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2020

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Articles 2491 - 2520 of 2675

Full-Text Articles in Computer Engineering

Detection Of Wagyu Beef Sources With Image Classification Using Convolutional Neural Network, Nattakorn Kointarangkul Jan 2020

Detection Of Wagyu Beef Sources With Image Classification Using Convolutional Neural Network, Nattakorn Kointarangkul

Chulalongkorn University Theses and Dissertations (Chula ETD)

Wagyu beef originated in Japan. However, there are many types of Wagyu beef in the market around the globe. Primary sources include Australia, USA, Canada and the United Kingdom. The authentic Japanese Wagyu is well known for its intense marbling, juicy rich flavor and tenderness. Observing that there are differences in flavor, texture, and quality between distinct sources of Wagyu. This research presents an AI-based approach to identify Wagyu beef sources with image classification. The input images were collected from reliable sources on the internet and augmented with DCGAN. Deep neural networks, CNN, was constructed to detect the marbled fat …

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Learning Personally Identifiable Information Transmission In Android Applications By Using Data From Fast Static Code Analysis, Nattanon Wongwiwatchai Jan 2020

Learning Personally Identifiable Information Transmission In Android Applications By Using Data From Fast Static Code Analysis, Nattanon Wongwiwatchai

Chulalongkorn University Theses and Dissertations (Chula ETD)

The ease of use of mobile devices has resulted in a significant increase in the everyday use of mobile applications as well as the amount of personal information stored on devices. Users are becoming more aware of applications' access to their personal information, as well as the risk that these applications may unwittingly transmit Personally Identifiable Information (PII) to third-party servers. There is no simple way to determine whether or not an application transmits PII. If this information could be made available to users before installing new applications, they could weigh the pros and cons of having the risk of …

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Using Automatic Speech Recognition To Assess Thai Speech Language Fluency In Montreal Cognitive Assessment (Moca), Pimarn Kantithammakorn Jan 2020

Using Automatic Speech Recognition To Assess Thai Speech Language Fluency In Montreal Cognitive Assessment (Moca), Pimarn Kantithammakorn

Chulalongkorn University Theses and Dissertations (Chula ETD)

The Montreal Cognitive Assessment (MoCA), a widely accepted screening tool for identifying patients with mild cognitive impairment (MCI), includes a language fluency test of verbal functioning where scores are based on the number of unique correct words produced by the test-taker. However, with different languages, it is possible that unique words may be counted differently. This study focuses on Thai as a language that differs from English in its type of word combination. We applied various automatic speech recognition (ASR) techniques to develop an assisted scoring system for the language fluency test of the MoCA with Thai language support. The …

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Accurate Surface Ultraviolet Radiation Forecasting For Clinical Applications With Deep Neural Network, Raksit Raksasat Jan 2020

Accurate Surface Ultraviolet Radiation Forecasting For Clinical Applications With Deep Neural Network, Raksit Raksasat

Chulalongkorn University Theses and Dissertations (Chula ETD)

Exposure to appropriate doses of UV radiation provides enormously health and medical treatment benefits including psoriasis. Typical hospital-based phototherapy cabinets contain a bunch of artificial lamps, either broad-band (main emission spectrum 280-360 nm, maximum 320 nm), or narrow-band UV B irradiation (main emission spectrum 310-315nm, maximum 311nm). For patients who cannot access phototherapy centers, sun-bathing, or heliotherapy, can be a safe and effective treatment alternative. However, as sunlight contains the full range of UV radiation (290-400 nm), careful sun-bathing supervised by photodermatologist based on accurate UV radiation forecast is vital to minimize potential adverse effects. Here, using 10-year UV radiation …

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Med-Asa Smart Task-Volunteer Matching System, Taweesin Wongpinkaew Jan 2020

Med-Asa Smart Task-Volunteer Matching System, Taweesin Wongpinkaew

Chulalongkorn University Theses and Dissertations (Chula ETD)

In the context of healthcare, volunteers play an important role in improving the patient's experience and lowering the operational cost. However, the process which facilitate their management is reported to be problematic. In this thesis, the problems of the current system is explored, and a potential solution of a new IT system is outlined. The system was tested for a duration of 2 month during the COVID-19 outbreak in Thailand. SUS and an in-depth interview was conducted in order to gauge the usability and the effectiveness the system. The time it takes for the volunteers to go through with the …

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Systematic Model-Based Design Assurance And Property-Based Fault Injection For Safety Critical Digital Systems, Athira Varma Jayakumar Jan 2020

Systematic Model-Based Design Assurance And Property-Based Fault Injection For Safety Critical Digital Systems, Athira Varma Jayakumar

Theses and Dissertations

With advances in sensing, wireless communications, computing, control, and automation technologies, we are witnessing the rapid uptake of Cyber-Physical Systems across many applications including connected vehicles, healthcare, energy, manufacturing, smart homes etc. Many of these applications are safety-critical in nature and they depend on the correct and safe execution of software and hardware that are intrinsically subject to faults. These faults can be design faults (Software Faults, Specification faults, etc.) or physically occurring faults (hardware failures, Single-event-upsets, etc.). Both types of faults must be addressed during the design and development of these critical systems. Several safety-critical industries have widely adopted …

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Implementation Of A Hierarchical, Embedded, Cyber Attack Detection System For Spi Devices On Unmanned Aerial Systems, Jeremy J. Price Jan 2020

Implementation Of A Hierarchical, Embedded, Cyber Attack Detection System For Spi Devices On Unmanned Aerial Systems, Jeremy J. Price

Theses and Dissertations

Unmanned Aerial Systems (UAS) create security concerns as their roles expand in commercial, military, and consumer spaces. The need to secure these systems is recognized in the architecture for a Hierarchical, Embedded, Cyber Attack Detection (HECAD) system. HECAD passively monitors the communication between a flight controller and all its peripherals like sensors and actuators. It ensures the functionality of a UAS is within the set of defined behavior and reports all potential problems, whether the errors were caused by cyber attacks or other physical faults. A portion of the design for Serial Peripheral Interface (SPI) devices on board a flight …

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Data Science Methods For Standardization, Safety, And Quality Assurance In Radiation Oncology, Khajamoinuddin Syed Jan 2020

Data Science Methods For Standardization, Safety, And Quality Assurance In Radiation Oncology, Khajamoinuddin Syed

Theses and Dissertations

Radiation oncology is the field of medicine that deals with treating cancer patients through ionizing radiation. The clinical modality or technique used to treat the cancer patients in the radiation oncology domain is referred to as radiation therapy. Radiation therapy aims to deliver precisely measured dose irradiation to a defined tumor volume (target) with as minimal damage as possible to surrounding healthy tissue (organs-at-risk), resulting in eradication of the tumor, high quality of life, and prolongation of survival. A typical radiotherapy process requires the use of different clinical systems at various stages of the workflow. The data generated in these …

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Remote Communication In Wilderness Search And Rescue: Implications For The Design Of Emergency Distributed-Collaboration Tools For Network-Sparse Environments, Brennan Jones, Anthony Tang, Carman Neustaedter Jan 2020

Remote Communication In Wilderness Search And Rescue: Implications For The Design Of Emergency Distributed-Collaboration Tools For Network-Sparse Environments, Brennan Jones, Anthony Tang, Carman Neustaedter

Research Collection School Of Computing and Information Systems

Wilderness search and rescue (WSAR) requires careful communication between workers in different locations. To understand the contexts from which WSAR workers communicate and the challenges they face, we interviewed WSAR workers and observed a mock-WSAR scenario. Our findings illustrate that WSAR workers face challenges in maintaining a shared mental model. This is primarily done through distributed communication using two-way radios and cell phones for text and photo messaging; yet both implicit and explicit communication suffer. WSAR workers send messages for various reasons and share different types of information with varying levels of urgency. This warrants the use of multiple communication …

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Business Analytics/Business Intelligence And It Infrastructure : Impact On Organizational Agility, Xiaofeng Chen, Keng Siau Jan 2020

Business Analytics/Business Intelligence And It Infrastructure : Impact On Organizational Agility, Xiaofeng Chen, Keng Siau

Research Collection School Of Computing and Information Systems

This is an empirical research investigating the impact of business analytics (BA) and business intelligence (BI) use, IT infrastructure flexibility, and their interactions on organizational agility. Synthesizing the systems theory and awareness-motivation-capability framework, the authors propose that BA-Use, IT infrastructure flexibility, and their interactions significantly influence organizational agility. The results show the significant association of BA use and IT infrastructure flexibility with organizational agility. The results also suggest that BA use may demand corporations to build a more flexible IT infrastructure. However, the data does not reveal the proposed interaction between the two drivers of organizational agility.

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A Review Of Emotion Sensing: Categorization Models And Algorithms, Zhaoxia Wang, Seng-Beng Ho, Erik Cambria Jan 2020

A Review Of Emotion Sensing: Categorization Models And Algorithms, Zhaoxia Wang, Seng-Beng Ho, Erik Cambria

Research Collection School Of Computing and Information Systems

Sentiment analysis consists in the identification of the sentiment polarity associated with a target object, such as a book, a movie or a phone. Sentiments reflect feelings and attitudes, while emotions provide a finer characterization of the sentiments involved. With the huge number of comments generated daily on the Internet, besides sentiment analysis, emotion identification has drawn keen interest from different researchers, businessmen and politicians for polling public opinions and attitudes. This paper reviews and discusses existing emotion categorization models for emotion analysis and proposes methods that enhance existing emotion research. We carried out emotion analysis by inviting experts from …

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A Review On Embedded Field Programmable Gate Array Architectures And Configuration Tools, Khouloud Bouaziz, Abdulfattah M. Obeid, Sonda Chtourou, Mohamed Abid Jan 2020

A Review On Embedded Field Programmable Gate Array Architectures And Configuration Tools, Khouloud Bouaziz, Abdulfattah M. Obeid, Sonda Chtourou, Mohamed Abid

Turkish Journal of Electrical Engineering and Computer Sciences

Nowadays, systems-on-chip have reached a level where nonrecurring engineering costs have become a great challenge due to the increase of design complexity and postfabrication errors. Embedded field programmable gate arrays (eFPGAs) represent a viable alternative to overcome these issues since they provide postmanufacturing flexibility that can reduce the number of chip redesigns and amortize chip fabrication cost. In this paper, we present an overview on eFPGAs and their architectures, computer aided design (CAD) tools, and design challenges. An eFPGA must be well-designed and accompanied by an optimized CAD tool suite to respond to target application's requirements in terms of power …

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Simulation And Analysis Of Wind Turbine Radar Echo Based On 3-D Scattering Point Model, Jiangong Zhang, Bin Hao, Bo Tang, Li Huang, Jiawei Yang Jan 2020

Simulation And Analysis Of Wind Turbine Radar Echo Based On 3-D Scattering Point Model, Jiangong Zhang, Bin Hao, Bo Tang, Li Huang, Jiawei Yang

Turkish Journal of Electrical Engineering and Computer Sciences

Wind turbine (WT) arrays in wind farms can cause serious interference on nearby radar stations. This interference could be filtered out if wind turbine radar echo (WTRE) can be obtained accurately. Considering the singleness of in-field experiments, numerical simulation became the majority among such works, but few of them reached necessary accuracy. Therefore, we propose a solution method of WTRE based on three-dimensional (3-D) scattering point model. Firstly, we use the nonuniform rational B-spline to build the 3-D model of WT. Secondly, based on the method of moments (MoM), the Rao-Wilton-Gisson (RWG) basis function is adopted to discretize the integral …

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Design Of A High Performance Narrowband Low Noise Amplifier Using An On-Chip Orthogonal Series Stacked Differential Fractal Inductor For 5g Applications, Sunil Kumar Tumma, Bheemarao Nistala Jan 2020

Design Of A High Performance Narrowband Low Noise Amplifier Using An On-Chip Orthogonal Series Stacked Differential Fractal Inductor For 5g Applications, Sunil Kumar Tumma, Bheemarao Nistala

Turkish Journal of Electrical Engineering and Computer Sciences

Inductors play a crucial role in the design of radio frequency integrated circuits (RFICs) and they typically consume a considerably large area and have a low-quality factor at high frequencies. The employment of fractal structure in on-chip inductors helps in improving the quality factor and also reduces the overall area besides improving the inductance value. In this paper, an orthogonal series stacked differential fractal inductor is proposed and the same is used to design a low noise amplifier (LNA) for 5G band (27--30 GHz) applications. The proposed inductor is fabricated on a multilayer printed circuit board and the measurement results …

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A Hybrid Model Based On The Convolutional Neural Network Model And Artificial Bee Colony Or Particle Swarm Optimization-Based Iterative Thresholding For The Detection Of Bruised Apples, Mahmut Heki̇m, Onur Cömert, Kemal Adem Jan 2020

A Hybrid Model Based On The Convolutional Neural Network Model And Artificial Bee Colony Or Particle Swarm Optimization-Based Iterative Thresholding For The Detection Of Bruised Apples, Mahmut Heki̇m, Onur Cömert, Kemal Adem

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, apple images taken with near-infrared (NIR) cameras were classified as bruised and healthy objects using iterative thresholding approaches based on artificial bee colony (ABC) and particle swarm optimization (PSO) algorithms supported by a convolutional neural network (CNN) deep learning model. The proposed model includes the following stages: image acquisition, image preprocessing, the segmentation of anatomical regions (stem-calyx regions) to be discarded, the detection of bruised areas on the apple images, and their classification. For this aim, by using the image acquisition platform with a NIR camera, a total of 1200 images at 6 different angles were taken …

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A Novel Semisupervised Classification Method Via Membership And Polyhedral Conic Functions, Nur Uylaş Sati Jan 2020

A Novel Semisupervised Classification Method Via Membership And Polyhedral Conic Functions, Nur Uylaş Sati

Turkish Journal of Electrical Engineering and Computer Sciences

In real-world problems, finding sufficient labeled data for defining classification rules is very difficult. This paper suggests a new semisupervised multiclass classification method. In the initialization, new membership functions are defined by utilizing the labeled data?Äôs medoids and means. Then the unlabeled points are labeled with the class of the highest membership value. In the supervised learning phase, separation via the polyhedral conic functions (PCFs) approach is improved by using defined membership values in the linear programming problem. The suggested algorithm is tested on real-world datasets and compared with the state-of-the-art semisupervised methods. The results obtained indicate that the suggested …

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Integrated Topic Modeling And Sentiment Analysis: A Review Rating Prediction Approach For Recommender Systems, Anbazhagan Mahadevan, Michael Arock Jan 2020

Integrated Topic Modeling And Sentiment Analysis: A Review Rating Prediction Approach For Recommender Systems, Anbazhagan Mahadevan, Michael Arock

Turkish Journal of Electrical Engineering and Computer Sciences

Recommender systems (RSs) are running behind E-commerce websites to recommend items that are likely to be bought by users. Most of the existing RSs are relying on mere star ratings while making recommendations. However, ratings alone cannot help RSs make accurate recommendations, as they cannot properly capture sentiments expressed towards various aspects of the items. The other rich and expressive source of information available that can help make accurate recommendations is user reviews. Because of their voluminous nature, reviews lead to the information overloading problem. Hence, drawing out the user opinion from reviews is a decisive job. Therefore, this paper …

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Retinal Vessel Segmentation Using Modified Symmetrical Local Threshold, Umar Özgünalp Jan 2020

Retinal Vessel Segmentation Using Modified Symmetrical Local Threshold, Umar Özgünalp

Turkish Journal of Electrical Engineering and Computer Sciences

Retinal vessel segmentation is important for the identification of many diseases including glaucoma, hypertensive retinopathy, diabetes, and hypertension. Moreover, retinal vessel diameter is associated with cardiovascular mortality. Accurate detection of blood vessels improves the detection of exudates in color fundus images, as well as detection of the retinal nerve, optic disc, or fovea. A retinal vessel is a darker stripe on a lighter background. Thus, the objective is very similar to the lane detection task for intelligent vehicles. A lane on a road is a light stripe on a darker background (i.e. asphalt). For lane detection, the symmetrical local threshold …

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Detailed Modeling Of A Thermoelectric Generator For Maximum Power Point Tracking, Hayati̇ Mamur, Yusuf Çoban Jan 2020

Detailed Modeling Of A Thermoelectric Generator For Maximum Power Point Tracking, Hayati̇ Mamur, Yusuf Çoban

Turkish Journal of Electrical Engineering and Computer Sciences

Thermoelectric generators (TEGs) are used in small power applications to generate electrical energy from waste heats. Maximum power is obtained when the connected load to the ends of TEGs matches their internal resistance. However, impedance matching cannot always be ensured. Therefore, TEGs operate at lower efficiency. For this reason, maximum power point tracking (MPPT) algorithms are utilized. In this study, both TEGs and a boost converter with MPPT were modeled together. Detailed modeling, simulation, and verification of TEGs depending on the Seebeck coefficient, the hot/cold side temperatures, and the number of modules in MATLAB/Simulink were carried out. In addition, a …

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Consumer Loans' First Payment Default Detection: A Predictive Model, Utku Koç, Türkan Sevgi̇li̇ Jan 2020

Consumer Loans' First Payment Default Detection: A Predictive Model, Utku Koç, Türkan Sevgi̇li̇

Turkish Journal of Electrical Engineering and Computer Sciences

A default loan (also called nonperforming loan) occurs when there is a failure to meet bank conditions and repayment cannot be made in accordance with the terms of the loan which has reached its maturity. In this study, we provide a predictive analysis of the consumer behavior concerning a loan?Äôs first payment default (FPD) using a real dataset of consumer loans with approximately 600,000 records from a bank. We use logistic regression, naive Bayes, support vector machine, and random forest on oversampled and undersampled data to build eight different models to predict FPD loans. A two-class random forest using undersampling …

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Applying Deep Learning Models To Structural Mri For Stage Prediction Of Alzheimer's Disease, Altuğ Yi̇ği̇t, Zerri̇n Işik Jan 2020

Applying Deep Learning Models To Structural Mri For Stage Prediction Of Alzheimer's Disease, Altuğ Yi̇ği̇t, Zerri̇n Işik

Turkish Journal of Electrical Engineering and Computer Sciences

Alzheimer's disease is a brain disease that causes impaired cognitive abilities in memory, concentration, planning, and speaking. Alzheimer's disease is defined as the most common cause of dementia and changes different parts of the brain. Neuroimaging, cerebrospinal fluid, and some protein abnormalities are commonly used as clinical diagnostic biomarkers. In this study, neuroimaging biomarkers were applied for the diagnosis of Alzheimer's disease and dementia as a noninvasive method. Structural magnetic resonance (MR) brain images were used as input of the predictive model. T1 weighted volumetric MR images were reduced to two-dimensional space by several preprocessing methods for three different projections. …

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Time Series Forecasting On Multivariate Solar Radiation Data Using Deep Learning (Lstm), Murat Ci̇han Sorkun, Özlem Durmaz İncel, Christophe Paoli Jan 2020

Time Series Forecasting On Multivariate Solar Radiation Data Using Deep Learning (Lstm), Murat Ci̇han Sorkun, Özlem Durmaz İncel, Christophe Paoli

Turkish Journal of Electrical Engineering and Computer Sciences

Energy management is an emerging problem nowadays and utilization of renewable energy sources is an efficient solution. Solar radiation is an important source for electricity generation. For effective utilization, it is important to know precisely the amount from different sources and at different horizons: minutes, hours, and days. Depending on the horizon, two main classes of methods can be used to forecast the solar radiation: statistical time series forecasting methods for short to midterm horizons and numerical weather prediction methods for medium- to long-term horizons. Although statistical time series forecasting methods are utilized in the literature, there are a limited …

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An Index-Based Joint Multilingual/Cross-Lingual Text Categorization Using Topic Expansion Via Babelnet, Eniafe Festus Ayetiran Jan 2020

An Index-Based Joint Multilingual/Cross-Lingual Text Categorization Using Topic Expansion Via Babelnet, Eniafe Festus Ayetiran

Turkish Journal of Electrical Engineering and Computer Sciences

The majority of the state-of-the-art text categorization algorithms are supervised and therefore require prior training. Besides the rigor involved in developing training datasets and the requirement for repetition of training for different texts, working with multilingual texts poses additional unique challenges. One of these challenges is that the developer is required to have many different languages involved. Term expansion such as query expansion has been applied in numerous applications; however, a major drawback of most of these applications is that the actual meaning of terms is not usually taken into consideration. Considering the semantics of terms is necessary because of …

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A New Biometric Identity Recognition System Based On A Combination Of Superior Features In Finger Knuckle Print Images, Hadis Heidari, Abdolah Chalechale Jan 2020

A New Biometric Identity Recognition System Based On A Combination Of Superior Features In Finger Knuckle Print Images, Hadis Heidari, Abdolah Chalechale

Turkish Journal of Electrical Engineering and Computer Sciences

Biometric methods are among the safest and most secure solutions for identity recognition and verification. One of the biometric features with sufficient uniqueness for identity recognition is the finger knuckle print (FKP). This paper presents a new method of identity recognition and verification based on FKP features, where feature extraction is combined with an entropy-based pattern histogram and a set of statistical texture features. The genetic algorithm (GA) is then used to find the superior features among those extracted. After extracting superior features, a support vector machine-based feedback scheme is used to improve the performance of the biometric system. Two …

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Fast Texture Classification Of Denoised Sar Image Patches Using Glcm On Spark, Caner Özcan, Kadri̇ Okan Ersoy, İskender Ülgen Oğul Jan 2020

Fast Texture Classification Of Denoised Sar Image Patches Using Glcm On Spark, Caner Özcan, Kadri̇ Okan Ersoy, İskender Ülgen Oğul

Turkish Journal of Electrical Engineering and Computer Sciences

Classification of a synthetic aperture radar (SAR) image is an essential process for SAR image analysis and interpretation. Recent advances in imaging technologies have allowed data sizes to grow, and a large number of applications in many areas have been generated. However, analysis of high-resolution SAR images, such as classification, is a time-consuming process and high-speed algorithms are needed. In this study, classification of high-speed denoised SAR image patches by using Apache Spark clustering framework is presented. Spark is preferred due to its powerful open-source cluster-computing framework with fast, easy-to-use, and in-memory analytics. Classification of SAR images is realized on …

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Filter Design For Small Target Detection On Infrared Imagery Using Normalized-Cross-Correlation Layer, Hüseyi̇n Seçki̇n Demi̇r, Erdem Akagündüz Jan 2020

Filter Design For Small Target Detection On Infrared Imagery Using Normalized-Cross-Correlation Layer, Hüseyi̇n Seçki̇n Demi̇r, Erdem Akagündüz

Turkish Journal of Electrical Engineering and Computer Sciences

n this paper, we introduce a machine learning approach to the problem of infrared small target detection filter design. For this purpose, similar to a convolutional layer of a neural network, the normalized-cross-correlational (NCC) layer, which we utilize for designing a target detection/recognition filter bank, is proposed. By employing the NCC layer in a neural network structure, we introduce a framework, in which supervised training is used to calculate the optimal filter shape and the optimum number of filters required for a specific target detection/recognition task on infrared images. We also propose the mean-absolute-deviation NCC (MAD-NCC) layer, an efficient implementation …

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Nonlocal Means Estimation Of Intrinsic Mode Functions For Speech Enhancement, Sagar Reddy Vumanthala, Bikshalu K Jan 2020

Nonlocal Means Estimation Of Intrinsic Mode Functions For Speech Enhancement, Sagar Reddy Vumanthala, Bikshalu K

Turkish Journal of Electrical Engineering and Computer Sciences

The main aim of this paper is to introduce a new approach to enhance speech signals by exploring the advantages of nonlocal means (NLM) estimation and empirical mode decomposition. NLM, a patch-based denoising method, is extensively used for two-dimensional signals like images. However, its use for one-dimensional signals has been attracting more attention recently. The NLM-based approach is quite useful for removing low-frequency noises based on nonlocal similarities present among samples of the signal. However, there is an issue of under averaging in the high-frequency regions. The temporal and spectral characteristics of the speech signal are changing markedly over time. …

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A Symmetric-Based Framework For Securing Cloud Data At Rest, Mohammed Mohammed, Fadhil Abed Jan 2020

A Symmetric-Based Framework For Securing Cloud Data At Rest, Mohammed Mohammed, Fadhil Abed

Turkish Journal of Electrical Engineering and Computer Sciences

Cloud computing is the umbrella term for delivering services via the Internet. It enables enterprises and individuals to access services such as virtual machines, storage, or applications on demand. It allows them to achieve more by paying less, and it removes the barrier of installing physical infrastructure. However, due to its openness and availability over the Internet, the issue of ensuring security and privacy arises. This requires careful consideration from enterprises and individuals before the adoption of cloud computing. In order to overcome security issues, cloud service providers are required to use strong security measures to secure their storage and …

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On The Asymptotic Analysis Of The High-Order Statistics Of The Channel Capacity Over Generalized Fading Channels, Ferkan Yilmaz Jan 2020

On The Asymptotic Analysis Of The High-Order Statistics Of The Channel Capacity Over Generalized Fading Channels, Ferkan Yilmaz

Turkish Journal of Electrical Engineering and Computer Sciences

In this article, we provide further asymptotic analysis to the higher-order statistics (HOS) of the channel capacity over generalized fading channels, especially by proposing simple and closed-form expressions each of which can be easily computed as a tight bound revealing the existence of constant gap between the actual and asymptotic HOS of the channel capacity in the limit of both high and low signal-to-noise ratios. As such, we show that these closed-form asymptotic expressions are insightful enough to comprehend the diversity gains. The mathematical formalism we followed in this article is illustrated with some selected numerical examples that validate the …

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Reliability Comparisons Of Mobile Network Operators: An Experimental Case Study From A Crowdsourced Dataset, Engi̇n Zeydan, Ahmet Yildirim Jan 2020

Reliability Comparisons Of Mobile Network Operators: An Experimental Case Study From A Crowdsourced Dataset, Engi̇n Zeydan, Ahmet Yildirim

Turkish Journal of Electrical Engineering and Computer Sciences

It is of great interest for Mobile Network Operators (MNOs) to know how well their network infrastructure performance behaves in different geographical regions of their operating country compared to their horizontal competitors. However, traditional network monitoring and measurement methods of network infrastructure use limited numbers of measurement points that are insufficient for detailed analysis and expensive to scale using an internal workforce. On the other hand, the abundance of crowdsourced content can engender various unforeseen opportunities for MNOs to cope with this scaling problem. This paper investigates end-to-end reliability and packet loss (PL) performance comparisons of MNOs using a previously …

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