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Large-scale mapping of date palm trees is vital for their consistent monitoring and sustainable management, considering their substantial commercial, environmental, and cultural value. This study presents an automatic approach for the large-scale mapping of date palm trees from very-high-spatial-resolution (VHSR) unmanned aerial vehicle (UAV) datasets, based on a deep learning approach. A U-Shape convolutional neural network (U-Net), based on a deep residual learning framework, was developed for the semantic segmentation of date palm trees. A comprehensive set of labeled data was established to enable the training and evaluation of the proposed segmentation model and increase its generalization capability. The performance of the proposed approach was compared with those of various state-of-the-art fully convolutional networks (FCNs) with different encoder architectures, including U-Net (based on VGG-16 backbone), pyramid scene parsing network, and two variants of DeepLab V3+. Experimental results showed that the proposed model outperformed other FCNs in the validation and testing datasets. The generalizability evaluation of the proposed approach on a comprehensive and complex testing dataset exhibited higher classification accuracy and showed that date palm trees could be automatically mapped from VHSR UAV images with an F-score, mean intersection over union, precision, and recall of 91%, 85%, 0.91, and 0.92, respectively. The proposed approach provides an efficient deep learning architecture for the automatic mapping of date palm trees from VHSR UAV-based images.
Mohamed Gibril; Helmi Shafri; Abdallah Shanableh; Rami Al-Ruzouq; Aimrun Wayayok; Shaiful Hashim. Deep Convolutional Neural Network for Large-Scale Date Palm Tree Mapping from UAV-Based Images. Remote Sensing 2021, 13, 2787 .
AMA StyleMohamed Gibril, Helmi Shafri, Abdallah Shanableh, Rami Al-Ruzouq, Aimrun Wayayok, Shaiful Hashim. Deep Convolutional Neural Network for Large-Scale Date Palm Tree Mapping from UAV-Based Images. Remote Sensing. 2021; 13 (14):2787.
Chicago/Turabian StyleMohamed Gibril; Helmi Shafri; Abdallah Shanableh; Rami Al-Ruzouq; Aimrun Wayayok; Shaiful Hashim. 2021. "Deep Convolutional Neural Network for Large-Scale Date Palm Tree Mapping from UAV-Based Images." Remote Sensing 13, no. 14: 2787.
Automatic building extraction has been applied in many domains. It is also a challenging problem because of the complex scenes and multiscale. Deep learning algorithms, especially fully convolutional neural networks (FCNs), have shown robust feature extraction ability than traditional remote sensing data processing methods. However, hierarchical features from encoders with a fixed receptive field perform weak ability to obtain global semantic information. Local features in multiscale subregions cannot construct contextual interdependence and correlation, especially for large-scale building areas, which probably causes fragmentary extraction results due to intra-class feature variability. In addition, low-level features have accurate and fine-grained spatial information for tiny building structures but lack refinement and selection, and the semantic gap of across-level features is not conducive to feature fusion. To address the above problems, this paper proposes an FCN framework based on the residual network and provides the training pattern for multi-modal data combining the advantage of high-resolution aerial images and LiDAR data for building extraction. Two novel modules have been proposed for the optimization and integration of multiscale and across-level features. In particular, a multiscale context optimization module is designed to adaptively generate the feature representations for different subregions and effectively aggregate global context. A semantic guided spatial attention mechanism is introduced to refine shallow features and alleviate the semantic gap. Finally, hierarchical features are fused via the feature pyramid network. Compared with other state-of-the-art methods, experimental results demonstrate superior performance with 93.19 IoU, 97.56 OA on WHU datasets and 94.72 IoU, 97.84 OA on the Boston dataset, which shows that the proposed network can improve accuracy and achieve better performance for building extraction.
Qinglie Yuan; Helmi Shafri; Aidi Alias; Shaiful Hashim. Multiscale Semantic Feature Optimization and Fusion Network for Building Extraction Using High-Resolution Aerial Images and LiDAR Data. Remote Sensing 2021, 13, 2473 .
AMA StyleQinglie Yuan, Helmi Shafri, Aidi Alias, Shaiful Hashim. Multiscale Semantic Feature Optimization and Fusion Network for Building Extraction Using High-Resolution Aerial Images and LiDAR Data. Remote Sensing. 2021; 13 (13):2473.
Chicago/Turabian StyleQinglie Yuan; Helmi Shafri; Aidi Alias; Shaiful Hashim. 2021. "Multiscale Semantic Feature Optimization and Fusion Network for Building Extraction Using High-Resolution Aerial Images and LiDAR Data." Remote Sensing 13, no. 13: 2473.
In downlink non-orthogonal multiple access (NOMA) with multiuser clustering, a single beamforming vector precodes the superimposed signal of strong and weak users. This precoding results in imperfect inter-cluster interference (ICI) cancellation at weak users since beamforming vectors are designed based on strong users' channels. Also, the ICI is highly increased with the number of transmit antennas, causing severe degradation in the performance of weak users and total system. In this paper, a new cooperative NOMA is introduced, in which we firstly, propose a receiver equalizer at weak users namely weak user-beam matching (WBM) to remove the ICI at weak users by matching their channels with the designed beams. The process of WBM is accomplished with the aid of device-to-device (D2D) channel state information (CSI) exchange between the nearby strong and weak users. Secondly, strong user beam matching (SBM) equalizer is proposed at strong users to eliminate the ICI that arises in case of limited feedback. Thirdly, a new power allocation strategy is proposed, which improves weak users' performance by considering the throughput gained from interference cancellation. Finally, besides the sum-rate, which is adopted as the performance metric by most of the existing NOMA works, the bit error rate (BER) of NOMA users is tested using the proposed equalizers and compared with those in non-cooperative schemes. Simulation results show that the proposed cooperative NOMA achieves significant sum-rate and BER improvements over non-cooperative NOMA schemes under both perfect and limited feedback scenarios.
Mohanad Mohammed Al-Wani; Aduwati Sali; Sumaya Dhari Awad; Asem A. Salah; Zhiguo Ding; Nor Kamariah Noordin; Shaiful J. Hashim; Chee Yen Leow. Interference Cancellation via D2D CSI Sharing for MU-MISO-NOMA System With Limited Feedback. IEEE Transactions on Vehicular Technology 2021, 70, 4569 -4584.
AMA StyleMohanad Mohammed Al-Wani, Aduwati Sali, Sumaya Dhari Awad, Asem A. Salah, Zhiguo Ding, Nor Kamariah Noordin, Shaiful J. Hashim, Chee Yen Leow. Interference Cancellation via D2D CSI Sharing for MU-MISO-NOMA System With Limited Feedback. IEEE Transactions on Vehicular Technology. 2021; 70 (5):4569-4584.
Chicago/Turabian StyleMohanad Mohammed Al-Wani; Aduwati Sali; Sumaya Dhari Awad; Asem A. Salah; Zhiguo Ding; Nor Kamariah Noordin; Shaiful J. Hashim; Chee Yen Leow. 2021. "Interference Cancellation via D2D CSI Sharing for MU-MISO-NOMA System With Limited Feedback." IEEE Transactions on Vehicular Technology 70, no. 5: 4569-4584.
The notion of smart cities has remained under evolution as its global implementations are challenged by numerous technological, economic, and governmental obstacles. Moreover, the synergy of the Internet of Things (IoT) and big data technologies could result in promising horizons in terms of smart city development which has not been explored yet. Thus, the current research aims to address the essence of smart cities. To this end, first, the concept of smart cities is briefly overviewed; then, their properties and specifications as well as generic architecture, compositions, and real-world implementations are addressed. Furthermore, possible challenges and opportunities in the field of smart cities are described. Numerous issues and challenges such as analytics and using big data in smart cities introduced in this study offers an enhancement in developing applications of the above-mentioned technologies. Hence, this study paves the way for future research on the issues and challenges of big data applications in smart cities.
Marieh Talebkhah; Aduwati Sali; Mohsen Marjani; Meisam Gordan; Shaiful Jahari Hashim; Fakhrul Zaman Rokhani. IoT and Big Data Applications in Smart Cities: Recent Advances, Challenges, and Critical Issues. IEEE Access 2021, 9, 55465 -55484.
AMA StyleMarieh Talebkhah, Aduwati Sali, Mohsen Marjani, Meisam Gordan, Shaiful Jahari Hashim, Fakhrul Zaman Rokhani. IoT and Big Data Applications in Smart Cities: Recent Advances, Challenges, and Critical Issues. IEEE Access. 2021; 9 (99):55465-55484.
Chicago/Turabian StyleMarieh Talebkhah; Aduwati Sali; Mohsen Marjani; Meisam Gordan; Shaiful Jahari Hashim; Fakhrul Zaman Rokhani. 2021. "IoT and Big Data Applications in Smart Cities: Recent Advances, Challenges, and Critical Issues." IEEE Access 9, no. 99: 55465-55484.
Several wireless devices and applications can be connected through wireless communication technologies to exchange data in future intelligent health systems (e.g., the Internet of Medical Things (IoMT)). Smart healthcare requires ample bandwidth, reliable and effective communications networks, energy-efficient operations, and quality of service support (QoS). Healthcare service providers host multi-servers to ensure seamless services are provided to the end-users. By supporting a multi-server environment, healthcare medical sensors produce many data transmitted via servers, which is impossible in a single-server architecture. To ensure data security, secure online communication must be considered since the transmitted data are sensitive. Hence, the adversary may try to interrupt the transmission and drop or modify the message. Many researchers have proposed an authentication scheme to secure the data, but the schemes are vulnerable to specific attacks (modification attacks, replay attacks, server spoofing attacks, Man-in-the middle (MiTM) attacks, etc.). However, the absence of an authentication scheme that supports a multi-server security in such a comprehensive development in a distributed server is still an issue. In this paper, a secure authentication scheme using wireless medical sensor networks for a multi-server environment is proposed (Cross-SN). The scheme is implemented with a smart card, password, and user identity. Elliptic curve cryptography is utilized in the scheme, and Burrows–Abadi–Needham (BAN) logic is utilized to secure mutual authentication and to analyse the proposed scheme’s security. It offers adequate protection against replies, impersonation, and privileged insider attacks and secure communication in multi-server parties that communicate with each other.
Haqi Khalid; Shaiful Hashim; Sharifah Syed Ahmad; Fazirulhisyam Hashim; Muhammad Chaudhary. Cross-SN: A Lightweight Authentication Scheme for a Multi-Server Platform Using IoT-Based Wireless Medical Sensor Network. Electronics 2021, 10, 790 .
AMA StyleHaqi Khalid, Shaiful Hashim, Sharifah Syed Ahmad, Fazirulhisyam Hashim, Muhammad Chaudhary. Cross-SN: A Lightweight Authentication Scheme for a Multi-Server Platform Using IoT-Based Wireless Medical Sensor Network. Electronics. 2021; 10 (7):790.
Chicago/Turabian StyleHaqi Khalid; Shaiful Hashim; Sharifah Syed Ahmad; Fazirulhisyam Hashim; Muhammad Chaudhary. 2021. "Cross-SN: A Lightweight Authentication Scheme for a Multi-Server Platform Using IoT-Based Wireless Medical Sensor Network." Electronics 10, no. 7: 790.
Cardiovascular Disease (CVD) is a primary cause of heart problems such as angina and myocardial ischemia. The detection of the stage of CVD is vital for the prevention of medical complications related to the heart, as they can lead to heart muscle death (known as myocardial infarction). The electrocardiogram (ECG) reflects these cardiac condition changes as electrical signals. However, an accurate interpretation of these waveforms still calls for the expertise of an experienced cardiologist. Several algorithms have been developed to overcome issues in this area. In this study, a new scheme for myocardial ischemia detection with multi-lead long-interval ECG is proposed. This scheme involves an observation of the changes in ischemic-related ECG components (ST segment and PR segment) by way of the Choi-Williams time-frequency distribution to extract ST and PR features. These extracted features are mapped to a multi-class SVM classifier for training in the detection of unknown conditions to determine if they are normal or ischemic. The use of multi-lead ECG for classification and 1 min intervals instead of beats or frames contributes to improved detection performance. The classification process uses the data of 92 normal and 266 patients from four different databases. The proposed scheme delivered an overall result with 99.09% accuracy, 99.49% sensitivity, and 98.44% specificity. The high degree of classification accuracy for the different and unknown data sources used in this study reflects the flexibility, validity, and reliability of this proposed scheme. Additionally, this scheme can assist cardiologists in detecting signal abnormality with robustness and precision, and can even be used for home screening systems to provide rapid evaluation in emergency cases.
Ahmed Hussein; Shaiful Hashim; Fakhrul Rokhani; Wan Wan Adnan. An Automated High-Accuracy Detection Scheme for Myocardial Ischemia Based on Multi-Lead Long-Interval ECG and Choi-Williams Time-Frequency Analysis Incorporating a Multi-Class SVM Classifier. Sensors 2021, 21, 2311 .
AMA StyleAhmed Hussein, Shaiful Hashim, Fakhrul Rokhani, Wan Wan Adnan. An Automated High-Accuracy Detection Scheme for Myocardial Ischemia Based on Multi-Lead Long-Interval ECG and Choi-Williams Time-Frequency Analysis Incorporating a Multi-Class SVM Classifier. Sensors. 2021; 21 (7):2311.
Chicago/Turabian StyleAhmed Hussein; Shaiful Hashim; Fakhrul Rokhani; Wan Wan Adnan. 2021. "An Automated High-Accuracy Detection Scheme for Myocardial Ischemia Based on Multi-Lead Long-Interval ECG and Choi-Williams Time-Frequency Analysis Incorporating a Multi-Class SVM Classifier." Sensors 21, no. 7: 2311.
The development of the industrial Internet of Things (IIoT) promotes the integration of the cross-platform systems in fog computing, which enable users to obtain access to multiple application located in different geographical locations. Fog users at the network’s edge communicate with many fog servers in different fogs and newly joined servers that they had never contacted before. This communication complexity brings enormous security challenges and potential vulnerability to malicious threats. The attacker may replace the edge device with a fake one and authenticate it as a legitimate device. Therefore, to prevent unauthorized users from accessing fog servers, we propose a new secure and lightweight multi-factor authentication scheme for cross-platform IoT systems (SELAMAT). The proposed scheme extends the Kerberos workflow and utilizes the AES-ECC algorithm for efficient encryption keys management and secure communication between the edge nodes and fog node servers to establish secure mutual authentication. The scheme was tested for its security analysis using the formal security verification under the widely accepted AVISPA tool. We proved our scheme using Burrows Abdi Needham’s logic (BAN logic) to prove secure mutual authentication. The results show that the SELAMAT scheme provides better security, functionality, communication, and computation cost than the existing schemes.
Haqi Khalid; Shaiful Hashim; Sharifah Syed Ahmad; Fazirulhisyam Hashim; Muhammad Chaudhary. SELAMAT: A New Secure and Lightweight Multi-Factor Authentication Scheme for Cross-Platform Industrial IoT Systems. Sensors 2021, 21, 1428 .
AMA StyleHaqi Khalid, Shaiful Hashim, Sharifah Syed Ahmad, Fazirulhisyam Hashim, Muhammad Chaudhary. SELAMAT: A New Secure and Lightweight Multi-Factor Authentication Scheme for Cross-Platform Industrial IoT Systems. Sensors. 2021; 21 (4):1428.
Chicago/Turabian StyleHaqi Khalid; Shaiful Hashim; Sharifah Syed Ahmad; Fazirulhisyam Hashim; Muhammad Chaudhary. 2021. "SELAMAT: A New Secure and Lightweight Multi-Factor Authentication Scheme for Cross-Platform Industrial IoT Systems." Sensors 21, no. 4: 1428.
With growing interest in Industry 4.0, machine-to-machine communication (M2M) will become the key enabler for low-power wide area networks (LPWANs) in connecting machines and sensor nodes distributed across a distance in the industrial environment. The choice of modulation and diversity techniques, and the selection of spectrum (licensed/unlicensed) will impact and influence the requirements of wireless M2M systems. Link reliability is one of the most important requirements for LPWAN deployment in industrial scenarios. Rotating Polarization Wave (RPW) system has been recently proposed as an LPWAN solution for reliable M2M communication in high clutter environment and it deploys BPSK modulation with polarization diversity (PD). This paper proposes a new multi-level Rotating Polarization Phase-Shift Keying (RP-MPSK) modulation to provide high data rate and energy efficiency. A novel quaternion model for RPW system (Q-RPW) is also proposed to reduce the complexity in modeling, simulation, and implementation. Results using Q-RPW model show that RP-MPSK modulation offers a high diversity gain over BPSK with second-order diversity. Bit error rate (BER) performance of RP-MPSK modulation compared against other LPWAN modulation like MPSK, FSK and QAM has shown high reliability and substantial improvement in SNR. To overcome the degradation in error performance caused by the proposed higher-order modulation, sampling rates are recommended based on BER performance. BER performance of RP-MPSK under multipath and interference conditions is also investigated.
Zaid Ahmad; Shaiful Jahari Hashim; Fakhrul Zaman Rokhani; Syed Abul Rahman Al-Haddad; Aduwati Sali; Ken Takei. Quaternion Model of Higher-Order Rotating Polarization Wave Modulation for High Data Rate M2M LPWAN Communication. Sensors 2021, 21, 383 .
AMA StyleZaid Ahmad, Shaiful Jahari Hashim, Fakhrul Zaman Rokhani, Syed Abul Rahman Al-Haddad, Aduwati Sali, Ken Takei. Quaternion Model of Higher-Order Rotating Polarization Wave Modulation for High Data Rate M2M LPWAN Communication. Sensors. 2021; 21 (2):383.
Chicago/Turabian StyleZaid Ahmad; Shaiful Jahari Hashim; Fakhrul Zaman Rokhani; Syed Abul Rahman Al-Haddad; Aduwati Sali; Ken Takei. 2021. "Quaternion Model of Higher-Order Rotating Polarization Wave Modulation for High Data Rate M2M LPWAN Communication." Sensors 21, no. 2: 383.
Unlike the fixed power grid cooperative networks, which are mainly based on the reception reliability parameter while choosing the best relay, the wireless-powered cooperative communication network (WPCCN) and in addition to the reception reliability the transmission requirement consideration is important for relay selection schemes. Hence, enabling efficient transmission techniques that address high attenuation of radio frequency (RF) signals according to the distance without increasing the total transmission power is an open issue worth studying. In this relation, a multiantennas power beacon (PB) that assists wireless-powered cooperative communication network (PB-WPCCN) is studied in this paper. The communication between source and destination is achieved with the aid of multiple relays, where both the source and the multiple relays need to harvest energy from the PB in the first place to enable their transmission functionalities. A novel relay selection scheme is proposed, named as two-round relay selection (2-RRS), where a group of relays that successfully decode the source information is selected in the first round selection. In the second round, the optimal relay is selected to forward the recorded information to the destination. The proposed 2-RRS scheme is compared with two existing relay selection schemes, i.e., partial relay selection (PRS) and opportunistic relay selection (ORS). The analytical closed-form expressions of outage probability and average system throughput are derived and validated by numerical simulation. The comparison results between different relay selection schemes show: (I) The superiority of the proposed 2-RRS scheme as it achieves around 17% better throughput compared to the conventional ORS scheme and 40% better than the PRS scheme, particularly when PB transmit power is 10 dB; (II) The proposed 2-RRS scheme guarantees the lowest outage probability, especially when the PB is equipped with multiantennas and performs beamforming technique; (III) The optimal localisation of the PB between the source and N relays depends on the adopted relay selection scheme; (IV) The exhaustive search of the maximum system throughput value shows that the proposed 2-RRS scheme required shorter energy harvesting time compared to other schemes. The increase in energy harvesting time and number of relays do not necessarily reflect positively on the system throughput performance; hence tradeoffs should be taken into consideration.
Oussama Messadi; Aduwati Sali; Vahid Khodamoradi; Asem A. Salah; Gaofeng Pan; Shaiful J. Hashim; Nor K. Noordin. Optimal Relay Selection Scheme with Multiantenna Power Beacon for Wireless-Powered Cooperation Communication Networks. Sensors 2020, 21, 147 .
AMA StyleOussama Messadi, Aduwati Sali, Vahid Khodamoradi, Asem A. Salah, Gaofeng Pan, Shaiful J. Hashim, Nor K. Noordin. Optimal Relay Selection Scheme with Multiantenna Power Beacon for Wireless-Powered Cooperation Communication Networks. Sensors. 2020; 21 (1):147.
Chicago/Turabian StyleOussama Messadi; Aduwati Sali; Vahid Khodamoradi; Asem A. Salah; Gaofeng Pan; Shaiful J. Hashim; Nor K. Noordin. 2020. "Optimal Relay Selection Scheme with Multiantenna Power Beacon for Wireless-Powered Cooperation Communication Networks." Sensors 21, no. 1: 147.
Field data collection and geospatial map generation are critical aspects in different fields such as road asset management, urban planning, and geospatial applications. However, one of the primary impediments to data collection is the availability of spatial and attribute data. This issue is aggravated by the high cost of conventional data collection and data processing methods and by the lack of geospatial data collection policies. This study proposes an inexpensive approach that enables real-time field data observation and geospatial data generation from video streams connected to a laptop and positioning sensors using deep learning technology. This proposed method was evaluated via an application called “DeepAutoMapping”, which was built on top of Python, then underwent through two different evaluation scenarios. The results demonstrated that the proposed approach is quick, easy to use and that it provides a high detection accuracy and an acceptable positioning accuracy in the outdoor environment. The proposed solution may also be considered as a pipeline for efficient and economical method of geospatial data collection and auto-map generation in the future.
Jalal Ibrahim Al-Azizi; Helmi Zulhaidi Mohd Shafri; Shaiful Jahari Bin Hashim; Shattri B. Mansor. DeepAutoMapping: low-cost and real-time geospatial map generation method using deep learning and video streams. Earth Science Informatics 2020, 1 -14.
AMA StyleJalal Ibrahim Al-Azizi, Helmi Zulhaidi Mohd Shafri, Shaiful Jahari Bin Hashim, Shattri B. Mansor. DeepAutoMapping: low-cost and real-time geospatial map generation method using deep learning and video streams. Earth Science Informatics. 2020; ():1-14.
Chicago/Turabian StyleJalal Ibrahim Al-Azizi; Helmi Zulhaidi Mohd Shafri; Shaiful Jahari Bin Hashim; Shattri B. Mansor. 2020. "DeepAutoMapping: low-cost and real-time geospatial map generation method using deep learning and video streams." Earth Science Informatics , no. : 1-14.
A single tree topology is a commonly employed topology for wireless sensor networks (WSN) to connect sensors to one or more remote gateways. However, its many-to-one traffic routing pattern imposes heavy burden on downstream nodes, as the same routes are repeatedly used for packet transfer, from one or more upstream branches. The challenge is how to choose the most optimal routing paths that minimizes energy consumption across the entire network. This paper proposes a proactive energy awareness-based many-to-one traffic routing scheme to alleviate the above said problem referred to as Energy Balance-Based Energy Hole Alleviation in tree topology (EBEHA-T). This protocol combines updated status of variations in energy consumption pattern around sink-hole zones and distribution of joint nodes among the trees. With this approach, EBEHA-T proactively prevents sink-hole formation instead of just a reactive response after they have occurred. Performance evaluation of EBEHA-T against benchmark method RaSMaLai shows increased energy saving across the entire network and a marked improvement in energy consumption balance in energy-hole zones. This precludes energy hole formation and the consequent network partitioning, leading to improved network lifetime beyond that of the RasMaLai. OMNET++ network simulation software has been used for the evaluation.
Mayada S. A. Mustafa; Borhanuddin M. Ali; Fadlee F. A. Rasid; Shaiful J. B. Hashim. A Proactive Energy-Awareness Based Traffic Routing in Tree Topology Wireless Sensor Networks Precluding Energy Holes Formation. 2020, 1 .
AMA StyleMayada S. A. Mustafa, Borhanuddin M. Ali, Fadlee F. A. Rasid, Shaiful J. B. Hashim. A Proactive Energy-Awareness Based Traffic Routing in Tree Topology Wireless Sensor Networks Precluding Energy Holes Formation. . 2020; ():1.
Chicago/Turabian StyleMayada S. A. Mustafa; Borhanuddin M. Ali; Fadlee F. A. Rasid; Shaiful J. B. Hashim. 2020. "A Proactive Energy-Awareness Based Traffic Routing in Tree Topology Wireless Sensor Networks Precluding Energy Holes Formation." , no. : 1.
Channel rendezvous is an initial and important process for establishing communications between secondary users (SUs) in distributed cognitive radio networks. Due to the drawbacks of the common control channel (CCC) based rendezvous approach, channel hopping (CH) has attracted a lot of research interests for achieving blind rendezvous. To ensure rendezvous within a finite time, most of the existing CH-based rendezvous schemes generate their CH sequences based on the whole global channel set in the network. However, due to the spatial and temporal variations in channel availabilities as well as the limitation of SUs sensing capabilities, the local available channel set (ACS) for each SU is usually a small subset of the global set. Therefore, following these global-based generated CH sequences can result in extensively long time-to-rendezvous (TTR) especially when the number of unavailable channels is large. In this paper, we propose two matrix-based CH rendezvous schemes in which the CH sequences are generated based on the ACSs only. We prove the guaranteed and full diversity rendezvous of the proposed schemes by deriving the theoretical upper bounds of their maximum TTRs. Furthermore, extensive simulation comparisons with other existing works are conducted which illustrate the superior performance of our schemes in terms of the TTR metrics.
Abdulmajid Al-Mqdashi; Aduwati Sali; Nor Kamariah Noordin; Shaiful J. Hashim; Rosdiadee Nordin. Efficient Matrix-Based Channel Hopping Schemes for Blind Rendezvous in Distributed Cognitive Radio Networks. Sensors 2018, 18, 4360 .
AMA StyleAbdulmajid Al-Mqdashi, Aduwati Sali, Nor Kamariah Noordin, Shaiful J. Hashim, Rosdiadee Nordin. Efficient Matrix-Based Channel Hopping Schemes for Blind Rendezvous in Distributed Cognitive Radio Networks. Sensors. 2018; 18 (12):4360.
Chicago/Turabian StyleAbdulmajid Al-Mqdashi; Aduwati Sali; Nor Kamariah Noordin; Shaiful J. Hashim; Rosdiadee Nordin. 2018. "Efficient Matrix-Based Channel Hopping Schemes for Blind Rendezvous in Distributed Cognitive Radio Networks." Sensors 18, no. 12: 4360.
Rendezvous is a prerequisite and important process for secondary users (SUs) to establish data communications in cognitive radio networks (CRNs). Recently, there has been a proliferation of different channel hopping- (CH-) based schemes that can provide rendezvous without relying on any predetermined common control channel. However, the existing CH schemes were designed with omnidirectional antennas which can degrade their rendezvous performance when applied in CRNs that are highly crowded with primary users (PUs). In such networks, the large number of PUs may lead to the inexistence of any common available channel between neighboring SUs which result in a failure of their rendezvous process. In this paper, we consider the utilization of directional antennas in CRNs for tackling the issue. Firstly, we propose two coprimality-based sector hopping (SH) schemes that can provide efficient pairwise sector rendezvous in directional antenna CRNs (DIR-CRNs). Then, we propose an efficient CH scheme that can be combined within the SH schemes for providing a simultaneous sector and channel rendezvous. The guaranteed rendezvous of our schemes are proven by deriving the theoretical upper bounds of their rendezvous delay metrics. Furthermore, extensive simulation comparisons with other related rendezvous schemes are conducted to illustrate the significant outperformance of our schemes.
Abdulmajid M. Al-Mqdashi; A. Sali; Nor K. Noordin; Shaiful J. Hashim; Rosdiadee Nordin. Combined Sector and Channel Hopping Schemes for Efficient Rendezvous in Directional Antenna Cognitive Radio Networks. Wireless Communications and Mobile Computing 2017, 2017, 1 -19.
AMA StyleAbdulmajid M. Al-Mqdashi, A. Sali, Nor K. Noordin, Shaiful J. Hashim, Rosdiadee Nordin. Combined Sector and Channel Hopping Schemes for Efficient Rendezvous in Directional Antenna Cognitive Radio Networks. Wireless Communications and Mobile Computing. 2017; 2017 ():1-19.
Chicago/Turabian StyleAbdulmajid M. Al-Mqdashi; A. Sali; Nor K. Noordin; Shaiful J. Hashim; Rosdiadee Nordin. 2017. "Combined Sector and Channel Hopping Schemes for Efficient Rendezvous in Directional Antenna Cognitive Radio Networks." Wireless Communications and Mobile Computing 2017, no. : 1-19.
The non-stationary and multi-frequency nature of biomedical signal activities makes the use of time-frequency distributions (TFDs) for analysis inevitable. Time-frequency analysis provides simultaneous interpretations in both time and frequency domain enabling comprehensive explanation, presentation and interpretation of electrocardiogram (ECG) signals. The diversity of TFDs and specific properties for each type show the need to determine the best TFD for ECG analysis. In this study, a performance evaluation of five TFDs in term of ECG abnormality detection is presented. The detection criteria based on extracted features from most important ECG signal components (QRS) to detect normal and abnormal cases. This is achieved by estimating its energy concentration magnitude using the TFDs. The TFDs analyse ECG signals in one-minute interval instead of conventional time domain approach that analyses based on beat or frame containing several beats. The MIT-BIH normal sinus rhythm ECG database total records of 18 long-term ECG sampled at 128 Hz have been analysed. The tested TFDs include Dual-Tree Wavelet Transform, Spectrogram, Pseudo Wigner-Ville, Choi-Williams, and Born-Jordan. Each record is divided into one-minute slots, which is not considered previously, and analysed. The sample periods (slots) are randomly selected ten minutes interval for each record. This result with 99.44% detection accuracy for 15,735 ECG beats shows that Choi-Williams distribution is most reliable to be used for heart problem detection especially in automated systems that provide continuous monitoring for long time duration.
Ahmed Faeq Hussein; Shaiful Jahari Hashim; Ahmad Fazli Abdul Aziz; Fakhrul Zaman Rokhani; Wan Azizun Wan Adnan. Performance Evaluation of Time-Frequency Distributions for ECG Signal Analysis. Journal of Medical Systems 2017, 42, 15 -15.
AMA StyleAhmed Faeq Hussein, Shaiful Jahari Hashim, Ahmad Fazli Abdul Aziz, Fakhrul Zaman Rokhani, Wan Azizun Wan Adnan. Performance Evaluation of Time-Frequency Distributions for ECG Signal Analysis. Journal of Medical Systems. 2017; 42 (1):15-15.
Chicago/Turabian StyleAhmed Faeq Hussein; Shaiful Jahari Hashim; Ahmad Fazli Abdul Aziz; Fakhrul Zaman Rokhani; Wan Azizun Wan Adnan. 2017. "Performance Evaluation of Time-Frequency Distributions for ECG Signal Analysis." Journal of Medical Systems 42, no. 1: 15-15.
Wearable wireless medical devices have the ability to significantly improve medical care eco-system. Collecting detailed real-time bio-signals data can be straightforward and flexible by equipping patients with wearable devices. The bio-signal sending data through wireless connections which harvest most system power consumption represent one of the main challenges due to battery power limitation. Therefore, reducing the power consumption during wireless data transmitting leads to reduce size and weight of the device which make the patient comfortable especially in long-term medical monitoring. In this study, we present a system level compression scheme for enhancing real-time Bluetooth Low Energy (BLE) Electrocardiogram (ECG) monitoring and recording system. The system is designed and implemented for ECG data capturing and sending it at reduced power transmitting by employing discrete cosine transform (DCT) supported by threshold capability. It is supported by a state-of-the-art system-on-chip (SoC) BLE module as well as the ECG amplifier modules for the amplification process to achieve 6-channel ECG real-time bio-signal which is essential for more accurate and comprehensive diagnosis. A 3-volt Lithium coin cell battery is used to supply the proposed wearable system. The total current consumed by this prototype is further reduced from 2.1 mA (without applying compression algorithm) to 1.5 mA (with enhanced compression algorithm), that leads to extending battery life by 40% from 100 to 140 h. Due to its compact design and an extended period working time, this prototype provides a suitable low-cost solution for long-term monitoring approach in clinical as well as home telemedicine application. The prototype was tested to record various ECG signals for both normal persons and patients. Specifically, it has been tested to capture ten normal cases and 24 arrhythmia and ischemic heart disease in a clinical environment within a specialist heart hospital with satisfactory results.
Ahmed Faeq Hussein; Shaiful Jahari Hashim; Ahmad Fazli Abdul Aziz; Fakhrul Zaman Rokhani; Wan Azizun Wan Adnan. A real time ECG data compression scheme for enhanced bluetooth low energy ECG system power consumption. Journal of Ambient Intelligence and Humanized Computing 2017, 1 -14.
AMA StyleAhmed Faeq Hussein, Shaiful Jahari Hashim, Ahmad Fazli Abdul Aziz, Fakhrul Zaman Rokhani, Wan Azizun Wan Adnan. A real time ECG data compression scheme for enhanced bluetooth low energy ECG system power consumption. Journal of Ambient Intelligence and Humanized Computing. 2017; ():1-14.
Chicago/Turabian StyleAhmed Faeq Hussein; Shaiful Jahari Hashim; Ahmad Fazli Abdul Aziz; Fakhrul Zaman Rokhani; Wan Azizun Wan Adnan. 2017. "A real time ECG data compression scheme for enhanced bluetooth low energy ECG system power consumption." Journal of Ambient Intelligence and Humanized Computing , no. : 1-14.
A low-complexity peak-to-average power ratio (PAPR) reduction scheme in an orthogonal frequency division multiplexing system is proposed. The proposed scheme utilizes a new phase sequence based on a gray code structure and a similarity measurement block. Due to the ordered phase sequences, a noteworthy reduction capacity is obtained in terms of the number of multiplication and addition operations and the side information. Simulations are performed with quadrature phase shift keying modulation and a Saleh model power amplifier. The proposed scheme offers a significant PAPR reduction and bit error rate performance at approximately the same total complexity compared to the conventional partial transmit sequence and the enhanced partial transmit sequence (EPTS) techniques. The results show that at the same PAPR reduction, this scheme provides a complexity reduction of at least 42.3 % over that of the EPTS technique.
Mohsen Kazemian; Pooria Varahram; Shaiful Jahari Bin Hashim; Borhanuddin Mohd Ali; Ronan Farrell. A Low Complexity Peak-to-Average Power Ratio Reduction Scheme Using Gray Codes. Wireless Personal Communications 2015, 88, 223 -239.
AMA StyleMohsen Kazemian, Pooria Varahram, Shaiful Jahari Bin Hashim, Borhanuddin Mohd Ali, Ronan Farrell. A Low Complexity Peak-to-Average Power Ratio Reduction Scheme Using Gray Codes. Wireless Personal Communications. 2015; 88 (2):223-239.
Chicago/Turabian StyleMohsen Kazemian; Pooria Varahram; Shaiful Jahari Bin Hashim; Borhanuddin Mohd Ali; Ronan Farrell. 2015. "A Low Complexity Peak-to-Average Power Ratio Reduction Scheme Using Gray Codes." Wireless Personal Communications 88, no. 2: 223-239.