3654 results
Search Results
Now showing 1 - 10 of 3654
Conference Object Embryo Spatial Model Reconstruction(Springer international Publishing Ag, 2020) Dirvanauskas, Darius; Maskeliunas, Rytis; Raudonis, Vidas; Misra, SanjayTime lapse microscopy offered new solutions to study embryo development process. It allows embryologist to monitor embryo growth in real time and evaluate them without interfering into their growth environment. Embryo evaluation during growth process is one of the key criteria in embryo selection for fertilization. Live embryo monitoring is time consuming and new tools are offered to automate part of process. Our proposed algorithm gives new possibilities for embryo monitoring. It uses embryo images which are taken from different embryo layers, extracts embryo cell features and returns metrical evaluation to compare different embryos. High number of extracted features shows embryo fragmentation. Other tool whichwe present is spatial embryo model. Features extracted from embryo layers are combined together to spatial model. It allows embryologist to examine embryo model and compare different layers in one space. The obtained spatial embryo model will be later used to develop new algorithms for embryo analysis tasks.Article Citation - WoS: 5Citation - Scopus: 7Mild Solutions for Conformable Fractional Order Functional Evolution Equations Via Meir-Keeler Type Fixed Point Theorem(Univ Nis, Fac Sci Math, 2025) Berrighi, Fatma; Medjadj, Imene; Karapinar, ErdalIn this study, we delve into the realm of mild solutions for conformable fractional order functional evolution equations, focusing on cases where the fractional order is strictly greater than 1 and less than 2 within a separable Banach space. We demonstrate the existence, uniqueness, attractivity, and controllability of these solutions under local conditions. Our approach involves leveraging a contribution of Meir-Keeler's fixed point theorem alongside the principle of measures of noncompactness. To demonstrate the practical ramifications of our theoretical finds, we provide a specific example that underscores the relevance and applications of the established results.Article Citation - WoS: 41Citation - Scopus: 52Discussion on Generalized-(αψ, Βφ)-Contractive Mappings Via Generalized Altering Distance Function and Related Fixed Point Theorems(Hindawi Ltd, 2014) Berzig, Maher; Karapinar, Erdal; Roldan-Lopez-de-Hierro, Antonio-FranciscoWe extend the notion of (alpha psi, beta phi)-contractive mapping, a very recent concept by Berzig and Karapinar. This allows us to consider contractive conditions that generalize a wide range of nonexpansive mappings in the setting of metric spaces provided with binary relations that are not necessarily neither partial orders nor preorders. Thus, using this kind of contractive mappings, we show some related fixed point theorems that improve some well known recent results and can be applied in a variety of contexts.Article Citation - WoS: 2Citation - Scopus: 19Periodic Points of Weaker Meir-Keeler Contractive Mappings on Generalized Quasimetric Spaces(Hindawi Publishing Corporation, 2014) Lin, Ing-Jer; Chen, Chi-Ming; Karapinar, ErdalBy using the weaker Meir-Keeler function phi and the triangular alpha-admissible mapping alpha, we introduce the notion of (alpha - phi)-weaker Meir-Keeler contractive mappings and prove a theorem which assures the existence of a periodic point for these mappings on generalized quasimetric spaces.Article Citation - WoS: 38Citation - Scopus: 60Career Abandonment Intentions among Software Workers(Wiley, 2014) Colomo-Palacios, Ricardo; Casado-Lumbreras, Cristina; Misra, Sanjay; Soto-Acosta, PedroWithin the software development industry, human resources have been recognized as one of the most decisive and scarce resources. Today, the retention of skilled IT (information technology) personnel is a major issue for employers and recruiters as well, since IT career abandonment is a common practice and means not only the loss of personnel, knowledge, and skills, but also the loss of business opportunities. This article seeks to discover the main motivations young practitioners abandon the software career. To achieve this objective, two studies were conducted. The first study was qualitative (performed through semistructured interviews) and intended to discover the main variables affecting software career abandonment. The second study was quantitative, consisting of a Web-based survey developed from the output of the first study and administered to a sample of 148 IT practitioners. Results show that work-related, psychological, and emotional variable are the most relevant group of variables explaining IT career abandonment. More specifically, the three most important variables that motivate employees to abandon the career are effort-reward imbalance, perceived workload, and emotional exhaustion. In contrast, variables such as politics and infighting, uncool work, and insufficient resources influence to a lesser extent the decision to leave the career. (c) 2012 Wiley Periodicals, Inc.Conference Object Citation - WoS: 1Citation - Scopus: 1A Novel Method To Detect Shadows on Multispectral Images(Spie-int Soc Optical Engineering, 2016) Sevim, Hazan Daglayan; Cetin, Yasemin Yardimci; Baskurt, Didem Ozisik; Yardlmcl Çetin, Yasemin; Özlşlk Başkurt, Didem; Daǧlayan Sevim, HazanShadowing occurs when the direct light coming from a light source is obstructed by high human made structures, mountains or clouds. Since shadow regions are illuminated only by scattered light, true spectral properties of the objects are not observed in such regions. Therefore, many object classification and change detection problems utilize shadow detection as a preprocessing step. Besides, shadows are useful for obtaining 3D information of the objects such as estimating the height of buildings. With pervasiveness of remote sensing images, shadow detection is ever more important. This study aims to develop a shadow detection method on multispectral images based on the transformation of C-1 C-2 C-3 space and contribution of NIR bands. The proposed method is tested on Worldview-2 images covering Ankara, Turkey at different times. The new index is used on these 8-band multispectral images with two NIR bands. The method is compared with methods in the literature.Article Citation - WoS: 5Citation - Scopus: 5Physical Characterization of Thermally Evaporated Sn-Sb Thin Films for Solar Cell Applications(Springer Heidelberg, 2023) Bektas, Tunc; Surucu, Ozge; Terlemezoglu, Makbule; Parlak, MehmetThe substitution of Sb in binary SnSe structure may lead to tailoring the physical properties of both SnSe and SbSe, promising absorber layers for thin film solar cells. The resulting Sn-Sb-Se structure could be an outstanding material for photovoltaic applications. In this study, Sn-Sb-Se thin films were deposited by thermal evaporation, and the effect of annealing on the films' structural, optical, and electrical properties were reported. XRD measurement shows that annealing at 300 degrees C yields the best crystalline quality, and structural parameters were calculated using XRD data. SEM and AFM measurements indicate deformation in the film surface after annealing at 400 degrees C. UV-Vis spectroscopy measurement provides a high absorption coefficient which indicates a direct band gap. The band gap and activation energies of the as-grown sample were found as 1.59 eV and 106.1 meV, respectively. The results of SEM, AFM, XRD, Raman, UV-Vis spectroscopy and temperature-dependent photoconductivity measurements were discussed throughout the paper.Article Citation - WoS: 18Citation - Scopus: 21Modeling Dependence Between Two Multi-State Components Via Copulas(Ieee-inst Electrical Electronics Engineers inc, 2014) Eryilmaz, SerkanModeling statistical dependence between two systems or components is an important problem in reliability theory. Such a problem has been well studied for binary systems and components. In the present paper, we provide a way for modeling s-dependence between two multi-state components. Our method is based on the use of copulas which are very popular for modeling s-dependence. We obtain expressions for the joint state probabilities of the two components, and illustrate the results for the case when the degradation in both components follows a Markov process.Book Part Citation - Scopus: 2Novel Covid-19 Recognition Framework Based on Conic Functions Classifier(Springer Science and Business Media Deutschland GmbH, 2022) Karim,A.M.; Mishra,A.The new coronavirus has been declared as a global emergency. The first case was officially declared in Wuhan, China, during the end of 2019. Since then, the virus has spread to nearly every continent, and case numbers continue to rise. The scientists and engineers immediately responded to the virus and presented techniques, devices and treatment approaches to fight back and eliminate the virus. Machine learning is a popular scientific tool and is applied to several medical image recognition problems, involving tumour recognition, cancer detection, organ transplantation and COVID-19 diagnosis. It is proved that machine learning presents robust, fast and accurate results in various medical image recognition problems. Generally, machine learning-based frameworks consist of two stages: feature extraction and classification. In the feature extraction, overwhelmingly unsupervised learning techniques are applied to reduce the input data’s size. This step extracts appropriate features by reducing the computational time and increasing the performance of the classifiers. A classifier is the second step that aims to categorise the input. Within the proposed step, the unsupervised part relies on the feature extraction by using local binary patterns (LBP), followed by feature selection relying on factor analysis technique. The LBP is a kind of visual descriptor, mainly applied for image recognition problem. The aim of using LBP is to analyse the input COVID-19 image and extract salient features. Furthermore, factor analysis is a statistical technique applied to define variability among observed variables in less unnoticed variables named factors. The factor analysis applied to the LBP wavelet aims to select sensitive features from input data (LBP output) and reduce the size input. In the last stage, conic functions classifier is applied to classify two sets of data, categorising the extracted features by using LBP and factor analysis as positive or negative COVID-19 cases. The proposed solution aims to diagnose COVID-19 by using LBP and factor analysis, based on conic functions classifier. The conic functions classifier presents remarkable results compared with these popular classifiers and state-of-the-art studies presented in the literature. © 2022, Springer Nature Switzerland AG.Article Complex Partial Differential Equations(Springer, 2025) Aksoy, Ü.; Begehr, H.; Çelebi, A.; Shupeyeva, B.The Schwarz and iterated Dirichlet boundary-value problems are reported on for the polyanalytic operator in certain plane domains having a harmonic Green function. Hybrid polyharmonic Green functions are reviewed upon which open a variety of boundary-value problems for the polyharmonic operator. This topic is far from being complete. The higher the order of the polyharmonic operator the richer is the theory of related hybrid Green functions: they are constructed by continued convoluting harmonic Green, Neumann, Robin functions also incorporating polyharmonic Green–Almansi functions. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.
