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Articles 2041 - 2070 of 5279
Full-Text Articles in Computer Sciences
Expected Coverage (Excov): A Proposal To Compare Fuzz Test Coverage Within An Infinite Input Space, Evan V. Swihart
Expected Coverage (Excov): A Proposal To Compare Fuzz Test Coverage Within An Infinite Input Space, Evan V. Swihart
Theses and Dissertations
A Fuzz test is an approach used to discover vulnerabilities by intentionally sending invalid inputs to a system for the purpose of triggering some type of fault or unintended effect that renders the system vulnerable to an exploit. Fuzz testing is an important cyber-testing technique used to find and fix vulnerabilities before they are exploited. The fuzzing of military data links presents a particular challenge because existing fuzzing tools cannot be easily applied to these systems. As a result, the tools and techniques used to fuzz these links vary widely in sophistication and effectiveness. Because of the infinite, or nearly …
Securing Data In Transit Using Two Channel Communication, Clark L. Wolfe
Securing Data In Transit Using Two Channel Communication, Clark L. Wolfe
Theses and Dissertations
Securing data in transit is critically important to the Department of Defense in todays contested environments. While encryption is often the preferred method to provide security, there exist applications for which encryption is too resource intensive, not cost-effective or simply not available. In this thesis, a two-channel communication system is proposed in which the message being sent can be intelligently and dynamically split over two or more channels to provide a measure of data security either when encryption is not available, or perhaps in addition to encryption. This data spiting technique employs multiple wireless channels operating at the physical layer, …
Spatial Dispersion Of Index Components Required For Building Invisibility Cloak Medium From Photonic Crystals, Saeid Jamilan, George Semouchkin, Navid Gandji, Elena Semouchkina
Spatial Dispersion Of Index Components Required For Building Invisibility Cloak Medium From Photonic Crystals, Saeid Jamilan, George Semouchkin, Navid Gandji, Elena Semouchkina
Michigan Tech Publications, Part 1
The opportunities to use dielectric photonic crystals (PhCs) as the media of cylindrical invisibility cloaks, designed using transformation optics (TO) concepts, are investigated. It is shown that TO-based prescriptions for radial index dispersion, responsible for turning waves around hidden objects, can be dropped if the PhC media support self-collimation of waves in bent crystals. Otherwise, to provide prescribed anisotropy of index dispersion, it is possible to employ PhCs with rectangular lattices. It is found, however, that at acceptable cloak thicknesses, modifications of crystal parameters do not allow for achieving the prescribed level of index anisotropy. This problem is solved by …
Scheduling Based On Interruption Analysis And Pso For Strictly Periodic And Preemptive Partitions In Integrated Modular Avionics, Hui Lu, Qianlin Zhou, Zongming Fei, Rongrong Zhou
Scheduling Based On Interruption Analysis And Pso For Strictly Periodic And Preemptive Partitions In Integrated Modular Avionics, Hui Lu, Qianlin Zhou, Zongming Fei, Rongrong Zhou
Computer Science Faculty Publications
Integrated modular avionics introduces the concept of partition and has been widely used in avionics industry. Partitions share the computing resources together. Partition scheduling plays a key role in guaranteeing correct execution of partitions. In this paper, a strictly periodic and preemptive partition scheduling strategy is investigated. First, we propose a partition scheduling model that allows a partition to be interrupted by other partitions, but minimizes the number of interruptions. The model not only retains the execution reliability of the simple partition sets that can be scheduled without interruptions, but also enhances the schedulability of the complex partition sets that …
Internet Of Underground Things: Sensing And Communications On The Field For Precision Agriculture, Mehmet C. Vuran, Abdul Salam, Rigoberto Wong, Suat Irmak
Internet Of Underground Things: Sensing And Communications On The Field For Precision Agriculture, Mehmet C. Vuran, Abdul Salam, Rigoberto Wong, Suat Irmak
School of Computing: Conference and Workshop Papers
The projected increases in World population and need for food have recently motivated adoption of information technology solutions in crop fields within precision agriculture approaches. Internet of underground things (IOUT), which consists of sensors and communication devices, partly or completely buried underground for real-time soil sensing and monitoring, emerge from this need. This new paradigm facilitates seamless integration of underground sensors, machinery, and irrigation systems with the complex social network of growers, agronomists, crop consultants, and advisors. In this paper, state-of-the-art communication architectures are reviewed, and underlying sensing technology and communication mechanisms for IOUT are presented. Recent advances in the …
A Fast And Robust Extrinsic Calibration For Rgb-D Camera Networks, Po-Chang Su, Ju Shen, Wanxin Xu, Sen-Ching S. Cheung, Ying Luo
A Fast And Robust Extrinsic Calibration For Rgb-D Camera Networks, Po-Chang Su, Ju Shen, Wanxin Xu, Sen-Ching S. Cheung, Ying Luo
Electrical and Computer Engineering Faculty Publications
From object tracking to 3D reconstruction, RGB-Depth (RGB-D) camera networks play an increasingly important role in many vision and graphics applications. Practical applications often use sparsely-placed cameras to maximize visibility, while using as few cameras as possible to minimize cost. In general, it is challenging to calibrate sparse camera networks due to the lack of shared scene features across different camera views. In this paper, we propose a novel algorithm that can accurately and rapidly calibrate the geometric relationships across an arbitrary number of RGB-D cameras on a network. Our work has a number of novel features. First, to cope …
An Overview Of The Usage Of Default Passwords, Brandon Knierem, Xiaolu Zhang, Philip Levine, Frank Breitinger, Ibrahim Baggili
An Overview Of The Usage Of Default Passwords, Brandon Knierem, Xiaolu Zhang, Philip Levine, Frank Breitinger, Ibrahim Baggili
Electrical & Computer Engineering and Computer Science Faculty Publications
The recent Mirai botnet attack demonstrated the danger of using default passwords and showed it is still a major problem. In this study we investigated several common applications and their password policies. Specifically, we analyzed if these applications: (1) have default passwords or (2) allow the user to set a weak password (i.e., they do not properly enforce a password policy). Our study shows that default passwords are still a significant problem: 61% of applications inspected initially used a default or blank password. When changing the password, 58% allowed a blank password, 35% allowed a weak password of 1 character.
Energy Slices: Benchmarking With Time Slicing, Katarina Grolinger, Hany F. Elyamany, Wilson Higashino, Miriam Am Capretz, Luke Seewald
Energy Slices: Benchmarking With Time Slicing, Katarina Grolinger, Hany F. Elyamany, Wilson Higashino, Miriam Am Capretz, Luke Seewald
Electrical and Computer Engineering Publications
Benchmarking makes it possible to identify low-performing buildings, establishes a baseline for measuring performance improvements, enables setting of energy conservation targets, and encourages energy savings by creating a competitive environment. Statistical approaches evaluate building energy efficiency by comparing measured energy consumption to other similar buildings typically using annual measurements. However, it is important to consider different time periods in benchmarking because of differences in their consumption patterns. For example, an office can be efficient during the night, but inefficient during operating hours due to occupants’ wasteful behavior. Moreover, benchmarking studies often use a single regression model for different building categories. …
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 …
Learning From Experience: An Automatic Ph Neutralization System Using Hybrid Fuzzy System And Neural Network, Ethar H.K. Alkamil, Seaar Al-Dabooni, Ahmed K. Abbas, Ralph Flori, Donald C. Wunsch
Learning From Experience: An Automatic Ph Neutralization System Using Hybrid Fuzzy System And Neural Network, Ethar H.K. Alkamil, Seaar Al-Dabooni, Ahmed K. Abbas, Ralph Flori, Donald C. Wunsch
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
In oil and gas industry, the pH level is one of the most important indicators of mud contamination while drilling. Although the process has simple components, the pH neutralization process is complicated in the mud circulation system. This difficulty is due to the high nonlinearity of the process. In this paper, the fuzzy neural network (FNN) is integrated to the fuzzy logic controller (FLC) to create a system which identifies pH fluctuation into a drilling mud system, assesses and signals its severity. And then, it automatically actuates a chemical treating fluids valve (CTFV), such as Caustic Soda (CS), for neutralizing …
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 …
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 …
Parallelization And Scalability Analysis Of The \\[1pc] 3d Spatially Variant Lattice Algorithm, Henry Roger Moncada Lopez
Parallelization And Scalability Analysis Of The \\[1pc] 3d Spatially Variant Lattice Algorithm, Henry Roger Moncada Lopez
Open Access Theses & Dissertations
The purpose of this research is to design a faster implementation of an algorithm to generate 3D spatially variant lattices (SVL) and improve its performance when it is running on a parallel computer system. The algorithm is used to synthesize a SVL for a periodic structure. The algorithm has the ability to spatially vary the unit cell, the orientation of the unit cells, lattice spacing, fill fraction, material composition, and lattice symmetry. The algorithm produces a lattice that is smooth, continuous and free of defects. The lattice spacing remains strikingly uniform even when the lattice is spatially varied. This is …
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, …