On evaluating Weibull fits to mechanical testing data

The use of coefficient of determination, R², and the Anderson–Darling (A²) hypothesis test to evaluate the goodness-of-fit to the two-parameter Weibull distribution was investigated. Results of Monte Carlo simulations for sample sizes between 5 and 100 indicated that guidelines provided previously in the literature are too conservative for sample sizes up to 80. New guidelines for the use of R² and A² for sample sizes between 5 and 100 have been developed. The two measures of goodness-of-fit were found to agree more than 95% of the time, regardless of sample size. The use of the new guidelines has been demonstrated on two datasets from the casting literature.     

Investigation of UV and I–V characteristics of high refractive index polymer thin film for optoelectronic applications

In this study, high refractive index polymer (HRIP) [poly(pentabromobenzyl methacrylate-co-glycidyl methacrylate)] was investigated to obtain its optical and electrical performance for optoelectronic applications. UV characteristics of the polymer in solution of tetrahydrofuran were obtained and optical band gap energy of the polymer was calculated as 3.8 eV. I–V characteristics of the polymer were investigated after HRIP thin film was prepared using spin coating technique. The electrical parameters such as barrier height Φ_Bo, ideality factor n and reverse saturation current I_o were extracted from the forward biasing I–V characteristics. At the same time, series resistance R_s and Φ_Bo were determined by using a modified Norde function combined with conventional forward I–V method.     

Properties of sol–gel synthesized n-ZnO/n-GaN (0001) isotype heterojunction

The electronic and optical properties of sol–gel synthesized n-ZnO/n-GaN (0001) isotype heterojunction were reported. By incorporating ZnO–GaN with the same wurtzite structure and the similar lattice constant, a heterojunction was fabricated. The junction properties were evaluated by measuring the electrical characteristics. The n-ZnO/n-GaN heterostructure exhibits a non-ideal I–V behavior with the ideality factor greater than unity that could be ascribed to the interfacial layer, interface states and series resistance. The forward turn on voltage is about 0.7 V and the reverse breakdown voltage is more than 2 V. The optical band gaps of the ZnO film and GaN using optical absorption method were found to be 3.272 eV and 3.309 eV, respectively. The fundamental absorption edge in the film is formed by the direct allowed transitions.     

The long‐term effects of arteriovenous fistula creation on the development of pulmonary hypertension in hemodialysis patients

The aim of this prospective study was to evaluate long‐term effects of arteriovenous fistula (AVF) on the development of pulmonary arterial hypertension (PAH) and the relationship between blood flow rate of AVF and pulmonary artery pressure (PAP) in the patients with end‐stage renal disease (ESRD). This prospective study was performed in 20 patients with ESRD. Before an AVF was surgically created for hemodialysis, the patients were evaluated by echocardiography. Then, an AVF was surgically created in all patients. After mean 23.50 ± 2.25 months, the second evaluation was performed by echocardiography. Also, the blood flow rate of AVF was measured at the second echocardiographic evaluation. Pulmonary arterial hypertension was defined as a systolic PAP above 35 mmHg at rest. Mean age of 20 patients with ESRD was 55.05 ± 13.64 years; 11 of 20 patients were males. Pulmonary arterial hypertension was detected in 6 (30%) patients before AVF creation and in 4 (20%) patients after AVF creation. Systolic PAP value was meaningfully lower after AVF creation than before AVF creation (29.95 ± 10.26 mmHg vs. 35.35 ± 7.86 mmHg, respectively, P: 0.047). However, there was no significant difference between 2 time periods in terms of presence of PAH (P>0.05). Pulmonary artery pressure did not correlate with blood flow rate of AVF and duration after AVF creation (P>0.05). In hemodialysis patients, a surgically created AVF has no significant effect on the development of PAH within a long‐term period. Similarly, blood flow rate of AVF also did not affect remarkably systolic PAP within the long‐term period.     

A greedy gradient-simulated annealing selection hyper-heuristic

Educational timetabling problem is a challenging real world problem which has been of interest to many researchers and practitioners. There are many variants of this problem which mainly require scheduling of events and resources under various constraints. In this study, a curriculum based course timetabling problem at Yeditepe University is described and an iterative selection hyper-heuristic is presented as a solution method. A selection hyper-heuristic as a high level methodology operates on the space formed by a fixed set of low level heuristics which operate directly on the space of solutions. The move acceptance and heuristic selection methods are the main components of a selection hyper-heuristic. The proposed hyper-heuristic in this study combines a simulated annealing move acceptance method with a learning heuristic selection method and manages a set of low level constraint oriented heuristics. A key goal in hyper-heuristic research is to build low cost methods which are general and can be reused on unseen problem instances as well as other problem domains desirably with no additional human expert intervention. Hence, the proposed method is additionally applied to a high school timetabling problem, as well as six other problem domains from a hyper-heuristic benchmark to test its level of generality. The empirical results show that our easy-to-implement hyper-heuristic is effective in solving the Yeditepe course timetabling problem. Moreover, being sufficiently general, it delivers a reasonable performance across different problem domains.     

HihO: accelerating artificial intelligence interpretability for medical imaging in IoT applications using hierarchical occlusion

Neural Computing and Applications - In the medical imaging domain, nonlinear warping has enabled pixel-by-pixel mapping of one image dataset to a reference dataset. This co-registration of data...     

BiLSTM and dynamic fuzzy AHP-GA method for procedural game level generation

Neural Computing and Applications - The use of games in daily life, especially in education, has been in an incline during the COVID-2019 pandemic. Thus, game-based learning environments have...     

MARS: A tool-based modeling,animation, and parallel rendering system

This paper describes a system for modeling, animating, previewing and rendering articulated objects. The system has a modeler of objects that consists of joints and segments. The animator interactively positions the articulated object in its stick, control vertex, or rectangular prism representation and previews the motion in real time. Then the data representing the motion and the models is sent to a multicomputer [iPSC/2 Hypercube (Intel)]. The frames are rendered in parallel, exploiting the coherence between successive frames, thus cutting down the rendering time significantly. Our main aim is to make a detailed study on rendering of a sequence of 3D scenes. The results show that due to an inherent correlation between the 3D scenes, an efficient rendering can be achieved.     

Derivation of a parameter stabilizing training criterion for adaptive neuro-fuzzy inference systems in motion control

This paper presents a novel training algorithm for adaptive neuro-fuzzy inference systems. The algorithm combines the error back-propagation algorithm with the variable structure systems approach. Expressing the parameter update rule as a dynamic system in continuous time and applying sliding mode control (SMC) methodology to the dynamic model of the gradient based training procedure results in the parameter stabilizing part of training algorithm. The proposed combination therefore exhibits a degree of robustness to the unmodelled multivariable internal dynamics of the gradient-based training algorithm. With conventional training procedures, the excitation of this dynamics during a training cycle can lead to instability, which may be difficult to alleviate owing to the multidimensionality of the solution space and the ambiguities concerning the environmental conditions. This paper shows that a neuro-fuzzy model can be trained such that the adjustable parameter values are forced to settle down (parameter stabilization) while minimizing an appropriate cost function (cost optimization), which is based on state tracking performance. In the application example, trajectory control of a two degrees of freedom direct drive robotic manipulator is considered. As the controller, an adaptive neuro-fuzzy inference mechanism is used and, in the parameter tuning, the proposed algorithm is utilized.