DSpace@ATÜ (Adana Alparslan Türkeş Bilim ve Teknoloji Universiti)
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Farklı Dijital Oyun Bağımlılığı Düzeyine Sahip Çocuklarda Görsel Uzaysal Bilişsel Beceriler ve Çalışma Belleği Kapasitesinin Karşılaştırılması
No full textAmaç: Bu çalışmanın amacı 10-14 yaşları arasında video oyunları oynayan çocukların dijital oyun bağımlılığı düzeyleri ile görsel uzaysal bilişsel becerileri ve çalışma belleği performansları arasındaki ilişkiyi incelemektir. Yöntem: Araştırmanın örneklemini yaş ortalaması 12,35 (SS=0,75) olan 98 çocuk (36 kız ve 62 erkek) oluşturmaktadır. Veri toplama araçları Bilgi Toplama Formu, Çocuklar İçin Dijital Oyun Bağımlılığı Ölçeği, Saat Çizme Testi ve Wechsler Bellek Ölçeği-III Harf-Sayı Dizisi Alt Testi’dir. Bulgular: Tek Yönlü Varyans Analizi (ANOVA) sonuçlarına göre dijital oyun bağımlılığı düzeyi riskli grupta Saat Çizme Testi puanı az riski grubun puanına göre artış gösterirken, bağımlı grupta bu test performansının riskli gruba göre düşük seviyede olduğu bulunmuştur. Benzer şekilde riskli grupta Harf-Sayı Dizisi Testi puanı az riskli gruba göre artarken, bağımlı grupta bu test performansının riskli gruptan düşük seviyede olduğu saptanmıştır. Sonuç: Video oyunları oynamanın çocukların görsel uzaysal becerilerini ve çalışma belleği performanslarını artırabildiği, ancak bağımlılık arttıkça bu becerilerin bozulabileceği görülmüştür. Dolayısıyla video oyunlarının daha nitelikli ve sınırlı süreli olarak kullanılabilmesi için çocuklara yönelik eğitim programlarının oluşturulması önerilmektedir
Linkage Learning Optimization of Aeroelastic and Structural Behavior of Composite Wings
No full textThe paper aims to develop a systematic numerical design for composite wings optimization subject to aerodynamic loading and to assess the aeroelastic and structural performance of the optimized composite wing. Aeroelastic tailoring is a powerful method for utilizing the anisotropic features of composite materials used in lightweight aerospace structures. The present proposed methodology combines three different analysis tools: a commercial FE software commonly used in industry, an in-house reduced order aeroelastic framework for aeroelastic analyses with tailoring capabilities, LLGA, in-house linkage-learning genetic algorithms for optimization of stacking sequences. As a multidisciplinary problem where structural and aeroelastic behaviors are interacted, developed multi-level optimization scenario in this research converges to the optimal design in a very short time. The proposed methodology implemented as a computer code can effectively be applied to any arbitrary air vehicle's composite wing by changing input data.Scientific and Technological Research Council of Turkey (TUBITAK) [220N396]; University of Tabriz; Iran Ministry of Science, Research and Technology (MSRT) [IRTU-2-1410]This study has been supported by the Scientific and Technological Research Council of Turkey (TUBITAK, Project No. 220N396) and University of Tabriz and Iran Ministry of Science, Research and Technology (MSRT, Project No. IRTU-2-1410). The authors gratefully acknowledge the support of this study
Sağlam sonlu durumlu yapay konuşma algılama: Derin sinir ağları ve maskelerle güçlendirilmiş bütünsel yaklaşım
No full textLisansüstü Eğitim Enstitüsü, Elektrik ve Elektronik Mühendisliği Ana Bilim Dalı, Elektrik Elektronik Mühendisliği Bilim DalıBu tez, gürültülü koşullar altında sentetik konuşma algılamanın i-vectörlerinin sağlamlığını artırmak için bir yöntem önermektedir. İ-vectörler, konuşmacı tanıma sistemlerinde yaygın olarak kullanılan sabit uzunluktaki temsillemelerdir. Ancak, performansları gürültü ile bozulmaktadır. Sistemi korumak için, gürültü maskesi üretmek için evrişimsel sinir ağı (CNN) kullanılması önerilmiştir. Bu maske, gürültü tarafından bozulan konuşma spektrogramındaki güvenilmez bölgeleri bastırır. Maske uygulanan spektrogram daha sağlam i-vectörlerin çıkarılması için kullanılır. Deneyler, eklenmiş gürültü, beyaz gürültü ve araba gürültüsü içeren ASVspoof 2015 veri kümesi kullanılarak yapılmıştır. CNN, her spektrogram çerçevesinde sinyal-gürültü oranını tahmin etmek üzere eğitilir. Bu, i-vectör çıkarılmasından önce uygulanan gürültü maskesini oluşturur. Sonuçlar, önerilen maskeleme yaklaşımının standart i-vectörlerle karşılaştırıldığında eşit hata oranlarını %50'den fazla azalttığını göstermektedir. Ancak, performans, CNN eğitimi sırasında görülmeyen araba gürültüsü üzerinde bozulur. Bu, daha çeşitli eğitim gürültü türlerine ihtiyaç duyulduğunu vurgular. Sonuç olarak, spektrogram maskesi kullanma tekniği ile derin öğrenme tabanlı bir CNN, gürültülü koşullarda i-vectörlerin sağlamlığını artırabilir. Gürültü maskesi, güvenilmez bölgeleri bastırmaya yardımcı olarak daha iyi sahtecilik karşıtı performans sağlar. Ancak, maske görünmeyen gürültü türlerine iyi genelleşmez. Genel olarak, çalışma, gürültü altında sahtecilik saldırılarına karşı konuşmacı tanıma sistemlerinin güvenliğini artırmak için derin öğrenmeye dayalı maskelerin potansiyelini göstermektedir. Ancak daha fazla araştırma, çeşitli gürültü koşullarını ele alma konusunda gereklidir.This thesis proposes a method to improve the robustness of i-vectors for synthetic speech detection under noisy conditions. I-vectors are fixed-length representations commonly used in speaker recognition systems. However, their performance degrades with noise. In order protect the system, using a convolutional neural network (CNN) to generate a noise mask is proposed. This mask suppresses unreliable regions in the speech spectrogram corrupted by noise. The masked spectrogram is then used to extract more robust i-vectors. Experiments use the ASVspoof 2015 dataset with added babble, white, and car noise. The CNN is trained to estimate the signal-to-noise ratio in each spectrogram frame. This generates the noise mask that is applied before i-vector extraction. Results show the proposed masking approach reduces equal error rates by over 50% compared to standard i-vectors from noisy speech. However, performance degrades on car noise which was not seen during CNN training. This highlights the need for more diverse training noise types. In conclusion, the proposed spectrogram masking technique using a CNN can increase robustness of i-vectors for synthetic speech detection in noisy conditions. The noise mask helps suppress unreliable regions to provide improved anti-spoofing performance. However, the mask does not generalize well to unseen noise types. Overall, the study shows potential for deep learning-based masking to improve security of speaker recognition systems against spoofing attacks under noise. But more research is needed into handling diverse noise conditions
Yavaş Şehir (Cittaslow) Kavramının Sürdürülebilirlik Bağlamında Karşılaştırmalı Bir Değerlendirmesi: Bra ve Seferihisar Örneği
No full textGeçmişten günümüze, toplumlar bir arada yaşayarak bir düzen oluşturmuş ve zamanla yerleşik hayata geçmişlerdir. Böylece köyler oluşmuş ve köylerin zaman içerisindeki gelişimi ile kentler meydana gelmiştir. Teknolojik gelişmeler ve sanayileşme kırsal bölgeden kentlere göç başlamasına neden olmuştur. Hızlı ve kontrolsüz büyüyen kentlerde yaşanan küreselleşme ile birlikte çarpık kentleşme ve tüketimin artması gibi sorunlar ortaya çıkmıştır. Buna tepki olarak 1989 yılında İtalya’da Slow Food Movement (Uluslararası Yavaş Beslenme Hareketi) düzenlenmiştir. Bu ha- reketin teşviki ile tüketim hızının azalması, yerel ekonominin iyileştirilmesi ve sürdürülebilir kal- kınmanın sağlanması ve yerel kaynakların sürdürülebilirliğinin sağlanarak gelecek nesillere akta- rılması amacıyla 1999 yılında İtalya’da dört küçük İtalyan kentinin dahil olduğu Uluslararası Yavaş Şehir (Cittaslow) Birliği kurulmuştur. Bu araştırma kapsamında, Uluslararası Yavaş Şehir Birliğinin kurucularından olan Bra kenti ile, 2009 yılında Türkiye’nin ilk yavaş şehir (Cittaslow) kenti seçilen Seferihisar kentlerinin Cittaslow üyelik kriterleri baz alınarak gerçekleştirdikleri faa- liyetleri karşılaştırılmış ve sürdürülebilirlik bağlamında incelenmiştir
Investigating the optical, electronic, magnetic properties and DFT of NiO films prepared using RF sputtering with various argon pressures
No full textIn this study, we investigated the structural, optical, magnetic, and conductive properties of nickel oxide (NiO) films on glass substrates deposited using Radio Frequency (RF) magnetron sputtering with varying Ar gas pressure and thickness. X-ray diffraction and Rietveld refinement analysis confirmed a cubic crystal structure and showed that the lattice parameters and the d(111)-space increased from 4.0559 & ANGS; to 4.2712 & ANGS; and from 2.3208 & ANGS; to 2.4582 & ANGS;, respectively, due to increased Ar pressure during deposition. Scanning electron microscopy and atomic force microscopy were used to determine the cross-sectional and surface topology of the NiO films, which exhibited uniform and homogeneous growth with an average spherical size of 54.28 & PLUSMN; 0.33 nm. The optical bandgap values of the films were calculated to be between 3.26 and 3.65 eV, increasing with pressure. Hall measurements confirmed the p-type semiconductor nature of the films with an average sheet carrier density of 1010 cm ? 2. The films exhibited soft magnetic properties, with a maximum Hc and Ms of 178.5 Oe and 5.82 emu/ cm3 for 246 nm NiO film, respectively. Density functional theory (DFT) calculations confirmed the experimental results for both single to five layers NiO films and bulk NiO formations. The refined energy gap value was found to be 3.2 eV by the DFT calculation. The films produced at room temperature were found to be stable and reproducible, making them suitable as p-type materials for device construction.Scientific Research Project Fund of Sivas Cumhuriyet University; Cukurova University Department of Physics facilities; [F-2021-640]This work is supported by the Scientific Research Project Fund of Sivas Cumhuriyet University under the project number F-2021-640. The authors acknowledge the usage of the Nanophotonics Research and Application Center at Sivas Cumhuriyet University (CUNAM) , Sivas Cumhuriyet University R & D Center (CUTAM) , Cukurova University Department of Physics facilities
Bioactive potential of ripened white cheeses manufactured in different geographical regions of Turkey
No full textThis study investigated the potential bioactive properties of white cheeses produced in different regions of Turkey, including their potential antioxidant, antihypertensive, antidiabetic, antimicrobial, and anticancer activities. The cheese samples were analyzed both before and after in vitro digestion. The study found that all cheese samples exhibited significant angiotensin-converting enzyme inhibition activity both before (45.5%-70.1% for 0.03 g cheese/mL) and after in vitro digestion (25.5%-63.5% for 0.0167 g cheese/mL), whereas alpha-amylase inhibition activity was present in all samples (in the range of 5.1%-50.0% for 3.0 x 10(-5) g cheese/mL) but disappeared after digestion, and alpha-glucosidase inhibition activity was only detected after in vitro digestion (from 20.5% to 60.4% for 5.6 x 10(-5) g cheese/mL), indicating potential antidiabetic properties. However, antimicrobial and anticancer activities were not observed in any of the samples. The results also suggest that the bioactivity potential of white cheese may vary depending on the region of production, as cheeses from the Marmara region exhibited high alpha-glucosidase inhibition activity after digestion. In conclusion, while white cheese is a valuable addition to the diet due to its high nutritional value and potential health benefits. This study revealed the bioactive potential of ripened white cheese and in vivo investigations of the cheese components would better show their possible benefits.Scientific Research Project Fund of AdanaAlparslan Turkes Science and Technology UniversityScientific Research Project Fund of AdanaAlparslan Turkes Science and Technology Universit
Effects of geometrical parameters on thermohydrodynamic performance of a bearing operating with nanoparticle additive oil
No full textPurposeBearing performance characteristics, such as stiffness and load capacity, are related to the viscosity of the fluid circulating through the gap. Nanoparticle additives in lubricant are one way to enhance of the viscosity. This study aims to investigate the effect of nanoparticle additives on the thermohydrodynamic performance of journal bearing with different bearing parameters. Design/methodology/approachThe temperature distribution is modeled using a three-dimensional energy equation. The velocity components are calculated on the pressure distribution governed by Dowson's equation. Moreover, the heat transfer between the journal and lubricant is modeled with Fourier heat conduction equation. On the other hand, the viscosity equation is derived for Al2O3 nanoparticles as a function of the volume ratio and the temperature. An algorithm based on the finite difference method is developed, and a serial simulation is performed for different parameters and different volume ratio of nanoparticle. FindingsWith the increase in the nanoparticle volume ratio, the maximum temperature decreases for the lower clearance values, but the addition of the nanoparticle influence on the maximum temperature reverses when the clearance grows up. The nanoparticle additives increase further the maximum temperature for higher values of L/D ratios. Moreover, the effects of the nanoparticle additives on the pressure are stronger at high eccentricity ratios for all bearing parameters. Originality/valueThis paper provides valuable design parameters for journal bearing with lubricant containing the nanoparticle additives
Image-based UAV position and velocity estimation using a monocular camera
No full textAutonomous landing of aerial vehicles is challenging, especially in emergency flight scenarios in which precise information about the vehicle and the environment is required for near-to-ground maneuvers. In this paper, the optic-flow concept based on feature detection is applied to estimate the vertical distance and the velocity vector of a multirotor UAV (MUAV) for landing. The UAV kinematics, the optical flow equations, and the detected feature states, provided by a low-cost monocular camera, are combined to develop a novel appropriate model for estimation. The proposed algorithm applies the variation of detected features, the angular velocities, as well as the Euler angles, measured by the Inertial Measurement Unit (IMU), to estimate the vertical distance of the UAV to the ground, the MUAV velocity vector, and also to predict the future features position. Extended Kalman filter (EKF) is applied as the estimation method on the coupled optic-flow and kinematic equations. The accuracy of state estimation is enhanced by the idea of multiple-feature tracking. The 6-DOF simulations, laboratory experiments, and comparison of results demonstrate the capability of height and velocity estimation of a MUAV in the landing phase of flight by just applying the low-cost camera information. Monte Carlo simulations have been performed to study the effect of IMU acceleration, and angular velocity measurement noises as well as the number of the detected features on the success probability of the estimation process. The results reveal that increasing the number of detected features, i.e tracking multiple features, increases the estimation accuracy, however, it mainly improves the success probability, which is a more important factor in practical scenarios.Scientific and Technological Research Council of Turkey (TUBITAK) under 3501 program [120M793]This research is supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under 3501 program, with project number [120M793]
LAM: Scrutinizing Leading APIs For Detecting Suspicious Call Sequences
No full textThe proliferation of smartphones has given exponential rise to the number of new mobile malware. These malware programs are employing stealthy obfuscations to hide their malicious activities. To perform malicious activities a program must make application programming interface (API) calls. Unlike dynamic, static analysis can find all the API call paths but have some issues: large number of features; higher false positives when features reduced; and lowering false positives increases the detection rate. Certain Android API calls, e.g. android.app.Activity:boolean requestWindowFeature(int) enable malware programs to call other APIs to hide their activities. We call them leading APIs as they can lead to malicious activities. To overcome these issues, we propose new heuristics and feature groupings for building a Leading API-call Map, named LAM. We create LAM from a dominant (leading) API call tree. Dominance is a transitive relation and hence enumerates all the call sequences that a leading API leads to. LAM substantially reduces the number and improves the quality of features for combating obfuscations and detecting suspicious call sequences with few false positives. For the dataset used in this paper, LAM reduced the number of features from 509 607 to 29 977. Using 10-fold cross-validation, LAM achieved an accuracy of 97.9% with 0.4% false positives
Antimicrobial chitosan-sodium tetrafluoroborate (NaBF4) hydrogels for topical applications
No full textInfection of a wound is one of the most important reasons delaying the recovery of an injured tissue. In this study, chitosan-based hydrogels were loaded with different concentrations of sodium tetrafluoroborate (NaBF4) to fabricate an antimicrobial wound care system. Antimicrobial activity, and cytotoxicity of NaBF4, and surface morphology, chemical bond structures and antimicrobial activity of Chitosan:NaBF4 hydrogels against a broad spectrum of microorganisms including an antibiotic resistant specie were investigated. NaBF4 showed higher antibacterial activity for gram-positive bacteria than gram-negative bacteria. MIC values of NaBF4 were 3.906, 1.953, and 7.813 µg/µL for every gram-negative, gram-positive, and fungal species, respectively. Direct cytotoxicity of NaBF4 on the L929 cell line was investigated by the 3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide (MTT) assay. IC50 value after 24 h incubation was calculated as 3.2 µg/µL which is within the range of concentration with antimicrobial activity. The antimicrobial activities of chitosan hydrogels were investigated by disc diffusion method. Antimicrobial activity of hydrogel increased with increasing NaBF4 concentration while high molecular weight chitosan-based hydrogel did not show antimicrobial activity. According to the results, group 1:3 (546.5mM NaBF4 containing hydrogel) was enough to achieve broad spectrum antimicrobial activity and hydrogels prepared with this formulation can be used as a potential antimicrobial wound care product. © 2023, Turkish Energy Nuclear and Mining Research Institute. All rights reserved