Showing items 1 - 20 of 193

Your selections:

A critical review of intrusion detection systems in the internet of things : techniques, deployment strategy, validation strategy, attacks, public datasets and challenges

- Khraisat, Ansam, Alazab, Ammar

  • Authors: Khraisat, Ansam , Alazab, Ammar
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Cybersecurity Vol. 4, no. 1 (2021), p.
  • Full Text:
  • Reviewed:
  • Description: The Internet of Things (IoT) has been rapidly evolving towards making a greater impact on everyday life to large industrial systems. Unfortunately, this has attracted the attention of cybercriminals who made IoT a target of malicious activities, opening the door to a possible attack on the end nodes. To this end, Numerous IoT intrusion detection Systems (IDS) have been proposed in the literature to tackle attacks on the IoT ecosystem, which can be broadly classified based on detection technique, validation strategy, and deployment strategy. This survey paper presents a comprehensive review of contemporary IoT IDS and an overview of techniques, deployment Strategy, validation strategy and datasets that are commonly applied for building IDS. We also review how existing IoT IDS detect intrusive attacks and secure communications on the IoT. It also presents the classification of IoT attacks and discusses future research challenges to counter such IoT attacks to make IoT more secure. These purposes help IoT security researchers by uniting, contrasting, and compiling scattered research efforts. Consequently, we provide a unique IoT IDS taxonomy, which sheds light on IoT IDS techniques, their advantages and disadvantages, IoT attacks that exploit IoT communication systems, corresponding advanced IDS and detection capabilities to detect IoT attacks. © 2021, The Author(s).

A new global index for short term voltage stability assessment

- Alshareef, Abdulrhman, Shah, Rakibuzzaman, Mithulananthan, Nadarajah, Alzahrani, Saeed

  • Authors: Alshareef, Abdulrhman , Shah, Rakibuzzaman , Mithulananthan, Nadarajah , Alzahrani, Saeed
  • Date: 2021
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 9, no. (2021), p. 36114-36124
  • Full Text:
  • Reviewed:
  • Description: The utility scale of non-conventional generators (NCGs), such as wind and photovoltaic (PV) plants, are competitive alternatives to synchronous machines (SMs) for power generation. Higher penetration of NCGs has been respondent of causing several recent incidents leading up to voltage collapse in power systems due to the distinct characteristics of NCGs under different operating conditions. Consequently, the so-called system strength has been reduced with higher NCGs penetration. A number of indices have been developed to quantify system strength from the short-term voltage stability (STVS) perspective. None of the indices capture the overall performances of power systems on dynamic voltage recovery. In this paper, an improvement in one of the STVS indices namely, the Voltage Recovery Index (VRI), is proposed to overcome shortcomings in the original index. Moreover, the improved index is globalized to establish a new index defined as system voltage recovery index (VRIsys) to quantify STVS at the system level. The amended VRI and developed VRIsys are used in systematic simulations to quantify the impact and interaction of various factors that could affect system strength. The assessment was conducted using time-domain simulation with direct connected induction motors (DCIMs) and a proliferation of converter-based technologies on both the generation and load sides, namely, NCGs and Variable Speed Drives (VSDs), respectively. © 2013 IEEE.

A scalable framework for healthcare monitoring application using the Internet of Medical Things

- Balasubramanian, Venki, Jolfaei, Alireza

  • Authors: Balasubramanian, Venki , Jolfaei, Alireza
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Software - Practice and Experience Vol. 51, no. 12 (2021), p. 2457-2468
  • Full Text: false
  • Reviewed:
  • Description: Internet of Things (IoT) is finding application in many areas, particularly in health care where an IoT can be effectively used in the form of an Internet of Medical Things (IoMT) to monitor the patients remotely. The quality of life of the patients and health care outcomes can be improved with the deployment of an IoMT because health care professionals can monitor conditions; access the electronic medical records and communicates with each other. This remote monitoring and consultations might reduce the traditional stressful and costly exercise of frequent hospitalization. Also, the rising costs of health care in many developed countries have influenced the introduction of the Healthcare Monitoring Application (HMA) to their existing health care practices. To materialize the HMA concepts for successful deployment for civilian and commercial use with ease, application developers can benefit from a generic, scalable framework that provides significant components for building an HMA. In this chapter, a generic maintainable HMA is advanced by amalgamating the advantages of event-driven and the layered architecture. The proposed framework is used to establish an HMA with an end-to-end Assistive Care Loop Framework (ACLF) to provide a real-time alarm and assistance to monitor pregnant women. © 2020 John Wiley & Sons, Ltd.

A unified model predictive voltage and current control for microgrids with distributed fuzzy cooperative secondary control

- Shan, Yinghao, Hu, Jiefeng, Chan, Ka, Islam, Syed

  • Authors: Shan, Yinghao , Hu, Jiefeng , Chan, Ka , Islam, Syed
  • Date: 2021
  • Type: Text , Journal article
  • Relation: IEEE Transactions on Industrial Informatics Vol. 17, no. 12 (DEC 2021), p. 8024-8034
  • Full Text: false
  • Reviewed:
  • Description: A microgrid formed by a cluster of parallel distributed generation (DG) units is capable of operating in either islanded mode or grid-connected mode. Traditionally, by using model predictive control algorithms, these two operation modes can be achieved with two separate and different cost functions, which brings in control complexity and hence, compromises system reliability. In this article, a unified model predictive voltage and current control strategy is proposed for both islanded and grid-connected operations and their smooth transition. The cost function is kept unified with voltage and current taken into account without altering the control architecture. It can be used for high-quality voltage supply at the primary control level and for bidirectional power flow at the tertiary control level. In addition, by only using DGs' own and neighboring information, a distributed fuzzy cooperative algorithm is developed at the secondary layer to mitigate the voltage and frequency deviations inherent from the power droop. The fuzzy controller can optimize the secondary control coefficients for further voltage quality improvement. Comprehensive tests under various scenarios demonstrate the merits of the proposed control strategy over traditional methods.

Adaptive droop control using adaptive virtual impedance for microgrids with variable PV outputs and load demands

- Li, Zilin, Chan, Ka, Hu, Jiefeng, Guerrero, Josep

  • Authors: Li, Zilin , Chan, Ka , Hu, Jiefeng , Guerrero, Josep
  • Date: 2021
  • Type: Text , Journal article
  • Relation: IEEE Transactions on Industrial Electronics Vol. 68, no. 10 (2021), p. 9630-9640
  • Full Text: false
  • Reviewed:
  • Description: In microgrids, intermittency of renewable energy sources (RES) and uncertain state-of-charge (SoC) of energy storage systems (ESS) can cause power deficiency to some distributed generation units (DGs). In this case, DGs with power deficiency may not meet the power demand, resulting in voltage collapse or frequency divergence. Unfortunately, this is seldom considered in inverter control design in existing literature. Thus, in-depth investigation into the microgrid performance under renewable energy resource fluctuations and appropriate control methods are urgently needed. In this article, an adaptive droop and adaptive virtual impedance control strategy is proposed. Unlike conventional droop control where the droop coefficients are fixed by assuming the DGs can always meet the load demand, the droop coefficients here are adjusted according to actual solar PV power output. In this way, proper power sharing among DGs can be achieved under renewable energy variation. Furthermore, the impact of varying DG capacities on system stability is mathematically investigated. An adaptive virtual impedance is then incorporated into the adaptive droop method to deal with the system instability caused by renewable energy variations. The proposed strategy is analyzed theoretically and validated in MATLAB/Simulink simulation and laboratory experiments. The results demonstrate the advantages of the proposed method over conventional approaches under various scenarios. © 1982-2012 IEEE.

Adversarial network with multiple classifiers for open set domain adaptation

- Shermin, Tasfia, Lu, Guojun, Teng, Shyh, Murshed, Manzur, Sohel, Ferdous

  • Authors: Shermin, Tasfia , Lu, Guojun , Teng, Shyh , Murshed, Manzur , Sohel, Ferdous
  • Date: 2021
  • Type: Text , Journal article
  • Relation: IEEE Transactions on Multimedia Vol. 23, no. (2021), p. 2732-2744
  • Full Text:
  • Reviewed:
  • Description: Domain adaptation aims to transfer knowledge from a domain with adequate labeled samples to a domain with scarce labeled samples. Prior research has introduced various open set domain adaptation settings in the literature to extend the applications of domain adaptation methods in real-world scenarios. This paper focuses on the type of open set domain adaptation setting where the target domain has both private ('unknown classes') label space and the shared ('known classes') label space. However, the source domain only has the 'known classes' label space. Prevalent distribution-matching domain adaptation methods are inadequate in such a setting that demands adaptation from a smaller source domain to a larger and diverse target domain with more classes. For addressing this specific open set domain adaptation setting, prior research introduces a domain adversarial model that uses a fixed threshold for distinguishing known from unknown target samples and lacks at handling negative transfers. We extend their adversarial model and propose a novel adversarial domain adaptation model with multiple auxiliary classifiers. The proposed multi-classifier structure introduces a weighting module that evaluates distinctive domain characteristics for assigning the target samples with weights which are more representative to whether they are likely to belong to the known and unknown classes to encourage positive transfers during adversarial training and simultaneously reduces the domain gap between the shared classes of the source and target domains. A thorough experimental investigation shows that our proposed method outperforms existing domain adaptation methods on a number of domain adaptation datasets. © 1999-2012 IEEE.

AI and IoT-Enabled smart exoskeleton system for rehabilitation of paralyzed people in connected communities

- Jacob, Sunil, Alagirisamy, Mukil, Xi, Chen, Balasubramanian, Venki, Srinivasan, Ram

  • Authors: Jacob, Sunil , Alagirisamy, Mukil , Xi, Chen , Balasubramanian, Venki , Srinivasan, Ram
  • Date: 2021
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 9, no. (2021), p. 80340-80350
  • Full Text:
  • Reviewed:
  • Description: In recent years, the number of cases of spinal cord injuries, stroke and other nervous impairments have led to an increase in the number of paralyzed patients worldwide. Rehabilitation that can aid and enhance the lives of such patients is the need of the hour. Exoskeletons have been found as one of the popular means of rehabilitation. The existing exoskeletons use techniques that impose limitations on adaptability, instant response and continuous control. Also most of them are expensive, bulky, and requires high level of training. To overcome all the above limitations, this paper introduces an Artificial Intelligence (AI) powered Smart and light weight Exoskeleton System (AI-IoT-SES) which receives data from various sensors, classifies them intelligently and generates the desired commands via Internet of Things (IoT) for rendering rehabilitation and support with the help of caretakers for paralyzed patients in smart and connected communities. In the proposed system, the signals collected from the exoskeleton sensors are processed using AI-assisted navigation module, and helps the caretakers in guiding, communicating and controlling the movements of the exoskeleton integrated to the patients. The navigation module uses AI and IoT enabled Simultaneous Localization and Mapping (SLAM). The casualties of a paralyzed person are reduced by commissioning the IoT platform to exchange data from the intelligent sensors with the remote location of the caretaker to monitor the real time movement and navigation of the exoskeleton. The automated exoskeleton detects and take decisions on navigation thereby improving the life conditions of such patients. The experimental results simulated using MATLAB shows that the proposed system is the ideal method for rendering rehabilitation and support for paralyzed patients in smart communities. © 2013 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Venki Balasubramanian” is provided in this record**

An efficient force-feedback hand exoskeleton for haptic applications

- Le, Duy, Nguyen, Linh

  • Authors: Le, Duy , Nguyen, Linh
  • Date: 2021
  • Type: Text , Journal article
  • Relation: International Journal of Intelligent Robotics and Applications Vol. 5, no. 3 (2021), p. 395-409
  • Full Text: false
  • Reviewed:
  • Description: In this paper, a study on wearable exoskeleton devices which are capable of delivering sensation to the fingers while interacting with the virtual objects in virtual reality environment has been conducted. A force-controllable hand exoskeleton system is proposed, which is able to apply force feedback to the fingertip while allowing natural finger motions. The linkage structure was inspired by the skeletal structure of a human finger. Moreover, a series elastic actuator (SEA) mechanism, which consisted of a linear motor, a spring and a potentiometer, was presented as an actuating system. The force transmission through linkage has been investigated to ensure the force feedback ability at the fingertip. By using a PID controller, the proposed actuator module could generate the desired force in two different modes: free mode and interaction mode. The experimental results show that the proposed system could effectively deliver forces to the fingertips. © 2021, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

An efficient hybrid system for anomaly detection in social networks

- Rahman, Md Shafiur, Halder, Sajal, Uddin, Ashraf, Acharjee, Uzzal

  • Authors: Rahman, Md Shafiur , Halder, Sajal , Uddin, Ashraf , Acharjee, Uzzal
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Cybersecurity Vol. 4, no. 1 (2021), p.
  • Full Text:
  • Reviewed:
  • Description: Anomaly detection has been an essential and dynamic research area in the data mining. A wide range of applications including different social medias have adopted different state-of-the-art methods to identify anomaly for ensuring user’s security and privacy. The social network refers to a forum used by different groups of people to express their thoughts, communicate with each other, and share the content needed. This social networks also facilitate abnormal activities, spread fake news, rumours, misinformation, unsolicited messages, and propaganda post malicious links. Therefore, detection of abnormalities is one of the important data analysis activities for the identification of normal or abnormal users on the social networks. In this paper, we have developed a hybrid anomaly detection method named DT-SVMNB that cascades several machine learning algorithms including decision tree (C5.0), Support Vector Machine (SVM) and Naïve Bayesian classifier (NBC) for classifying normal and abnormal users in social networks. We have extracted a list of unique features derived from users’ profile and contents. Using two kinds of dataset with the selected features, the proposed machine learning model called DT-SVMNB is trained. Our model classifies users as depressed one or suicidal one in the social network. We have conducted an experiment of our model using synthetic and real datasets from social network. The performance analysis demonstrates around 98% accuracy which proves the effectiveness and efficiency of our proposed system. © 2021, The Author(s).

An improved memetic approach for protein structure prediction incorporating maximal hydrophobic core estimation concept

- Nazmul, Rumana, Chetty, Madhu, Chowdhury, Ahsan

  • Authors: Nazmul, Rumana , Chetty, Madhu , Chowdhury, Ahsan
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Knowledge-Based Systems Vol. 219, no. (2021), p. 104395
  • Full Text: false
  • Reviewed:
  • Description: Protein Structure Prediction (PSP) from the primary amino acid sequence, even using a simplified Hydrophobic-Polar (HP) lattice model, continues to be extremely challenging. Finding an optimal conformation, even for a small sequence, by any of the currently known evolutionary approaches is computationally extensive and time consuming. Although Memetic Algorithms (MAs) have shown success in finding the optimal solution for PSP, no significant work on the incorporation of domain or problem specific knowledge into the search process to significantly improve their performance is reported. In this paper, we present an approach to incorporate such knowledge into the initial population to enhance the effectiveness of MA for PSP. The domain knowledge we propose to use is based on the concept of maximal ‘core’ formation by exploiting the fundamental property of the H residues to be at the core of the minimum energy optimal protein structure. A generic technique is proposed for estimating the maximal Hydrophobic core (H-core) in a protein sequence for 2D Square, 3D Cubic and a more complex and realistic 3D FCC (Face Centered Cubic) lattice models. Subsequently, the knowledge of this estimated core is incorporated in an MA. The experiments conducted using HP benchmark sequences for 2D Square, 3D Cubic and 3D FCC lattice models show that the proposed MA with the new core-based population initialization technique has superior performance to the existing methods in terms of convergence speed as well as minimal energy. © 2018 Elsevier B.V.

Application of adaptive phase-field scaled boundary finite element method for functionally graded materials

- Pramod, Aladurthi, Hirshikesh, Natarajan, Sundararajan, Ooi, Ean Tat

  • Authors: Pramod, Aladurthi , Hirshikesh , Natarajan, Sundararajan , Ooi, Ean Tat
  • Date: 2021
  • Type: Text , Journal article
  • Relation: International Journal of Computational Methods Vol. 18, no. 3 (2021), p.
  • Full Text: false
  • Reviewed:
  • Description: In this paper, an adaptive phase-field scaled boundary finite element method for fracture in functionally graded material (FGM) is presented. The model accounts for spatial variation in the material and fracture properties. The quadtree decomposition is adopted for refinement, and the refinement is based on an error indicator evaluated directly from the solutions of the scaled boundary finite element method. This combination makes it a suitable choice to study fracture using the phase field method, as it reduces the mesh burden. A few standard benchmark numerical examples are solved to demonstrate the improvement in computational efficiency in terms of the number of degrees of freedom. © 2021 World Scientific Publishing Company.

Big data and predictive analytics in healthcare in Bangladesh: regulatory challenges

- Hassan, Shafiqul, Dhali, Mohsin, Zaman, Fazluz, Tanveer, Muhammad

  • Authors: Hassan, Shafiqul , Dhali, Mohsin , Zaman, Fazluz , Tanveer, Muhammad
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Vol. 7, no. 6 (2021), p.
  • Full Text:
  • Reviewed:
  • Description: Big data analytics and artificial intelligence are revolutionizing the global healthcare industry. As the world accumulates unfathomable volumes of data and health technology grows more and more critical to the advancement of medicine, policymakers and regulators are faced with tough challenges around data security and data privacy. This paper reviews existing regulatory frameworks for artificial intelligence-based medical devices and health data privacy in Bangladesh. The study is legal research employing a comparative approach where data is collected from primary and secondary legal materials and filtered based on policies relating to medical data privacy and medical device regulation of Bangladesh. Such policies are then compared with benchmark policies of the European Union and the USA to test the adequacy of the present regulatory framework of Bangladesh and identify the gaps in the current regulation. The study highlights the gaps in policy and regulation in Bangladesh that are hampering the widespread adoption of big data analytics and artificial intelligence in the industry. Despite the vast benefits that big data would bring to Bangladesh's healthcare industry, it lacks the proper data governance and legal framework necessary to gain consumer trust and move forward. Policymakers and regulators must work collaboratively with clinicians, patients and industry to adopt a new regulatory framework that harnesses the potential of big data but ensures adequate privacy and security of personal data. The article opens valuable insight to regulators, academicians, researchers and legal practitioners regarding the present regulatory loopholes in Bangladesh involving exploiting the promise of big data in the medical field. The study concludes with the recommendation for future research into the area of privacy as it relates to artificial intelligence-based medical devices should consult the patients' perspective by employing quantitative analysis research methodology. © 2021 The Author(s)

Bipolar radiofrequency ablation treatment of liver cancer employing monopolar needles : a comprehensive investigation on the efficacy of time-based switching

- Yap, Shelley, Ooi, Ean, Foo, Ji, Ooi, Ean Tat

  • Authors: Yap, Shelley , Ooi, Ean , Foo, Ji , Ooi, Ean Tat
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Computers in Biology and Medicine Vol. 131, no. (2021), p.
  • Full Text: false
  • Reviewed:
  • Description: Radiofrequency ablation (RFA) is a thermal ablative treatment method that is commonly used to treat liver cancer. However, the thermal coagulation zone generated using the conventional RFA system can only successfully treat tumours up to 3 cm in diameter. Switching bipolar RFA has been proposed as a way to increase the thermal coagulation zone. Presently, the understanding of the underlying thermal processes that takes place during switching bipolar RFA remains limited. Hence, the objective of this study is to provide a comprehensive understanding on the thermal ablative effects of time-based switching bipolar RFA on liver tissue. Five switch intervals, namely 50, 100, 150, 200 and 300 s were investigated using a two-compartment 3D finite element model. The study was performed using two pairs of RF electrodes in a four-probe configuration, where the electrodes were alternated based on their respective switch interval. The physics employed in the present study were verified against experimental data from the literature. Results obtained show that using a shorter switch interval can improve the homogeneity of temperature distribution within the tissue and increase the rate of temperature rise by delaying the occurrence of roll-off. The coagulation volume obtained was the largest using switch interval of 50 s, followed by 100, 150, 200 and 300 s. The present study demonstrated that the transient thermal response of switching bipolar RFA can be improved by using shorter switch intervals. © 2021 Elsevier Ltd

Canonical duality theory and algorithm for solving bilevel knapsack problems with applications

- Gao, David

  • Authors: Gao, David
  • Date: 2021
  • Type: Text , Journal article
  • Relation: IEEE Transactions on Systems, Man, and Cybernetics: Systems Vol. 51, no. 2 (2021), p. 893-904
  • Full Text:
  • Reviewed:
  • Description: A novel canonical duality theory (CDT) is presented for solving general bilevel mixed integer nonlinear optimization governed by linear and quadratic knapsack problems. It shows that the challenging knapsack problems can be solved analytically in term of their canonical dual solutions. The existence and uniqueness of these analytical solutions are proved. NP-hardness of the knapsack problems is discussed. A powerful CDT algorithm combined with an alternative iteration and a volume reduction method is proposed for solving the NP-hard bilevel knapsack problems. Application is illustrated by benchmark problems in optimal topology design. The performance and novelty of the proposed method are compared with the popular commercial codes. © 2013 IEEE.

Comparisons between impedance-based and time-based switching bipolar radiofrequency ablation for the treatment of liver cancer

- Yap, Shelley, Ooi, Ean, Foo, Ji, Ooi, Ean Tat

  • Authors: Yap, Shelley , Ooi, Ean , Foo, Ji , Ooi, Ean Tat
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Computers in Biology and Medicine Vol. 134, no. (2021), p.
  • Full Text: false
  • Reviewed:
  • Description: Switching bipolar radiofrequency ablation (bRFA) is a cancer treatment technique that activates multiple pairs of electrodes alternately based on a predefined criterion. Various criteria can be used to trigger the switch, such as time (ablation duration) and tissue impedance. In a recent study on time-based switching bRFA, it was determined that a shorter switch interval could produce better treatment outcome than when a longer switch interval was used, which reduces tissue charring and roll-off induced cooling. In this study, it was hypothesized that a more efficacious bRFA treatment can be attained by employing impedance-based switching. This is because ablation per pair can be maximized since there will be no interruption to RF energy delivery until roll-off occurs. This was investigated using a two-compartment 3D computational model. Results showed that impedance-based switching bRFA outperformed time-based switching when the switch interval of the latter is 100 s or higher. When compared to the time-based switching with switch interval of 50 s, the impedance-based model is inferior. It remains to be investigated whether the impedance-based protocol is better than the time-based protocol for a switch interval of 50 s due to the inverse relationship between ablation and treatment efficacies. It was suggested that the choice of impedance-based or time-based switching could ultimately be patient-dependent. © 2021 Elsevier Ltd

Efficient high-resolution video compression scheme using background and foreground layers

- Afsana, Fariha, Paul, Manoranjan, Murshed, Manzur, Taubman, David

  • Authors: Afsana, Fariha , Paul, Manoranjan , Murshed, Manzur , Taubman, David
  • Date: 2021
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 9, no. (2021), p. 157411-157421
  • Full Text:
  • Reviewed:
  • Description: Video coding using dynamic background frame achieves better compression compared to the traditional techniques by encoding background and foreground separately. This process reduces coding bits for the overall frame significantly; however, encoding background still requires many bits that can be compressed further for achieving better coding efficiency. The cuboid coding framework has been proven to be one of the most effective methods of image compression which exploits homogeneous pixel correlation within a frame and has better alignment with object boundary compared to traditional block-based coding. In a video sequence, the cuboid-based frame partitioning varies with the changes of the foreground. However, since the background remains static for a group of pictures, the cuboid coding exploits better spatial pixel homogeneity. In this work, the impact of cuboid coding on the background frame for high-resolution videos (Ultra-High-Definition (UHD) and 360-degree videos) is investigated using the multilayer framework of SHVC. After the cuboid partitioning, the method of coarse frame generation has been improved with a novel idea by keeping human-visual sensitive information. Unlike the traditional SHVC scheme, in the proposed method, cuboid coded background and the foreground are encoded in separate layers in an implicit manner. Simulation results show that the proposed video coding method achieves an average BD-Rate reduction of 26.69% and BD-PSNR gain of 1.51 dB against SHVC with significant encoding time reduction for both UHD and 360 videos. It also achieves an average of 13.88% BD-Rate reduction and 0.78 dB BD-PSNR gain compared to the existing relevant method proposed by X. Hoang Van. © 2013 IEEE.

Examination of effective VAr with respect to dynamic voltage stability in renewable rich power grids

- Alzahrani, Saeed, Shah, Rakibuzzaman, Mithulananthan, N.

  • Authors: Alzahrani, Saeed , Shah, Rakibuzzaman , Mithulananthan, N.
  • Date: 2021
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 9, no. (2021), p. 75494-75508
  • Full Text:
  • Reviewed:
  • Description: High penetrations of inverter-based renewable resources (IBRs) diminish the resilience that traditional power systems had due to constant research and developments for many years. In particular, dynamic voltage stability becomes one of the major concerns for transmission system operators due to the limited capabilities of IBRs (i.e., voltage and frequency regulation). A heavily loaded renewable-rich network is susceptible to fault-induced delayed voltage recovery (FIDVR) due to insufficient effective reactive power (E-VAr) in power grids. Hence, it is crucial to thoroughly scrutinize each VAr resources' participation in E-VAr under various operating conditions. Moreover, it is essential to investigate the influence of E-VAr on system post-fault performance. The E-VAr investigation would help in determining the optimal location and sizing of grid-connected IBRs and allow more renewable energy integration. Furthermore, it would enrich decision-making about adopting additional grid support devices. In this paper, a comprehensive assessment framework is utilized to assess the E-VAr of a power system with a large-scale photovoltaic power. Plant under different realistic operating conditions. Several indices quantifying the contribution of VAr resources and load bus voltage recovery assists to explore the transient response and voltage trajectories. The recovery indices help have a better understanding of the factors affecting E-VAr. The proposed framework has been tested in the New England (IEEE 39 bus system) through simulation by DIgSILENT Power Factory. © 2013 IEEE.

Forced oscillation in power systems with converter controlled-based resources- a survey with case studies

- Surinkaew, Tossaporn, Emami, Koanoush, Shah, Rakibuzzaman, Islam, Syed, Mithulananthan, N.

  • Authors: Surinkaew, Tossaporn , Emami, Koanoush , Shah, Rakibuzzaman , Islam, Syed , Mithulananthan, N.
  • Date: 2021
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 9, no. (2021), p. 150911-150924
  • Full Text:
  • Reviewed:
  • Description: In future power systems, conventional synchronous generators will be replaced by converter controlled-based generations (CCGs), i.e., wind and solar generations, and battery energy storage systems. Thus, the paradigm shift in power systems will lead to the inferior system strength and inertia scarcity. Therefore, the problems of forced oscillation (FO) will emerge with new features of the CCGs. The state-of-the-art review in this paper emphasizes previous strategies for FO detection, source identification, and mitigation. Moreover, the effect of FO is investigated in a power system with CCGs. In its conclusion, this paper also highlights important findings and provides suggestions for subsequent research in this important topic of future power systems. © 2013 IEEE.

Fuzzy logic and gradient descent-based optimal adaptive robust controller with inverted pendulum verification

- Hadipour Lakmesari, S., Mahmoodabadi, M., Ibrahim, Yousef

  • Authors: Hadipour Lakmesari, S. , Mahmoodabadi, M. , Ibrahim, Yousef
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Chaos, Solitons and Fractals Vol. 151, no. (2021), p.
  • Full Text: false
  • Reviewed:
  • Description: This paper develops an adaptive robust combination of feedback linearization (FL) and sliding mode controller (SMC) based on fuzzy rules and gradient descent laws. The new suggested control algorithm is tested to stabilize a fourth-order under-actuated nonlinear inverted pendulum system. More precisely, the reliable feedback linearization approach and the robust SMC controller are combined to design a stable control effort. In order to enhance the performance of the suggested controller, an adaptation technique as long as fuzzy rules are applied to update the control gains and the boundary layer parameter. Then, a novel evolutionary algorithm termed multi-objective ant lion optimizer (MOALO) is implemented to determine the control coefficients. The analysis and results conducted on the inverted pendulum system demonstrate the desired performance of the proposed control scheme by providing an optimal smooth control input, suitable tracking performance, and proper time responses. © 2021 Elsevier Ltd

Green underwater wireless communications using hybrid optical-acoustic technologies

- Islam, Kazi, Ahmad, Iftekhar, Habibi, Daryoush, Zahed, M., Kamruzzaman, Joarder

  • Authors: Islam, Kazi , Ahmad, Iftekhar , Habibi, Daryoush , Zahed, M. , Kamruzzaman, Joarder
  • Date: 2021
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 9, no. (2021), p. 85109-85123
  • Full Text:
  • Reviewed:
  • Description: Underwater wireless communication is a rapidly growing field, especially with the recent emergence of technologies such as autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs). To support the high-bandwidth applications using these technologies, underwater optics has attracted significant attention, alongside its complementary technology - underwater acoustics. In this paper, we propose a hybrid opto-acoustic underwater wireless communication model that reduces network power consumption and supports high-data rate underwater applications by selecting appropriate communication links in response to varying traffic loads and dynamic weather conditions. Underwater optics offers high data rates and consumes less power. However, due to the severe absorption of light in the medium, the communication range is short in underwater optics. Conversely, acoustics suffers from low data rate and high power consumption, but provides longer communication ranges. Since most underwater equipment relies on battery power, energy-efficient communication is critical for reliable underwater communications. In this work, we derive analytical models for both underwater acoustics and optics, and calculate the required transmit power for reliable communications in various underwater communication environments. We then formulate an optimization problem that minimizes the network power consumption for carrying data from underwater nodes to surface sinks under varying traffic loads and weather conditions. The proposed optimization model can be solved offline periodically, hence the additional computational complexity to find the optimum solution for larger networks is not a limiting factor for practical applications. Our results indicate that the proposed technique yields up to 35% power savings compared to existing opto-acoustic solutions. © 2013 IEEE.