Digital Commons Network^™

Deep Learning For Turkish Makam Music Composition, İsmai̇l Hakki Parlak, Yalçin Çebi̇, Ci̇han Işikhan, Derya Bi̇rant

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we introduce a new deep-learning-based system that can compose structured Turkish makam music (TMM) in the symbolic domain. Presented artificial TMM composer (ATMMC) takes eight initial notes from a human user and completes the rest of the piece. The backbone of the composer system consists of multilayered long short-term memory (LSTM) networks. ATMMC can create pieces in Hicaz and Nihavent makams in Şarkı form, which can be viewed and played with Mus2, a notation software for microtonal music. Statistical analysis shows that pieces composed by ATMMC are approximately 84% similar to training data. ATMMC is an open-source …

Clustered Mobile Data Collection In Wsns: An Energy-Delay Trade-Of, İzzet Fati̇h Şentürk

Turkish Journal of Electrical Engineering and Computer Sciences

Wireless sensor networks enable monitoring remote areas with limited human intervention. However, the network connectivity between sensor nodes and the base station (BS) may not be always possible due to the limited transmission range of the nodes. In such a case, one or more mobile data collectors (MDCs) can be employed to visit nodes for data collection. If multiple MDCs are available, it is desirable to minimize the energy cost of mobility while distributing the cost among the MDCs in a fair manner. Despite availability of various clustering algorithms, there is no single fits all clustering solution when different requirements …

Benchmarking Of Deep Learning Algorithms For Skin Cancer Detection Based On Ahybrid Framework Of Entropy And Vikor Techniques, Baidaa Al-Bander, Qahtan M. Yas, Hussain Mahdi, Rwayda Kh. S. Al-Hamd

Turkish Journal of Electrical Engineering and Computer Sciences

Skin cancer is one of the most common cancers worldwide caused by excessive development of skin cells. Considering the rapid growth of the use of deep learning algorithms for skin cancer detection, selecting the optimal algorithm has become crucial to determining the efficiency of computer-aided diagnosis (CAD) systems developed for the healthcare sector. However, a sufficient number of criteria and parameters must be considered when selecting an ideal deep learning algorithm. A generally accepted method for benchmarking deep learning models for skin cancer classification is unavailable in the current literature. This paper presents a multi-criteria decision-making framework for evaluating and …

New Normal: Cooperative Paradigm For Covid-19 Timely Detection Andcontainment Using Internet Of Things And Deep Learning, Farooque Hassan Kumbhar, Ali Hassan Syed, Soo Young Shin

Turkish Journal of Electrical Engineering and Computer Sciences

The spread of the novel coronavirus (COVID-19) has caused trillions of dollars of damages to the governments and health authorities by affecting the global economies. It is essential to identify, track and trace COVID-19 spread at its earliest detection. Timely action can not only reduce further spread but also help in providing an efficient medical response. Existing schemes rely on volunteer participation, and/or mobile traceability, which leads to delays in containing the spread. There is a need for an autonomous, connected, and centralized paradigm that can identify, trace and inform connected personals. We propose a novel connected Internet of Things …

A Transfer Learning-Based Deep Learning Approach For Automated Covid-19diagnosis With Audio Data, Devri̇m Akgün, Abdullah Talha Kabakuş, Zehra Karapinar Şentürk, Arafat Şentürk, Enver Küçükkülahli

Turkish Journal of Electrical Engineering and Computer Sciences

The COVID-19 pandemic has caused millions of deaths and changed daily life globally. Countries have declared a half or full lockdown to prevent the spread of COVID-19. According to medical doctors, as many people as possible should be tested to identify their status, and corresponding actions then should be taken for COVID-19 positive cases. Despite the clear necessity of these medical tests, many countries are still struggling to acquire them. This fact clearly indicates the necessity of a large-scale, cheap, fast, and accurate alternative prescreening tool that can be used for the diagnosis of COVID-19 while waiting for the medical …

A Consistent Estimator Of Nontrivial Stationary Solutions Of Dynamic Neural Fields, Eddy Kwessi

Mathematics Faculty Research

Dynamics of neural fields are tools used in neurosciences to understand the activities generated by large ensembles of neurons. They are also used in networks analysis and neuroinformatics in particular to model a continuum of neural networks. They are mathematical models that describe the average behavior of these congregations of neurons, which are often in large numbers, even in small cortexes of the brain. Therefore, change of average activity (potential, connectivity, firing rate, etc.) are described using systems of partial different equations. In their continuous or discrete forms, these systems have a rich array of properties, among which is the …

A Continuous-Time Mathematical Model And Discrete Approximations For The Aggregation Of Β-Amyloid, A. S. Ackleh, Saber Elaydi, G. Livadiotis, A. Veprauskas

Mathematics Faculty Research

Alzheimer's disease is a degenerative disorder characterized by the loss of synapses and neurons from the brain, as well as the accumulation of amyloid-based neuritic plaques. While it remains a matter of contention whether β-amyloid causes the neurodegeneration, β-amyloid aggregation is associated with the disease progression. Therefore, gaining a clearer understanding of this aggregation may help to better understand the disease. We develop a continuous-time model for β-amyloid aggregation using concepts from chemical kinetics and population dynamics. We show the model conserves mass and establish conditions for the existence and stability of equilibria. We also develop two …

The School Principal And Teacher Retention, Jonathan D. Becker, Lauren Grob

MERC Publications

This report comes from the MERC Teacher Retention study. This study was designed to identify patterns of teacher retention in the MERC region and to determine the school and system-level factors driving them. The study also provides an overview of state and regional policies and programs relevant to teacher retention, and includes evaluations of existing policies and initiatives to determine efficacy and cost benefit. This policy brief examines the role of leadership, and specifically the school principal, in retaining teachers. The brief includes a review of studies that used survey scales to measure leadership and then disaggregate and re-aggregate the …

Introducing The Copyright Anxiety Scale, Amanda Wakaruk, Céline Gareau-Brennan, Matthew Pietrosanu

Copyright, Fair Use, Scholarly Communication, etc.

Navigating copyright issues can be frustrating to the point of causing anxiety, potentially discouraging or inhibiting legitimate uses of copyright-protected materials. A lack of data about the extent and impact of these phenomena, known as copyright anxiety and copyright chill, respectively, motivated the authors to create the Copyright Anxiety Scale (CAS). This article provides an overview of the CAS’s development and validity testing. Results of an initial survey deployment drawing from a broad cross-section of respondents living in Canada and the United States (n = 521) establishes that the phenomenon of copyright anxiety is prevalent and likely associated with …

Assessment Of Performance Parameter Uncertainty Of A Solid Fuel Ramjet, William Jarrett Hankins

Theses

This research develops a methodology for quantifying the uncertainties in key experimentally determined performance parameters for two solid fuel ramjet propellants in a connected pipe ramjet using the Monte Carlo Method. The performance parameters include characteristic velocity, characteristic velocity efficiency, thrust, specific impulse, and vacuum specific impulse. The burning rate equations and their uncertainty intervals were also calculated. Burning rate equations were constructed with terms in air flux and air temperature. The uncertainty intervals were found to be 4% - 5.1% at the test points. The burning rates were found to be accurate within ± 7.7%. Uncertainties in the performance …

An Analysis Of Use And Performance Data Aggregated From 35 Institutional Repositories, Kenning Arlitsch, Jonathan Wheeler, Minh Thi Ngoc Pham, Nikolaus Nova Parulian

Copyright, Fair Use, Scholarly Communication, etc.

Purpose – This study demonstrates that aggregated data from the Repository Analytics and Metrics Portal (RAMP) have significant potential to analyze visibility and use of institutional repositories (IR) as well as potential factors affecting their use, including repository size, platform, content, device and global location. The RAMP dataset is unique and public.

Design/methodology/approach – The webometrics methodology was followed to aggregate and analyze use and performance data from 35 institutional repositories in seven countries that were registered with the RAMP for a five-month period in 2019. The RAMP aggregates Google Search Console (GSC) data to show IR items that surfaced …

Streptococcus Sanguinis: The Good, The Bad, And The Metal-Binding Lipoprotein, Cody Murgas

Theses and Dissertations

Streptococcus sanguinis is an opportunistic bacterium living beneficially in the human mouth. When S. sanguinis gains access to the bloodstream, it can result in colonization on damaged tissue and generate heart valve vegetations that can develop into infective endocarditis. It has been suggested that Mn and Fe are cofactors in the pathogenic capacity of this bacterium, and that these redox active metals are imported by the metal binding lipoprotein S. sanguinis adhesin B (SsaB). The SsaB lipoprotein is an integral part of SsaACB, an ATP-binding cassette (ABC) transport system in S. sanguinis. When SsaB is deleted, the resulting strain displays …

The Algorithmic Mashrabiya: Reimagining The Traditional Islamic Screen, Ahmed Nour

Theses and Dissertations

Traditionally, a mashrabiya was an ornate wooden structure attached to the side of an Arabian building or house, with small, intricately patterned openings to provide both ventilation and privacy for the people inside. The patterns, following the geometric rules of Islamic ornament, lent a distinctive appearance to buildings in the region. A mashrabiya converted the house into a safe, private sanctuary, providing a magical scene inside, characterized by linear sun rays, filtered points of light and shadow. Over time, as building technology changed and the number of skilled craftsmen dwindled, the traditional mashrabiya has all but vanished. The aim of …

Will They Stay Or Will They Go? Analysis Of The 2019 Doe Working Conditions Survey, Jonathan D. Becker, Valerie Robnolt, Kasey Dye, Erica Ross

MERC Publications

This report is part of the MERC Teacher Retention study. This study was designed to identify patterns of teacher retention in the MERC region and to determine the school and system-level factors driving them. The study also provides an overview of state and regional policies and programs relevant to teacher retention, and includes evaluations of existing policies and initiatives to determine efficacy and cost benefit. Teacher shortages continue to be a problem in the United States. While a range of policy solutions have attempted to stem the loss of teachers, at the base of many of these efforts is the …

Research Data Curation And Management Bibliography, Charles W. Bailey Jr.

Copyright, Fair Use, Scholarly Communication, etc.

Preface

The Research Data Curation and Management Bibliography includes over 800 selected English-language articles and books that are useful in understanding the curation of digital research data in academic and other research institutions.

The "digital curation" concept is still evolving. In "Digital Curation and Trusted Repositories: Steps toward Success," Christopher A. Lee and Helen R. Tibbo define digital curation as follows:

Digital curation involves selection and appraisal by creators and archivists; evolving provision of intellectual access; redundant storage; data transformations; and, for some materials, a commitment to long-term preservation. Digital curation is stewardship that provides for the reproducibility and re-use …

Sources Of Formaldehyde In Bountiful Ut Data, Nitish Bhardwaj, Ariel Kelsch, Delbert Eatough, Ryan Thalman, Nancy Daher, Kerry Kelly, Isabel Cristina Jaramillo, Jaron Hansen

ScholarsArchive Data

Source of Formaldehyde in Bountiful, UT Data

This file contains the X and U matrix used in the positive matrix factorization analysis done on the data collected in Bountiful, UT. The X matrix contains the concentration of species measured and the U matrix is the calculated uncertainty in each measured value. This data is stored in the Excel format.

Included in this file is the two-hour averaged concentrations of formaldehyde and ozone, wind direction, time of day, and date that the data was collected at the Bountiful, UT air sampling site located at the Bountiful Utah High School. This data …

In Vitro Screening Of Tp5801 Against Kinases For Nature Communications Publication, Joshua Andersen

ScholarsArchive Data

Data from screen of TP-5801 against in vitro kinases

Improvement In 14-3-3 Binding Site Prediction, Katherine K. Mccormack

ScholarsArchive Data

The 14-3-3 family of phospho-binding proteins regulate a variety of major cellular processes through interaction with a network of dynamic proteins. Deregulation of the 14-3-3 interaction network contributes to a variety of degenerative disorders and cancers. Our lab focuses on identifying novel 14-3-3 interactions and understanding how 14-3-3 binding regulates protein function. A major gap in this process is that identifying the phospho-site where 14-3-3 docks on a given protein is time- and resource-consuming. Prediction algorithms have been developed to predict canonical 14-3-3 binding sites, however, there are many non-canonical sites that existing software is unable to predict. To fill …

Kinase Screen Data For Nature Communications Publication, Joshua Andersen

ScholarsArchive Data

A TNK1 peptide encompassing S502 was screened against 245 Ser/Thr kinases. This file contains kinase activity values (against S502) from an n=1 experiment. These data support a manuscript to be published in Nature Communications (Chan and Egbert et al.)

Evaluation On Reducing Toxicity Of Fluoxastrobine With Doped Tio$_{2}$ Nanoparticles, Abbas Güngördü, Nesri̇n Özmen, Sema Erdemoğlu, Duygu Özhan Turhan, Meltem Asi̇ltürk, Emrah Akgeyi̇k, Murat Özmen

Turkish Journal of Zoology

In this study, toxic effects caused by the degradation of fluoxastrobin, which is a commonly used fungicide where newly synthesized manganese or sulfur-doped TiO$_{2}$ nanoparticles exist were evaluated. The characterization study of nanoparticles was performed by scanning an electron microscopy (SEM), X-ray diffractometry, Brunau-Emmet-Teller analysis, X-ray fluorescence spectroscopy, and UV-Vis (ultraviolet-visible) reflectance spectra. Subsequently, the photocatalytic performance of nanoparticles, their toxicity, and the photocatalytic degradation products of fluoxastrobin with the same nanoparticles were tested during the two development stages of Xenopus laevis. The LC$_{50}$s of fluoxastrobin were determined on test organisms, and a 5 mg L$^{-1}$ fluoxastrobin was selected to …

A Novel Method For Soc Estimation Of Li-Ion Batteries Using A Hybrid Machinelearning Technique, Eymen İpek, Murat Yilmaz

Turkish Journal of Electrical Engineering and Computer Sciences

The battery system is one of the key components of electric vehicles (EV) which has brought groundbreaking technologies. Since modern EVs have mostly Li-ion batteries, they need to be monitored and controlled to achieve safe and high-performance operation. Particularly, the battery management system (BMS) uses complex processing systems that perform measurements, estimation of the battery states, and protection of the system. State of charge (SOC) estimation is a major part of these processes which defines remaining capacity in the battery until the next charging operation as a proportion to the total battery capacity. Since SOC is not a parameter that …

Evolutionary Neural Networks For Improving The Prediction Performance Ofrecommender Systems, Berna Şeref, Gazi̇ Erkan Bostanci, Mehmet Serdar Güzel

Turkish Journal of Electrical Engineering and Computer Sciences

Recommender systems provide recommendations to users using background data such as ratings of users about items and features of items. These systems are used in several areas such as e-commerce, news websites, and article websites. By using recommender systems, customers are provided with relevant data as soon as possible and are able to make good decisions. There are more studies about recommender systems and improving their performance. In this study, prediction performances of neural networks are evaluated and their performances are improved using genetic algorithms. Performances obtained in this study are compared with those of other studies. After that, superiority …

Time-Oriented Interactive Process Miner: A New Approach For Time Prediction, İsmai̇l Yürek, Derya Bi̇rant, Özlem Ece Yürek, Kökten Ulaş Bi̇rant

Turkish Journal of Electrical Engineering and Computer Sciences

Everyday information systems collect a different kind of process instances of a business flow. As time goes on, the size of the collected data builds up speedily and constitutes a huge amount of data. It is a very challenging task to obtain valuable information and features of processes from such big data. Considering in advance, the trend and different features of the ongoing process are essential. Especially, time management is crucial in designing and conducting business processes. In this article, a novel process miner algorithm is proposed for time prediction, named time-oriented İnteractive process miner (T-IPM), which predicts the remaining …

Abnormal Behavior Detection Using Sparse Representations Through Sequentialgeneralization Of K-Means, Ahlam Aldhamari, Rubita Sudirman, Nasrul Humaimi Mahmood

Turkish Journal of Electrical Engineering and Computer Sciences

The potential capability to automatically detect and classify human behavior as either normal or abnormal events is an important aspect in intelligent monitoring/surveillance systems. This study presents a new high-performance framework for detecting behavioral abnormalities in video streams by utilizing only the patterns for normal behaviors. In this paper, we used a hybrid descriptor, called a foreground optical flow energy (FGOFE), which makes use of two effective motion techniques in order to extract the most descriptive spatiotemporal features in video sequences. The FGOFE descriptor can effectively capture both weak and sudden incidents in a scene. The sequential generalization of k-means …

A Novel Optimum Pi Controller Design Based On Stability Boundary Locussupported Particle Swarm Optimization In Avr System, Mahmut Temel Özdemi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes a new approach that combines stability and optimization in the design of proportional? integral (PI) controller of automatic voltage regulators (AVR) of synchronous generators with variable system parameters. Thanks to this approach, a PI controller, providing the desired performance and the stability of the AVR system, has been designed. The approach follows a method investigating the PI gain values to achieve the desired goals. In the first step of the study, a new stability boundary locus is calculated for the case in which AVR system?s parameters have changed. The stability boundary locus (SBL) method is a graphic-based …

A Novel Data Placement Strategy To Reduce Data Traffic During Run-Time, Sridevi Sridhar, Rhymend Uthariaraj Vaidyanathan

Turkish Journal of Electrical Engineering and Computer Sciences

High impact scientific applications processed in distributed data centers often involve big data. To avoid the intolerable delays due to huge data movements across data centers during processing, the concept of moving tasks to data was introduced in the last decade. Even after the realization of this concept termed as data locality, the expected quality of service was not achieved. Later, data colocality was introduced where data groupings were identified and then data chunks were placed wisely. However, the aspect of the expected data traffic during run time is generally not considered while placing data. To identify the expected data …

Performance Improvement Of The Shunt Active Power Filter Using A Novel Adaptivefiltering Approach, Abderrezzaq Zoghbi, Daoud Berkani

Turkish Journal of Electrical Engineering and Computer Sciences

This paper introduces an efficient control approach to enhance harmonics mitigation performance of the shunt active power filter (SAPF). This approach is based on adaptive filters favored by their built-in automatic parameters adaptation capability. The proposed filter, which uses a variable leaky least mean square (VLLMS) adaptation, is applied with a modified instantaneous power PQ theory. This enhances its dynamic performance over the use of conventional time-invariant filters, and overcomes its limitations in the presence of nonsinusoidal voltage conditions. The studied SAPF model is simulated in MATLAB/SIMULINK with combinations of nonlinear and unbalanced loads. Simulation results indicate a significant improvement …

A Two-Stage Hair Region Localization Method For Guided Laser Hair Removal, Murat Avşar, İmam Şami̇l Yeti̇k

Turkish Journal of Electrical Engineering and Computer Sciences

Removal of hair using laser is a widely used method, where our goal is to permanently remove hair by using laser to cause heat in order to thermally damage the hair follicle. However, currently available laser hair removal systems affect the outer skin layers besides hair follicles. This is a disadvantage of classical methods with major health risks. We propose a method to overcome these health risks by guiding the laser beam only to automatically localized hair regions. This study aims to develop an automated feature-based hair region localization method as an integral part of the proposed hair removal system …

Renewable Energy Transition Towards Krabi’S Sustainable Energy, Chariya Senpong

Chulalongkorn University Theses and Dissertations (Chula ETD)

The present study was conducted with an aim to investigate Krabi's electricity outlook, renewable energy transition timeline, and potential of renewable energy resources, key drivers, barriers, and challenges towards Krabi's sustainable energy. Guideline as well as policy recommendation for successful renewable energy transition was also developed. The study found that Krabi's electricity demand has continuously increasing and tends to increase up to 320 MW by the year 2037. Meanwhile, electricity supply has still relied on national grid since 1995. Meanwhile, Krabi Goes Green which is a provincial roadmap has set a target to be self-reliance and all electricity supply would …

Developing Tanjung Kelayang As A New Bali: An Analysis Of Sustainable Tourism Policy And Implementation, Herdi Andrariladchi

Chulalongkorn University Theses and Dissertations (Chula ETD)

Indonesia has seen the success of Bali as the most prominent tourism destination in the country. Therefore, the initiative to deploy the benefits of tourism development throughout several regions of Indonesia is known as the “10 New Bali’s”. Nevertheless, it is still questionable whether Bali is an example of sustainable tourism or not. In developing the “10 New Bali’s”, the Indonesian government is aiming at increasing the number of tourists rather than at achieving the goal of sustainable tourism destination development. One of the destinations designated under this initiative is Tanjung Kelayang in Belitung Island, and therefore it is selected …