An efficient multiscale scheme using local zernike moments for face recognition

In this study, we propose a face recognition scheme using local Zernike moments (LZM), which can be used for both identification and verification. In this scheme, local patches around the landmarks are extracted from the complex components obtained by LZM transformation. Then, phase magnitude histograms are constructed within these patches to create descriptors for face images. An image pyramid is utilized to extract features at multiple scales, and the descriptors are constructed for each image in this pyramid. We used three different public datasets to examine the performance of the proposed method:Face Recognition Technology (FERET), Labeled Faces in the Wild (LFW), and Surveillance Cameras Face (SCface). The results revealed that the proposed method is robust against variations such as illumination, facial expression, and pose. Aside from this, it can be used for low-resolution face images acquired in uncontrolled environments or in the infrared spectrum. Experimental results show that our method outperforms state-of-the-art methods on FERET and SCface datasets.WOS:000437326800174Scopus - Affiliation ID: 60105072Science Citation Index ExpandedQ2 - Q3ArticleUluslararası işbirliği ile yapılmayan - HAYIRMayıs2018YÖK - 2017-1

An efficient framework for visible-infrared cross modality person re-identification

Visible-infrared cross-modality person re-identification (VI-ReId) is an essential task for video surveillance in poorly illuminated or dark environments. Despite many recent studies on person re-identification in the visible domain (ReId), there are few studies dealing specifically with VI-ReId. Besides challenges that are common for both ReId and VI-ReId such as pose/illumination variations, background clutter and occlusion, VI-ReId has additional challenges as color information is not available in infrared images. As a result, the performance of VI-ReId systems is typically lower than that of ReId systems. In this work, we propose a four-stream framework to improve VI-ReId performance. We train a separate deep convolutional neural network in each stream using different representations of input images. We expect that different and complementary features can be learned from each stream. In our framework, grayscale and infrared input images are used to train the ResNet in the first stream. In the second stream, RGB and three-channel infrared images (created by repeating the infrared channel) are used. In the remaining two streams, we use local pattern maps as input images. These maps are generated utilizing local Zernike moments transformation. Local pattern maps are obtained from grayscale and infrared images in the third stream and from RGB and three-channel infrared images in the last stream. We improve the performance of the proposed framework by employing a re-ranking algorithm for post-processing. Our results indicate that the proposed framework outperforms current state-of-the-art with a large margin by improving Rank-1/mAP by 29.79%/30.91% on SYSU-MM01 dataset, and by 9.73%/16.36% on RegDB dataset.WOS:000551127300017Scopus - Affiliation ID: 60105072Science Citation Index ExpandedQ2ArticleUluslararası işbirliği ile yapılmayan - HAYIREylül2020YÖK - 2020-2

Glyphosate inhibition of ferric reductase activity in iron deficient sunflower roots

Iron (Fe) deficiency is increasingly being observed in cropping systems with frequent glyphosate applications. A likely reason for this is that glyphosate interferes with root uptake of Fe by inhibiting ferric reductase in roots required for Fe acquisition by dicot and nongrass species. This study investigated the role of drift rates of glyphosate (0.32, 0.95 or 1.89 mM glyphosate corresponding to 1, 3 and 6% of the recommended herbicidal dose, respectively) on ferric reductase activity of sunflower (Helianthus annuus) roots grown under Fe deficiency conditions. Application of 1.89 mM glyphosate resulted in almost 50% inhibition of ferric reductase within 6 h and complete inhibition 24 h after the treatment. Even at lower rates of glyphosate (e.g. 0.32 mM and 0.95 mM), ferric reductase was inhibited. Soluble sugar concentration and the NAD(P)H oxidizing capacity of apical roots were not decreased by the glyphosate applications. To our knowledge, this is the first study reporting the effects of glyphosate on ferric reductase activity. The nature of the inhibitory effect of glyphosate on ferric reductase could not be identified. Impaired ferric reductase could be a major reason for the increasingly observed Fe deficiency in cropping systems associated with widespread glyphosate usage

The Effect of Personality Traits on Post-Traumatic Stress Disorder in Those Who Survived the 2020 Izmir Earthquake

Bu çalışmanın amacı 2020 İzmir depremini yaşayan bireylerde TSSB (Travma Sonrası Stres Bozukluğu) yaygınlığını, TSSB’yi etkileyen faktörleri ve kişilik özelliklerinin TSSB’ye etkisini incelemektir. Çalışmanın örneklemi İzmir depremini yaşayan 423 yetişkin kişiden oluşmaktadır. Çalışmada demografik bilgi formu, depremle ilgili soruların yer aldığı bilgi formu, DSM 5 için Travma Sonrası Stres Bozukluğu Kontrol Listesi (TSSBKL) ve Büyük Beş- 50 Kişilik Testi kullanılmıştır. Çalışmada 97 kişinin DSM 5 için TSSBKL ölçeğinden 48 puan ve üstü alarak TSSB tanısı alabilecek düzeyde oldukları tespit edilmiştir. TSSB’yi yordayan risk faktörleri arasında kadın olmak, genç yaşta olmak, depremden ekonomik anlamda olumsuz etkilenmek, deprem sonrası evin hasar alması, deprem sonrası ev değiştirmek ve tanıdığı birinin yaralanması yer almıştır. Kişilik özelliklerinin TSSB’yi yordayıcı etkisinin incelenmesi amacıyla yapılan Çoklu Doğrusal Regresyon Analizi sonuçlarına göre ise Duygusal Dengelilik Faktörünün TSSB’yi yordadığı tespit edilmiştir. Bu bulguların, psikologların doğal afetlere maruz kalan insanlar için müdahale stratejileri geliştirmeleri ve TSSB tanısı olan bireylerin iyileşmesine yardımcı olmaları için faydalı olacağı düşünülmektedir.The aim of this study is to examine the prevalence of PTSD (Post-traumatic Stress Disorder), the predictive factors of PTSD, and the effect of personality traits on PTSD in individuals who experienced the 2020 Izmir earthquake. The study sample consists of 423 adults who experienced the Izmir earthquake. Demographic information form, information form including questions about earthquakes, Post Traumatic Stress Disorder Checklist for DSM 5, and the Big Five- 50 Personality Test were used in the study. The study determined that 97 people were at a level to be diagnosed with PTSD by getting 48 points and above from the PTSDCL (Post-traumatic Stress Disorder Control List) scale for DSM 5. Among the risk factors predicting PTSD were being a woman, being young, being negatively affected by the earthquake, damage to the house after the earthquake, changing house after the earthquake, and injury to a friend. According to the results of the Multiple Linear Regression Analysis conducted to examine the predictive effect of personality traits on PTSD, it was determined that the Emotional Stability Factor predicted PTSD. It is thought that these findings will be helpful for psychologists to develop intervention strategies for people exposed to natural disasters and to help individuals with a diagnosis of PTSD recover

Passenger Flows Estimation of Light Rail Transit (LRT) System in Izmir, Turkey Using Multiple Regression and ANN Methods

Passenger flow estimation of transit systems is essential for new decisions about additional facilities and feeder lines. For increasing the efficiency of an existing transit line, stations which are insufficient for trip production and attraction should be examined first. Such investigation supports decisions for feeder line projects which may seem necessary or futile according to the findings. In this study, passenger flow of a light rail transit (LRT) system in Izmir, Turkey is estimated by using multiple regression and feed-forward back-propagation type of artificial neural networks (ANN). The number of alighting passengers at each station is estimated as a function of boarding passengers from other stations. It is found that ANN approach produced significantly better estimations specifically for the low passenger attractive stations. In addition, ANN is found to be more capable for the determination of trip-attractive parts of LRT lines.   Keywords: light rail transit, multiple regression, artificial neural networks, public transportatio

Human semantic parsing for person re-identification

Person re-identification is a challenging task mainly dueto factors such as background clutter, pose, illuminationand camera point of view variations. These elements hinder the process of extracting robust and discriminative representations, hence preventing different identities from being successfully distinguished. To improve the representation learning, usually local features from human body partsare extracted. However, the common practice for such aprocess has been based on bounding box part detection.In this paper, we propose to adopt human semantic parsing which, due to its pixel-level accuracy and capabilityof modeling arbitrary contours, is naturally a better alternative. Our proposed SPReID integrates human semanticparsing in person re-identification and not only considerably outperforms its counter baseline, but achieves stateof-the-art performance. We also show that, by employinga simple yet effective training strategy, standard populardeep convolutional architectures such as Inception-V3 andResNet-152, with no modification, while operating solelyon full image, can dramatically outperform current stateof-the-art. Our proposed methods improve state-of-the-artperson re-identification on: Market-1501 [48] by ~17% inmAP and ~6% in rank-1, CUHK03 [24] by ~4% in rank-1and DukeMTMC-reID [50] by ~24% in mAP and ~10% inrank-1.Computer Vision FoundationWOS:000457843601020Scopus - Affiliation ID: 60105072Conference Proceedings Citation Index- ScienceProceedings PaperHaziran2018YÖK - 2017-1

FT3/FT4 ratio predicts non-alcoholic fatty liver disease independent of metabolic parameters in patients with euthyroidism and hypothyroidism

OBJECTIVE: This study was performed to evaluate the effects of metabolic parameters and thyroid dysfunction on the development of non-alcoholic fatty liver disease (NAFLD). METHODS: The current study evaluated a total of 115 patients, 75 female and 40 male. Physical examination and anthropometric measurements were applied to all participants. Hypothyroidism was considered at a thyroid stimulating hormone level ≥ 4.1 mIU/L. Patients with euthyroidism and patients with hypothyroidism were compared. Abdominal ultrasonography was used to diagnose non-alcoholic fatty liver disease. The participants were further compared with regard to the presence of non-alcoholic fatty liver disease. Logistic regression modeling was performed to identify the relationship between non-alcoholic fatty liver disease and independent variables, such as metabolic parameters and insulin resistance. RESULTS: Non-alcoholic fatty liver disease was identified in 69 patients. The mean waist circumference, body mass index, fasting plasma insulin, HOMA-IR (

SAKARYA NEHRİ ÜZERİNDEKİ HİDROLİK YAPILARIN NEHİR AKIMI REJİMİNE OLAN ETKİLERİNİN ARAŞTIRILMASI

Barajlar, üzerine inşaa edildikleri akarsuların Hidrolojik, Morfolojik ve Sediment Taşıma Kapasitesi gibi karakteristik özelliklerinde zaman içinde önemli ölçüde değişiklikler meydana getirmektedirler. Bu çalışmada, Orta Sakarya Havzasında Sarıyar, Gökçekaya ve Yenice Barajlarının ve Pamukova Hidroelektrik Santrali (HES) ve Regülatörünün inşa edilmesinden sonra Aşağı Sakarya Nehrinde meydana gelen hidrolik değişimler araştırılmıştır. Her bir barajın tam kapasite işletmeye alınmasından önce ve sonraki durumlar için nehirdeki akımların değişimi ayrı ayrı incelenmiştir. Aşağı Sakarya Nehri üzerindeki Doğançay ve Botbaşı istasyonlarına ait değerler her bir baraj ve regülatörün işletmeye alındığı tarihlerin öncesi ve sonrası akım değişimleri grafikler halinde gösterilmektedir. Ayrıca, her iki istasyona ait maksimum anlık feyezan akımları kullanılarak gelmesi muhtemel taşkınlardaki değişimler incelenmektedir. Sonuçlar incelendiğinde; Nehirde taşkın pik debileri düşerken, nehir rejiminin düzenlendiği görülmüştür

Functional and Oncological Outcomes of Open Partial Laryngectomy vs. Transoral Laser Surgery in Supraglottic Larynx Cancer

Objective: The aim of the presented study was to evaluate the outcomes of open partial laryngectomy (OPL) versus transoral laser surgery (TLS) in patients operated on for supraglottic laryngeal carcinoma based on functional parameters (duration of hospitalization, oral nutritional status and duration of transition to oral feeding, weaning status and duration after tracheotomy, and postoperative voice results) and oncological results (overall survival rate, disease-specific survival rate, recurrence, and presence of second primary tumors) in both groups.Methods: All laryngeal carcinoma patients who had undergone either OPL or TLS in the period from January 2012 to March 2017 in our center and were followed-up at least for 36 months were included in the study. Statistical analyses were carried out using the t-test and the Mann-Whitney U test to compare the means, and the Kaplan-Meier test for survival analysis.Results: Fifty patients (44 males and 6 females) met the study criteria, of whom 31 had undergone OPL and 19 TLS. Patients that underwent TLS had less tracheotomy needs, needed shorter hospitalization periods, and transitioned to oral feeding earlier, compared to those that underwent OPL. There were no significant differences between the two groups based on oral feeding rates and voice outcomes. The impact of TLS and OPL on organ preservation in supraglottic laryngeal cancer were comparable. For local recurrences, repeated endolaryngeal laser surgeries and adjuvant treatments could be used in the TLS patient group. There were no significant differences between the two groups based on overall survival rate and disease specific survival rate.Conclusion: Although no significant differences were found in our study between the two surgical procedures in terms of oncological outcomes, TLS appeared to produce better functional outcomes in supraglottic laryngeal carcinoma than OPL