Physical Sciences and Mathematics Commons^™

Improving Word Embeddings Projection For Turkish Hypernym Extraction, Savaş Yildirim

Turkish Journal of Electrical Engineering and Computer Sciences

Corpus-driven approaches can automatically explore is-a relations between the word pairs from corpus. This problem is also called hypernym extraction. Formerly, lexico-syntactic patterns have been used to solve hypernym relations. The language-specific syntactic rules have been manually crafted to build the patterns. On the other hand, recent studies have applied distributional approaches to word semantics. They extracted the semantic relations relying on the idea that similar words share similar contexts. Former distributional approaches have applied one-hot bag-of-word (BOW) encoding. The dimensionality problem of BOW has been solved by various neural network approaches, which represent words in very short and dense …

Modified Recycling Folded Cascode Ota With Enhancement In Transconductance And Output Impedance, Sudheer Raja Venishetty, Kumaravel Sundaram

Turkish Journal of Electrical Engineering and Computer Sciences

A modified recycling folded cascode (MRFC) operational transconductance amplifier (OTA) for achieving high DC gain, slew rate, and unity gain bandwidth (UGB) is proposed in this paper. Positive feedback is adopted to enhance DC gain and unity gain bandwidth. The proposed MRFC OTA is compared with conventional folded cascode (FC), recycling folded cascode (RFC), and other OTAs existing in the literature. Three OTAs, FC, RFC, and MRFC, are realized and implemented using the UMC 180 nm CMOS process for the same bias current of 300 $\mu$A. The designs are simulated in the Cadence Spectre Environment. From the simulation results, it …

Nvrh-Lut: A Nonvolatile Radiation-Hardened Hybrid Mtj/Cmos-Based Look-Up Table For Ultralow Power And Highly Reliable Fpga Designs, Vahid Jamshidi

Turkish Journal of Electrical Engineering and Computer Sciences

Complementary metal oxide semiconductor (CMOS) downscaling leads to various challenges, such as high leakage current and increase in radiation sensitivity. To solve such challenges, hybrid MTJ/CMOS technology-based design has been considered as a very promising approach thanks to the high speed, low power, good scalability, and full compatibility of magnetic tunnel junction (MTJ) devices with CMOS technology. One important application of MTJs is the efficient utilization in building nonvolatile look-up tables (NV-LUTs) used in reconfigurable logic. However, NV-LUTs face severe reliability issues in nanotechnology due to the increasing process variations, reduced supply voltage, and high energetic particle strike at sensitive …

An Improved Space Charge Distribution Analytical Model To Assess Field-Effect Transistor's Intrinsic Capacitors, Saif Ur Rehman, Umer Farooq Ahmed, Muhammad Mansoor Ahmed, Umair Rafique

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, an analytical model has been developed for improved assessment of Miller capacitors for high-frequency metal?semiconductor field-effect transistors. Depletion layer underneath the Schottky barrier gate has been divided into four distinct regions, and by evaluating the charges associated with each region, gate-to-source ($C_{GS}$) and gate-to-drain ($C_{GD}$) capacitors, {commonly known as Miller capacitors,} have been defined accordingly. Mathematical expressions have been developed both for the linear as well as for the saturation region. Miller capacitors and their variation as a function of applied bias have been assessed. It has been shown that the proposed technique offers better accuracy in …

Hypothesis-Based Vertex Shift Method For Embedding Secret Logos In The Geometric Features Of 3d Objects, Arthy R, Mala K, Suresh Babu R

Turkish Journal of Electrical Engineering and Computer Sciences

A recent challenge in information technology is to protect secret data and preserve the ownership of a product. There are many duplicate products being released on a daily basis. Owners have a high risk in proving their products. Watermarking is a technique used to preserve ownership by hiding the owner's information in their products. The proposed hypothesis-based vertex shifting algorithm embeds 2D secret logos in 3D cover objects. The 3D objects are represented using vertices and facets. 3D watermarking faces various challenges and one among them is capacity. In this work, capacity is addressed by using a hypothesis-based vertex shift …

A Novel Method Based On Comparison Using Threshold Scale For Cfar Detectors Under Environments With Conditions Of Electromagnetic Interference, Milad Daneshvar, Naser Parhizgar, Pouria Salehi

Turkish Journal of Electrical Engineering and Computer Sciences

Detection of a noisy signal is a complex process. Many radar systems are working in an environment where the signal processing parts cannot overcome the effects of interference sources due to their high power. These sources of conflict may completely erode the signal or may make a mistake in deciding. It may make the return of the echoes of the goals difficult. To solve this problem, the detector processor can use a new algorithm to estimate noise power and then can set the threshold in different positions of the cell under test. The proposed algorithm, by differentiating between homogeneous and …

Optimal Siting, Sizing, And Parameter Tuning Of Statcom And Sssc Using Mpso And Remote Coordination Of The Facts For Oscillation Damping Of Power Systems, James Garba Ambafi, Sunusi Sani Adamu

Turkish Journal of Electrical Engineering and Computer Sciences

In electromechanical oscillation damping within power system, power system stabilizers (PSSs) are often deployed. However, a PSS is less effective in damping interarea oscillation and is limited by changes in network configuration due to weak tie-lines and load variations. Consequently, this paper presents a wide-area coordination approach that damps interarea oscillations using FACTS devices and phasor measurement units. We selected a static synchronous compensator (STATCOM) and static series synchronous compensator (SSSC) for realistic power system interarea oscillation damping. The performance of the coordinated FACTS installed in a power system depends on their suitable locations, sizes, tuned parameters, and remote input …

Global Maximum Operating Point Tracking For Pv System Using Fast Convergence Firefly Algorithm, Madhusmita Mohanty, Sankar Selvakumar, Chandrasekaran Koodalsamy, Sishaj Pulikottil Simon

Turkish Journal of Electrical Engineering and Computer Sciences

Global maximum operating point (GMOP) tracking is an important requirement of solar photovoltaic (PV) systems under partial shading conditions (PSCs). Though the perturb and observe algorithm is simple and effective, it fails to recognize the GMOP. This paper explores the application of the firefly algorithm (FA) to the maximum power point tracking (MPPT) problem of PV systems. In order to determine the shortest path to reach the GMOP under various PSCs, a new fast convergence firefly algorithm (FA) is proposed. Additionally, the change in firefly position is limited to a maximum value identified based on the characteristics of the PSC. …

Dynamic Radar Cross-Section Characteristic Analysis Of Wind Turbine Based On Scaled Model Experimental, Bo Tang, Hao Chen, Li Huang, Fa Ting Yuan, Peng Feng

Turkish Journal of Electrical Engineering and Computer Sciences

Accurately acquiring and analyzing the dynamic radar cross-section (RCS) of wind turbine have a great significance to solve the reradiation interference between wind farms and radar stations. Since the results of high-frequency approximation algorithm are only applicable to the qualitative analysis of electromagnetic scattering, it is almost impossible to accurately acquire the dynamic RCS of wind turbine in actual engineering cases. To this end, we proposed to acquire the dynamic RCS of wind turbine based on the scaled model experimental measurement in a large anechoic chamber. The key techniques of setting up the scaled model as well as the experimental …

Design And Control Of An Lcl-Type Single-Phase Grid-Connected Inverter With Inverter Current Feedback Using The Phase-Delay Method, Fati̇h Evran

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a novel single-phase grid-connected microinverter system and its control applications are introduced for solar energy systems. The proposed system consists of two stages to transfer solar power to the grid. In the first stage, an isolated high-gain DC/DC converter is used to increase low solar panel output voltage. In the second stage, an inverter is used to supply a sinusoidal current to the grid. Moreover, a proportional resonant controller is adopted to reduce grid current total harmonic distortions (THDs) and an LCL filter is used to provide better harmonic attenuation. However, the ratio between the sampling frequency …

A Novel Initial Rotor Position Alignment Method For Permanent Magnet Synchronous Motor Using Incremental Encoder, Si̇nan Yilmaz, Mehmet Ti̇mur Aydemi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a new method for the alignment of the rotor of permanent magnet synchronous motors with the phase axis of the stator during start-up. Once the rotor alignment is achieved, the real rotor position angle can be measured by using an incremental encoder and this value can be used in the field oriented control of the motor. Typically, a current is forced into the q-axis. In the proposed method a current is formed in the d-axis instead. Rotor alignment with the phase axis is achieved without any sudden motion by using a PI controller in the current loop. …

A Two-Stage Power Converter Architecture With Maximum Power Extraction For Low-Power Energy Sources, Ridvan Umaz

Turkish Journal of Electrical Engineering and Computer Sciences

A two-stage power converter with maximum power extraction for energy harvesting is presented. The power converter consists of two stages; a maximum power extraction stage (i.e. first stage) and a regulation stage (i.e. second stage). The first stage consists of a number of charge pumps connected in parallel to extract power from the energy source while the second stage steps up low input voltage level to a usable level for a load. Proposed converter operates as low as 0.3 V and the output up-converts to 3.3 V. The proposed converter is aimed to extract maximum power from either low-power energy …

Survey Of Network Embedding Techniques For Social Networks, Pranav Nerurkar, Madhav Chandane, Sunil Bhirud

Turkish Journal of Electrical Engineering and Computer Sciences

High dimensionality of data is a challenging scenario in the current era as the digital transformation of the society is in process. This problem is particularly complex in social networks as in such systems, it is coupled with other challenges such as interdependency of data points and heterogeneity of data sources. To overcome such disadvantages and aid in creation of downstream applications for social network analysis, network embedding techniques have been proposed. These techniques, in themselves, are not important but are the backbone of various network-based applications. Due to the scientific interest in this domain there has been a mushrooming …

Predicting Co And Nox Emissions From Gas Turbines: Novel Data And A Benchmark Pems, Heysem Kaya, Pinar Tüfekci̇, Erdi̇nç Uzun

Turkish Journal of Electrical Engineering and Computer Sciences

Predictive emission monitoring systems (PEMS) are important tools for validation and backing up of costly continuous emission monitoring systems used in gas-turbine-based power plants. Their implementation relies on the availability of appropriate and ecologically valid data. In this paper, we introduce a novel PEMS dataset collected over five years from a gas turbine for the predictive modeling of the CO and NOx emissions. We analyze the data using a recent machine learning paradigm, and present useful insights about emission predictions. Furthermore, we present a benchmark experimental procedure for comparability of future works on the data

Recurrent Residual U-Net For Medical Image Segmentation, Md Zahangir Alom, Christopher Yakopcic, Mahmudul Hasan, Tarek M. Taha, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Deep learning (DL)-based semantic segmentation methods have been providing state-of-the-art performance in the past few years. More specifically, these techniques have been successfully applied in medical image classification, segmentation, and detection tasks. One DL technique, U-Net, has become one of the most popular for these applications. We propose a recurrent U-Net model and a recurrent residual U-Net model, which are named RU-Net and R2U-Net, respectively. The proposed models utilize the power of U-Net, residual networks, and recurrent convolutional neural networks. There are several advantages to using these proposed architectures for segmentation tasks. First, a residual unit helps when training deep …

A Survey Of Techniques For Mobile Service Encrypted Traffic Classification Using Deep Learning, Pan Wang, Xuejiao Chen, Feng Ye, Zhixin Sun

Electrical and Computer Engineering Faculty Publications

The rapid adoption of mobile devices has dramatically changed the access to various net- working services and led to the explosion of mobile service traffic. Mobile service traffic classification has been a crucial task that attracts strong interest in mobile network management and security as well as machine learning communities for past decades. However, with more and more adoptions of encryption over mobile services, it brings a lot of challenges about mobile traffic classification. Although classical machine learning approaches can solve many issues that port and payload-based methods cannot solve, it still has some limitations, such as time-consuming, costly handcrafted …

Deep Temporal Convolutional Networks For Short-Term Traffic Flow Forecasting, Wentian Zhao, Yanyun Gao, Tingxiang Ji, Xili Wan, Feng Ye, Guangwei Bai

Electrical and Computer Engineering Faculty Publications

To reduce the increasingly congestion in cities, it is essential for intelligent transportation system (ITS) to accurately forecast the short-term traffic flow to identify the potential congestion sites. In recent years, the emerging deep learning method has been introduced to design traffic flow predictors, such as recurrent neural network (RNN) and long short-term memory (LSTM), which has demonstrated its promising results. In this paper, different from existing work, we study the temporal convolutional network (TCN) and propose a deep learning framework based on TCN model for short-term city-wide traffic forecast to accurately capture the temporal and spatial evolution of traffic …

Detecting Special-Cause Variation 'Events' From Process Data Signatures, Timothy M. Young, Olga Khaliukova, Nicolas André, Alexander Petutschnigg, Timothy G. Rials, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The ability to detect the special-cause variation of incoming feedstocks from advanced sensor technology is invaluable to manufacturers. Many on-line sensors produce data signatures that require further off-line statistical processing for interpretation by operational personnel. However, early detection of changes in variation in incoming feedstocks may be imperative to promote early-stage preventive measures. A method is proposed in this applied study for developing control bands to quantify the variation of data signatures in the context of statistical process control (SPC). Control bands based on pointwise prediction intervals constructed from the Bonferroni Inequality and Bayesian smoothing splines are developed. Applications using …

Charge Storage In Wo³ Polymorphs And Their Application As Supercapacitor Electrode Material, Vaibhav Lokhande, Abhishek Lokhande, Gon Namkoong, Jin Hyeok Kim, Taeksoo Ji

Electrical & Computer Engineering Faculty Publications

Tungsten oxide is a versatile material with different applications. It has many polymorphs with varying performance in energy storage application. We report simple and facile way to synthesize four phases of tungsten oxide from same precursor materials only by changing the pH and temperature values. Monoclinic, hexagonal, orthorhombic and tetragonal phase obtained, were analyzed and tested for supercapacitor application. The electrochemical analysis of four phases indicates that the hexagonal phase is best-suited electrode material for supercapacitor. The hexagonal phase exhibits higher specific capacitance (377.5 Fg^-1 at 2 mVs^-1), higher surface capacitive contribution (75%), better stability and rate …

The Effect Of Tube Geometry On The Chiral Plasma, S. Jin, D. Zou, X. Lu, Mounir Laroussi

Electrical & Computer Engineering Faculty Publications

A chiral plasma plume has recently been reported inside a circular quartz tube without the use of an external magnetic field. It is believed that the quartz tube plays an important role in the formation of the chiral plasma plume. In this paper, to better understand how this interesting structure is generated, the effect of the tube geometry on the chiral plasma is investigated. First, the effect of the thickness of the tube wall on the chiral plasma is investigated. It is interesting to find that a too thin or too thick tube wall is not favorable for generating the …

Compact -300 Kv Dc Inverted Insulator Photogun With Biased Anode And Alkali-Antimonide Photocathode, C. Hernandez-Garcia, P. Adderley, B. Bullard, J. Benesch, J. Grames, J. Gubeli, F. Hannon, J. Hansknecht, J. Jordan, R. Kazimi, G. A. Krafft, M. A. Mamun, M. Poelker, M. L. Stutzman, R. Suleiman, M. Tiefenback, Y. Wang, S. Zhang, H. Baumgart, G. Palacios-Serrano, S. Wijethunga, J. Yoskowitz, C. A. Valerio Lizarraga, R. Montoya Soto, A. Canales Ramos

Electrical & Computer Engineering Faculty Publications

This contribution describes the latest milestones of a multiyear program to build and operate a compact −300  kV dc high voltage photogun with inverted insulator geometry and alkali-antimonide photocathodes. Photocathode thermal emittance measurements and quantum efficiency charge lifetime measurements at average current up to 4.5 mA are presented, as well as an innovative implementation of ion generation and tracking simulations to explain the benefits of a biased anode to repel beam line ions from the anode-cathode gap, to dramatically improve the operating lifetime of the photogun and eliminate the occurrence of micro-arc discharges.

Transfer Learning Approach To Multiclass Classification Of Child Facial Expressions, Megan A. Witherow, Manar D. Samad, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

The classification of facial expression has been extensively studied using adult facial images which are not appropriate ground truths for classifying facial expressions in children. The state-of-the-art deep learning approaches have been successful in the classification of facial expressions in adults. A deep learning model may be better able to learn the subtle but important features underlying child facial expressions and improve upon the performance of traditional machine learning and feature extraction methods. However, unlike adult data, only a limited number of ground truth images exist for training and validating models for child facial expression classification and there is a …

Ignition Of A Plasma Discharge Inside An Electrodeless Chamber: Methods And Characteristics, Mounir Laroussi

Electrical & Computer Engineering Faculty Publications

In this paper the generation and diagnostics of a reduced pressure (300 mTorr to 3 Torr) plasma generated inside an electrodeless containment vessel/chamber are presented. The plasma is ignited by a guided ionization wave emitted by a low temperature pulsed plasma jet. The diagnostics techniques include Intensified Charge Coupled Device (ICCD) imaging, emission spectroscopy, and Langmuir probe. The reduced-pressure discharge parameters measured are the magnitude of the electric field, the plasma electron number density and temperature, and discharge expansion speed.

Ferrite Characterization Techniques & Particle Simulations For Semiconductor Devices, Nicholas Erickson

Doctoral Dissertations

"This dissertation is divided into three papers, covering two major topics. The first topic, techniques for ferrite characterization, is discussed over the course of two papers. The second topic, particle simulations for semiconductor devices, is discussed in the last paper. In the first paper, the method for extracting permeability from ferrite materials is discussed for the Keysight 16454A permeability extraction fixture, where the ferrite material to be characterized is assumed to be homogeneous. Then the method is updated to account for layered materials. The updated method is verified through full-wave simulations. In the second paper, a planar printed circuit board …

Deep Neural Network Learning-Based Classifier Design For Big-Data Analytics, Krishnan Raghavan

Doctoral Dissertations

"In this digital age, big-data sets are commonly found in the field of healthcare, manufacturing and others where sustainable analysis is necessary to create useful information. Big-data sets are often characterized by high-dimensionality and massive sample size. High dimensionality refers to the presence of unwanted dimensions in the data where challenges such as noise, spurious correlation and incidental endogeneity are observed. Massive sample size, on the other hand, introduces the problem of heterogeneity because complex and unstructured data types must analyzed. To mitigate the impact of these challenges while considering the application of classification, a two step analysis approach is …

Relation Prediction Over Biomedical Knowledge Bases For Drug Repositioning, Mehmet Bakal

Theses and Dissertations--Computer Science

Identifying new potential treatment options for medical conditions that cause human disease burden is a central task of biomedical research. Since all candidate drugs cannot be tested with animal and clinical trials, in vitro approaches are first attempted to identify promising candidates. Likewise, identifying other essential relations (e.g., causation, prevention) between biomedical entities is also critical to understand biomedical processes. Hence, it is crucial to develop automated relation prediction systems that can yield plausible biomedical relations to expedite the discovery process. In this dissertation, we demonstrate three approaches to predict treatment relations between biomedical entities for the drug repositioning task …

Tuning The Reactivity Of Nanoenergetic Gas Generators Based On Bismuth And Iodine Oxidizers, Mkhitar A. Hobosyan, Karen S. Martirosyan

Physics and Astronomy Faculty Publications and Presentations

There is a growing interest on novel energetic materials called Nanoenergetic Gas- Generators (NGGs) which are potential alternatives to traditional energetic materials including pyrotechnics, propellants, primers and solid rocket fuels. NGGs are formulations that utilize metal powders as a fuel and oxides or hydroxides as oxidizers that can rapidly release large amount of heat and gaseous products to generate shock waves. The heat and pressure discharge, impact sensitivity, long term stability and other critical properties depend on the particle size and shape, as well as assembling procedure and intermixing degree between the components. The extremely high energy density and the …

Storage Systems For Mobile-Cloud Applications, Nafize R. Paiker

Dissertations

Mobile devices have become the major computing platform in todays world. However, some apps on mobile devices still suffer from insufficient computing and energy resources. A key solution is to offload resource-demanding computing tasks from mobile devices to the cloud. This leads to a scenario where computing tasks in the same application run concurrently on both the mobile device and the cloud.

This dissertation aims to ensure that the tasks in a mobile app that employs offloading can access and share files concurrently on the mobile and the cloud in a manner that is efficient, consistent, and transparent to locations. …

Research Progress In Hydrogen Evolution Low Noble/Non-Precious Metal Catalysts Of Water Electrolysis, Yang Li, Zhao-Yan Luo, Jun-Jie Ge, Chang-Peng Liu, Wei Xing

Journal of Electrochemistry

Hydrogen energy technology with hydrogen as an energy carrier is gaining more and more attention due to its cleanliness and high energy density. Hydrogen fuel cell vehicles have been listed as one of the ultimate energy technologies in the 21st century. Among them, sustainable hydrogen production technology is a necessary prerequisite for the future development of hydrogen energy economy. Electrolyzed water technology driven by renewable resources represents an important way to support the sustainable development of hydrogen energy economy. The development and utilization of high activity, low cost hydrogen evolution catalysts is a key factor in improving the efficiency and …

Recent Progress In Pt-Based Catalysts For Oxygen Reduction Reaction, Jing Li, Xin Feng, Zi-Dong Wei

Journal of Electrochemistry

One major challenge for a large-scale commercialization of the proton-exchange membrane fuel cells (PEMFCs) technologies that enable a shift to ‘zero-emission’ personal transportation, is the expensive and unstable Pt catalysts, which are mainly used to catalyze the sluggish kinetics of the oxygen reduction reaction (ORR) occurred on the air electrode of PEMFCs. Many research works have targets to improve the stability of Pt-based catalysts and to construct Pt/transitional metal alloys with low Pt loading amount. Herein, we provide a minireview for the Pt-based ORR catalysts based on our recent work, which covers a brief background introduction, the stability improvement of …