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Energy saving is a significant research area in Saudi Arabia; however, significant problems have emerged related to its distribution and consumption. Use of an agent is assumed to combat these problems by forming efficient coalitions to control the energy consumption and energy distribution process. This study presents a novel algorithm for distributing the value calculation among the cooperative agents. This is likely to reduce the consumption of energy and extend the coalition lifetime used. The developed algorithm is compared with the basic modified coalition formation algorithm for evaluating its effectiveness. The results showed a reduction in cooling consumption by 20% after applying optimization algorithms. The amount of reduction in the cooling consumption reflects a 31% reduction in expected cooling costs, without affecting the household comfort. Therefore, the study concludes that DNsys provided better performance than the NNsys.
Areej Malibari; Daniyal Alghazzawi; Maha Lashin. Coalition Formation among the Cooperative Agents for Efficient Energy Consumption. Sustainability 2021, 13, 8662 .
AMA StyleAreej Malibari, Daniyal Alghazzawi, Maha Lashin. Coalition Formation among the Cooperative Agents for Efficient Energy Consumption. Sustainability. 2021; 13 (15):8662.
Chicago/Turabian StyleAreej Malibari; Daniyal Alghazzawi; Maha Lashin. 2021. "Coalition Formation among the Cooperative Agents for Efficient Energy Consumption." Sustainability 13, no. 15: 8662.
This paper investigates the mechanical properties of two different types of recycled concrete, which use wood and rubber, relative to those characteristics of pure concrete, in terms of maximum load and natural frequencies. This paper contributes to the state of the art in this area in a number of ways. Firstly, the paper provides furtherance to the progressively growing literature in the field of recycled concrete and mechanical properties of materials. Secondly, the paper investigates the mechanical properties of two different types of recycled concrete by means of investigating the natural frequency of the samples, which is a new contribution. Lastly, the results from predicting the natural frequencies of concrete using fuzzy logic have been effectively assessed and compared with the analytical results. Results from the study show that the pure concrete samples produced maximum natural frequency, then concrete samples with wood, and lastly, concrete samples with rubber. The tolerance between the lab test results and fuzzy logic is approximately 5%. These results could have significant implications for furthering recycled concrete research and for designing machine foundations. Evidence of the applicability of fuzzy logic as a predictive and analysis tool for the mechanical properties of recycled concrete are discussed.
Maha Lashin; Aamir Khokhar; Fadwa Alrowais; Areej Malibari; Wafaa Saleh. Using Artificial Intelligence for Optimizing Natural Frequency of Recycled Concrete for Mechanical Machine Foundation. Recycling 2021, 6, 43 .
AMA StyleMaha Lashin, Aamir Khokhar, Fadwa Alrowais, Areej Malibari, Wafaa Saleh. Using Artificial Intelligence for Optimizing Natural Frequency of Recycled Concrete for Mechanical Machine Foundation. Recycling. 2021; 6 (3):43.
Chicago/Turabian StyleMaha Lashin; Aamir Khokhar; Fadwa Alrowais; Areej Malibari; Wafaa Saleh. 2021. "Using Artificial Intelligence for Optimizing Natural Frequency of Recycled Concrete for Mechanical Machine Foundation." Recycling 6, no. 3: 43.
The utilization of mobile learning continues to rise and has attracted many organizations, university environments and institutions of higher education all over the world. The cloud storage system consists of several defense issues since data security and privacy have become known as the foremost apprehension for the users. Uploading and storing specific data in the cloud is familiar and widespread, but securing the data is a complicated task. This paper proposes a cloud-based mobile learning system using a hybrid optimal elliptic curve cryptography (HOECC) algorithm comprising public and private keys for data encryption. The proposed approach utilizes an adaptive tunicate slime-mold (ATS) algorithm to generate optimal key value. Thus, the data uploaded in the cloud system are secured with high authentication, data integrity and confidentiality. The study investigation employed a survey consisting of 50 students and the questionnaire was sent to all fifty students. In addition to this, for obtaining secure data transmission in the cloud, various performance measures, namely the encryption time, decryption time and uploading/downloading time were evaluated. The results reveal that the time of both encryption and decryption is less in ATF approach when compared with other techniques.
Ghadah Aldabbagh; Daniyal Alghazzawi; Syed Hasan; Mohammed Alhaddad; Areej Malibari; Li Cheng. Secure Data Exchange in M-Learning Platform using Adaptive Tunicate Slime-Mold-Based Hybrid Optimal Elliptic Curve Cryptography. Applied Sciences 2021, 11, 5316 .
AMA StyleGhadah Aldabbagh, Daniyal Alghazzawi, Syed Hasan, Mohammed Alhaddad, Areej Malibari, Li Cheng. Secure Data Exchange in M-Learning Platform using Adaptive Tunicate Slime-Mold-Based Hybrid Optimal Elliptic Curve Cryptography. Applied Sciences. 2021; 11 (12):5316.
Chicago/Turabian StyleGhadah Aldabbagh; Daniyal Alghazzawi; Syed Hasan; Mohammed Alhaddad; Areej Malibari; Li Cheng. 2021. "Secure Data Exchange in M-Learning Platform using Adaptive Tunicate Slime-Mold-Based Hybrid Optimal Elliptic Curve Cryptography." Applied Sciences 11, no. 12: 5316.
The term “mobile learning” (or “m-learning”) refers to using handheld phones to learn and wireless computing as a learning tool and connectivity technology. This paper presents and explores the latest mobile platform for teaching and studying programming basics. The M-Learning tool was created using a platform-independent approach to target the largest available number of learners while reducing development and maintenance time and effort. Since the code is completely shared across mobile devices (iOS, Android, and Windows Phone), students can use any smartphone to access the app. To make the programme responsive, scalable, and dynamic, and to provide students with personalised guidance, the core application is based on an analysis design development implementation and assessment (ADDIE) model implemented in the Xamarin framework. The application’s key features are depicted in a prototype. An experiment is carried out on BS students at a university to evaluate the efficacy of the generated application. A usefulness questionnaire is administered to an experimental community in order to determine students’ expectations of the developed mobile application’s usability. The findings of the experiment show that the application is considerably more successful than conventional learning in developing students’ online knowledge assessment abilities, with an impact size of 1.96. The findings add to the existing mobile learning literature by defining usability assessment features and offering a basis for designing platform-independent m-learning applications. The current findings are explored in terms of their implications for study and teaching practice.
Daniyal Alghazzawi; Syed Hasan; Ghadah Aldabbagh; Mohammed Alhaddad; Areej Malibari; Muhammad Asghar; Hanan Aljuaid. Development of Platform Independent Mobile Learning Tool in Saudi Universities. Sustainability 2021, 13, 5691 .
AMA StyleDaniyal Alghazzawi, Syed Hasan, Ghadah Aldabbagh, Mohammed Alhaddad, Areej Malibari, Muhammad Asghar, Hanan Aljuaid. Development of Platform Independent Mobile Learning Tool in Saudi Universities. Sustainability. 2021; 13 (10):5691.
Chicago/Turabian StyleDaniyal Alghazzawi; Syed Hasan; Ghadah Aldabbagh; Mohammed Alhaddad; Areej Malibari; Muhammad Asghar; Hanan Aljuaid. 2021. "Development of Platform Independent Mobile Learning Tool in Saudi Universities." Sustainability 13, no. 10: 5691.
In this article, a low-profile, compact, quad-port super-wideband (SWB) multiple-input–multiple-output (MIMO) antenna is presented for the internet of things (IoT) applications. The proposed antenna comprises four identical sickle-shaped resonating elements, which are excited by tapered coplanar waveguide (CPW) feed lines. The antenna elements are arranged in rotational symmetry (mutually orthogonal to each other) to achieve high port isolation. A complementary slot, which matches the sickle-shaped radiator, is etched from the ground of the proposed monopole antenna element to achieve massive bandwidth. The MIMO antenna possesses a resonating bandwidth ( $\vert S_{11}\vert \le -10$ dB) of 1.3–40 GHz and a bandwidth ratio of 31:1. In addition, an L-shaped slit and a complementary split-ring resonator (CSRR) are introduced in the sickle-shaped radiator to reject Bluetooth (2.4 GHz), WLAN (5.5 GHz), and downlink of X-band satellite communication (7.5 GHz) signals from the SWB. The proposed MIMO antenna is fabricated and experimental results are found in agreement with the simulated results.
Pawan Kumar; Shabana Urooj; Areej Malibari. Design and Implementation of Quad-Element Super-Wideband MIMO Antenna for IoT Applications. IEEE Access 2020, 8, 226697 -226704.
AMA StylePawan Kumar, Shabana Urooj, Areej Malibari. Design and Implementation of Quad-Element Super-Wideband MIMO Antenna for IoT Applications. IEEE Access. 2020; 8 ():226697-226704.
Chicago/Turabian StylePawan Kumar; Shabana Urooj; Areej Malibari. 2020. "Design and Implementation of Quad-Element Super-Wideband MIMO Antenna for IoT Applications." IEEE Access 8, no. : 226697-226704.
Widespread development of system software, the process of learning, and the excellence in profession of teaching are the formidable challenges faced by the learning behavior prediction system. The learning styles of teachers have different kinds of content designs to enhance their learning. In this learning environment, teachers can work together with the students, but the learning materials are designed by the teachers. The cognitive style deals with mental activities such as learning, remembering, thinking, and the usage of language. Therefore, being motivated by the problems mentioned above, this paper proposes the concept of adaptive optimization-based neural network (AONN). The learning behavior and browsing behavior features are extracted and incorporated into the input of artificial neural network (ANN). Hence, in this paper, the neural network weights are optimized with the use of grey wolf optimizer (GWO) algorithm. The output operation of e-learning with teaching equipment is chosen based on the cognitive style predicted by AONN. In experimental section, the measures of accuracy, sensitivity, specificity, time (sec), and memory (bytes) are carried out. Each of the measure is compared with the proposed AONN and existing fuzzy logic methodologies. Ultimately, the proposed AONN method produces higher accuracy, specificity, and sensitivity results. The results demonstrate that the algorithm proposed in this study can automatically learn network structures competitively, unlike those achieved for neural networks through standard approaches.
Ghada Aldabbagh; Daniyal M. AlGhazzawi; Syed Hamid Hasan; Mohammed Alhaddad; Areej Malibari; Li Cheng. Optimal Learning Behavior Prediction System Based on Cognitive Style Using Adaptive Optimization-Based Neural Network. Complexity 2020, 2020, 1 -13.
AMA StyleGhada Aldabbagh, Daniyal M. AlGhazzawi, Syed Hamid Hasan, Mohammed Alhaddad, Areej Malibari, Li Cheng. Optimal Learning Behavior Prediction System Based on Cognitive Style Using Adaptive Optimization-Based Neural Network. Complexity. 2020; 2020 ():1-13.
Chicago/Turabian StyleGhada Aldabbagh; Daniyal M. AlGhazzawi; Syed Hamid Hasan; Mohammed Alhaddad; Areej Malibari; Li Cheng. 2020. "Optimal Learning Behavior Prediction System Based on Cognitive Style Using Adaptive Optimization-Based Neural Network." Complexity 2020, no. : 1-13.
This article presents a compact, planar, quad-port ultra-wideband (UWB) multiple-input–multiple-output (MIMO) antenna with wide axial ratio bandwidth (ARBW). The proposed MIMO design consists of four identical square-shaped antenna elements, where each element is made up of a circular slotted ground plane and feed by a 50 Ω microstrip line. The circular polarization is achieved using a protruding hexagonal stub from the ground plane. The four elements of the MIMO antenna are placed orthogonally to each other to obtain high inter-element isolation. FR-4 dielectric substrate of size 45 × 45 × 1.6 mm3 is used for the antenna prototype, and a good agreement is noticed among the simulated and experimental results. The proposed MIMO antenna shows 3-dB ARBW of 52% (3.8–6.5 GHz) and impedance bandwidth (S11 ≤ −10 dB) of 144% (2.2–13.5 GHz).
Pawan Kumar; Shabana Urooj; Areej Malibari. Design of Quad-Port Ultra-Wideband Multiple-Input-Multiple-Output Antenna with Wide Axial-Ratio Bandwidth. Sensors 2020, 20, 1174 .
AMA StylePawan Kumar, Shabana Urooj, Areej Malibari. Design of Quad-Port Ultra-Wideband Multiple-Input-Multiple-Output Antenna with Wide Axial-Ratio Bandwidth. Sensors. 2020; 20 (4):1174.
Chicago/Turabian StylePawan Kumar; Shabana Urooj; Areej Malibari. 2020. "Design of Quad-Port Ultra-Wideband Multiple-Input-Multiple-Output Antenna with Wide Axial-Ratio Bandwidth." Sensors 20, no. 4: 1174.
Energy saving has been a global concern since the last few years. Due to the massive growth of population in Saudi Arabia and its extremely hot climate, electricity consumption, and costs are expected to increase every year. This work presents an intelligent and efficient technology to create a balance between the need of energy consumption minimization and standards regarding the comfort of people in Saudi Arabia. Thermal Modelling and Optimization of Cooling Systems have been considered to generate the outcomes of study. The sample size comprised of 10 houses, which have been selected randomly from Royal Commission for Yanbu province. It has been revealed through testing that there is a reduction by 20% in cooling consumption. This reduction reflects in 31% reduction in expected cooling costs without affecting the comfort of householders.
Areej A. Malibari; Amjad H. Gamlo. Agent-Based Adaptive Cooling Optimising Systems for Homes in KSA. Computer and Information Science 2017, 10, 76 .
AMA StyleAreej A. Malibari, Amjad H. Gamlo. Agent-Based Adaptive Cooling Optimising Systems for Homes in KSA. Computer and Information Science. 2017; 10 (2):76.
Chicago/Turabian StyleAreej A. Malibari; Amjad H. Gamlo. 2017. "Agent-Based Adaptive Cooling Optimising Systems for Homes in KSA." Computer and Information Science 10, no. 2: 76.
Objectives: The consumption of electricity and its costs are expected to be increased in Saudi Arabia due to its rapid growth in population. As the Kingdom is characterized by extreme hot climate, a massive amount of electricity consumed by the residential sector goes to power air conditioners. To control this huge amount of energyconsumedin homes, thermal models have been generated with two or more parameters. Methodology: The households’ surveys have been conducted in order to collect the data. The Non-linear regression analysis has been carried out to obtain the outcomes of study. Moreover, household surveys have been conducted for data collection. The grid algorithm and the non-linear regression have been used to learn the parameters in the model to simulate the weather in Saudi Arabia. The temperature loggers have been placed in the houses to observe the behavior of residents of using cooling system. The web forecast has been used to analyze the temperature of cities on hourly basis. Results: Simple thermal model has been built using two parameters by applying the grid and non-linear regression methods for data fitting. Then the thermal model with envelope has also been created using four parameters by applying non-linear regression method for data fitting. Conclusion: It has been evaluated through outcomes that thermal model with envelope is better as compared to simple thermal model. Moreover, the data fitting by non-linear regression method has also been observed to perform better than data fitting by grid method.
Areej A. Malibari; Amjad H. Gamlo. Home Thermal Modeling: Cooling Energy Consumption and Costs in Saudi Arabia. Computer and Information Science 2016, 9, 22 .
AMA StyleAreej A. Malibari, Amjad H. Gamlo. Home Thermal Modeling: Cooling Energy Consumption and Costs in Saudi Arabia. Computer and Information Science. 2016; 9 (4):22.
Chicago/Turabian StyleAreej A. Malibari; Amjad H. Gamlo. 2016. "Home Thermal Modeling: Cooling Energy Consumption and Costs in Saudi Arabia." Computer and Information Science 9, no. 4: 22.
Sakha'a Al Manaseer; Areej Malibari. Improve Teaching Method of Data Mining Course. International Journal of Modern Education and Computer Science 2012, 4, 15 -22.
AMA StyleSakha'a Al Manaseer, Areej Malibari. Improve Teaching Method of Data Mining Course. International Journal of Modern Education and Computer Science. 2012; 4 (2):15-22.
Chicago/Turabian StyleSakha'a Al Manaseer; Areej Malibari. 2012. "Improve Teaching Method of Data Mining Course." International Journal of Modern Education and Computer Science 4, no. 2: 15-22.