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Articles 2881 - 2910 of 7216
Full-Text Articles in Computer Engineering
Non-Vacuum Preparation Of Wse2 Thin Films Via The Selenization Of Hydrated Tungsten Oxide Prepared Using Chemical Solution Methods, Christopher L. Exstrom, Scott A. Darveau, Megan E. Flaconer, Jessica R. Blum, Whitney M. Colling, Natale J. Ianno
Non-Vacuum Preparation Of Wse2 Thin Films Via The Selenization Of Hydrated Tungsten Oxide Prepared Using Chemical Solution Methods, Christopher L. Exstrom, Scott A. Darveau, Megan E. Flaconer, Jessica R. Blum, Whitney M. Colling, Natale J. Ianno
Department of Electrical and Computer Engineering: Faculty Publications
It is known that tungsten oxide may be reacted with selenium sources to form WSe2 but literature reports include processing steps that involve high temperatures, reducing atmospheres, and/or oxidative pre-treatments of tungsten oxide. In this work, we report a non-vacuum process for the fabrication of compositionally high quality WSe2 thin films via the selenization of tungsten oxide under milder conditions. Tungsten source materials were various hydrated WO3 and WO2.9 compounds that were prepared using chemical solution techniques. Resulting films were selenized using a two-stage heating profile (250 oC for 15 minutes and 550 oC for 30 minutes) under a static …
Toward Biologically-Inspired Self-Healing, Resilient Architectures For Digital Instrumentation And Control Systems And Embedded Devices, Shawkat Sabah Khairullah
Toward Biologically-Inspired Self-Healing, Resilient Architectures For Digital Instrumentation And Control Systems And Embedded Devices, Shawkat Sabah Khairullah
Theses and Dissertations
Digital Instrumentation and Control (I&C) systems in safety-related applications of next generation industrial automation systems require high levels of resilience against different fault classes. One of the more essential concepts for achieving this goal is the notion of resilient and survivable digital I&C systems. In recent years, self-healing concepts based on biological physiology have received attention for the design of robust digital systems. However, many of these approaches have not been architected from the outset with safety in mind, nor have they been targeted for the automation community where a significant need exists. This dissertation presents a new self-healing digital …
Interactive Process Miner: A New Approach For Process Mining, İsmai̇l Yürek, Derya Bi̇rant, Kökten Ulaş Bi̇rant
Interactive Process Miner: A New Approach For Process Mining, İsmai̇l Yürek, Derya Bi̇rant, Kökten Ulaş Bi̇rant
Turkish Journal of Electrical Engineering and Computer Sciences
Process mining is a technique for extracting knowledge from event logs recorded by an information system. In the process discovery phase of process mining, a process model is constructed to represent the business processes systematically and to give a general opinion about the progressive of processes in the event log. The constructed process model can be very complex as a result of structured and unstructured processes recorded in real life. Previous studies proposed different approaches to filter or eliminate some processes from the model to simplify it by implementing some statistical or mathematical formulas rather than user interactions. The main …
An Integrated Approach For The Development Of An Electric Vehicle Powertrain: Design, Analysis, And Implementation, Özgür Üstün, Ramazan Nejat Tuncay, Mert Safa Mökükcü, Ömer Ci̇han Kivanç, Gürkan Tosun, Can Gökce, Murat Çakan
An Integrated Approach For The Development Of An Electric Vehicle Powertrain: Design, Analysis, And Implementation, Özgür Üstün, Ramazan Nejat Tuncay, Mert Safa Mökükcü, Ömer Ci̇han Kivanç, Gürkan Tosun, Can Gökce, Murat Çakan
Turkish Journal of Electrical Engineering and Computer Sciences
Electric motor and power electronic systems are essential elements for the performance and efficiency of electric vehicles (EVs) and hybrid electric vehicles. The inadequacy of the range due to battery limitations is compensated by powertrain solutions and innovative control algorithms. Future targets of electric powertrains are mostly based on weight, space, and efficiency issues. Highly efficient low-volume and light-weight propulsion systems increase the performance of EVs and also enhance their importance as an alternative to internal combustion engine vehicles. In this paper, a detailed propulsion system design study is presented by considering all of the important constraints of the electric …
Real-Time Implementation Of Three-Level Inverter-Based D-Statcom Using Neuro-Fuzzy Controller, Resul Çöteli̇, Hakan Açikgöz, Beşi̇r Dandil, Servet Tuncer
Real-Time Implementation Of Three-Level Inverter-Based D-Statcom Using Neuro-Fuzzy Controller, Resul Çöteli̇, Hakan Açikgöz, Beşi̇r Dandil, Servet Tuncer
Turkish Journal of Electrical Engineering and Computer Sciences
A distribution static compensator (D-STATCOM) is a custom power device connected in parallel to a power system to address electric power quality problems caused by reactive power and harmonics. To obtain high performance from a D-STATCOM, the D-STATCOM's \textit{dq}-axis currents must be controlled in an internal control loop. However, control of the D-STATCOM's currents is difficult because of its nonlinear structure, cross-coupling effect between the \textit{d}- and \textit{q}-axis, undefined dynamics, and fast changing load. Therefore, the controller to be preferred for a D-STATCOM should have a nonlinear and robust structure. In this study, a neuro-fuzzy controller (NFC), which is a …
Chronic Risk And Disease Management Model Using Structured Query Language And Predictive Analysis, Mamata Ojha
Chronic Risk And Disease Management Model Using Structured Query Language And Predictive Analysis, Mamata Ojha
Electronic Theses and Dissertations
Individuals with chronic conditions are the ones who use health care most frequently and more than 50% of top ten causes of death are chronic diseases in United States and these members always have health high risk scores. In the field of population health management, identifying high risk members is very important in terms of patient health care, disease management and cost management. Disease management program is very effective way of monitoring and preventing chronic disease and health related complications and risk management allows physicians and healthcare companies to reduce patient’s health risk, help identifying members for care/disease management along …
Design, Implementation And A Pilot Study Of Mobile Framework For Pedestrian Safety Using Smartphone Sensors, Aawesh Man Shrestha
Design, Implementation And A Pilot Study Of Mobile Framework For Pedestrian Safety Using Smartphone Sensors, Aawesh Man Shrestha
Electronic Theses and Dissertations
Pedestrian distraction from smartphones is a serious social problem that caused an ever increasing number of fatalities especially as virtual reality (VR) games have gained popularity recently. In this thesis, we present the design, implementation, and a pilot study of WiPedCross, a WiFi direct-based pedestrian safety system that senses and evaluates a risk, and alerts accordingly the user to prevent traffic accidents. In order to develop a non-intrusive, accurate, and energy-efficient pedestrian safety system, a number of technical challenges are addressed: to enhance the positioning accuracy of the user for precise risk assessment, a map-matching algorithm based on a Hidden …
Enabling Low Cost Wifi-Based Traffic Monitoring System Using Deep Learning, Sayan Sahu
Enabling Low Cost Wifi-Based Traffic Monitoring System Using Deep Learning, Sayan Sahu
Electronic Theses and Dissertations
A traffic monitoring system (TMS) is an integral part of Intelligent Transportation Systems (ITS) for traffic analysis and planning. However, covering huge miles of rural highways (119,247 miles in U.S.) with a large number of TMSs is a very challenging problem due to the cost issue. This paper aims to address the problem by developing a low-cost and portable TMS called DeepWiTraffic based on COTs WiFi devices. The proposed system enables accurate vehicle detection (counting) and classification by exploiting the unique WiFi Channel State Information (CSI) of passing vehicles. Spatial and temporal correlations of CSI amplitude and phase data are …
Cyber-Physical Embedded Systems With Transient Supervisory Command And Control: A Framework For Validating Safety Response In Automated Collision Avoidance Systems, Daniel K. Trembley
Cyber-Physical Embedded Systems With Transient Supervisory Command And Control: A Framework For Validating Safety Response In Automated Collision Avoidance Systems, Daniel K. Trembley
Graduate Dissertations and Theses
The ability to design and engineer complex and dynamical Cyber-Physical Systems (CPS) requires a systematic view that requires a definition of level of automation intent for the system. Since CPS covers a diverse range of systemized implementations of smart and intelligent technologies networked within a system of systems (SoS), the terms “smart” and “intelligent” is frequently used in describing systems that perform complex operations with a reduced need of a human-agent. The difference between this research and most papers in publication on CPS is that most other research focuses on the performance of the CPS rather than on the correctness …
Datanet: Deep Learning Based Encrypted Network Traffic Classification In Sdn Home Gateway, Pan Wang, Feng Ye, Xuejiao Chen, And Yi Qian
Datanet: Deep Learning Based Encrypted Network Traffic Classification In Sdn Home Gateway, Pan Wang, Feng Ye, Xuejiao Chen, And Yi Qian
Electrical and Computer Engineering Faculty Publications
A smart home network will support various smart devices and applications, e.g., home automation devices, E-health devices, regular computing devices, and so on. Most devices in a smart home access the Internet through a home gateway (HGW). In this paper, we propose a software-defined- network (SDN)-HGW framework to better manage distributed smart home networks and support the SDN controller of the core network. The SDN controller enables efficient network quality-of-service management based on real-time traffic monitoring and resource allocation of the core network. However, it cannot provide network management in distributed smart homes. Our proposed SDN-HGW extends the control to …
Multilabel Learning For The Online Transient Stability Assessment Of Electric Power Systems, Peyman Beyranvand, Veysel Murat İstemi̇han Genç, Zehra Çataltepe
Multilabel Learning For The Online Transient Stability Assessment Of Electric Power Systems, Peyman Beyranvand, Veysel Murat İstemi̇han Genç, Zehra Çataltepe
Turkish Journal of Electrical Engineering and Computer Sciences
Dynamic security assessment of a large power system operating over a wide range of conditions requires an intensive computation for evaluating the system's transient stability against a large number of contingencies. In this study, we investigate the application of multilabel learning for improving training and prediction time, along with the prediction accuracy, of neural networks for online transient stability assessment of power systems. We introduce a new multilabel learning method, which uses a contingency clustering step to learn similar contingencies together in the same multilabel multilayer perceptron. Experimental results on two different power systems demonstrate improved accuracy, as well as …
Novel Modified Impedance-Based Methods For Fault Location In The Presence Of A Fault Current Limiter, Javad Barati, Aref Doroudi
Novel Modified Impedance-Based Methods For Fault Location In The Presence Of A Fault Current Limiter, Javad Barati, Aref Doroudi
Turkish Journal of Electrical Engineering and Computer Sciences
A fault current limiter (FCL) is promising novel electric equipment to effectively reduce excessive short circuit current in power networks. The presence of a FCL at the time of a fault occurrence makes it necessary to consider new settings for protective relays and fault locators. This paper examines the presence of a FCL in power networks and its effects on single-ended impedance-based fault location methods. It will be shown that FCL deployment in a transmission line makes the traditional fault location method inefficient. Two modified methods are presented to solve the problem. The modified methods locate the fault point using …
Localization Of Microcalcification On The Mammogram Using Deep Convolutional Neural Network, Jieun Jhang
Localization Of Microcalcification On The Mammogram Using Deep Convolutional Neural Network, Jieun Jhang
Electronic Theses and Dissertations
Breast cancer is the most common cancer in women worldwide, and the mammogram is the most widely used screening technique for breast cancer. To make a diagnosis in the early stage of breast cancer, the appearance of masses and microcalcifications on the mammogram are two crucial indicators. Notably, the early detection of malignant microcalcifications can facilitate the diagnosis and the treatment of breast cancer at the appropriate time. Making an accurate evaluation on microcalcifications is a timeconsuming and challenging task for the radiologists due to the small size and the low contrast of microcalcification. Compared to the background and mammogram …
An Approach To Finding Parking Space Using The Csi-Based Wifi Technology, Yunfan Zhang
An Approach To Finding Parking Space Using The Csi-Based Wifi Technology, Yunfan Zhang
Electronic Theses and Dissertations
With ever-increasing number of vehicles and shortages of parking spaces, parking has always been a very important issue in transportation. It is necessary to use advanced intelligent technologies to help drivers find parking spaces, quickly. In this thesis, an approach to finding empty spaces in parking lots using the CSI-based WiFi technology is presented. First, the channel state information (CSI) of received WiFi signals is analyzed. The features of CSI data that are strongly correlated with the number of empty slots in parking lots are identified and extracted. A machine learning technique to perform multi-class classification that categorizes the input …
Wi-Fi Finger-Printing Based Indoor Localization Using Nano-Scale Unmanned Aerial Vehicles, Appala Narasimha Raju Chekuri
Wi-Fi Finger-Printing Based Indoor Localization Using Nano-Scale Unmanned Aerial Vehicles, Appala Narasimha Raju Chekuri
Electronic Theses and Dissertations
Explosive growth in the number of mobile devices like smartphones, tablets, and smartwatches has escalated the demand for localization-based services, spurring development of numerous indoor localization techniques. Especially, widespread deployment of wireless LANs prompted ever increasing interests in WiFi-based indoor localization mechanisms. However, a critical shortcoming of such localization schemes is the intensive time and labor requirements for collecting and building the WiFi fingerprinting database, especially when the system needs to cover a large space. In this thesis, we propose to automate the WiFi fingerprint survey process using a group of nano-scale unmanned aerial vehicles (NAVs). The proposed system significantly …
Review Of The Effectiveness Of Impulse Testing For The Evaluation Of Cable Insulation Quality And Recommendations For Quality Testing, Adrian Coughlan, Joseph Kearney, Tom Looby
Review Of The Effectiveness Of Impulse Testing For The Evaluation Of Cable Insulation Quality And Recommendations For Quality Testing, Adrian Coughlan, Joseph Kearney, Tom Looby
Conference papers
Abstract— This project investigates impulse breakdown testing as a means of determining the as constructed standard of MV power cable. A literature survey is undertaken to elucidate the place of this test in an overall cable test regime and to determine the factors that impact on the performance of the test method. Testing was undertaken on ESB Networks cables to establish if a merit order ranking was feasible based on this test and to determine if the test could detect defects in the inner semiconducting layer. Based on this, conclusions and recommendations are made regarding the overall applicability and usefulness …
Transformer Incipient Fault Diagnosis On The Basis Of Energy-Weighted Dga Usingan Artificial Neural Network, Md Danish Equbal, Shakeb Ahmad Khan, Tarikul Islam
Transformer Incipient Fault Diagnosis On The Basis Of Energy-Weighted Dga Usingan Artificial Neural Network, Md Danish Equbal, Shakeb Ahmad Khan, Tarikul Islam
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a transformer incipient fault diagnosis model has been developed with the help of an artificial neural network (ANN), taking into account the difference in the energy required to produce the different fault gases. The key fault gases are indicative of the fault type prevailing in the transformer. However, in conventional studies, the energy difference in fault gas formation is not considered while adopting the key gas method for fault diagnosis. In this work, a weighting factor has been used to take into account this relative difference in energy requirement for various fault gas formations. The fault gas …
Real-Time Chaff Generation For A Biometric Fuzzy Vault, Manvjeet Kaur, Sanjeev Sofat
Real-Time Chaff Generation For A Biometric Fuzzy Vault, Manvjeet Kaur, Sanjeev Sofat
Turkish Journal of Electrical Engineering and Computer Sciences
Biometric technology is rapidly being adopted in wide variety of security applications. However, the system itself is not completely foolproof and is vulnerable to many attacks. Some of the attacks on the biometric system are very severe, one of which is the attack on template security. In spite of the various template security techniques presented in the literature, none of them is able to provide security, diversity, revocability, and good performance simultaneously to the biometric system. Fuzzy vault is one of the most promising bio-cryptographic techniques to prevent the template data from being misused. To make the fuzzy vault practically …
Construction Of A Turkish Proposition Bank, Koray Ak, Cansu Toprak, Volkan Esgel, Olcay Taner Yildiz
Construction Of A Turkish Proposition Bank, Koray Ak, Cansu Toprak, Volkan Esgel, Olcay Taner Yildiz
Turkish Journal of Electrical Engineering and Computer Sciences
This paper describes our approach to developing the Turkish PropBank by adopting the semantic role-labeling guidelines of the original PropBank and using the translation of the English Penn-TreeBank as a resource. We discuss the semantic annotation process of the PropBank and language-specific cases for Turkish, the tools we have developed for annotation, and quality control for multiuser annotation. In the current phase of the project, more than 9500 sentences are semantically analyzed and predicate-argument information is extracted for 1330 verbs and 1914 verb senses. Our plan is to annotate 17,000 sentences by the end of 2017.
Analysis And Design Of A Converter Based On Noncascading Structure, Sunil Kumar, Kanwar Pal Singh Rana, Vineet Kumar
Analysis And Design Of A Converter Based On Noncascading Structure, Sunil Kumar, Kanwar Pal Singh Rana, Vineet Kumar
Turkish Journal of Electrical Engineering and Computer Sciences
In the present work, a converter employing two noncascading structures, combined in a single circuit, is presented. The power stored by the storage element is transferred to two subconverters by means of two storage capacitors that complement each other. The stress on the main power switch is of interest as it reduces as the load falls, which in turn reduces the power loss. By means of the storage elements, the input power factor as well as the load transient response can be improved simultaneously. The overall efficiency is high because the amount of power processed twice decreases. There is no …
Mutatedsocioagentsim (Msas): Semisupervised Modelling Of Multiagent Simulation To Predict And Detect The Mutation In A Camouflaged Social Network, Karthika Subbaraj, Bose Sundan
Mutatedsocioagentsim (Msas): Semisupervised Modelling Of Multiagent Simulation To Predict And Detect The Mutation In A Camouflaged Social Network, Karthika Subbaraj, Bose Sundan
Turkish Journal of Electrical Engineering and Computer Sciences
A social network is a networked structure formed by a set of agents/actors. It describes their interrelationships that facilitate the exchange and flow of resources and information. A camouflaged social network is one such community that influences the underlying structure and the profile of the agents, to cause mutation. The proposed MSAM is a novel system that simulates a multiagent network whose community structure is analyzed to identify the critical agents by studying the mutations caused due to attachment and detachment of agents. The isolation of the tagged agents will demonstrate disruption of information flow, which leads to the dismantling …
Improvement Of Air Pollution Prediction In A Smart City And Its Correlation With Weather Conditions Using Metrological Big Data, Talat Zaree, Ali Reza Honarvar
Improvement Of Air Pollution Prediction In A Smart City And Its Correlation With Weather Conditions Using Metrological Big Data, Talat Zaree, Ali Reza Honarvar
Turkish Journal of Electrical Engineering and Computer Sciences
Smart cities are an important concept for urban development. This concept addresses many current critical urban problems including traffic and environmental pollution. As utilization of the Internet of things and technology in smart cities increases, large volumes of big data are generated and collected by sensors embedded at different places in the city, which present a real-time display of what is happening throughout the city at all times. Such data should be processed and analyzed as a response to ensure effectiveness and improvement in quality of provided services; correct use and analysis of such data is valuable. Big data mining …
Topological Feature Extraction Of Nonlinear Signals And Trajectories And Its Application In Eeg Signals Classification, Saleh Lashkari, Ali Sheikhani, Mohammad Reza Hashemi Golpayegani, Ali Moghimi, Hamid Reza Kobravi
Topological Feature Extraction Of Nonlinear Signals And Trajectories And Its Application In Eeg Signals Classification, Saleh Lashkari, Ali Sheikhani, Mohammad Reza Hashemi Golpayegani, Ali Moghimi, Hamid Reza Kobravi
Turkish Journal of Electrical Engineering and Computer Sciences
This study introduces seven topological features that characterize attractor dynamic of nonlinear and chaotic trajectories in a phase space. These features quantify volume, occupied space, nonuniformity, and curvature of trajectory. The features are evaluated as initial point invariant measures by a practical approach, which means that a feature is only sensitive to dynamic changes. The Lorenz and Rossler system trajectories are employed in this evaluation. Moreover, the proposed features are used in a real world application, i.e. epileptic seizure electroencephalogram signal classification. As the result shows, these features are efficient in this task in comparison with others studies that used …
Optimum, Projected, And Regularized Extreme Learning Machine Methods With Singular Value Decomposition And L$_{2}$-Tikhonov Regularization, Mohanad Abd Shehab, Ni̇han Kahraman
Optimum, Projected, And Regularized Extreme Learning Machine Methods With Singular Value Decomposition And L$_{2}$-Tikhonov Regularization, Mohanad Abd Shehab, Ni̇han Kahraman
Turkish Journal of Electrical Engineering and Computer Sciences
The theory and implementation of an extreme learning machine (ELM) have proved that it is a simple, efficient, and accurate machine learning methodology. In an ELM, the hidden nodes are randomly initiated and fixed without iterative tuning. However, the optimal hidden layer neuron number ($L_{opt})$ is the key to ELM generalization performance where initializing this number by trial and error is not reasonably satisfied. Optimizing the hidden layer size using the leave-one-out cross validation method is a costly approach. In this paper, a fast and reliable statistical approach called optimum ELM (OELM) was developed to determine the minimum hidden layer …
Novel Low-Loss Microstrip Triplexer Using Coupled Lines And Step Impedance Cells For 4g And Wimax Applications, Abbas Rezaei, Leila Noori
Novel Low-Loss Microstrip Triplexer Using Coupled Lines And Step Impedance Cells For 4g And Wimax Applications, Abbas Rezaei, Leila Noori
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a new microstrip triplexer with flexible resonance frequencies is designed based on the properties of coupled lines, steps, and spiral cells. It operates at 2.67 GHz for 4G LTE and at 3.1 GHz and 3.43 GHz for IEEE 802.16 WiMAX. The close resonance frequencies make it suitable for frequency division duplex applications. In order to improve insertion loss, the LC equivalent circuit of the proposed resonator is analyzed. Moreover, careful alignment of the coupled lines and step impedance structures is performed to improve the insertion and return losses so that they are 0.72/0.63/0.81 dB and 24.5/24/24.7 dB, …
Secure Access Control In Multidomain Environments And Formal Analysis Of Model Specifications, Fatemeh Nazerian, Homayun Motameni, Hossein Nematzadeh
Secure Access Control In Multidomain Environments And Formal Analysis Of Model Specifications, Fatemeh Nazerian, Homayun Motameni, Hossein Nematzadeh
Turkish Journal of Electrical Engineering and Computer Sciences
Distributed multiple organizations interact with each other. If the domains employ role-based access control, one method for interaction between domains is role-mapping. However, it may violate constraints in the domains such as role hierarchy, separation of duty, and cardinality. Therefore, autonomy of the domains is lost. This paper proposes secure interoperation in multidomain environments. For this purpose, a cross-domain is created by foreign permission assignment. In an effort to maintain the autonomy of every domain, several rules are defined formally. Then, a decentralized scheme is used to provide permission mapping between domains. At the next stage, the proposed cross-domain is …
Prediction Of Gross Calorific Value Of Coal Based On Proximate Analysis Using Multiple Linear Regression And Artificial Neural Networks, Mustafa Açikkar, Osman Si̇vri̇kaya
Prediction Of Gross Calorific Value Of Coal Based On Proximate Analysis Using Multiple Linear Regression And Artificial Neural Networks, Mustafa Açikkar, Osman Si̇vri̇kaya
Turkish Journal of Electrical Engineering and Computer Sciences
Gross calorific value (GCV) of coal was predicted by using as-received basis proximate analysis data. Two main objectives of the study were to develop prediction models for GCV using proximate analysis variables and to reveal the distinct predictors of GCV. Multiple linear regression (MLR) and artifcial neural network (ANN) (multilayer perceptron MLP, general regression neural network GRNN, and radial basis function neural network RBFNN) methods were applied to the developed 11 models created by different combinations of the predictor variables. By conducting 10-fold cross-validation, the prediction accuracy of the models has been tested by using $ R^2 $, $ RMSE …
Q-Axis Current Perturbation Based Active Islanding Detection For Converter Interfaced Distributed Generators, Suman Murugesan, Venkatakirthiga Murali
Q-Axis Current Perturbation Based Active Islanding Detection For Converter Interfaced Distributed Generators, Suman Murugesan, Venkatakirthiga Murali
Turkish Journal of Electrical Engineering and Computer Sciences
Thanks to the incessant developments in technology towards extracting electric power from renewable energy resources, incorporation of distributed generators has been gaining great importance in recent years. The key expedients for such power generation include reduction in power loss and improvement in the power quality and reliability. In spite of the numerous advantages, it is mandatory to ascertain the island formation and shut down the distributed generators (DGs) during an unplanned islanding. An analyzing technique subsequent to an active islanding detection technique is proposed in this work for faster and accurate detection of island formation. The proposed technique is investigated …
Estimation Of The Depth Of Anesthesia By Using A Multioutput Least-Square Support Vector Regression, Mercedeh Jahanseir, Kamal Setarehdan, Sirous Momenzadeh
Estimation Of The Depth Of Anesthesia By Using A Multioutput Least-Square Support Vector Regression, Mercedeh Jahanseir, Kamal Setarehdan, Sirous Momenzadeh
Turkish Journal of Electrical Engineering and Computer Sciences
Today, most surgeries are performed under general anesthesia where one of the most growing methods for anesthesia depth monitoring is using electroencephalogram (EEG). The bispectral index (BIS) is the most commonly used parameter for anesthesia depth monitoring using EEG, the validity of which is still to be studied before being accepted as a routine method by clinicians. This paper proposes a new technique for detecting the depth of anesthesia by means of EEG, which is based on multioutput least-squares support vector regression (MLS-SVR), which provides the probability that the patient is in the four different possible anesthesia states. In this …
Dynamic Liquid Level Detection Method Based On Resonant Frequency Difference For Oil Wells, Wei Zhou, Juan Liu, Liqun Gan
Dynamic Liquid Level Detection Method Based On Resonant Frequency Difference For Oil Wells, Wei Zhou, Juan Liu, Liqun Gan
Turkish Journal of Electrical Engineering and Computer Sciences
The dynamic liquid level of an oil well can be used to determine the oil production strategies and analyze the reservoir performance. Therefore, it is important to measure the dynamic liquid level in an oil field. This paper proposes a novel dynamic liquid level measurement method for oil wells, where the resonant frequency difference (RFD) of the resonant acoustic signal in annular is used to calculate the dynamic liquid level. To solve the noise interference problem in the resonant acoustic signal, a spectral fast Fourier transform (FFT) method based on Welch power spectrum is proposed to obtain the RFD. First, …