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Articles 1051 - 1080 of 7209
Full-Text Articles in Computer Engineering
Lightweight Distributed Computing Framework For Orchestrating High Performance Computing And Big Data, Muhammed Numan İnce, Meli̇h Günay, Joseph Ledet
Lightweight Distributed Computing Framework For Orchestrating High Performance Computing And Big Data, Muhammed Numan İnce, Meli̇h Günay, Joseph Ledet
Turkish Journal of Electrical Engineering and Computer Sciences
In recent years, the need for the ability to work remotely and subsequently the need for the availability of remote computer-based systems has increased substantially. This trend has seen a dramatic increase with the onset of the 2020 pandemic. Often local data is produced, stored, and processed in the cloud to remedy this flood of computation and storage needs. Historically, HPC (high performance computing) and the concept of big data have been utilized for the storage and processing of large data. However, both HPC and Hadoop can be utilized as solutions for analytical work, though the differences between these may …
A Novel Fault Detection Approach Based On Multilinear Sparse Pca: Application Onthe Semiconductor Manufacturing Processes, Riadh Toumi, Yahia Kourd, Dimitri Lefebvre
A Novel Fault Detection Approach Based On Multilinear Sparse Pca: Application Onthe Semiconductor Manufacturing Processes, Riadh Toumi, Yahia Kourd, Dimitri Lefebvre
Turkish Journal of Electrical Engineering and Computer Sciences
Batch processes are extremely important to researchers since they are widely used in many fields such as biochemistry, pharmacy, and semiconductors. The powerful batch detection method is critical to increase the performance of the overall equipment and to reduce the use of check wafers. Many techniques have been used in batch process monitoring. Among them, the multivariate statistical process control (MSPC) is very useful in batch process monitoring because of the large number of records data. Therefore, batch processes have certain characteristics, such as multimodal batch nonlinearity trajectories, which were challenged by these MSPCs. In this paper, a novel process …
Strategic Integration Of Battery Energy Storage And Photovoltaic At Low Voltage Level Considering Multiobjective Cost-Benefit, Samarjit Patnaik, Manas Nayak, Meera Viswavandya
Strategic Integration Of Battery Energy Storage And Photovoltaic At Low Voltage Level Considering Multiobjective Cost-Benefit, Samarjit Patnaik, Manas Nayak, Meera Viswavandya
Turkish Journal of Electrical Engineering and Computer Sciences
Renewable energy sources, such as solar photovoltaic (PV) systems and battery energy storage systems (BESS), help reduce greenhouse gas emissions while fulfilling the world?s growing energy demand. The inclusion of BESS reduces the peak hour demand, and control of charging and discharging of BESS can be economical for distributors facing time-based energy pricing. This paper discusses a novel multiobjective Horse herd optimisation algorithm (MOHHOA) approach, which is inspired by the social behaviour of horses in herds for PV and BESS optimal allocation in the radial distribution system. The proposed algorithm combines multiple benefits like benefits from economic gain per day, …
Two Person Interaction Recognition Based On A Dual-Coded Modified Metacognitive (Dcmmc) Extreme Learning Machine, Saman Nikzad, Afshin Ebrahimi
Two Person Interaction Recognition Based On A Dual-Coded Modified Metacognitive (Dcmmc) Extreme Learning Machine, Saman Nikzad, Afshin Ebrahimi
Turkish Journal of Electrical Engineering and Computer Sciences
Human action recognition has been an active research area for over three decades. However, state-of-the-art proposed algorithms are still far from developing error-free and fully-generalized systems to perform accurate interaction recognition. This work proposes a new method for two-person interaction recognition from videos, based on well-known cognitive theories. The main idea is to perform classification based on a theory of cognition known as dual coding theory. The theory states that human brain processes and represents two types of information to learn/classify data named analogue and symbolic codes, i.e. (verbal as analogue and visual as symbolic). To implement such a theory …
Anomaly Detection In Rotating Machinery Using Autoencoders Based On Bidirectional Lstm And Gru Neural Networks, Krishna Patra, Rabi Narayan Sethi, Dhiren Kkumar Behera
Anomaly Detection In Rotating Machinery Using Autoencoders Based On Bidirectional Lstm And Gru Neural Networks, Krishna Patra, Rabi Narayan Sethi, Dhiren Kkumar Behera
Turkish Journal of Electrical Engineering and Computer Sciences
A time series anomaly is a form of anomalous subsequence that indicates future faults will occur. The development of novel techniques for detecting this type of anomaly is significant for real-time system monitoring. Several algorithms have been used to classify anomalies successfully. However, the time series anomaly detection algorithm was not studied well. We use a new bidirectional LSTM and GRU neural networks-based hybrid autoencoder to detect if a machine is operating normally in this research. An autoencoder is trained on a set of 12 features taken from healthy operating data gathered promptly after a planned maintenance period using vibration …
Design And Implementation Of I2c Bus Protocol On Master And Slave Data Transfer Based On Fpga, Mohamad Khairi Ishak, Meenal Pradeep Kumar
Design And Implementation Of I2c Bus Protocol On Master And Slave Data Transfer Based On Fpga, Mohamad Khairi Ishak, Meenal Pradeep Kumar
Makara Journal of Technology
This paper presents the design of the inter-integrated circuit (I2C) protocol with different types of features, such as combined messages, addressing modes, different data patterns and start addresses, clock frequencies, and types of modes between the field-programmable gate array (FPGA) and test card. Moreover, all these features can be randomized and run for long hours. The FPGA and the test card respectively act as master and slave. The design architecture comprises master and slave. The master generates a START condition, in which the serial data will transact between high to low levels and the serial clock will remain high. Then, …
Enhancement Of Biogas Production Through Solid-State Anaerobic Co-Digestion Of Food Waste And Corn Cobs, Lukhi Mulia Shitophyta, Anisa Salsabila, Firanita Angraini Putri, Siti Jamilatun
Enhancement Of Biogas Production Through Solid-State Anaerobic Co-Digestion Of Food Waste And Corn Cobs, Lukhi Mulia Shitophyta, Anisa Salsabila, Firanita Angraini Putri, Siti Jamilatun
Makara Journal of Technology
Although biogas has been primarily produced through liquid anaerobic digestion, this method leads to the floating and stratification of fibers and non-homogeneous mixing, which can reduce the biogas yield. Alternatively, biogas can be produced by the solid-state anaerobic digestion (SS-AD) of organic material with a high solid content, such as corn cobs. We investigated the co-digestion of food waste and corn cobs as a biomass feedstock for SS-AD in biogas production. We measured the effects of the total solid (TS) content, percentage of food waste, and reduction in volatile solids (VS), from which we determined its appropriate kinetic model. We …
Control Strategy For Solar Energy-Saving Lamps For Optimized Energy Utilization And Sustainability Of Operation Durability: Indonesia Case, Burhanuddin Halimi, Agus Purwadi, Nana Heryana
Control Strategy For Solar Energy-Saving Lamps For Optimized Energy Utilization And Sustainability Of Operation Durability: Indonesia Case, Burhanuddin Halimi, Agus Purwadi, Nana Heryana
Makara Journal of Technology
To solve the electrification ratio issue, the Indonesian government has promoted the use of solar energy-saving lamps. This study proposes a control strategy that adopts current reference time-based profiling for solar energy-saving lamps. For optimal energy consumption, the current reference profile is determined according to users’ daily energy requirements. From the aspect of user comfort, a gradual step reference profile is also introduced to provide a subtle change in lighting intensity level. The proposed control strategy can minimize energy consumption and optimize the operation durability of the system. The concept is verified by simulating four scenarios, the results of which …
Autonomous Navigator Mobile Robot Upgrade, David Sansoucy
Autonomous Navigator Mobile Robot Upgrade, David Sansoucy
Thinking Matters Symposium
The mobile robot platform has been developed over the course of 10 years at USM. In Spring 2020, Belle-Isle and Werner updated the previous framework by rewriting the software to use the ROS framework running on an on-board Raspberry Pi 3. They also implemented navigation using an A* motion planning algorithm and image processing. In Summer 2021, Ames incorporated Lidar and Kinect sensors onto the robot to improve its real-time navigation capabilities. He also made improvements to the power distribution systems. This project aimed to build on the ROS frameworks developed by the previous 2 teams with the main goal …
Identification Of Orthologous Gene Groups Using Machine Learning, Dillon Burgess
Identification Of Orthologous Gene Groups Using Machine Learning, Dillon Burgess
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
Identification of genes that show similarity between different organisms, a.k.a orthologous genes, is an open problem in computational biology. The purpose of this thesis is to create an algorithm to group orthologous genes using machine learning. Following an optimization step to find the best characterization based on training data, we represented sequences of genes or proteins with kmer vectors. These kmer vectors were then clustered into orthologous groups using hierarchical clustering. We optimized the clustering phase with the same training data for the method and parameter selection. Our results indicated that use of protein sequences with k=2 and scaling the …
Cognality Vr: Exploring A Mobile Vr App With Multiple Stakeholders To Reduce Meltdowns In Autistic Children, Louanne E. Boyd, Espen Garner, Ian Kim, Gianna Valencia
Cognality Vr: Exploring A Mobile Vr App With Multiple Stakeholders To Reduce Meltdowns In Autistic Children, Louanne E. Boyd, Espen Garner, Ian Kim, Gianna Valencia
Engineering Faculty Articles and Research
Many autistic children can have difficulty communicating, understanding others, and interacting with new and unfamiliar environments. At times they may suffer from a meltdown. The major contributing factor to meltdowns is sensory overwhelm. Technological solutions have shown promise in improving the quality of life for autistic children-however little exists to manage meltdowns. In this work with stakeholders, we design and deploy a low cost, mobile VR application to provide relief during sensory discomfort. Through the analysis of surveys from 88 stakeholders from a variety of groups (i.e., autistic adults, children with autism, parents of autistic individuals, and medical practitioners), we …
A Low-Cost, Arduino-Based Platform For Emulating Energy Harvesting In Wireless Sensor Networks, Braden A. Miller
A Low-Cost, Arduino-Based Platform For Emulating Energy Harvesting In Wireless Sensor Networks, Braden A. Miller
ONU Student Research Colloquium
This paper presents an Arduino-based platform for emulating energy harvesting in Wireless Sensor Networks (WSNs) as a form of hardware-in-the-loop simulation. The platform makes use of a battery monitoring circuit and code implemented on the Arduino as an alternative to using significantly more expensive fully equipped energy harvesting nodes. Using embedded code to emulate the energy harvesting process allows for various energy harvesting models and processes to be tested using the same platform. The main contributions of this paper are the experimental data and analyses demonstrating the energy use characterization of the Arduino-based platform in a three-node relay network using …
Combat Robot, Wayne Lambert, Elijah Harris, Brian Eiseman, Jordan Meyer
Combat Robot, Wayne Lambert, Elijah Harris, Brian Eiseman, Jordan Meyer
ONU Student Research Colloquium
The senior capstone project that was tasked to the team was the decision of choosing a challenge within a national robotics competition. The group decided to compete at the National Robotics Challenge in Marion, Ohio. The idea was to participate in the combat robot competition at this NRC event. Once this decision had been made the next steps were to get an idea of what the rules and requirements of the competition were and to try and to sketch a very rough drawing of what the ideal robot should look like. From there it was decided to start a timeline …
Microscopic Nuclei Classification, Segmentation, And Detection With Improved Deep Convolutional Neural Networks (Dcnn), Md Zahangir Alom, Vijayan K. Asari, Anil Parwani, Tarek M. Taha
Microscopic Nuclei Classification, Segmentation, And Detection With Improved Deep Convolutional Neural Networks (Dcnn), Md Zahangir Alom, Vijayan K. Asari, Anil Parwani, Tarek M. Taha
Electrical and Computer Engineering Faculty Publications
Background Nuclei classification, segmentation, and detection from pathological images are challenging tasks due to cellular heterogeneity in the Whole Slide Images (WSI). Methods In this work, we propose advanced DCNN models for nuclei classification, segmentation, and detection tasks. The Densely Connected Neural Network (DCNN) and Densely Connected Recurrent Convolutional Network (DCRN) models are applied for the nuclei classification tasks. The Recurrent Residual U-Net (R2U-Net) and the R2UNet-based regression model named the University of Dayton Net (UD-Net) are applied for nuclei segmentation and detection tasks respectively. The experiments are conducted on publicly available datasets, including Routine Colon Cancer (RCC) classification and …
Development Of A Compliant Gripper Driven By 3 Dof Soft Robot, Derek M. Price Ii, Ricardo Ramirez, Pt Angel Tran
Development Of A Compliant Gripper Driven By 3 Dof Soft Robot, Derek M. Price Ii, Ricardo Ramirez, Pt Angel Tran
Symposium of Student Scholars
Industrial robots are moving toward automation, which makes it increasingly necessary to replace the functions traditionally performed by humans with robotics. Pick and place operation is a prime example of such automation. Robots that pick up and place objects mimic the human action of picking an object up and placing it in a targeted location. It has led to the development of robotic end-effectors that have a human-like feel. Grippers can be articulated in various ways depending on their application area and well-defined desired tasks. As compliant and soft links deflect more under the same load than their rigid body …
Practical Considerations And Applications For Autonomous Robot Swarms, Rory Alan Hector
Practical Considerations And Applications For Autonomous Robot Swarms, Rory Alan Hector
LSU Doctoral Dissertations
In recent years, the study of autonomous entities such as unmanned vehicles has begun to revolutionize both military and civilian devices. One important research focus of autonomous entities has been coordination problems for autonomous robot swarms. Traditionally, robot models are used for algorithms that account for the minimum specifications needed to operate the swarm. However, these theoretical models also gloss over important practical details. Some of these details, such as time, have been considered before (as epochs of execution). In this dissertation, we examine these details in the context of several problems and introduce new performance measures to capture practical …
Machine Learning Based Medical Image Deepfake Detection: A Comparative Study, Siddharth Solaiyappan, Yuxin Wen
Machine Learning Based Medical Image Deepfake Detection: A Comparative Study, Siddharth Solaiyappan, Yuxin Wen
Engineering Faculty Articles and Research
Deep generative networks in recent years have reinforced the need for caution while consuming various modalities of digital information. One avenue of deepfake creation is aligned with injection and removal of tumors from medical scans. Failure to detect medical deepfakes can lead to large setbacks on hospital resources or even loss of life. This paper attempts to address the detection of such attacks with a structured case study. Specifically, we evaluate eight different machine learning algorithms, which include three conventional machine learning methods (Support Vector Machine, Random Forest, Decision Tree) and five deep learning models (DenseNet121, DenseNet201, ResNet50, ResNet101, VGG19) …
Manipulating Image Luminance To Improve Eye Gaze And Verbal Behavior In Autistic Children, Louanne Boyd, Vincent Berardi, Deanna Hughes, Franceli L. Cibrian, Jazette Johnson, Viseth Sean, Eliza Delpizzo-Cheng, Brandon Mackin, Ayra Tusneem, Riya Mody, Sara Jones, Karen Lotich
Manipulating Image Luminance To Improve Eye Gaze And Verbal Behavior In Autistic Children, Louanne Boyd, Vincent Berardi, Deanna Hughes, Franceli L. Cibrian, Jazette Johnson, Viseth Sean, Eliza Delpizzo-Cheng, Brandon Mackin, Ayra Tusneem, Riya Mody, Sara Jones, Karen Lotich
Engineering Faculty Articles and Research
Autism has been characterized by a tendency to attend to the local visual details over surveying an image to understand the gist–a phenomenon called local interference. This sensory processing trait has been found to negatively impact social communication. Although much work has been conducted to understand these traits, little to no work has been conducted to intervene to provide support for local interference. Additionally, recent understanding of autism now introduces the core role of sensory processing and its impact on social communication. However, no interventions to the end of our knowledge have been explored to leverage this relationship. This work …
A Low-Cost, Long-Range, And Solar-Based Iot Soil Quality Monitor, Salvador Garcia, Trina Nguyen, Julian Wong
A Low-Cost, Long-Range, And Solar-Based Iot Soil Quality Monitor, Salvador Garcia, Trina Nguyen, Julian Wong
Interdisciplinary Design Senior Theses
The project objective is to create a low-cost, long-range, and solar-based IoT soil quality monitoring system. The system must transmit packages of data gathered from separate nodes, consisting of two dierent types of sensors, to a centralized gateway receiver to be displayed to the user in an elegant and readable manner. The end goal of the project is to supplement produce grown by large agricultural bodies around the United States without the misuse of water resources. This report presents the need for this system, details the components of the system, and the rationale behind design choices. It serves as a …
Towards Improved Inertial Navigation By Reducing Errors Using Deep Learning Methodology, Hua Chen, Tarek M. Taha, Vamsy P. Chodavarapu
Towards Improved Inertial Navigation By Reducing Errors Using Deep Learning Methodology, Hua Chen, Tarek M. Taha, Vamsy P. Chodavarapu
Electrical and Computer Engineering Faculty Publications
Autonomous vehicles make use of an Inertial Navigation System (INS) as part of vehicular sensor fusion in many situations including GPS-denied environments such as dense urban places, multi-level parking structures, and areas with thick tree-coverage. The INS unit incorporates an Inertial Measurement Unit (IMU) to process the linear acceleration and angular velocity data to obtain orientation, position, and velocity information using mechanization equations. In this work, we describe a novel deep-learning-based methodology, using Convolutional Neural Networks (CNN), to reduce errors from MEMS IMU sensors. We develop a CNN-based approach that can learn from the responses of a particular inertial sensor …
Learning Domain Invariant Information To Enhance Presentation Attack Detection In Visible Face Recognition Systems, Jennifer Hamblin
Learning Domain Invariant Information To Enhance Presentation Attack Detection In Visible Face Recognition Systems, Jennifer Hamblin
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
Face signatures, including size, shape, texture, skin tone, eye color, appearance, and scars/marks, are widely used as discriminative, biometric information for access control. Despite recent advancements in facial recognition systems, presentation attacks on facial recognition systems have become increasingly sophisticated. The ability to detect presentation attacks or spoofing attempts is a pressing concern for the integrity, security, and trust of facial recognition systems. Multi-spectral imaging has been previously introduced as a way to improve presentation attack detection by utilizing sensors that are sensitive to different regions of the electromagnetic spectrum (e.g., visible, near infrared, long-wave infrared). Although multi-spectral presentation attack …
Assessing Security Risks With The Internet Of Things, Faith Mosemann
Assessing Security Risks With The Internet Of Things, Faith Mosemann
Senior Honors Theses
For my honors thesis I have decided to study the security risks associated with the Internet of Things (IoT) and possible ways to secure them. I will focus on how corporate, and individuals use IoT devices and the security risks that come with their implementation. In my research, I found out that IoT gadgets tend to go unnoticed as a checkpoint for vulnerability. For example, often personal IoT devices tend to have the default username and password issued from the factory that a hacker could easily find through Google. IoT devices need security just as much as computers or servers …
The Music Bluetooth Controller: An Intersection Between Technology And Music, Lydia Wu
The Music Bluetooth Controller: An Intersection Between Technology And Music, Lydia Wu
Senior Honors Theses
The modern musician faces a new challenge: how can technology be used to enhance a performance? This thesis documents the development of a Bluetooth remote controller that will aid today’s performing musicians by interacting with a digital display (e.g., an iPad) to flip musical score pages remotely. At its core, while mimicking a Bluetooth pedal (the current industry standard), this device attaches to the musician’s hand. In its pilot stages, the device has been referred to “MBC” (Music Bluetooth Controller).
Ux/U-Eye: Designing Graphical User Interfaces For Exclusive Eye Gaze Control, Timothy Curol
Ux/U-Eye: Designing Graphical User Interfaces For Exclusive Eye Gaze Control, Timothy Curol
Honors Capstones
No abstract provided.
Privacy-Preserving Information Security For The Energy Grid Of Things, Mohammed Alsaid, Nirupama Bulusu, Abdullah Barghouti, N. Sonali Fernando, John M. Acken, Tylor E. Slay, Robert B. Bass
Privacy-Preserving Information Security For The Energy Grid Of Things, Mohammed Alsaid, Nirupama Bulusu, Abdullah Barghouti, N. Sonali Fernando, John M. Acken, Tylor E. Slay, Robert B. Bass
Electrical and Computer Engineering Faculty Publications and Presentations
Smart grid infrastructure relies on information exchange between multiple actors in order to ensure system reliability. These actors include but are not limited to smart loads, grid control, and energy management technologies. As information exchange between these actors is susceptible to cyber-attacks, security and privacy issues are indispensable to ensure a reliable and stable grid. This position paper proposes a privacy-preserving, trust-augmented secure scheme for a smart grid implementation.
A Deep Learning-Based Approach To Extraction Of Filler Morphology In Sem Images With The Application Of Automated Quality Inspection, Md. Fashiar Rahman, Tzu-Liang Bill Tseng, Jianguo Wu, Yuxin Wen, Yirong Lin
A Deep Learning-Based Approach To Extraction Of Filler Morphology In Sem Images With The Application Of Automated Quality Inspection, Md. Fashiar Rahman, Tzu-Liang Bill Tseng, Jianguo Wu, Yuxin Wen, Yirong Lin
Engineering Faculty Articles and Research
Automatic extraction of filler morphology (size, orientation, and spatial distribution) in Scanning Electron Microscopic (SEM) images is essential in many applications such as automatic quality inspection in composite manufacturing. Extraction of filler morphology greatly depends on accurate segmentation of fillers (fibers and particles), which is a challenging task due to the overlap of fibers and particles and their obscure presence in SEM images. Convolution Neural Networks (CNNs) have been shown to be very effective at object recognition in digital images. This paper proposes an automatic filler detection system in SEM images, utilizing a Mask Region-based CNN architecture. The proposed system …
Queueing Theory Model Of Pentose Phosphate Pathway, Sylwester M. Kloska, Krzysztof Pałczyński, Tomasz Marciniak, Tomasz Talaśka, Marissa Miller, Beata J. Wysocki, Paul H. Davis, Tadeusz A. Wysocki
Queueing Theory Model Of Pentose Phosphate Pathway, Sylwester M. Kloska, Krzysztof Pałczyński, Tomasz Marciniak, Tomasz Talaśka, Marissa Miller, Beata J. Wysocki, Paul H. Davis, Tadeusz A. Wysocki
Department of Electrical and Computer Engineering: Faculty Publications
Due to its role in maintaining the proper functioning of the cell, the pentose phosphate pathway (PPP) is one of the most important metabolic pathways. It is responsible for regulating the concentration of simple sugars and provides precursors for the synthesis of amino acids and nucleotides. In addition, it plays a critical role in maintaining an adequate level of NADPH, which is necessary for the cell to fight oxidative stress. These reasons prompted the authors to develop a computational model, based on queueing theory, capable of simulating changes in PPP metabolites’ concentrations. The model has been validated with empirical data …
Three Wave Mixing In Epsilon-Near-Zero Plasmonic Waveguides For Signal Regeneration, Nicholas Mirchandani, Mark C. Harrison
Three Wave Mixing In Epsilon-Near-Zero Plasmonic Waveguides For Signal Regeneration, Nicholas Mirchandani, Mark C. Harrison
Engineering Faculty Articles and Research
Vast improvements in communications technology are possible if the conversion of digital information from optical to electric and back can be removed. Plasmonic devices offer one solution due to optical computing’s potential for increased bandwidth, which would enable increased throughput and enhanced security. Plasmonic devices have small footprints and interface with electronics easily, but these potential improvements are offset by the large device footprints of conventional signal regeneration schemes, since surface plasmon polaritons (SPPs) are incredibly lossy. As such, there is a need for novel regeneration schemes. The continuous, uniform, and unambiguous digital information encoding method is phase-shift-keying (PSK), so …
Adaptive Output Tracking Of Distributed Parameter Systems, İhsan Berk Altiner, Mustafa Doğan, Janset Daşdemi̇r
Adaptive Output Tracking Of Distributed Parameter Systems, İhsan Berk Altiner, Mustafa Doğan, Janset Daşdemi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we consider the unknown trajectory tracking problem for stable distributed parameter systems. The main assumptions are that trajectory signals are generated by an unknown finite-dimensional exosystem that is a marginally stable system and the tracking error is available for measurement. In order to achieve perfect error regulation, a frequency estimator scheme is proposed to estimate unknown exosystem parameters, and the control law that is designed based on geometric output regulation theory is revisited. The success of the proposed method is demonstrated on a parabolic heat equation and a first-order hyperbolic partial differential equation.
Microwave Hyperthermia Application With Bioimplant Single Slot Coaxial Antennadesign For Mouse Breast Cancer Treatment, Ahmet Ri̇fat Görgün, Cem Baytöre, Selçuk Çömlekçi̇, Mehmet İbrahi̇m Tuğlu, Adnan Kaya
Microwave Hyperthermia Application With Bioimplant Single Slot Coaxial Antennadesign For Mouse Breast Cancer Treatment, Ahmet Ri̇fat Görgün, Cem Baytöre, Selçuk Çömlekçi̇, Mehmet İbrahi̇m Tuğlu, Adnan Kaya
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, a novel animal model for the breast cancer treatment which contains hyperthermia is proposed. For this main purpose a low cost, interstitial, bioimplant antenna by short ended single slot design is proposed to heat the cancerous tissues. Both the theoretical background of the proposed system and the simulation and measurement results of antenna design are presented. An artificial tissue phantom model has been created under laboratory conditions and then the utility of the proposed antenna has been tested on this model. Artificial tissues have been heated by 25W to (41-44 ? C) in a short time like …