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Density functional theory (DFT) is a computational quantum mechanical modelling method used in physics, chemistry and materials science to investigate the electronic structure (principally the ground state) of many-body systems, in particular atoms, molecule…

It is well-known that the Sturm-Liouville type boundary value problems appears in solving many important problems in physics. For example, some problems of theory of elasticity in a half-strip ,the problems of theory of vibrations of an elastic cylinder redu…

With the development of technology and growth of social networking among individuals, the quantitative study of social dynamics has attracted a great interest from researchers. In this study, we propose a stochastic binary opinion model where agents are consid…

A useful and flexible method based on the salp swarm algorithm (SSA) for the pattern nulling of linear antenna arrays with the prescribed nulls is presented. SSA is a relatively new population based evolutionary optimization algorithm. Nulling of the pattern i…

Handwritten Signature Recognition (HSR) is a vital task in document authentication and verification systems. This paper proposes a novel approach for offline HSR leveraging pre-trained Convolutional Neural Network (CNN) models. CNNs have demonstrated remarkabl…

In this paper, signal recognition system is proposed for classification of soil types and buried object by using feature extraction and artificial neural networks. Using GprMax simulation program, 300 GPR A scan signals were obtained for different ground plane…

Çok-modlu medikal görüntü birleştirme, görüntü kalitesini artırmak için iki ya da daha fazla medikal görüntünün birleştirilmesidir. Tıbbi görüntüleme sağlık alanında teşhis, araştırma ve tedavide önemli bir rolü üstlenmektedir. Tanı ve tedavide daha doğru klin…

Traffic flow forecasting has an important place in designing a successful intelligent transportation system. The success of the forecasting is related to the accuracy and timely acquisition of the traffic flow data. The inadequacy in the number of data has led…

Evrimsel algoritma ve parçacık sürü algoritması çok uzun zamandır ayrı ayrı çeşitli karmaşık problemlerin çözümünde yaygın olarak kullanılan sezgisel algoritmalardır. Evrimsel algoritma canlıların çoğalmasını ve hayatta kalmak için en iyilerin seçilmesi tekniğ…

This study basically presents a review of robotic hands and its applications based on human hand motion. In the context of the review, different kinds of articles are analyzed. There are some hand motion-sensing methods, which are noncontact and direct contact…

Accurate and transparent blood glucose forecasting is crucial for effective diabetes management. This paper presents an interpretable deep learning (DL) framework based on multi-task learning (MTL) for forecasting glucose levels at multiple prediction horizons…

It is important to determine the initial level of failures of induction motors used in many industrial applications. The sudden stops of the system can be prevented with the pre-detection of the fault. The experiment mechanism was established to detect mechani…

Deep learning is a machine learning sub-field that uses deep neural networks. Instead of customized algorithms for each study in this field, it is aimed to cover the wider data set of solutions based on learning the data. Deep learning is a promising approach …

İnsan ve bilgisayar etkileşimi, interaktif teknolojilerin tasarımı, değerlendirilmesi ve uygulanması ile ilgilenen disiplinler arası bir çalışma alanıdır. Bankalar, hastaneler, okullar, internet siteleri gibi hayatın her alanında insan ve bilgisayar etkileşimi…

Özetçe - Mobil manipülatörler, çeşitli endüstrilerde önemli bir rol oynamakta olup, üretim ve lojistikten sağlık hizmetleri ve felaket müdahalesine kadar birçok göreve katkı sağlamaktadır. Bu nedenle dünya genelinde çeşitli endüstriler büyüdükçe mobil manipüla…

Maritime vessel detection in satellite images address real time issues such as maritime security, illegal fishing and environmental monitoring, which require efficient tracking of vessels in large scale. Maritime vessel detection is challenged by limited annot…

In this paper we presents an application of deep learning techniques to recognize handwritten source code characters. Although there are many works on the handwritten character recognition (HCR) problem, very few works have been done about the offline handwrit…

Predictive maintenance (PdM) enhances industrial operational efficiency by facilitating timely detection of equipment failures using machine learning models developed from historical maintenance data.  Real-world industrial datasets frequently exhibit signific…

Open-finance systems increasingly compose portfolio models, data services, and execution interfaces supplied by different parties. This modularity is useful only if the executed wealth path can be checked independently of the model that proposed it. We study a…

Accurate and efficient detection of aircraft at airports is crucial for enhancing airport security, ensuring safe operations, and improving overall air traffic management. As airports grow in complexity and traffic density increases, automated object detection…