Mohamed Elshaikh Elobaid Said Ahmed
Thumbnail Image
Preferred name
Mohamed Elshaikh Elobaid Said Ahmed
Official Name
Mohamed Elshaikh Elobaid , Said Ahmed
Alternative Name
Ahmed, Mohamed Elshaikh Elobaid Said
Said Ahmed, Mohamed Elshaikh Elobaid
Elobaid, Mohamed Elshaikh
Main Affiliation
Scopus Author ID
57190012447
Researcher ID
R-7502-2019

Research Output

Filters

25
Reset filters

Settings
Now showing 1 - 10 of 25
  • Publication
    Multipoint Relay Path for Efficient Topology Maintenance Algorithm in Optimized Link State Routing-Based for VANET
    ( 2024-01-01)
    Waleed Khalid Ahmed
    ;
    Mohd Nazri Mohd Warip
    ;
    Mohamed Elshaikh Elobaid Said Ahmed
    ;
    Phak Len Al Eh Kan
    The Optimal Link State Routing (OLSR) protocol employs multipoint relay (MPR) nodes to disseminate topology control (TC) messages, enabling network topology discovery and maintenance. However, this approach increases control overhead and leads to wasted network bandwidth in stable topology scenarios due to fixed flooding periods. To address these challenges, this paper presents an Efficient Topology Maintenance Algorithm (ETM-OLSR) for Enhanced Link-State Routing Protocols. By reducing the number of MPR nodes, TC message generation and forwarding frequency are minimized. Furthermore, the algorithm selects a smaller subset of TC messages based on the changes in the MPR selection set from the previous cycle, adapting to stable and fluctuating network conditions. Additionally, the sending cycle of TC messages is dynamically adjusted in response to network topology changes. Simulation results demonstrate that the ETM-OLSR algorithm effectively reduces network control overhead, minimizes end-to-end delay, and improves network throughput compared to traditional OLSR and HTR-OLSR algorithms.
  • Publication
    Development of Cloud-based Electronic Nose for University Laboratories Air Monitoring
    ( 2020-12-18)
    Abu Hassan Abdullah
    ;
    Muhammad Aizat Abu Bakar
    ;
    Saad F.S.A.
    ;
    Sukhairi Sudin
    ;
    Zahari Awang Ahmad
    ;
    Mohamed Elshaikh Elobaid Said Ahmed
    ;
    Ismail K.A.
    Indoor air in area such as house, shopping complex, hospital, university, office and hotel should be monitor for human safety and wellbeing. These closed areas are prone to harmful air pollutants i.e. allergens, smoke, mold, particles, radon and hazardous gas. Laboratories in university are special room in which workers (student, technician, teaching/research assistants, researcher and lecturer) conduct their works and experiments. These activities and the environment will generate air pollutants which concentration depending on their parameters. Anyone in the environment that exposure to these pollutants may have safety and health issue. This paper propose a study of development of a cloud-based electronic nose system for university laboratories air monitoring. The system consists of five dsPIC33-based electronic nose (e-nose) as node which measure main indoor air pollutants along with two thermal comfort variables, i.e. temperature and relative humidity. The nodes are placed at five different laboratories for acquiring air pollutants data in real time. The data will be sent to a web server and the cloud-based system will process, analyse and display by a website in real time. The system will monitor the laboratories main air pollutants and thermal comfort by forecast the contaminants concentration and dispersion in the area. In case of air hazard safety (e.g., gas spills detection and pollution monitoring), the system will alert the security by activate an alarm and through e-mail. The website will display the Air Pollution Index (API) of the area in real-time. Results show that the system performance is good and can be used to monitor the air pollution in the university laboratories.
  • Publication
    Cloud-based System for University Laboratories Air Monitoring
    ( 2020-09-21)
    Abu Hassan Abdullah
    ;
    Sukhairi Sudin
    ;
    Mustafa M.H.
    ;
    Fathinul Syahir Ahmad Sa'ad
    ;
    Khairul Azwan Ismail
    ;
    Muhammad Aizat Abu Bakar
    ;
    Mohamed Elshaikh Elobaid Said Ahmed
    ;
    Abdul Ghapar Ahmad
    ;
    Zahari Awang Ahmad
    ;
    Sara Yasina Yusuf
    Indoor air such as house, shopping complex, hospital, university, office and hotel should be monitor for human safety and wellbeing. These closed areas are prone to harmful air pollutants i.e. allergens, smoke, mold, particles radon and hazardous gas. Laboratories in university are special room in which workers (student, technician, teaching/research assistants, researcher and lecturer) conduct their works and experiment. The activities and the environment will generate specific air pollutant which concentration depending to their parameters. Anyone in the environment that exposure to these pollutants may affect safety and health issue. This paper proposes a study of development of a cloud-based electronic nose system for university laboratories air monitoring. The system consists of DSP33-based electronic nose (e-nose) as nodes which measure main indoor air pollutant along with two thermal comfort variables, temperature and relative humidity. The e-noses are placed at five different laboratories for acquiring data in real time. The data will be sent to a web server and the cloud-based system will process, analyse using Neuro-Fuzzy classifier and display on a website in real time. The system will monitor the laboratories air pollutants and thermal comfort by predict the pollutant concentration and dispersion in the area i.e. Air Pollution Index (API). In case of air hazard safety (e.g., gas spills detection and pollution monitoring), the system will alert the security by activate an alarm and through e-mail. The website will display the API of the area in real-time. Results show that the system performance is good and can be used to monitor the air pollutant in the university laboratories.
  • Publication
    Imporved MPR selection algorithm-based WS-OLSR routing protocol
    ( 2024-05-01)
    Ahmed W.K.
    ;
    Mohd Nazri Mohd Warip
    ;
    Mohamed Elshaikh Elobaid Said Ahmed
    ;
    Phak Len Al Eh Kan
    Vehicle Ad Hoc Networks (VANETs) have become a viable technology to improve traffic flow and safety on the roads. Due to its effectiveness and scalability, the Wingsuit Search-based Optimised Link State Routing Protocol (WS-OLSR) is frequently used for data distribution in VANETs. However, the selection of MultiPoint Relays (MPRs) plays a pivotal role in WS-OLSR’s performance. This paper presents an improved MPR selection algorithm tailored to WS-OLSR, designed to enhance the overall routing efficiency and reduce overhead. The analysis found that the current OLSR protocol has problems such as redundancy of HELLO and TC message packets or failure to update routing information in time, so a WS-OLSR routing protocol based on improved-MPR selection algorithm was proposed. Firstly, factors such as node mobility and link changes are comprehensively considered to reflect network topology changes, and the broadcast cycle of node HELLO messages is controlled through topology changes. Secondly, a new MPR selection algorithm is proposed, considering link stability issues and nodes. Finally, evaluate its effectiveness in terms of packet delivery ratio, end-to-end delay, and control message overhead. Simulation results demonstrate the superior performance of our improved MR selection algorithm when compared to traditional approaches.
      1
  • Publication
    Shape Recognition of GPR Images using Hough Transform and PCA plus LDA
    ( 2022-01-01)
    Hasimah Ali
    ;
    Norfatihah Bahari
    ;
    Mohamed Elshaikh Elobaid Said Ahmed
    ;
    Siti Nurul Aqmariah Mohd Kanafiah
    ;
    Amran T.S.T.
    ;
    Jusman Y.
    Ground penetrating radar (GPR) is a nondestructive test used for shallow subsurface investigation such as land mine detection, mapping and locating buried utilities. In practical applications, GPR images could be noisy due to system noise, the heterogeneity of the medium, and mutual wave interactions. Hence, it is a complex task to recognize the hyperbolic pattern from GPR B-scan images. Thus, this project proposes combined shape recognition of buried objects using Hough Transform (HT) and PCA plus LDA in GPR images. The use of HT is justified because it has the property of transforming global curve detection into efficient peak detection in the Hough parameter space. Whereas PCA plus LDA tries to maximize between-class scatter while minimizing within-class scatter. In this framework, the preprocessed GPR images were extracted using HT. The extracted HT features were subjected to PCA plus LDA to map them from high into lower dimensional features. Then, the reduced PCA+LDA features were used as input to the k-NN classifier to recognize four geometrical shapes cubic, disc, and spherical of the buried objects. Based on the results obtained, the average recognition rate of reduced HT features using PCA plus LDA was achieved 85.30% thus shows a promising result.
      1
  • Publication
    Gaining Speedup with OpenMP Schedule Type under Imbalance Workload
    ( 2023-10-06)
    Zahereel Ishwar Abdul Khalib
    ;
    Mohamed Elshaikh Elobaid Said Ahmed
    ;
    Qun N.H.
    ;
    Rahman M.
    ;
    Hossen M.A.
    Despite OpenMP being the defacto standard for parallel programming on shared memory system, little is known on how its schedule type and chunk size effect the parallel performance of shared memory multicore processor. Performance analysis in the literature have overlooked the effects of different schedule type and chunk size, possibly it was simply not the focus of their research. Often, the researchers did not specify the schedule type explicitly. This has resulted in the default way of assigning the loop iterations among threads. By default, the static schedule is used and the size of chunk which is the ratio of total number of iterations to the number of threads is implemented. Contrary to above, this research proposes a guideline to select the appropriate schedule type and chunk size for achieving optimum performance on different shared memory multicore platform for balanced and imbalance workload. Three multicore technology namely Intel Core i5-2410M, AMD A12-9700P and ARM Cortex-A53 are used for this work. The speedup obtained after turning on/off certain multicore technologies and a selected number of active cores per processor is analyzed. The result of analysis enables the user to justify and exercise trade-offs in selecting OpenMP schedule type and chunk size, and also in choosing the multicore technologies to meet the desired performance gain. Results analyzed over various configurations of multicore platform and workload suggested that under certain constraint different schedule types and chunk sizes have led to better speedup.
      1
  • Publication
    Velocity Based Performance Analysis of GreedLea Routing Protocol in Internet of Vehicle (IoV)
    ( 2024-12-01)
    Normaliza Omar
    ;
    Naimah Yaakob
    ;
    Mohamed Elshaikh Elobaid Said Ahmed
    ;
    Zulkifli Husin
    ;
    Iszaidy Ismail
    ;
    Alaa KY Dafhalla
    Intelligent routing protocols for IoV have also been made possible by the convergence of IoT and machine learning algorithm. In order to make informed routing decisions, these intelligent routing protocols examine data gathered from IoT devices like vehicle sensors and traffic monitoring systems using machine learning algorithms. Moreover, as the number of vehicles increases and road networks become more complex, traditional routing protocols for ad hoc networks are being replaced by more advanced and efficient protocols. The purpose of this study is to concentrate on these unique qualities of IoVs network scenario. A combined routing method has been developed to construct periodic connectivity and find routes on-demand in order to save route data as graphs. The simulation's findings show that GreedLea routing protocol outperforms GPSR and AODV routing protocols in terms of delay and packet delivery ratio (PDR). The results demonstrate that the average AODV latency is significantly higher when there are fewer vehicles on the network. This is due to the fact that connections are frequently lost at higher speeds and lower densities, and re-establishing new channels takes a lot of time. As the number of vehicles rises, efficiency improves and the wait gets shorter. The average latency, yet, keeps increasing as vehicle density increases due to the additional overheads related with routing.
      1  10
  • Publication
    Design and Development of GreedLea Routing Protocol for Internet of Vehicle (IoV)
    ( 2020-03-20)
    Normaliza Omar
    ;
    Naimah Yaakob
    ;
    Zulkifli Husin
    ;
    Mohamed Elshaikh Elobaid Said Ahmed
    In Internet of Vehicle (IoV), each vehicle uses a routing protocol to find a path for sending its messages to the last destination. Nowadays, the studies of IoV routing protocols and their impact on the performances of network with different network scenarios has significantly developed a precise understanding of the requirements and goals for designing an IoV routing protocol. In IoV, topology of network diverse promptly which leads to the fragmentation of network, frequent route breakage, and packet loss. This paper discusses on the development of an integrated routing protocol for IoV scenario. Greedy Perimeter Stateless Routing (GPSR) and Reinforcement Learning (RL) is integrate to determine a route based on demand. Then, the mobility model has been designed to reduce road collision. Lastly, traffic management also been focused to deal with the loss, mobility and network delay to meet the application demands.
      3  11
  • Publication
    GPSR Routing Performances Enhancement for VANET networks with Taguchi Optimization Mechanism
    ( 2021-07-26)
    Mohamed Elshaikh Elobaid Said Ahmed
    ;
    Dafhalla A.K.Y.
    ;
    Naimah Yaakob
    ;
    Hasimah Ali
    Routing mechanism plays an important role in the performances of Vehicular Ad Hoc Networks (VANET). Hence, various routing mechanisms are proposed to enhance VANET performances, however few researches are dedicated to optimize these routing mechanisms. In this paper an optimization mechanism is proposed to improve the performances of Greedy Perimeter stateless Routing (GPSR) protocol. Design of Experiments is used along with Taguchi Optimization method to fine tune GPSR internal routing parameters against VANET network scenarios. The target of optimization in this work is set to network performances including network throughput, delay and packet delivery ration (PDR). These targets are mathematically combined to form a single optimization target. A simulation experiments are performed to evaluate VANET performances. Obtained results showed that the proposed optimization improves the VANET performances in terms of throughput, PDR and delay. Further real-time integration of Optimization and routing mechanism can improve network performances.
      1
  • Publication
    Feature extraction using Radon transform and Discrete Wavelet Transform for facial emotion recognition
    ( 2017-02-08)
    Hasimah Ali
    ;
    Vinothan Sritharan
    ;
    Muthusamy Hariharan
    ;
    Siti Khadijah Za'aba
    ;
    Mohamed Elshaikh Elobaid Said Ahmed
    This paper presents a new pattern framework of using Radon and wavelet transform for facial emotion recognition. The Radon transform is translation and rotation invariants, hence it preserves the variations in pixel intensities. In this work, Radon transform has been used to project the 2D image into Radon space before subjected to Discrete Wavelet Transform (DWT). In DWT framework, the approximate coefficients (cA2) at second level decomposition are extracted and used as informative features to recognize the facial emotion. Since there are a large number of coefficients, hence the principal component analysis (PCA) is applied on the extracted features. The k-nearest neighbor classifier is adopted as classifier to classify seven (anger, disgust, fear, happiness, neutral, sadness and surprise) facial emotions. To evaluate the effectiveness of the proposed method, the JAFFE database has been employed. Based on the results obtained, the proposed method demonstrates the recognition rate of 91.3%, thus it is promising.
      17  2