Artificial intelligence enabled digital twin for predictive maintenance in industrial automation system : a novel framework and case study
- Authors: Siddiqui, Mustafa , Kahandawa, Gayan , Hewawasam, Hasitha
- Date: 2023
- Type: Text , Conference paper
- Relation: 2023 IEEE International Conference on Mechatronics, ICM 2023, Leicestershire UK, 15-17 March 2023, Proceedings - 2023 IEEE International Conference on Mechatronics, ICM 2023
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- Description: Industrial automation systems are excessively used in advanced manufacturing environments. These systems are always prone to failure which not only disturbs smooth manufacturing operations but can also cause injuries to operators. Therefore, in this research, a novel predictive maintenance algorithm is proposed that can be used to detect anomalies in the automation system to avoid asset failure. Artificial Intelligence enabled Digital Twin model was used to detect early anomalies to avoid catastrophic effects of equipment failure. Real-time sensor data were used to validate the proposed novel algorithm. The data were recorded via sensors mounted on the physical system. This paper presents the effectiveness of the proposed algorithm to detect anomalies in industrial automation systems under faulty conditions. © 2023 IEEE.
Machine learning driven digital twin for industrial control black box system : a novel framework and case study
- Authors: Siddiqui, Mustafa , Kahandawa, Gayan , Hewawasam, Hasitha , Rehman Siddiqi, Muftooh
- Date: 2023
- Type: Text , Conference paper
- Relation: 28th International Conference on Automation and Computing, ICAC 2023, Birmingham, UK, 30 August-1 September 2023, ICAC 2023 The 28th International Conference on Automation and Computing Digitalisation for Smart Manufacturing and Systems
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- Description: Industrial control systems are excessively used in advanced manufacturing environments. The lack of information and data regarding the internal workings of certain systems makes virtual modelling for their Digital Twin challenging. As a result, these systems are often classified as 'black box' systems. There is minimal research found on DT models for industrial control black box systems. Therefore, a novel algorithm to model the Digital Twin of the industrial control black box system in the cyber domain has been presented in this paper. Machine Learning techniques were used to develop a high-fidelity Digital Twin model of a black box system. Real-time sensor data were recorded and used to validate the proposed novel algorithm. This paper presents the proposed algorithm's effectiveness in developing a robust Digital Twin model of industrial control back box system. © 2023 IEEE.
Machine learning-based agoraphilic navigation algorithm for use in dynamic environments with a moving goal
- Authors: Hewawasam, Hasitha , Kahandawa, Gayan , Ibrahim, Yousef
- Date: 2023
- Type: Text , Journal article
- Relation: Machines Vol. 11, no. 5 (2023), p. 513
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- Description: This paper presents a novel development of a new machine learning-based control system for the Agoraphilic (free-space attraction) concept of navigating robots in unknown dynamic environments with a moving goal. Furthermore, this paper presents a new methodology to generate training and testing datasets to develop a machine learning-based module to improve the performances of Agoraphilic algorithms. The new algorithm presented in this paper utilises the free-space attraction (Agoraphilic) concept to safely navigate a mobile robot in a dynamically cluttered environment with a moving goal. The algorithm uses tracking and prediction strategies to estimate the position and velocity vectors of detected moving obstacles and the goal. This predictive methodology enables the algorithm to identify and incorporate potential future growing free-space passages towards the moving goal. This is supported by the new machine learning-based controller designed specifically to efficiently account for the high uncertainties inherent in the robot’s operational environment with a moving goal at a reduced computational cost. This paper also includes comparative and experimental results to demonstrate the improvements of the algorithm after introducing the machine learning technique. The presented experiments demonstrated the success of the algorithm in navigating robots in dynamic environments with the challenge of a moving goal.
A novel optimistic local path planner : agoraphilic navigation algorithm in dynamic environment
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan
- Date: 2022
- Type: Text , Journal article
- Relation: Machines Vol. 10, no. 11 (2022), p.
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- Description: This paper presents a novel local path planning algorithm developed based on the new free space attraction (Agoraphilic) concept. The proposed algorithm is capable of navigating robots in unknown static, as well as dynamically cluttered environments. Unlike the other navigation algorithms, the proposed algorithm takes the optimistic approach of the navigation problem. It does not look for problems to avoid, but rather for solutions to follow. This human-like decision-making behaviour distinguishes the new algorithm from all the other navigation algorithms. Furthermore, the new algorithm utilises newly developed tracking and prediction algorithms, to safely navigate mobile robots. This is further supported by a fuzzy logic controller designed to efficiently account for the inherent high uncertainties in the robot’s operational environment at a reduced computational cost. This paper also includes physical experimental results combined with bench-marking against other recent methods. The reported results verify the algorithm’s successful advantages in navigating robots in both static and dynamic environments. © 2022 by the authors.
Agoraphilic navigation algorithm in dynamic environment with obstacles motion tracking and prediction
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer
- Date: 2022
- Type: Text , Journal article
- Relation: Robotica Vol. 40, no. 2 (2022), p. 329-347
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- Description: This paper presents a new algorithm to navigate robots in dynamically cluttered environments. The proposed algorithm uses basic concepts of space attraction (hence the term Agoraphilic) to navigate robots through dynamic obstacles. The new algorithm in this paper is an advanced development of the original Agoraphilic navigation algorithm that was only able to navigate robots in static environments. The Agoraphilic algorithm does not look for obstacles (problems) to avoid but rather for a free space (solutions) to follow. Therefore, it is also described as an optimistic navigation algorithm. This algorithm uses only one attractive force created by the available free space. The free-space concept allows the Agoraphilic algorithm to overcome inherited challenges of general navigation algorithms. However, the original Agoraphilic algorithm has the limitation in navigating robots only in static, not in dynamic environments. The presented algorithm was developed to address this limitation of the original Agoraphilic algorithm. The new algorithm uses a developed object tracking module to identify the time-varying free spaces by tracking moving obstacles. The capacity of the algorithm was further strengthened by the new prediction module. Future space prediction allowed the algorithm to make decisions considering future growing/diminishing free spaces. This paper also includes a bench-marking study of the new algorithm compared with a recently published APF-based algorithm under a similar operating environment. Furthermore, the algorithm was validated based on experimental tests and simulation tests. © 2022 Cambridge University Press. All rights reserved.
Failure analysis of Slurry Pump assets in refinery for reduction of risks and costs
- Authors: Welandage Don , Chattopadhyay, Gopi , Kahandawa, Gayan , Kamruzzaman, Joarder , Zhang, L.
- Date: 2022
- Type: Text , Conference paper
- Relation: 2022 International Conference on Maintenance and Intelligent Asset Management, ICMIAM 2022, Anand, India, 12-15 December 2022, 2022 International Conference on Maintenance and Intelligent Asset Management, ICMIAM 2022
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- Description: Assets fail due to design, manufacturing, installation, operations and maintenance, including ageing. Analysis of failures is needed for understanding the failure mechanism and identifying improvement opportunities to reduce risks and costs. Every year, the refinery spends a large amount of money on the maintenance of pumps and related accessories. There are unplanned maintenance and downtimes due to breakdowns. Reliability Centre Maintenance (RCM), Failure Mode and Effect Analysis (FMEA) and Residual life tracker, Equipment Management Strategy (EMS) were considered to create Preventive Maintenance (PM) activities and forecast the maintenance costs. However, budget overruns continued due to unplanned failures. This study analysed failures and identified gaps within the existing strategy for Washer and thickener underflow pumps. A review of maintenance activities was conducted along with review of design capabilities, failure modes and failure mechanisms and trends. Opportunities for improvements (OFI) were identified, and improvement actions were carried out to reduce risks and costs. © 2022 IEEE.
Machine learning-based agoraphilic navigation algorithm
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan
- Date: 2022
- Type: Text , Conference paper
- Relation: 48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022, Brussels, 17-20 October 2022, Proceedings IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society Vol. 2022-October
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- Description: This paper presents a novel machine learning-based Agoraphilic (free space attraction) navigation algorithm. The proposed algorithm is capable of undertaking local path planning for mobile robots in unknown dynamic environments with a moving goal. The inability to track and reach a moving goal is one of the common weaknesses of most existing navigation algorithms operating in dynamic environments. High uncertainty involved in dynamic environments is also another major challenge. The novel machine learning-based approach helps the proposed algorithm to successfully overcome these challenges. This paper also introduces the integrated modular-based architecture for free-space attraction-based algorithms. This allows the algorithm to incorporate ten different modules with miscellaneous algorithms to perform sub-tasks such as tracking, prediction, map generation, machine learning-based free space attraction force generation and robot motion command generation. The new modular-based architecture integrates those sub-modules to create the robot's driving force. This driving force is the single attractive force to pull the robot towards the moving goal via current free space leading to future free space passages. The proposed algorithm was experimentally tested under a dynamic environment. The experiment was focused on testing the behaviour of the algorithm under the challenge of reaching a moving goal. Furthermore, the test results demonstrate that the Agoraphilic algorithm is successful in reaching a moving goal in an unknown dynamically cluttered environment. © 2022 IEEE.
Views of American and Australian mobility device users and ambulant bus users regarding occupant restraint systems on public buses
- Authors: Unsworth, Carolyn , Baker, Anne , Brito, Sara , Das Neves, B. , Dickson, N. , Gohil, Apeksha , Kahandawa, Gayan , Naweed, Anjum , Timmer, Amanda
- Date: 2022
- Type: Text , Journal article
- Relation: Journal of Transport and Health Vol. 25, no. (2022), p.
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- Description: Introduction: With an ageing population, increasing numbers of people are using mobility devices, such as wheelchairs or scooters, whilst travelling on public route buses. The regulations and availability of active (wheelchair tie down and occupant restraint systems or WTORS) and passive (rearward facing) mobility device restraint systems on buses varies between countries. To date few studies have investigated passenger feedback on the use of restraint systems. This study aimed to gather feedback about WTORS on buses from passengers where these are in use (United States) and not in routine use (Australia) to guide decisions on their introduction. Methods: A prospective study using a purpose-designed electronic survey. Participants, predominantly recruited by Qualtrics, comprised two groups; mobility device and ambulant bus users in two countries; Australia and the United States (US). Results: The 448 participants rated the top two most important factors when deciding if buses should have WTORS as safety and comfort. Ninety-two percent of respondents believed people using mobility devices should use a WTORS which was rated 7.66/10 (SD1.97) as effective to prevent injuries to self or others. Only a minority of participants (13.2%) had ever slid or fallen from their mobility device, or seen a person slide or fall (13.6%) while on a bus with no differences between countries despite WTORS not being in use in Australia. Respondents reported it was OK to delay a journey an average of 5.52 (SD 2.89) minutes to secure/release a restraint system, which compares favourably to literature-reported real time of one to 4 min. Conclusions: Although WTORS were widely perceived by participants as important for safety, questions concerning their effectiveness to prevent slide or tip remain. Prior to the introduction of any securement system in Australia, the effectiveness of passive occupant containment systems to prevent slide or tip also warrants investigation. © 2022
Delivery of online electronics and mechatronics labs during lockdowns
- Authors: Jayawardena, Amal , Kahandawa, Gayan , Piyathilaka, Lasitha
- Date: 2021
- Type: Text , Conference paper
- Relation: 8th IEEE International Conference on e-Learning in Industrial Electronics, ICELIE 2021, Virtual, Toronto, 13-16 October 2021, Proceedings - 2021 8th IEEE International Conference on e-Learning in Industrial Electronics, ICELIE 2021
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- Description: This paper provides a detailed explanation of several approaches that can be used to conduct online labs for elec-tronics/mechatronics engineering courses and explains the results obtained from a survey conducted. The detailed explanations provide information on how to implement the method, benefits of the stated process, possible challenges, and how to overcome those challenges. Furthermore, this paper presents the analyzed results from a survey conducted to capture the student experience in online labs. © 2021 IEEE.
E-Learning challenges for electronics and mechatronics education during lockdowns
- Authors: Jayawardena, Amal , Kahandawa, Gayan , Petty, Mark
- Date: 2021
- Type: Text , Conference paper
- Relation: 8th IEEE International Conference on e-Learning in Industrial Electronics, ICELIE 2021, Virtual, Toronto, 13-16 October 2021, Proceedings - 2021 8th IEEE International Conference on e-Learning in Industrial Electronics, ICELIE 2021
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- Description: This paper explains methods used to deliver online electronics and mechatronics courses and clarifies the results obtained by an online survey to understand students' e-learning experience. The purpose of this paper is to outline the challenges of online learning and to explain effective content delivery methods used to overcome those challenges. This study gives detailed descriptions for each content delivery technique, for each online lab delivery method, and for all the online assessment types used while analyzing the effectiveness of those procedures. A case study on the delivery of an online mechatronics project has also been presented. In addition, the paper presents the analyzed results obtained from the survey to improve the future delivery of online electronics and mechatronics courses in a pandemic. © 2021 IEEE.
The agoraphilic navigation algorithm under dynamic environment with a moving goal
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer
- Date: 2021
- Type: Text , Conference paper
- Relation: 30th IEEE International Symposium on Industrial Electronics, ISIE 2021 Vol. 2021-June
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- Description: This paper presents a research conducted in developing a new navigation algorithm to navigate robots under dynamically cluttered environments with a moving goal. There are only a few navigation algorithms capable of navigating robots under dynamic environments compared to static environments. The inability to track and reach a moving goal/target is a one of the common weakness of existing navigating algorithms operating in dynamic environments. The existing free space attraction (Agoraphilic) based navigation algorithms also suffer from this common problem. The proposed algorithm, in this paper was developed to overcome this issue. Agoraphilic Navigation Algorithm under Dynamic Environment, 'ANADE' consists of eight main modules. These modules are iteratively used to create the robot's driving force which pulls the robot towards the moving goal. An obstacle tracking module is used to identify the time varying free spaces by tracking moving obstacles. Furthermore, a tracking system is also used to track the moving goal. The capacity of the ANADE was further strengthen by obstacle and goal path prediction modules. Future location prediction allowed the algorithm to make decision considering future environments around the robot. The proposed algorithm was tested under dynamic environment. These tests were focused on testing the behavior of the algorithm under the challenge of reaching a moving goal. Furthermore, the test results demonstrate that ANADE is successful in reaching a moving goal under an unknown dynamically cluttered environment. © 2021 IEEE.
Evaluating the Performances of the Agoraphilic Navigation Algorithm under Dead-Lock Situations
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer
- Date: 2020
- Type: Text , Conference proceedings , Conference paper
- Relation: 29th IEEE International Symposium on Industrial Electronics, ISIE 2020 Vol. 2020-June, p. 536-542
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- Description: This paper presents a summary of the research which was conducted in developing a new free-space based (Agoraphilic) navigation algorithm. This new methodology is capable of maneuvering robots in static as well as dynamically cluttered unknown environments. The new algorithm uses only one force to drive the robot. This force is always an attractive force created by the freespace. This force is focused towards the goal by a force shaping module. Consequently, the robot is motivated to follow free-space directing towards the goal. As this method only based on the attractive forces, the robot always moves towards the goal as long as there is free-space . This method has eradicated many drawbacks of the traditional APF method. Several experimental tests were conducted using Turtlebot3 research platform. These tests were focused on testing the behavior of the new algorithm under dead-lock (local minima) situations for APF method. The test results proved that the proposed algorithm has successfully eliminated the local minima problem of APF method. © 2020 IEEE.
Agoraphilic navigation algorithm in dynamic environment with and without prediction of moving objects location
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019 Vol. 2019-October, p. 5179-5185
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- Description: This paper presents a summary of research conducted in performance improvement of Agoraphilic Navigation Algorithm under Dynamic Environment (ANADE). The ANADE is an optimistic navigation algorithm which is capable of navigating robots in static as well as in unknown dynamic environments. ANADE has been successfully extended the capacity of original Agoraphilic algorithm for static environment. However, it could identify that ANADE takes costly decisions when it is used in complex dynamic environments. The proposed algorithm in this paper has been successfully enhanced the performance of ANADE in terms of safe travel, speed variation, path length and travel time. The proposed algorithm uses a prediction methodology to estimate future growing free space passages which can be used for safe navigation of the robot. With motion prediction of moving objects, new set of future driving forces were developed. These forces has been combined with present driving force for safe and efficient navigation. Furthermore, the performances of proposed algorithm (Agoraphilic algorithm with prediction) was compared and benched-marked with ANADE (Without predication) under similar environment conditions. From the investigation results, it was observed that the proposed algorithm extends the effective decision making ability in a complex navigation environment. Moreover, the proposed algorithm navigated the robot in a shorter and quicker path with smooth speed variations. © 2019 IEEE.
- Description: E1
Comparative study on object tracking algorithms for mobile robot navigation in GPS-denied environment
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer
- Date: 2019
- Type: Text , Conference proceedings
- Relation: 2019 IEEE International Conference on Industrial Technology, ICIT 2019; Melbourne, Australia; 13th-15th February 2019 Vol. 2019-February, p. 19-26
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- Description: This paper presents a comparative study conducted on the performance of the commonly used object tracking and location prediction algorithms for mobile robot navigation in a dynamically cluttered and GPS-denied mining environment. The study was done to test the different algorithms for the same set criteria (such as accuracy and computational time) under the same conditions.The identified commonly used algorithms for object tracking and location prediction of moving objects used in this investigation are Kalman filter (KF), extended Kalman filter (EKF) and particle filter (PF). The study results of those algorithms are analyzed and discussed in this paper. A trade-off was apparent. However, in overall performance KF has shown its competitiveness.The result from the study has found that the KF based algorithm provides better performance in terms of accuracy in tracking dynamic objects under commonly used benchmarks. This finding can be used in development of an efficient robot navigation algorithm.
- Description: Proceedings of the IEEE International Conference on Industrial Technology
Development and bench-marking of agoraphilic navigation algorithm in dynamic environment
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer , IEEE
- Date: 2019
- Type: Text , Book chapter
- Relation: 2019 IEEE 28th International Symposium on Industrial Electronics p. 1156-1161
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- Description: This paper presents a summary of research which was conducted in developing a new human-like navigation methodology based on the Agoraphilic algorithm. This new methodology is capable of maneuvering robots in both static and dynamically clutter unknown environments. The Agoraphilic algorithm is an "optimistic" navigation algorithm. The algorithm is based on free space attraction rather than repulsion of obstacles for navigation. Therefore, this algorithm directs robots to follow the free space leading to the goal instead of avoiding obstacles. This approach has eliminated many draw backs of the traditional APF algorithm. However, the major limitation of the previously developed Agoraphilic algorithm could only deal with static environment. The new proposed algorithm has successfully extended the capacity of Agoraphilic algorithm to deal with environment cluttered with dynamic obstacles. The new Agoraphilic algorithm uses a tracking and prediction methodology to estimate the path of unknown moving objects. The estimated locations of the moving objects are combined with static object locations in the robot's visible region to generate time-varying free space attractive forces. These time varying forces maneuver the robot to the goal in dynamically cluttered unknown environment without collusions. To demonstrate the algorithm's ability, several simulations were performed. Furthermore, the new algorithm was tested and bench-marked against other APF published work under similar environment and conditions. The comparative results are discussed and showed the effectiveness of the new Algoraphilic navigation algorithm.
Measuring soil strain using fibre optic sensors
- Authors: Costa, Susanga , Kahandawa, Gayan , Chen, Jian , Xue, Jianfeng
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 8th International Congress on Environmental Geotechnics, ICEG 2018; Hangzhou, China; 28th October-1st November 2018; part of the Environmental Science and Engineering book series p. 43-50
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- Description: Monitoring subsurface soil movement is important in many geotechnical engineering applications such as stability of slopes, road embankments and settlement in foundations. Soil displacement measurement is also helpful in understanding the formation of shrinkage cracks. Clay soils undergo shrinkage during drying and experience substantial stresses and strains, which results in shrinkage cracks. This paper presents a novel approach to measure soil strain using Fibre Bragg grating (FBG) sensors. In the experiments described, FBG sensors have been used to investigate the strain development in clay during drying. FBG sensors are fabricated in the core region of specially fabricated single mode low-loss germanium doped silicate optical fibres. The grating is the laser-inscribed region with a periodically varying refractive index, which reflects a specific light wavelength. Due to the applied strain, ε, there is a change in the wavelength which can be measured and is directly proposal to strain. Kaolin clay, mixed with water close to the liquid limit, was allowed to dry under room temperature. The specimens were prepared in thin, long linear shrinkage moulds. FBG sensors were placed inside soil at the centre of the specimen. The strain development during drying underwent four phases moving from compression to tension. An oscillating nature of strain was also observed throughout the drying process. Results obtained are useful to develop analytical solutions to describe stress-strain behavior of drying soil. © Springer Nature Singapore Pte Ltd. 2019.
Detecting splicing and copy-move attacks in color images
- Authors: Islam, Mohammad , Karmakar, Gour , Kamruzzaman, Joarder , Murshed, Manzur , Kahandawa, Gayan , Parvin, Nahida
- Date: 2018
- Type: Text , Conference proceedings
- Relation: 2018 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2018; Canberra, Australia; 10th-13th December 2018 p. 1-7
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- Description: Image sensors are generating limitless digital images every day. Image forgery like splicing and copy-move are very common type of attacks that are easy to execute using sophisticated photo editing tools. As a result, digital forensics has attracted much attention to identify such tampering on digital images. In this paper, a passive (blind) image tampering identification method based on Discrete Cosine Transformation (DCT) and Local Binary Pattern (LBP) has been proposed. First, the chroma components of an image is divided into fixed sized non-overlapping blocks and 2D block DCT is applied to identify the changes due to forgery in local frequency distribution of the image. Then a texture descriptor, LBP is applied on the magnitude component of the 2D-DCT array to enhance the artifacts introduced by the tampering operation. The resulting LBP image is again divided into non-overlapping blocks. Finally, summations of corresponding inter-cell values of all the LBP blocks are computed and arranged as a feature vector. These features are fed into a Support Vector Machine (SVM) with Radial Basis Function (RBF) as kernel to distinguish forged images from authentic ones. The proposed method has been experimented extensively on three publicly available well-known image splicing and copy-move detection benchmark datasets of color images. Results demonstrate the superiority of the proposed method over recently proposed state-of-the-art approaches in terms of well accepted performance metrics such as accuracy, area under ROC curve and others.
- Description: 2018 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2018
Passive detection of splicing and copy-move attacks in image forgery
- Authors: Islam, Mohammad , Kamruzzaman, Joarder , Karmakar, Gour , Murshed, Manzur , Kahandawa, Gayan
- Date: 2018
- Type: Text , Conference proceedings , Conference paper
- Relation: 25th International Conference on Neural Information Processing, ICONIP 2018; Siem Reap, Cambodia; 13th-16th December 2018; published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11304 LNCS, p. 555-567
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- Description: Internet of Things (IoT) image sensors for surveillance and monitoring, digital cameras, smart phones and social media generate huge volume of digital images every day. Image splicing and copy-move attacks are the most common types of image forgery that can be done very easily using modern photo editing software. Recently, digital forensics has drawn much attention to detect such tampering on images. In this paper, we introduce a novel feature extraction technique, namely Sum of Relevant Inter-Cell Values (SRIV) using which we propose a passive (blind) image forgery detection method based on Discrete Cosine Transformation (DCT) and Local Binary Pattern (LBP). First, the input image is divided into non-overlapping blocks and 2D block DCT is applied to capture the changes of a tampered image in the frequency domain. Then LBP operator is applied to enhance the local changes among the neighbouring DCT coefficients, magnifying the changes in high frequency components resulting from splicing and copy-move attacks. The resulting LBP image is again divided into non-overlapping blocks. Finally, SRIV is applied on the LBP image blocks to extract features which are then fed into a Support Vector Machine (SVM) classifier to identify forged images from authentic ones. Extensive experiment on four well-known benchmark datasets of tampered images reveal the superiority of our method over recent state-of-the-art methods.
Tire size identification using extreme learning machine algorithm
- Authors: Kahandawa, Gayan , Choudhury, Tanveer , Ibrahim, Yousef
- Date: 2018
- Type: Text , Conference proceedings
- Relation: 27th IEEE International Symposium on Industrial Electronics, ISIE 2018; Cairns, Australia; 13th-15th June 2018 Vol. 2018-June, p. 571-576
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- Description: Precise tire size identification is needed to increase the efficiency and the reliability of tire inflators and to minimize the inflation cycle time. On the other hand the correct inflation pressure improve the road safety and tire life as well. A single hidden layer feed forward neural network (SLFN) is used in this study to precisely identify a tire size to enhance the tire inflation cycle. The training times of traditional back propagation algorithms, mostly used to model such tire identification processes, are far slower than desired for implementation of an on-line control system. Use of slow gradient based learning methods and iterative tuning of all network parameters during the learning process are the two major causes for such slower learning speed. An extreme learning machine (ELM) algorithm, which randomly selects the input weights and biases and analytically determines the output weights, is used in this work to train the SLFNs. It is found that networks trained with ELM have relatively good generalization performance, much shorter training times and stable performance with regard to the changes in number of hidden layer neurons. The result represents robustness of the trained networks and enhance reliability of the mode. Together with short training time, the algorithm has valuable application in tire identification process.
- Description: IEEE International Symposium on Industrial Electronics
Industry-led mechatronics degree development in regional Australia
- Authors: Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer , Mazid, Abdul Md
- Date: 2017
- Type: Text , Conference proceedings , Conference paper
- Relation: 2017 IEEE International Conference on Mechatronics, ICM 2017; Gippsland, Australia; 13th-15th February 2017 p. 419-424
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- Description: This paper presents a technique that was used in the recent development of a new Mechatronics degree in Australia. This technique addressed the local industry needs and the available resources for a well-balanced Mechatronics degree program. The degree development was based on project-based learning and industry engagement. The development of the new Mechatronics degree was made possible via a State Government grant of AU$2.4 Million which was matched by industry contribution of AU$10 Million in cash and in-kind. Since industry was a major stake holder in this degree, a specific industry survey was conducted to check the desired graduates attributes, from industry point of view. The results of this survey is also included in this papers. In addition, the program also addressed the regional industry's challenge of retaining qualified engineers via a clear pathway program for students knowledge and skills development. This paper presents industry's anticipated outputs of the academic Mechatronics program. In addition the paper also discusses the mechanisms adopted for the development of this new degree. The developed fully integrated Mechatronics program was founded on the realisation that if a person undertook a mechanical degree followed by an electronics degree followed by a computer science degree, that person is, still, NOT a Mechatronics engineer. © 2017 IEEE.
- Description: Proceedings - 2017 IEEE International Conference on Mechatronics, ICM 2017