abeer Abdulaziz Alsanad; Lulwah Alsuwaidan; Ahmed Alsanad; Abdu Gumaei; Muhammad Shafiq; Muhammad Tanveer Riaz. 2020. "Requirements Change Management Challenges of Global Software Development: An Empirical Investigation." IEEE Access 8, no. 99: 203070-203085.

Journal article
Published: 21 October 2020 in IEEE Access
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In this research work, a multifunctional metamaterial inspired surface is designed for two different applications, namely, electromagnetic (EM) absorber and radiator with pattern agility. The designed surface consists of periodic arrays of metallic loops and circular patches printed on a thin grounded dielectric slab. Lumped resistors are fixed in the outer ring where the inner patch is connected to the feeding network through metallic vias. Firstly, the basic unit cell of the surface is utilized as a dual-band EM absorber. Secondly, the same surface is utilized as a beam switching radiator. Each unit cell has two switchable feeding points which are connected to a single-pole double-throw (SPDT) switch designed on the bottom layer. The surface is symmetrical therefore the excitation of each unit cell at two feeding ports can produce a phase shift of 180°. By properly selecting the feeding point of the four elements, the surface can generate sum-beams and difference-beams. The surface exhibit low radar cross section (RCS), high gain, and high efficiency. A prototype of ${4} \times {4}$ elements array is manufactured and experimentally verified in an anechoic chamber.

ACS Style

Saeed Ur Rahman; Qunsheng Cao; Muhammad Azeem Akbar; Ahmed AlSanad; Abdul Gumaei; Wang Yi. An Integrated Switchable EM Absorber and Beam Switchable Radiator. IEEE Access 2020, 8, 1 -1.

AMA Style

Saeed Ur Rahman, Qunsheng Cao, Muhammad Azeem Akbar, Ahmed AlSanad, Abdul Gumaei, Wang Yi. An Integrated Switchable EM Absorber and Beam Switchable Radiator. IEEE Access. 2020; 8 ():1-1.

Chicago/Turabian Style

Saeed Ur Rahman; Qunsheng Cao; Muhammad Azeem Akbar; Ahmed AlSanad; Abdul Gumaei; Wang Yi. 2020. "An Integrated Switchable EM Absorber and Beam Switchable Radiator." IEEE Access 8, no. : 1-1.

Journal article
Published: 14 September 2020 in IEEE Access
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In this paper, a comprehensive overview of the Crow Search Algorithm (CSA) is introduced with detailed discussions, which is intended to keep researchers interested in swarm intelligence algorithms and optimization problems. CSA is a new swarm intelligence algorithm recently developed, which simulates crow behavior in storing excess food and retrieving it when needed. In the optimization theory, the crow is the searcher, the surrounding environment is the search space, and randomly storing the location of food is a feasible solution. Among all food locations, the location where the most food is stored is considered to be the global optimal solution, and the objective function is the amount of food. By simulating the intelligent behavior of crows, CSA tries to find optimal solutions to various optimization problems. It has gained a considerable interest worldwide since its advantages like simple implementation, a few numbers of parameters, flexibility, etc. This survey introduces a comprehensive variant of CSA, including hybrid, modified, and multi-objective versions. Furthermore, based on the analyzed papers published in the literature by some publishers such as IEEE, Elsevier, and Springer, the comprehensive application scenarios of CSA such as power, computer science, machine learning, civil engineering have also been reviewed. Finally, the advantages and disadvantages of CSA have been discussed by conducting some comparative experiments with other similar published peers.

ACS Style

Abdelazim G. Hussien; Mohamed Amin; Mingjing Wang; Guoxi Liang; Ahmed Alsanad; Abdu Gumaei; Huiling Chen. Crow Search Algorithm: Theory, Recent Advances, and Applications. IEEE Access 2020, 8, 173548 -173565.

AMA Style

Abdelazim G. Hussien, Mohamed Amin, Mingjing Wang, Guoxi Liang, Ahmed Alsanad, Abdu Gumaei, Huiling Chen. Crow Search Algorithm: Theory, Recent Advances, and Applications. IEEE Access. 2020; 8 (99):173548-173565.

Chicago/Turabian Style

Abdelazim G. Hussien; Mohamed Amin; Mingjing Wang; Guoxi Liang; Ahmed Alsanad; Abdu Gumaei; Huiling Chen. 2020. "Crow Search Algorithm: Theory, Recent Advances, and Applications." IEEE Access 8, no. 99: 173548-173565.

Journal article
Published: 17 July 2020 in Applied Soft Computing
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Cloud-Based Outsource Software Development (COSD) is a new methodology adopted by organizations to develop software using teams of knowledge workers located across the globe using cloud computing services. However, there is a lack of understanding of challenges associated with successful execution of COSD projects. The objective of this study is to identify and prioritize the challenges that influence COSD projects. First, we conducted a Systematic Literature Review (SLR) and identified 21 challenges that impact COSD projects. Next, a questionnaire survey was developed based on the SLR findings to collect feedback from industry practitioners. Finally, we applied the Fuzzy Analytical Hierarchy Process (FAHP) to rank the identified challenges for COSD projects. We also present a prioritization-based taxonomy of the identified challenges which will help practitioners to focus on the critical areas for successful implementation of COSD projects.

ACS Style

Muhammad Azeem Akbar; Mohammad Shameem; Sajjad Mahmood; Ahmed Alsanad; Abdu Gumaei. Prioritization based Taxonomy of Cloud-based Outsource Software Development Challenges: Fuzzy AHP analysis. Applied Soft Computing 2020, 95, 106557 .

AMA Style

Muhammad Azeem Akbar, Mohammad Shameem, Sajjad Mahmood, Ahmed Alsanad, Abdu Gumaei. Prioritization based Taxonomy of Cloud-based Outsource Software Development Challenges: Fuzzy AHP analysis. Applied Soft Computing. 2020; 95 ():106557.

Chicago/Turabian Style

Muhammad Azeem Akbar; Mohammad Shameem; Sajjad Mahmood; Ahmed Alsanad; Abdu Gumaei. 2020. "Prioritization based Taxonomy of Cloud-based Outsource Software Development Challenges: Fuzzy AHP analysis." Applied Soft Computing 95, no. : 106557.

Journal article
Published: 13 July 2020 in Processes
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Global human pollutant activities have raised greenhouse gas (GHG) emissions, which have directly affected the climate. Fossil fuel-based energy has brought a negative impact on the environment and is considered one of the largest sources of GHG emissions. It is envisaged that GHG emissions will increase in the future due to rapid population growth and industrialization. Thus, it is imperative to mitigate climate variability and reduce GHGs by adopting renewable energy (RE) sources for electricity generation. In this regard, the multi-criteria decision analysis (MCDA) process would serve the purpose of framing out energy policy to analyze these environmentally friendly energy sources. This study uses an integrated decision methodology—a combination of Delphi, fuzzy analytical hierarchy process (FAHP), and the fuzzy weighted aggregated sum product assessment (FWASPAS)—for the adoption of RE sources for electricity generation in Turkey. Initially, the study identified five main criteria and seventeen sub-criteria using the Delphi method. Then, the FAHP method was used to evaluate and rank the main criteria and sub-criteria. Finally, the FWASPAS method was used to assess and prioritize five major RE sources for electricity generation. The FAHP analysis indicated that political criteria are the most influential, followed by economic and technical criteria. Further, the FWASPAS method revealed that wind energy is the most significant option for electricity generation. This decision-making process can help the energy planners to utilize RE sources for sustainable development.

ACS Style

Yasir Ahmed Solangi; Cheng Longsheng; Syed Ahsan Ali Shah; Ahmed AlSanad; Munir Ahmad; Muhammad Azeem Akbar; Abdu Gumaei; Sharafat Ali. Analyzing Renewable Energy Sources of a Developing Country for Sustainable Development: An Integrated Fuzzy Based-Decision Methodology. Processes 2020, 8, 825 .

AMA Style

Yasir Ahmed Solangi, Cheng Longsheng, Syed Ahsan Ali Shah, Ahmed AlSanad, Munir Ahmad, Muhammad Azeem Akbar, Abdu Gumaei, Sharafat Ali. Analyzing Renewable Energy Sources of a Developing Country for Sustainable Development: An Integrated Fuzzy Based-Decision Methodology. Processes. 2020; 8 (7):825.

Chicago/Turabian Style

Yasir Ahmed Solangi; Cheng Longsheng; Syed Ahsan Ali Shah; Ahmed AlSanad; Munir Ahmad; Muhammad Azeem Akbar; Abdu Gumaei; Sharafat Ali. 2020. "Analyzing Renewable Energy Sources of a Developing Country for Sustainable Development: An Integrated Fuzzy Based-Decision Methodology." Processes 8, no. 7: 825.

Focus
Published: 06 July 2020 in Soft Computing
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DevOps (development and operations) is a collaborative and multidisciplinary organizational effort to automate continuous delivery of a software project with an aim to improve software quality. The implementation of DevOps practices is not straightforward as there are several complexities associated with it. The aim of this study is to identify and prioritize the factors that positively influence the DevOps practices in software organizations. Using a systematic literature review, 19 factors were identified. The identified factors were further validated with experts via a questionnaire survey study. Finally, Fuzzy Analytical Hierarchy Process (FAHP) was used to prioritize the identified success factors. The results indicate that “DevOps security pipeline,” “use system orchestration” and “attempt matrix organization and transparency” factors are the highest ranked success factors for the successful implementation of DevOps practices. The FAHP analysis is novel in this research area as it provides the prioritization based taxonomy of the identified factors which will assist the researchers and practitioners to focus on the critical areas that are significant for the successful adoption of DevOps practices.

ACS Style

Muhammad Azeem Akbar; Sajjad Mahmood; Muhammad Shafiq; Ahmed AlSanad; Abeer Abdul-Aziz AlSanad; Abdu Gumaei. Identification and prioritization of DevOps success factors using fuzzy-AHP approach. Soft Computing 2020, 1 -25.

AMA Style

Muhammad Azeem Akbar, Sajjad Mahmood, Muhammad Shafiq, Ahmed AlSanad, Abeer Abdul-Aziz AlSanad, Abdu Gumaei. Identification and prioritization of DevOps success factors using fuzzy-AHP approach. Soft Computing. 2020; ():1-25.

Chicago/Turabian Style

Muhammad Azeem Akbar; Sajjad Mahmood; Muhammad Shafiq; Ahmed AlSanad; Abeer Abdul-Aziz AlSanad; Abdu Gumaei. 2020. "Identification and prioritization of DevOps success factors using fuzzy-AHP approach." Soft Computing , no. : 1-25.

Journal article
Published: 02 March 2020 in Sustainability
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Higher education institutions (HEIs) in many developed and developing countries are facing big challenges in terms of quality in the face of growing global demand. Ensuring quality education is necessary to secure future prosperity and promote sustainable development. Hence; to ensure the success and sustainability of higher strategy; it is necessary for HEIs to improve the quality of strategy implementation processes and address the dynamic complexities of their attributes to identify areas for improvement. However; there are obvious issues associated with strategy implementation related to process modeling; automation; dynamic complexity; and cognitive limitations. This research is a step toward bridging the gap in adopting computational models in the higher education strategy implementation process to foster its automation and promote its sustainability. The aim of this research is to study the phenomenon of computational strategy implementation in the higher education domain using grounded theory to understand the criteria and quality attributes of the strategy implementation process and to generate a descriptive and explanatory model for strategy quality attributes (SQAs) of higher education; which entails the implementation of automated technology and computational models for more effective and sustainable strategy.

ACS Style

Saleh Alkhodhair; Ahmed Alsanad; Khaled Alghathbar; Abdu Gumaei. Key Quality Attributes for Computational and Sustainable Higher Education Strategy Implementation in Saudi Arabia. Sustainability 2020, 12, 1881 .

AMA Style

Saleh Alkhodhair, Ahmed Alsanad, Khaled Alghathbar, Abdu Gumaei. Key Quality Attributes for Computational and Sustainable Higher Education Strategy Implementation in Saudi Arabia. Sustainability. 2020; 12 (5):1881.

Chicago/Turabian Style

Saleh Alkhodhair; Ahmed Alsanad; Khaled Alghathbar; Abdu Gumaei. 2020. "Key Quality Attributes for Computational and Sustainable Higher Education Strategy Implementation in Saudi Arabia." Sustainability 12, no. 5: 1881.

Journal article
Published: 18 September 2019 in Future Generation Computer Systems
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Mental health has become a severe problem that significantly influences people’s living quality. With the rapid development of science and technology, a completely new direction for mental health improving by using the interaction between robots and people has emerged. As an intelligent personal agent, a robot can be easily accepted in people’s daily life, meeting users’ behavior and mental demands to a certain extent. Nevertheless, the existing robot design is very limited, and a household personal robot is too large to be carried anywhere . The usage of wearable devices is simple, but these devices cannot offer diversified services. Therefore, this paper puts forward an emotion-aware system that integrates a personal robot, smart clothing, and cloud terminal. A new ’people-centered’ emotion-interaction mode is realized. Namely, personal robot and smart clothing supplement each other seamlessly and interact jointly with users . Artificial intelligence technology and knowledge graph are used to design emotion perception and interaction algorithms including intelligent recommendation, relation recognition, emotional expression recognition. Also, different scenarios are analyzed . Finally, a testbed is built to carry out relevant tests to verify the effectiveness of the proposed algorithms and emotion-aware system. According to the obtained test results, the system can be widely used to serve people and improve people’s mental health.

ACS Style

Jun Yang; Rui Wang; Xin Guan; Mohammad Mehedi Hassan; Ahmad Almogren; Ahmed Alsanad. AI-enabled emotion-aware robot: The fusion of smart clothing, edge clouds and robotics. Future Generation Computer Systems 2019, 102, 701 -709.

AMA Style

Jun Yang, Rui Wang, Xin Guan, Mohammad Mehedi Hassan, Ahmad Almogren, Ahmed Alsanad. AI-enabled emotion-aware robot: The fusion of smart clothing, edge clouds and robotics. Future Generation Computer Systems. 2019; 102 ():701-709.

Chicago/Turabian Style

Jun Yang; Rui Wang; Xin Guan; Mohammad Mehedi Hassan; Ahmad Almogren; Ahmed Alsanad. 2019. "AI-enabled emotion-aware robot: The fusion of smart clothing, edge clouds and robotics." Future Generation Computer Systems 102, no. : 701-709.

Journal article
Published: 04 August 2019 in Information Fusion
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Recently, human healthcare from body sensor data has been getting remarkable research attentions by a huge range of human-computer interaction and pattern analysis researchers due to its practical applications such as smart health care systems. For example, smart wearable-based behavior recognition system can be used to assist the rehabilitation of patients in a smart clinic to improve the rehabilitation process and to prolong their independent life. Although there are many ways of using distributed sensors to monitor vital signs and behavior of people, physical human action recognition via body sensors provides valuable data regarding an individual's functionality and lifestyle. In this work, we propose a body sensor-based system for behavior recognition using deep Recurrent Neural Network (RNN), a promising deep learning algorithm based on sequential information. We perform data fusion from multiple body sensors such as electrocardiography (ECG), accelerometer, magnetometer, etc. The extracted features are further enhanced via kernel principal component analysis (KPCA). The robust features are then used to train an activity RNN, which is later used for behavior recognition. The system has been compared against the conventional approaches on three publicly available standard datasets. The experimental results show that the proposed approach outperforms the available state-of-the-art methods.

ACS Style

Zia Uddin; Mohammed Mehedi Hassan; Ahmed Alsanad; Claudio Savaglio. A body sensor data fusion and deep recurrent neural network-based behavior recognition approach for robust healthcare. Information Fusion 2019, 55, 105 -115.

AMA Style

Zia Uddin, Mohammed Mehedi Hassan, Ahmed Alsanad, Claudio Savaglio. A body sensor data fusion and deep recurrent neural network-based behavior recognition approach for robust healthcare. Information Fusion. 2019; 55 ():105-115.

Chicago/Turabian Style

Zia Uddin; Mohammed Mehedi Hassan; Ahmed Alsanad; Claudio Savaglio. 2019. "A body sensor data fusion and deep recurrent neural network-based behavior recognition approach for robust healthcare." Information Fusion 55, no. : 105-115.