Bilgisayar Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12469/45

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Citation - WoS: 12
Citation - Scopus: 15
Accurate Refinement of Docked Protein Complexes Using Evolutionary Information and Deep Learning
(Imperıal College Press, 2016) Akbal-Delibas, Bahar; Farhoodi, Roshanak; Pomplun, Marc; Haspel, Nurit
One of the major challenges for protein docking methods is to accurately discriminate native-like structures from false positives. Docking methods are often inaccurate and the results have to be refined and re-ranked to obtain native-like complexes and remove outliers. In a previous work we introduced AccuRefiner a machine learning based tool for refining protein-protein complexes. Given a docked complex the refinement tool produces a small set of refined versions of the input complex with lower root-mean-square-deviation (RMSD) of atomic positions with respect to the native structure. The method employs a unique ranking tool that accurately predicts the RMSD of docked complexes with respect to the native structure. In this work we use a deep learning network with a similar set of features and five layers. We show that a properly trained deep learning network can accurately predict the RMSD of a docked complex with 1.40 angstrom error margin on average by approximating the complex relationship between a wide set of scoring function terms and the RMSD of a docked structure. The network was trained on 35000 unbound docking complexes generated by RosettaDock. We tested our method on 25 different putative docked complexes produced also by RosettaDock for five proteins that were not included in the training data. The results demonstrate that the high accuracy of the ranking tool enables AccuRefiner to consistently choose the refinement candidates with lower RMSD values compared to the coarsely docked input structures.
Citation - WoS: 1
Citation - Scopus: 2
A Bayesian Approach To Developing a Strategic Early Warning System for the French Milk Market
(Halmstad University, 2017) Bisson, Christophe; Gürpınar, Furkan
A new approach is provided in our paper for creating a strategic early warning system allowing the estimation of the future state of the milk market as scenarios. This is in line with the recent call from the EU commission for tools that help to better address such a highly volatile market. We applied different multivariate time series regression and Bayesian networks on a pre-determined map of relations between macro-economic indicators. The evaluation of our findings with root mean square error (RMSE) performance score enhances the robustness of the prediction model constructed. Our model could be used by competitive intelligence teams to obtain sharper scenarios, leading companies and public organisations to better anticipate market changes and make more robust decisions.
Citation - WoS: 13
Characterization of Mps Capped Cds Quantum Dots and Formation Self-Assembled Quantum Dots Thin Films on a Glass Substrate
(Natl Inst R&D Materials Physics, 2011) Koç, Kenan; Tepehan, Fatma Zehra; Tepehan, Galip Gültekin
Colloidal powdered and thin film forms of MPS capped CdS quantum dots have been produced by combination of colloidal chemistry and sol-gel method. Nanoparticles were self-assembled directly on a glass substrate using spin coating method without introducing any matrix. Colloidal powdered and thin film forms were characterised by absorbance photolimunescence XRD FT-IR HRTEM and AFM measurements. The HRTEM images give a grain size of 2.5-3.0 nm and this is in agreement with the values found in the absorbance and XRD measurement. Average size of the quantum dots increase with increasing of heat treatment temperature due to Oswald ripening.
Citation - Scopus: 11
Competitive Intelligence and Information Technology Adoption of Smes in Turkey: Diagnosing Current Performance and Identifying Barriers
(Halmstad University, 2013) Wright, Sheila; Bisson, Christophe; Duffy, Alistair P.
The need for SMEs to behave in a more concise and coherent competitive fashion is well recognised. This study reports on an empirical study of SMEs in Turkey. Their responses were applied to a behavioural and information technology adoption framework which enabled the identification of areas where changes would be required for these firms to begin operating at a higher level of competence. The findings revealed significant scope for improvements on all strands of the diagnostic framework: attitude gathering location technology support IT systems support and finally use of intelligence-based output by decision-makers. Through free form responses it was also possible to identify barrier to higher level adoption and performance inhibiters which were subsequently categorised and assessed for significance.
Citation - WoS: 11
Citation - Scopus: 13
Lsb Image Steganography Based on Blocks Matrix Determinant Method
(KSII-KOR SOC Internet Information, 2019) Shehzad, Danish; Dağ, Tamer
Image steganography is one of the key types of steganography where a message to be sent is hidden inside the cover image. The most commonly used techniques for image steganography rely on LSB steganography. In this paper, a novel image steganography technique based on blocks matrix determinant method is proposed. Under this method, a cover image is divided into blocks of size 2 x 2 pixels and the determinant of each block is calculated. The comparison of the determinant values and corresponding data bits yields a delicate way for the embedment of data bits. The main aim of the proposed technique is to ensure concealment of secret data inside an image without affecting the cover image quality. When the proposed steganography method is compared with other existing LSB steganography methods, it is observed that it not only provides higher PSNR, lower MSE but also guarantees better quality of the stego image.
Citation - WoS: 6
Citation - Scopus: 6
Slow Release of Trapped Homopolymers From a Swelling Polymeric Gel: a Fluorescence Study
(Taylor & Francis Inc, 2008) Erdoğan, Matem; Yağcı, Yusuf; Pekcan, Önder
In-situ steady-state fluorescence experiments were performed for studying slow release of pyrene-labeled polystyrene chains from polystyrene gels formed by free-radical crosslinking copolymerization. Atom transfer radical polymerization was used to produce the pyrene end-capped polystyrene chains. In order to load the pyrene end-capped polystyrene chains into the gel disc-shaped gels were left in toluene solutions of pyrene end-capped polystyrene chains of various molecular weights. These swollen gels were redried in air and then immersed in pure toluene solution for monitoring slow release from the gel. These reswelling experiments were performed at room temperature in real time by monitoring the pyrene emission intensity using steady-state fluorescence measurements. Slow-release diffusion coefficients were measured and found to decrease as the crosslink density of the gels increased. It was observed that higher molecular weight pyrene end-capped polystyrene chains released much faster than low molecular ones during the slow-release process.
Citation - WoS: 10
Threshold-Based Steganography: a Novel Technique for Improved Payload and Snr
(Zarka Private Univ, 2016) Khan, Zakir; Shah, Mohsin; Naeem, Muhammad; Mahmood, Toqeer; Khan, Shah; Amin, Noor Ul; Shehzad, Danish
Steganography is the art of hiding user information in various file types including image audio and video. Security of steganography lies in imperceptibility of secret information in the cover image. Human Visual System (HVS) is not able to detect the changes in low color values of an image. To the best of our knowledge none of the available steganographic techniques have exploited this weakness of HVS. In this paper a new LSB technique is presented which hides information in the cover image taking into account the pixel value of color or grey level of every pixel. Our experiments show that the proposed technique has a high payload and low perceptibility of secret information hidden in the cover image as compared to the existing Least Significant Bit (LSB) based algorithms. We have used MATLAB for the implementation of proposed algorithm.

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