Kutu Enkesitli Sandviç Tipi Çelik Çaprazların Çevrimsel Yük Etkisindeki Davranışlarının Deneysel Olarak İncelenmesisi

Bu çalışmada, yapısal sistemlerde yanal yük taşıyıcı elemanlar olarak kullanılan, kutu enkesitli geleneksel çelik çapraz elemanların burkulma davranışının kontrolü için bir yöntem önerilmektedir. Önerilen yöntemde, kutu enkesitli çelik çapraz içten ve dıştan iki ayrı kutu profilin arasına yerleştirilerek sandviç tipi bir çelik çapraz eleman elde edilmiştir. Burkulma kontrolünü sağlamak için kullanılan iç ve dış profillerin boyu yanal yük taşıyıcı elemanın boyundan daha kısa bırakılarak, bu profillerin eksenel yük taşımaları engellenmiştir. Deneysel çalışmalar kapsamında bir adet kutu enkesitli sandviç tipi çelik çapraz ile aynı özelliklerdeki kutu enkesitli profilden üretilmiş bir geleneksel çelik çapraz çevrimsel yük etkisinde test edilmiştir. Elde edilen bulgular yük taşıma kapasitesi, burkulma yerdeğiştirmesi ve enerji tüketme kapasitesi açısından karşılaştırılmalı olarak incelenmiştir. Sonuç olarak, önerilen burkulma kontrolü tasarımının, geleneksel çelik çaprazların yük taşıma kapasitesini, burkulma yerdeğiştirmesini ve enerji tüketme kapasitesini artırdığı belirlenmiştir

Modelling and simulation with neural and fuzzy-neural networks of switched circuits

Recently, the modelling and simulation of switched systems containing new nonlinear components in electronics and power electronics industry have gained importance. In this paper, both feed‐forward artificial neural networks (ANN) and adaptive network‐based fuzzy inference systems (ANFIS) have been applied to switched circuits and systems. Then their performances have been compared in this contribution by developed simulation programs. It has been shown that ANFIS require less training time and offer better performance than those of ANN. In addition, ANFIS using “clustering algorithm” to generate the rules and the numbers of membership functions gives a smaller number of parameters, better performance and less training time than those of ANFIS using “grid partition” to generate the rules. The work not only demonstrates the advantage of the ANFIS architecture using clustering algorithm but also highlights the advantages of the architecture for hardware realizations

Job satisfaction of advisors working in Private Educational Institutions: Izmir case Özel Eğitim Kurumlarında çalışan rehber öğretmenlerin iş doyumları: İzmir örneği

The aim of his study was to help teachers by preparing a more consistent work environment, their institutions to understand teachers’ purpose and motivate them to perform better in terms of providing better conditions and guidance services. A demographic information form and occupational satisfaction measure were applied to the advisors working in 108 special education institutions in Izmir. A significant relationship between marital status, age, graduation, professional experience, income level and job satisfaction was found. However, there was no significant relationship between gender, level of education, duration of study, type of service, and job satisfaction.Extended English abstract is in the end of PDF (TURKISH) file.  ÖzetBu araştırma, rehber öğretmenlere daha tutarlı bir çalışma ortamı hazırlayarak onların çalıştıkları kurumların amaç ve değerlerini anlamalarını sağlama, onları ileri düzeyde motive ederek daha iyi bir performans göstermelerine olanak verme ve rehberlik hizmetlerini daha sağlıklı koşullarda sunabilme amaçlarını gütmektedir. Araştırmada, İzmir iline bağlı 108 özel eğitim kurumunda çalışan rehber öğretmene kişisel bilgi formu ve mesleki doyum ölçeğini içeren anket uygulanmıştır. Araştırmanın sonucunda, demografik değişkenler içerisinde yer alan medeni durum, yaş, mezuniyet, mesleki tecrübe, ve gelir düzeyi ile iş doyumu arasında anlamlı bir ilişkinin olduğu; cinsiyet, öğrenim düzeyi, çalışma süresi, hizmet türü ve yer değişkeni ile iş doyumu arasında anlamlı bir ilişkinin olmadığı saptanmıştır.

Moving towards in object recognition with deep learning for autonomous driving applications

Object recognition and pedestrian detection are of crucial importance to autonomous driving applications. Deep learning based methods have exhibited very large improvements in accuracy and fast decision in real time applications thanks to CUDA support. In this paper, we propose two Convolutions Neural Networks (CNNs) architectures with different layers. We extract the features obtained from the proposed CNN, CNN in AlexNet architecture, and Bag of visual Words (BOW) approach by using SURF, HOG and k-means. We use linear SVM classifiers for training the features. In the experiments, we carried out object recognition and pedestrian detection tasks using the benchmark the Caltech 101 and the Caltech Pedestrian Detection datasets

Syndrome of Inappropriate Antidiuretic Hormone Secretion Associated with Pramipexole

One of the most common causes of hyponatremia is inappropriate antidiuretic hormone release syndrome (SIADH). Serotonin reuptake inhibitors, tricyclic antidepressants, carbamazepine, amantadine and cytotoxic drugs can cause of hyponatremia as a result of SIADH. Pramipexole is a non-ergot dopamine agonist. It is frequently used for treatment of Parkinson disease and restless legs syndrome. Pramipexole-associated SIADH are rare in Parkinson disease. Also, pathogenetic mechanisms are uncertain. In our case, SIADH associated with pramipexole was presented in Parkinson disease. Clinical symptoms and hyponatremia occurred 12 days after the drug dose increase. Serum sodium level and clinical complaints returned to normal with drug dose reduction. SIADH-related hyponatremia occurs especially within the first 2-3 weeks after pramipexole treatment. Therefore, patients treated with pramipexole should be monitored more frequently for hyponatremia in the first weeks and dose increase

Türkiye’nin sağlık turizmi pazar payını arttırıcı stratejilerin bulanık AHP yöntemi kullanılarak geliştirilmesi

The purpose of this study is to develop health tourism strategies in order to get more share of the international market. In this scope, firstly the negatives for health tourism of Turkey are examined by researching literature. Then a fuzzy AHP (Analytic Hierarchy Process) method was employed in the study. The decision-making group consists of the health tourism and management and strategy experts of hospital and university who have at least twelve years of experience. According to analysis findings, decision makers primarily chose the subjects of Insufficient legal sanctions for faulty applications, lack of coordination with agencies and insurance companies abroad and insufficient number of physicians and health personnel who can speak a foreign language and qualified. For increasing market share of Turkey on health tourism priority strategies can be as follows; legal regulations should be made that are comprehensive, future-oriented and protect all stakeholders, including important organs of the public and private sector and complication insurance may be required, in order to ensure the coordination of national and international stakeholders, the conference, fairs and events should be increased and each stakeholder should be taken into account, and finally in order to increase the foreign language skills of physicians and healthcare personnel, it is necessary to cooperate with Ministry of Health, Ministry of National Education and Universities.Bu çalışmanın amacı, Türkiye’nin uluslararası sağlık turizmi pazarından daha fazla pay alabilmesi için strateji önerilerinde bulunmaktır. Bu kapsamda öncelikle Türkiye’nin sağlık turizmine yönelik zayıf yönleri literatür taraması yapılarak incelenmiştir. Akabinde çalışmada öncelikli alanların belirlenebilmesi amacıyla Bulanık AHS (Analitik Hiyerarşi Süreci) yöntemi kullanılmıştır. Yöntemde, en az on iki yıllık deneyime sahip, sağlık turizmi ve yönetim strateji alanındaki üç farklı uzmanın görüşleri alınmıştır. Analiz bulgularına göre uzmanlar, hatalı uygulamalar sonucunda yeterli yasal yaptırımların olmamasını, yurt dışındaki acente ve sigorta şirketleri ile yaşanan koordinasyon eksikliğini ve yetersiz sayıdaki yabancı dil bilen, kalifiye hekim ve sağlık personelini öncelikli alanlar olarak seçmiştir. Türkiye'nin sağlık turizminde pazar payını artırmak için öncelikli stratejiler şu şekilde olabilir; geleceğe yönelik, kamu ve özel sektörün önemli organları dahil tüm paydaşları güvence altına alan yasal düzenlemeler yapılmalıdır. Buna ek olarak, Ulusal ve uluslararası paydaşlar arasındaki koordinasyon ve bilgi paylaşımını artırmak amacıyla konferans, fuar vb. etkinlikler artırılmalıdır. Son olarak hekim ve sağlık personelinin mesleki yetkinlerinin ve yabancı dil becerilerinin artırılması için Sağlık Bakanlığı, Milli Eğitim Bakanlığı ve Üniversiteler ile iş birliği yapılması gerekmektedir

Unocculuded object grasping by using visual data

Automatic grasping objects can become important in the areas such as industrial processes, processes which are dangerous for human, or the operations which should be executed in the places, small for people work. In this study, it is aimed to design a robotic system for grasping unocculuded certain objects by using visual data. For this aim an experimental process was implemented. Visual data process can be divided in two main parts: identification and three dimensional positioning. Identification issue suffers from several conditions as rotation, camera position, and location of the subject in the frame. Also obtaining the features invariant from these conditions is important. Therefore Zernike moment method can be used to overcome these negativities. In order to identify the objects an artificial neural network was used to classify the objects by using Zernike moment coefficients. In the experimental system a parallel axis stereovision subsystem, a DSPFPGA embedded media processor, and five-axis robot arm were used. The success rate of artificial neural network was 98%. After identifying the objects, a sequential algebra were performed in the DSP part of the media processor and the position of the object according to robot arm reference point was extracted. After all, desired object in the instant frame was grasped and placed in different location by the robot arm

An implementation of vision based deep reinforcement learning for humanoid robot locomotion

Deep reinforcement learning (DRL) exhibits a promising approach for controlling humanoid robot locomotion. However, only values relating sensors such as IMU, gyroscope, and GPS are not sufficient robots to learn their locomotion skills. In this article, we aim to show the success of vision based DRL. We propose a new vision based deep reinforcement learning algorithm for the locomotion of the Robotis-op2 humanoid robot for the first time. In experimental setup, we construct the locomotion of humanoid robot in a specific environment in the Webots software. We use Double Dueling Q Networks (D3QN) and Deep Q Networks (DQN) that are a kind of reinforcement learning algorithm. We present the performance of vision based DRL algorithm on a locomotion experiment. The experimental results show that D3QN is better than DQN in that stable locomotion and fast training and the vision based DRL algorithms will be successfully able to use at the other complex environments and applications.TÜBİTAK ve NVIDI

A Novel MPTHP Modified Glassy Carbon Sensor Electrode: Investigation of Electrochemical Behaviors and Determination of Cu (II) Ions in Drinking Water Sample

In the present work report, 2-methyl-6-((2-(4-(3-methyl-3-phenylcyclobutyl)thiazol-2-yl)hydrazono)methyl) phenol (MPTHP) has been newly synthesized and characterized. The new molecule has been used to modify the glassy carbon (GC) electrode surface through the alcohol oxidation method due to –OH group on its structure. MPTHP modified GC (MPTHP/GC) electrode has been used as a chemical sensor electrode for the quantitative determination of Cu (II) ions. Following the modification process, the surface characterization process of the modified electrode has been carried out by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS) and scanning electron microscopy (SEM). In this work, Cu (II) ions have been quantitatively determined by using differential pulse voltammetry (DPV) technique. A quite low detection limit (based on 3sbl/m) for Cu (II) using developed sensor electrode was found to be as 1.0x10-9 M. For the calibration curve, solutions of Cu (II) ions changing from 1.0x10-9 M to 1.0x10-3 M have been prepared using Britton-Robinson (BR) buffer solution at pH 5. The developed sensor electrode has been applied to tap water sample for the quantitation of Cu (II) ions and the amount of Cu (II) was determined as 4.07 x 10-9 M in this sample

Total antioxidant and oxidant status in obese children without insulin resistance

Objective: Oxidative stress in obese children may lead in adulthood serious conditions such as coronary heart diseases or type 2 diabetes mellitus. In childhood oxidative stress is associated with insulin resistance or extreme obesity. In this study, we aimed to evaluate oxidative stress status in moderately obese children without insulin resistance. Methods: A total of 38 obese children (21 male, 17 female) without insulin resistance, mean aged 9.4±3.8 years) and 51 normal weight children (25 male, 26 female) as the control group, mean aged 9.3±3.9 years) were enrolled to the study. Total oxidative status (TOS), total antioxidant capacity (TAC) were measured and oxidative stress index (OSI) was calculated. Results: The results reveal that obese children had lower TAC than normal weight children (2,27±0,28 vs. 2.76±0.35 mmol Trolox Eq./L; p<0,001). There was no statistical difference between obese and control groups regarding TOS (6,08±3,63 vs 5.25±4.16 μmol H2O2 Eq./L; p=0.333). OSI was higher in obese group (2.65±1.52 vs 1.92±1.56; p=0.029) Conclusion: Balance between oxidant and antioxidant system is disrupted due to the reduced TAC even in moderately obese children without insulin resistance. Further studies should also be performed to evaluate the beneficial effects of dietary intake of antioxidants in these children