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Articles 1 - 30 of 34
Full-Text Articles in Engineering
Detection And Recognition Of Moving Video Objects: Kalman Filtering With Deep Learning, Hind Rustum Mohammed, Zahir M. Hussain
Detection And Recognition Of Moving Video Objects: Kalman Filtering With Deep Learning, Hind Rustum Mohammed, Zahir M. Hussain
Research outputs 2014 to 2021
© 2021. All rights reserved. Research in object recognition has lately found that Deep Convolutional Neuronal Networks (CNN) provide a breakthrough in detection scores, especially in video applications. This paper presents an approach for object recognition in videos by combining Kalman filter with CNN. Kalman filter is first applied for detection, removing the background and then cropping object. Kalman filtering achieves three important functions: predicting the future location of the object, reducing noise and interference from incorrect detections, and associating multi-objects to tracks. After detection and cropping the moving object, a CNN model will predict the category of object. The …
A Range Error Reduction Technique For Positioning Applications In Sports, Adnan Waqar, Iftekhar Ahmad, Daryoush Habibi, Quoc V. Phung
A Range Error Reduction Technique For Positioning Applications In Sports, Adnan Waqar, Iftekhar Ahmad, Daryoush Habibi, Quoc V. Phung
Research outputs 2014 to 2021
In recent times, ultra-wideband (UWB)-based positioning systems have become popular in sport performance monitoring. UWB positioning system uses time of arrival to calculate the range data between devices (i.e. anchors, tags), and then use trilateration algorithms to estimate position coordinates. In practical applications, non-line-of-sight transmissions and multipath propagations lead to inaccurate range data and lower positioning accuracy. This paper introduces a range error minimisation algorithm to address this limitation of error in range data in UWB-based positioning system. The proposed solution analyses the range error for each anchor and sequentially reduces this error based on the distance between each anchor …
Green Underwater Wireless Communications Using Hybrid Optical-Acoustic Technologies, Kazi Y. Islam, Iftekhar Ahmad, Daryoush Habibi, M. Ishtiaque A. Zahed, Joarder Kamruzzaman
Green Underwater Wireless Communications Using Hybrid Optical-Acoustic Technologies, Kazi Y. Islam, Iftekhar Ahmad, Daryoush Habibi, M. Ishtiaque A. Zahed, Joarder Kamruzzaman
Research outputs 2014 to 2021
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 …
Class Distribution-Aware Adaptive Margins And Cluster Embedding For Classification Of Fruit And Vegetables At Supermarket Self-Checkouts, Khurram Hameed, Douglas Chai, Alexander Rassau
Class Distribution-Aware Adaptive Margins And Cluster Embedding For Classification Of Fruit And Vegetables At Supermarket Self-Checkouts, Khurram Hameed, Douglas Chai, Alexander Rassau
Research outputs 2014 to 2021
The complex task of vision based fruit and vegetables classification at a supermarket self-checkout poses significant challenges. These challenges include the highly variable physical features of fruit and vegetables i.e. colour, texture shape and size which are dependent upon ripeness and storage conditions in a supermarket as well as general product variation. Supermarket environments are also significantly variable with respect to lighting conditions. Attempting to build an exhaustive dataset to capture all these variations, for example a dataset of a fruit consisting of all possible colour variations, is nearly impossible. Moreover, some fruit and vegetable classes have significant similar physical …
Rgb-D Data-Based Action Recognition: A Review, Muhammad Bilal Shaikh, Douglas Chai
Rgb-D Data-Based Action Recognition: A Review, Muhammad Bilal Shaikh, Douglas Chai
Research outputs 2014 to 2021
Classification of human actions is an ongoing research problem in computer vision. This review is aimed to scope current literature on data fusion and action recognition techniques and to identify gaps and future research direction. Success in producing cost-effective and portable vision-based sensors has dramatically increased the number and size of datasets. The increase in the number of action recognition datasets intersects with advances in deep learning architectures and computational support, both of which offer significant research opportunities. Naturally, each action-data modality—such as RGB, depth, skeleton, and infrared (IR)—has distinct characteristics; therefore, it is important to exploit the value of …
Short Word-Length Entering Compressive Sensing Domain: Improved Energy Efficiency In Wireless Sensor Networks, Nuha A. S. Alwan, Zahir M. Hussain
Short Word-Length Entering Compressive Sensing Domain: Improved Energy Efficiency In Wireless Sensor Networks, Nuha A. S. Alwan, Zahir M. Hussain
Research outputs 2014 to 2021
This work combines compressive sensing and short word-length techniques to achieve localization and target tracking in wireless sensor networks with energy-efficient communication between the network anchors and the fusion center. Gradient descent localization is performed using time-of-arrival (TOA) data which are indicative of the distance between anchors and the target thereby achieving range-based localization. The short word-length techniques considered are delta modulation and sigma-delta modulation. The energy efficiency is due to the reduction of the data volume transmitted from anchors to the fusion center by employing any of the two delta modulation variants with compressive sensing techniques. Delta modulation allows …
Optimal Sizing Of Energy Storage System To Reduce Impacts Of Transportation Electrification On Power Distribution Transformers Integrated With Photovoltaic, Pravakar Pradhan, Iftekhar Ahmad, Daryoush Habibi, Asma Aziz, Bassam Al-Hanahi, Mohammad A S Masoum
Optimal Sizing Of Energy Storage System To Reduce Impacts Of Transportation Electrification On Power Distribution Transformers Integrated With Photovoltaic, Pravakar Pradhan, Iftekhar Ahmad, Daryoush Habibi, Asma Aziz, Bassam Al-Hanahi, Mohammad A S Masoum
Research outputs 2014 to 2021
Transportation systems are one of the leading sectors that contribute to greenhouse gas emissions that lead to enhance global warming. The electrification of vehicles is a promising solution to this widespread problem; however, integrating electric vehicles (EVs) into existing grid systems on a large scale creates several problems, both for consumers and for utilities. Accelerated aging of expensive grid assets, such as power transformers, is one of the primary issues that these utilities are facing. This problem can be addressed with battery energy storage systems (BESS), which acts as buffer between demand and supply. Accordingly, this paper proposes a novel …
Realization And Optimization Of Optical Logic Gates Using Bias Assisted Carrier-Injected Triple Parallel Microring Resonators, Fayza Kizhakkakath, Sooraj Ravindran, Kwangwook Park, Kamal Alameh, Yong Tak Lee
Realization And Optimization Of Optical Logic Gates Using Bias Assisted Carrier-Injected Triple Parallel Microring Resonators, Fayza Kizhakkakath, Sooraj Ravindran, Kwangwook Park, Kamal Alameh, Yong Tak Lee
Research outputs 2014 to 2021
We propose a p-i-n diode embedded parallel triple microring resonator (MRR) configuration to simultaneously realize optical OR and AND, or NAND and NOR logic gates using a bias-assisted carrier injection mechanism. The applied bias on the rings induces refractive index change in the intrinsic region through bandfilling, bandgap shrinkage and free carrier absorption effects, leading to intensity variation at the output ports of the MRR due to respective resonant wavelength shift. The optical logic gate operational outputs are represented as the light intensities at the output ports of the MRR with the wavelength of the input optical signal launched into …
Voltage Stability Of Power Systems With Renewable-Energy Inverter-Based Generators: A Review, Nasser Hosseinzadeh, Asma Aziz, Apel Mahmud, Ameen Gargoom, Mahbub Rabbani
Voltage Stability Of Power Systems With Renewable-Energy Inverter-Based Generators: A Review, Nasser Hosseinzadeh, Asma Aziz, Apel Mahmud, Ameen Gargoom, Mahbub Rabbani
Research outputs 2014 to 2021
© 2021 by the authors. The main purpose of developing microgrids (MGs) is to facilitate the integration of renewable energy sources (RESs) into the power grid. RESs are normally connected to the grid via power electronic inverters. As various types of RESs are increasingly being connected to the electrical power grid, power systems of the near future will have more inverter-based generators (IBGs) instead of synchronous machines. Since IBGs have significant differences in their characteristics compared to synchronous generators (SGs), particularly concerning their inertia and capability to provide reactive power, their impacts on the system dynamics are different compared to …
Breaking-Down And Parameterising Wave Energy Converter Costs Using The Capex And Similitude Methods, Ophelie Choupin, Michael Henriksen, Amir Etemad-Shahidi, Rodger Tomlinson
Breaking-Down And Parameterising Wave Energy Converter Costs Using The Capex And Similitude Methods, Ophelie Choupin, Michael Henriksen, Amir Etemad-Shahidi, Rodger Tomlinson
Research outputs 2014 to 2021
Wave energy converters (WECs) can play a significant role in the transition towards a more renewable-based energy mix as stable and unlimited energy resources. Financial analysis of these projects requires WECs cost and WEC capital expenditure (CapEx) information. However, (i) cost information is often limited due to confidentiality and (ii) the wave energy field lacks flexible methods for cost breakdown and parameterisation, whereas they are needed for rapid and optimised WEC configuration and worldwide site pairing. This study takes advantage of the information provided by Wavepiston to compare different costing methods. The work assesses the Froude-Law-similarities-based “Similitude method” for cost-scaling …
Hybrid Mamdani Fuzzy Rules And Convolutional Neural Networks For Analysis And Identification Of Animal Images, Hind R. Mohammed, Zahir M. Hussain
Hybrid Mamdani Fuzzy Rules And Convolutional Neural Networks For Analysis And Identification Of Animal Images, Hind R. Mohammed, Zahir M. Hussain
Research outputs 2014 to 2021
Accurate, fast, and automatic detection and classification of animal images is challenging, but it is much needed for many real-life applications. This paper presents a hybrid model of Mamdani Type-2 fuzzy rules and convolutional neural networks (CNNs) applied to identify and distinguish various animals using different datasets consisting of about 27,307 images. The proposed system utilizes fuzzy rules to detect the image and then apply the CNN model for the object’s predicate category. The CNN model was trained and tested based on more than 21,846 pictures of animals. The experiments’ results of the proposed method offered high speed and efficiency, …
Deep Learning Versus Spectral Techniques For Frequency Estimation Of Single Tones: Reduced Complexity For Software-Defined Radio And Iot Sensor Communications, Hind R. Almayyali, Zahir M. Hussain
Deep Learning Versus Spectral Techniques For Frequency Estimation Of Single Tones: Reduced Complexity For Software-Defined Radio And Iot Sensor Communications, Hind R. Almayyali, Zahir M. Hussain
Research outputs 2014 to 2021
Despite the increasing role of machine learning in various fields, very few works considered artificial intelligence for frequency estimation (FE). This work presents comprehensive analysis of a deep-learning (DL) approach for frequency estimation of single tones. A DL network with two layers having a few nodes can estimate frequency more accurately than well-known classical techniques can. While filling the gap in the existing literature, the study is comprehensive, analyzing errors under different signal-to-noise ratios (SNRs), numbers of nodes, and numbers of input samples under missing SNR information. DL-based FE is not significantly affected by SNR bias or number of nodes. …
Deep Learning Control For Digital Feedback Systems: Improved Performance With Robustness Against Parameter Change, Nuha A. S. Alwan, Zahir M. Hussain
Deep Learning Control For Digital Feedback Systems: Improved Performance With Robustness Against Parameter Change, Nuha A. S. Alwan, Zahir M. Hussain
Research outputs 2014 to 2021
Training data for a deep learning (DL) neural network (NN) controller are obtained from the input and output signals of a conventional digital controller that is designed to provide the suitable control signal to a specified plant within a feedback digital control system. It is found that if the DL controller is sufficiently deep (four hidden layers), it can outperform the conventional controller in terms of settling time of the system output transient response to a unit-step reference signal. That is, the DL controller introduces a damping effect. Moreover, it does not need to be retrained to operate with a …
Frequency Estimation From Compressed Measurements Of A Sinusoid In Moving‐Average Colored Noise, Nuha A. S. Alwan, Zahir M. Hussain
Frequency Estimation From Compressed Measurements Of A Sinusoid In Moving‐Average Colored Noise, Nuha A. S. Alwan, Zahir M. Hussain
Research outputs 2014 to 2021
Frequency estimation of a single sinusoid in colored noise has received a considerable amount of attention in the research community. Taking into account the recent emergence and advances in compressive covariance sensing (CCS), the aim of this work is to combine the two disci-plines by studying the effects of compressed measurements of a single sinusoid in moving‐average colored noise on its frequency estimation accuracy. CCS techniques can recover the second‐order statistics of the original uncompressed signal from the compressed measurements, thereby enabling correlation‐based frequency estimation of single tones in colored noise using higher order lags. Ac-ceptable accuracy is achieved for …
A Secure And Energy-Aware Approach For Cognitive Radio Communications, Haitham Khaled, Iftekhar Ahmad, Daryoush Habibi, Quoc Viet Phung
A Secure And Energy-Aware Approach For Cognitive Radio Communications, Haitham Khaled, Iftekhar Ahmad, Daryoush Habibi, Quoc Viet Phung
Research outputs 2014 to 2021
The cognitive radio (CR) technique has revealed a novel way of utilizing the precious radiospectrum via allowing unlicensed users to opportunistically access unutilized licensed bands. Using sucha technique enables agile and flexible access to the radio spectrum and can resolve the spectrum-scarcityproblem and maximize spectrum efficiency. However, two major impediments have been limiting thewidespread adoption of cognitive radio technology. The software-defined radio technology, which is theenabling technology for the CR technique, is power-hungry and this raises a major concern for battery-constrained devices such as smart phones and laptops. Secondly, the opportunistic and open nature ofthe CR can lead to major …
An Intelligent Controlling Method For Battery Lifetime Increment Using State Of Charge Estimation In Pv-Battery Hybrid System, Md Ohirul Qays, Yonis Buswig, Hazrul Basri, Md Liton Hussain, Ahmed Abu-Siada, Md Momtazur Rahman, S. M. Muyeen
An Intelligent Controlling Method For Battery Lifetime Increment Using State Of Charge Estimation In Pv-Battery Hybrid System, Md Ohirul Qays, Yonis Buswig, Hazrul Basri, Md Liton Hussain, Ahmed Abu-Siada, Md Momtazur Rahman, S. M. Muyeen
Research outputs 2014 to 2021
In a photovoltaic (PV)-battery integrated system, the battery undergoes frequent charging and discharging cycles that reduces its operational life and affects its performance considerably. As such, an intelligent power control approach for a PV-battery standalone system is proposed in this paper to improve the reliability of the battery along its operational life. The proposed control strategy works in two regulatory modes: maximum power point tracking (MPPT) mode and battery management system (BMS) mode. The novel controller tracks and harvests the maximum available power from the solar cells under different atmospheric conditions via MPPT scheme. On the other hand, the state …
Reducing The Impacts Of Electric Vehicle Charging On Power Distribution Transformers, Pravakar Pradhan, Iftekhar Ahmad, Daryoush Habibi, Ganesh Kothapalli, Mohammad A.S. Masoum
Reducing The Impacts Of Electric Vehicle Charging On Power Distribution Transformers, Pravakar Pradhan, Iftekhar Ahmad, Daryoush Habibi, Ganesh Kothapalli, Mohammad A.S. Masoum
Research outputs 2014 to 2021
This article investigates the effects of high penetration levels of Electric Vehicle (EV) charging on power distribution transformers and proposes a new solution to minimize its negative impacts. There has been growing concern over Greenhouse Gas (GHG) emissions within the transportation sector, which accounts for about 23% of total energy-related carbon-dioxide emissions. The main solution to this problem is the electrification of vehicles. However, large scale integration of EVs into existing grid systems poses some challenges. One major challenge is the accelerated aging of expensive grid assets such as transformers. In this article, a demand response mechanism based on the …
A Sample Weight And Adaboost Cnn-Based Coarse To Fine Classification Of Fruit And Vegetables At A Supermarket Self-Checkout, Khurram Hameed, Douglas Chai, Alexander Rassau
A Sample Weight And Adaboost Cnn-Based Coarse To Fine Classification Of Fruit And Vegetables At A Supermarket Self-Checkout, Khurram Hameed, Douglas Chai, Alexander Rassau
Research outputs 2014 to 2021
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. The physical features of fruit and vegetables make the task of vision-based classification of fruit and vegetables challenging. The classification of fruit and vegetables at a supermarket self-checkout poses even more challenges due to variable lighting conditions and human factors arising from customer interactions with the system along with the challenges associated with the colour, texture, shape, and size of a fruit or vegetable. Considering this complex application, we have proposed a progressive coarse to fine classification technique to classify fruit and vegetables at supermarket checkouts. The image and weight of …
Strategies To Improve The Thermal Performance Of Heat Pipe Solar Collectors In Solar Systems: A Review, Abdellah Sharifian, Mehdi Khiadani, Ataollah Nosrati
Strategies To Improve The Thermal Performance Of Heat Pipe Solar Collectors In Solar Systems: A Review, Abdellah Sharifian, Mehdi Khiadani, Ataollah Nosrati
Research outputs 2014 to 2021
Invention of evacuated tube heat pipe solar collectors (HPSCs) was a huge step forward towards resolving the challenges of conventional solar systems due to their unique features and advantages. This has led to their utilization in a wide range of solar applications surpassing other conventional collectors. However, relatively low thermal efficiency of heat pipe solar (HPS) systems is still the major challenge of solar industry evidenced by numerous studies conducted mainly during the last decade to improve their efficiency. To date, several review papers have been published summarizing studies relevant to utilization of HPSCs in various thermal applications. However, to …
Optimal Placement Of Distributed Energy Storage Systems In Distribution Networks Using Artificial Bee Colony Algorithm, Choton K. Das, Octavian Bass, Ganesh Kothapalli, Thair S. Mahmoud, Daryoush Habibi
Optimal Placement Of Distributed Energy Storage Systems In Distribution Networks Using Artificial Bee Colony Algorithm, Choton K. Das, Octavian Bass, Ganesh Kothapalli, Thair S. Mahmoud, Daryoush Habibi
Research outputs 2014 to 2021
The deployment of utility-scale energy storage systems (ESSs) can be a significant avenue for improving the performance of distribution networks. An optimally placed ESS can reduce power losses and line loading, mitigate peak network demand, improve voltage profile, and in some cases contribute to the network fault level diagnosis. This paper proposes a strategy for optimal placement of distributed ESSs in distribution networks to minimize voltage deviation, line loading, and power losses. The optimal placement of distributed ESSs is investigated in a medium voltage IEEE-33 bus distribution system, which is influenced by a high penetration of renewable (solar and wind) …
Muscle Activity-Driven Green-Oriented Random Number Generation Mechanism To Secure Wbsn Wearable Device Communications, Yuanlong Cao, Guanghe Zhang, Fanghua Liu, Ilsun You, Guanglou Zheng, Oluwarotimi W. Samuel, Shixiong Chen
Muscle Activity-Driven Green-Oriented Random Number Generation Mechanism To Secure Wbsn Wearable Device Communications, Yuanlong Cao, Guanghe Zhang, Fanghua Liu, Ilsun You, Guanglou Zheng, Oluwarotimi W. Samuel, Shixiong Chen
Research outputs 2014 to 2021
Wireless body sensor networks (WBSNs) mostly consist of low-cost sensor nodes and implanted devices which generally have extremely limited capability of computations and energy capabilities. Hence, traditional security protocols and privacy enhancing technologies are not applicable to the WBSNs since their computations and cryptographic primitives are normally exceedingly complicated. Nowadays, mobile wearable and wireless muscle-computer interfaces have been integrated with the WBSN sensors for various applications such as rehabilitation, sports, entertainment, and healthcare. In this paper, we propose MGRNG, a novel muscle activity-driven green-oriented random number generation mechanism which uses the human muscle activity as green energy resource to generate …
Issues And Mitigations Of Wind Energy Penetrated Network: Australian Network Case Study, Asma Aziz, Aman M. Than Oo, Alex Stojcevski
Issues And Mitigations Of Wind Energy Penetrated Network: Australian Network Case Study, Asma Aziz, Aman M. Than Oo, Alex Stojcevski
Research outputs 2014 to 2021
Longest geographically connected Australian power system is undergoing an unprecedented transition, under the effect of increased integration of renewable energy systems. This change in generation mix has implications for the whole interconnected system designs, its operational strategies and the regulatory framework. Frequency control policies about real-time balancing of demand and supply is one of the prominent and priority operational challenge requiring urgent attention. This paper reviews the Australian electricity market structure in presence of wind energy and its governance. Various issues related to increased wind generation systems integration are discussed in detail. Currently applied mitigations along with prospective mitigation methods …
Grey Wolf Optimization-Based Optimum Energy-Management And Battery-Sizing Method For Grid-Connected Microgrids, Kutaiba Sabah Nimma, Monaaf D. A. Al-Falahi, Hung Duc Nguyen, S. D. G. Jayasinghe, Thair Mahmoud, Michael Negnevitsky
Grey Wolf Optimization-Based Optimum Energy-Management And Battery-Sizing Method For Grid-Connected Microgrids, Kutaiba Sabah Nimma, Monaaf D. A. Al-Falahi, Hung Duc Nguyen, S. D. G. Jayasinghe, Thair Mahmoud, Michael Negnevitsky
Research outputs 2014 to 2021
In the revolution of green energy development, microgrids with renewable energy sources such as solar, wind and fuel cells are becoming a popular and effective way of controlling and managing these sources. On the other hand, owing to the intermittency and wide range of dynamic responses of renewable energy sources, battery energy-storage systems have become an integral feature of microgrids. Intelligent energy management and battery sizing are essential requirements in the microgrids to ensure the optimal use of the renewable sources and reduce conventional fuel utilization in such complex systems. This paper presents a novel approach to meet these requirements …
Universal Signal Conditioning Technique For Fiber Bragg Grating Sensors In Plc And Scada Applications, Gary Allwood, Graham Wild, Steven Hinkley
Universal Signal Conditioning Technique For Fiber Bragg Grating Sensors In Plc And Scada Applications, Gary Allwood, Graham Wild, Steven Hinkley
Research outputs 2014 to 2021
Optical fibre sensors, such as Fibre Bragg Gratings (FBGs), are growing in their utilisation, although very niche in their applications. To enable a more diverse range of end users, expensive application-specific optical fibre interrogation hardware needs to be made compatible with and, ideally, easily incorporated into existing instrumentation and measurement hardware. The Programmable Logic Controller (PLC) is an ideal example of hardware used for data acquisition in many industries. As such, a module that can be connected into an existing PLC slot to collect data from electrically-neutral, EMI-immune and versatile FBG sensors is of significant advantage to the growing optical …
An Investigation Into Spike-Based Neuromorphic Approaches For Artificial Olfactory Systems, Anup Vanarse, Adam Osseiran, Alexander Rassau
An Investigation Into Spike-Based Neuromorphic Approaches For Artificial Olfactory Systems, Anup Vanarse, Adam Osseiran, Alexander Rassau
Research outputs 2014 to 2021
The implementation of neuromorphic methods has delivered promising results for vision and auditory sensors. These methods focus on mimicking the neuro-biological architecture to generate and process spike-based information with minimal power consumption. With increasing interest in developing low-power and robust chemical sensors, the application of neuromorphic engineering concepts for electronic noses has provided an impetus for research focusing on improving these instruments. While conventional e-noses apply computationally expensive and power-consuming data-processing strategies, neuromorphic olfactory sensors implement the biological olfaction principles found in humans and insects to simplify the handling of multivariate sensory data by generating and processing spike-based information. Over …
Influence Of Neural Network Training Parameters On Short-Term Wind Forecasting, Adel Brka, Yasir M. Al-Abdeli, Ganesh Kothapalli
Influence Of Neural Network Training Parameters On Short-Term Wind Forecasting, Adel Brka, Yasir M. Al-Abdeli, Ganesh Kothapalli
Research outputs 2014 to 2021
This paper investigates factors which can affect the accuracy of short-term wind speed prediction when done over long periods spanning different seasons. Two types of neural networks (NNs) are used to forecast power generated via specific horizontal axis wind turbines. Meteorological data used are for a specific Western Australian location. Results reveal that seasonal variations affect the prediction accuracy of the wind resource, but the magnitude of this influence strongly depends on the details of the NN deployed. Factors investigated include the span of the time series needed to initially train the networks, the temporal resolution of these data, the …
Synthesis, Characteristics, And Material Properties Dataset Of Bi:Dyig-Oxide Garnet-Type Nanocomposites, M Nur-E-Alam, Mikhail Vasiliev, Kamal Alameh
Synthesis, Characteristics, And Material Properties Dataset Of Bi:Dyig-Oxide Garnet-Type Nanocomposites, M Nur-E-Alam, Mikhail Vasiliev, Kamal Alameh
Research outputs 2014 to 2021
The fabrication, annealing crystallization processes, and material properties of (Bi,Dy)3(Fe,Ga)5O12:Bi2O3 nanocomposites are investigated and summarized. The stoichiometry of these nanocomposites is optimized for magnetooptic applications using the approach of stoichiometry adjustment (implemented by means of varying RF power densities applied to the sputtering targets used to prepare the nanocomposite thin films). The crystallization processes for all developed batches of as-deposited films are carried out by annealing runs at different temperatures and process durations. This paper describes the methodologies used to optimize the compositions (by calculating the volumetric fractions of excess bismuth oxide to be mixed with the garnet-stoichiometry species during …
The Ph Sensing Properties Of Rf Sputtered Ruo2 Thin-Film Prepared Using Different Ar/O2 Flow Ratio, Ali Sardarinejad, Devendra Kumar Maurya, Kamal Alameh
The Ph Sensing Properties Of Rf Sputtered Ruo2 Thin-Film Prepared Using Different Ar/O2 Flow Ratio, Ali Sardarinejad, Devendra Kumar Maurya, Kamal Alameh
Research outputs 2014 to 2021
The influence of the Ar/O2 gas ratio during radio frequency (RF) sputtering of the RuO2 sensing electrode on the pH sensing performance is investigated. The developed pH sensor consists in an RF sputtered ruthenium oxide thin-film sensing electrode, in conjunction with an electroplated Ag/AgCl reference electrode. The performance and characterization of the developed pH sensors in terms of sensitivity, response time, stability, reversibility, and hysteresis are investigated. Experimental results show that the pH sensor exhibits super-Nernstian slopes in the range of 64.33-73.83 mV/pH for Ar/O2 gas ratio between 10/0-7/3. In particular, the best pH sensing performance, in …
Properties Of Exchange Coupled All-Garnet Magneto-Optic Thin Film Multilayer Structures, Mohammed Nur-E-Alam, Mikhail Vasilev, Viacheslav A. Kotov, Dmitry Balabanov, Ilya Akimov, Kamal Alameh
Properties Of Exchange Coupled All-Garnet Magneto-Optic Thin Film Multilayer Structures, Mohammed Nur-E-Alam, Mikhail Vasilev, Viacheslav A. Kotov, Dmitry Balabanov, Ilya Akimov, Kamal Alameh
Research outputs 2014 to 2021
The effects of exchange coupling on magnetic switching properties of all-garnet multilayer thin film structures are investigated. All-garnet structures are fabricated by sandwiching a magneto-soft material of composition type Bi1.8Lu1.2Fe3.6Al1.4O12 or Bi3Fe5O12:Dy2O3 in between two magneto-hard garnet material layers of composition type Bi2Dy1Fe4Ga1O12 or Bi2Dy1Fe4Ga1O12:Bi12O3. The fabricated RF magnetron sputtered exchange-coupled all-garnet multilayers demonstrate a very attractive combination of …
Tunable Optical Nanocavity Of Iron-Garnet With A Buried Metal Layer, Alexey N. Kuz'michev, Lars E. Kreilkamp, Mohammed Nur-E-Alam, Evgeni Bezus, Mikhail Vasilev, Iliya A. Akimov, Kamal Alameh, Manfred Bayer, Vladimir I. Belotelov
Tunable Optical Nanocavity Of Iron-Garnet With A Buried Metal Layer, Alexey N. Kuz'michev, Lars E. Kreilkamp, Mohammed Nur-E-Alam, Evgeni Bezus, Mikhail Vasilev, Iliya A. Akimov, Kamal Alameh, Manfred Bayer, Vladimir I. Belotelov
Research outputs 2014 to 2021
We report on the fabrication and characterization of a novel magnetophotonic structure designed as iron garnet based magneto-optical nanoresonator cavity constrained by two noble metal mirrors. Since the iron garnet layer requires annealing at high temperatures, the fabrication process can be rather challenging. Special approaches for the protection of metal layers against oxidation and morphological changes along with a special plasma-assisted polishing of the iron garnet layer surface were used to achieve a 10-fold enhancement of the Faraday rotation angle (up to 10.8°=μm) within a special resonance peak of 12 nm (FWHM) linewidth at a wavelength of 772 nm, in …