Optimization for automated assembly of puzzles

The puzzle assembly problem has many application areas such as restoration and reconstruction of archeological findings, repairing of broken objects, solving jigsaw type puzzles, molecular docking problem, etc. The puzzle pieces usually include not only geometrical shape information but also visual information such as texture, color, and continuity of lines. This paper presents a new approach to the puzzle assembly problem that is based on using textural features and geometrical constraints. The texture of a band outside the border of pieces is predicted by inpainting and texture synthesis methods. Feature values are derived from these original and predicted images of pieces. An affinity measure of corresponding pieces is defined and alignment of the puzzle pieces is formulated as an optimization problem where the optimum assembly of the pieces is achieved by maximizing the total affinity measure. An fft based image registration technique is used to speed up the alignment of the pieces. Experimental results are presented on real and artificial data sets

A texture based approach to reconstruction of archaeological finds

Reconstruction of archaeological finds from fragments, is a tedious task requiring many hours of work from the archaeologists and restoration personnel. In this paper we present a framework for the full reconstruction of the original objects using texture and surface design information on the sherd. The texture of a band outside the border of pieces is predicted by inpainting and texture synthesis methods. The confidence of this process is also defined. Feature values are derived from these original and predicted images of pieces. A combination of the feature and confidence values is used to generate an affinity measure of corresponding pieces. The optimization of total affinity gives the best assembly of the piece. Experimental results are presented on real and artificial data

Gladiolus osmaniyensis (Iridaceae), a new species from south anatolia, Turkey

A new species, Gladiolus osmaniyensis Sağıroğlu (Iridaceae), is described and illustrated from South Anatolia, Turkey. G. osmaniyensis is morphologically close to G. attilae and G. atroviolaceus. The ecology and phenology of the new species as well as its etymology, conservation status, and diagnostic morphological features are discussed. In addition, the seed surfaces of the G. osmaniyensis, G. attilae, and G. atroviolaceus are examined by SEM. The geographical distribution of the new species and the morphologically related species are mapped as well

Hazelnut seed lipase: extraction, purificatıon, and characterization

Interest in lipases has markedly increased to their potential industrial applications. The most of lipases produced commercially are obtained from animal and microbial sources. Nowadays, also obtained from plant seeds such as sunflower, soybean, peanut, castor bean and hazelnut. Hazelnut is one of the most important foods in majority of the world and Turkey is largest hazelnut producer. In this study, It was aimed that Lipase from hazelnut seed identified as yomra species isolated, purified and characterized. Lipase from hazelnut seed was purified 1255 fold to homogeneous state by ammonium sulfate precipitation, dialysis and Sephadex G-100 gel filtration chromatography after by defatting from hazelnut proteins. The purified enzyme showed single band when it was subjected to SDS-PAGE. The molecular weight of the determined by SDS-PAGE was 20 kDa. Purified lipase from hazelnut seed exhibited the maximum activity at 9.0 and 50˚C and stable under alkaline conditions (pH 7.0-10.0) and at temperatures between 20-55˚C. Lipase from hazelnut seed more specified versus triolein and tributyrin and olive oil among the nature oils as substrate. The enzyme activity was measured by using 0.1 ml of enzyme solution for 5 min. To determine the storage stability of lipase from hazelnut seed, the activity assays carried out for a period of one year. it was observed that about 83% of its activity was retained of 9 months at -20˚C. Purified lipase from hazelnut seed versus triolein as substrate calculated Km and Vmax values, 4.545mM and 80 U/dk.mg.Enzyme, respectively

Yapay Sinir Ağları ile Web İçeriklerini Sınıflandırma

Recent developments and widespread usage of the Internet have made business and processes to be completed faster and easily in electronic media. The increasing size of the stored, transferred and processed data brings many problems that affect access to information on the Web. Because of users’ need get to access to the information in electronic environment quickly, correctly and appropriately, different methods of classification and categorization of data are strictly needed. Millions of search engines should be supported with new approaches every day in order for users to get access to relevant information quickly. In this study, Multilayered Perceptrons (MLP) artificial neural network model is used to classify the web sites according to the specified subjects. A software is developed to select the feature vector, to train the neural network and finally to categorize the web sites correctly. It is considered that this intelligent approach will provide more accurate and secure platform to the Internet users for classifying web contents precisely

Comparison of sirolimus and colchicine treatment on the development of peritoneal fibrozis in rats having peritoneal dialysis

Background: Continuous ambulatory peritoneal dialysis is a successful treatment modality for patients with end-stage renal disease. Peritoneal fibrosis (PF) is the most critical complication of long-term peritoneal di- alysis (PD). Aims: In our study, we aimed to compare the effects of colchicine and sirolimus on PF induced by hypertonic peritoneal dialysis solutions in rats. Study Design: Animal experiment. Methods: Twenty-four rats were randomly divided into three groups. The control group received an intraperitoneal injection (ip) of saline. The sirolimus group received the PD solution, plus 1.0 mg/kg/day Rapamune®. The colchicine group received the PD solution ip plus 1.0 mg/kg/day of colchicine. Blood sam- ples were taken to measure the serum levels of VEGF, TGF-β, and TNF-α. Peritoneal tissue samples were taken for histopathological evaluation. Results: TGF-β and TNF-α values in the sirolimus group were found to be statistically significantly lower than in the control and colchicine groups, but the differences between the control and colchicine groups were not statistically significant. No statistically significant differences were found between the groups regarding the VEGF values. Vascular neogenesis and peritoneal thickness were compared; the values in the sirolimus group were statistically reduced compared to the values in the control group. Mild fibrosis developed in 75% of all animals in the sirolimus group; there was no moderate or severe fibrosis observed. Fibrosis developed to varying degrees in 100% of the animals in the control and colchicine groups. Conclusion: The present study demonstrates that sirolimus might be beneficial for preventing or delaying the progression of PF and neoangiogenesis. These alterations in the peritoneal membrane may be connected with reduced TNF-α and TGF-β levels

Differential Invariants of Non-degenerate Surfaces

This paper aims to prove that the set {g_{ij}(x), L_{ij} (x), i, j = 1, 2} is a complete system of the SM(3)- invariants of a nondegenerate surface in R3, where {g_{ij}(x)} and {L_{ij}(x)}, 1, j = 1, 2 are the sets of all coefficients of the first and second fundamental forms of a surface x in R3. A similar result was obtained for the group M(3)

Burnout Among General Surgeons in Turkey

Aim: Burnout is a syndrome that is very common among surgeons. It is defined by emotional exhaustion (EE), depersonalization (DP), and decreased personal success. This study aimed to investigate burnout in general surgeons in Turkey and to determine the risk factors for burnout. Method: Of the total of 4,395 general surgeons in Turkey, 630 were included in this study. Each participant was asked to complete the Sociodemographic Data Form, Maslach Burnout Inventory, and Minnesota Satisfaction Questionnaire (MSQ) either by face-to-face interview or via electronic questionnaire. Results: Of the 630 participants included in this study, 53 (8.4%) and 577 (91.6%) was female and male, respectively. The highest participation rate was from the Marmara region (36%), while the lowest participation rate was from the Eastern Anatolia region (3.13%). Attending physicians comprised the largest number of participants (72%). Those who perceived themselves as successful, with more work experience and higher academic Mtitles, had decreased EE, personal accomplishment, and DP as well as increased general, external, and internal satisfaction. Conclusion: We observed that most of the general surgeons in Turkey experienced burnout syndrome. To address this, we suggest that health systems and working conditions in Turkey should be reviewed and that the working standards and rights of the healthcare workers should be revised

Explainable Credit Card Fraud Detection with Image Conversion

The increase in the volume and velocity of credit card transactions causes class imbalance and concept deviation problems in data sets where credit card fraud is detected. These problems make it very difficult for traditional approaches to produce robust detection models. In this study, a different perspective has been developed for this problem and a novel approach named Fraud Detection with Image Conversion (FDIC) is proposed. FDIC handles credit card transactions as time series and transforms them into images. These images, which comprise temporal correlations and bilateral relationships of features, are classified by a convolutional neural network architecture as fraudulent or legitimate. When the obtained results are compared with the related studies, FDIC has the best F1-score and recall values, which are 85.49% and 80.35%, respectively. Since the images created during the FDIC process are difficult to interpret, a new explainable artificial intelligence approach is also presented. In this way, feature relationships that have a dominant effect on fraud detection are revealed