Use of Association Rule Mining within the Framework of a Customer-Oriented Approach

In this study, it was aimed to investigate whether an association rule exists between the products sold, using the sales data of a supermarket with the data mining method within the framework of a customer-oriented approach. For this purpose, the Association Rule Mining Method was used, and analyses were carried out on existing data with the Apriori Algorithm that is widely used in this method. Various association rules were determined between the products sold as a result of these analyses. It was assessed that Association Rule Mining is an alternative technique to proactive customer orientation by revealing the latent purchasing behaviour patterns of the customers

Utilisation of waste marble dust for improved durability and cost efficiency of pozzolanic concrete

This study demonstrates that the incorporation of waste marble dust to pozzolanic concrete improves the long-term mechanical properties and durability characteristics. A comprehensive study utilising specimens containing a cement and silica fume binder were manufactured with incremental levels of marble dust fine aggregate. Important physical properties including compressive strength, water penetration depth, porosity, resistance to sulphate attack and resistance to freeze/thaw cycling were evaluated over a period of 1 year. Microstructural development attributed to cement hydration and pozzolanic reaction was imaged at 28 days and 1 year using scanning electron microscopy. The inclusion of marble dust greatly improved the salt crystallization and freeze and thaw resistance of the concrete over the long-term with only a small decrease in compressive strength observed. Importantly this highlights the beneficial properties of marble dust on durability. Additional advantages were shown through cost efficiency analysis which revealed that utilisation of marble dust and silica fume in concrete can reduce the embodied CO2 emissions improving the economic credentials and environmental impact. Marble dust not only improves the physical characteristics but also provides an environmentally friendly route for waste disposal and creation of a more sustainable concrete

Workplace violence against medical students- A Turkish perspective

Background: Workplace violence against healthcare providers including the medical students being an important issue all over the world. The aim of this study is to survey the medical students about exposure to workplace violence (WPV) while they are doing their medical training in private tertiary hospitals. Methods: This was a cross-sectional study carried out among all medical students (4th, 5th, and 6th class) attending a teaching hospital at Bezmialem Vakif University (BVU), Istanbul, Turkey. A total of 150 students in the 2017-2018 academic year were recruited in this study. Data were collected using a modified questionnaire through a face to face interview. Data were analyzed using SPSS 16. Results: About one-third of the surveyed students (54, 36.0%) exposed to violence and 71.3% of them witnessed incidents of violence against healthcare providers at the workplace. The prevalence of physical violence and verbal abuse among medical students was reported at 5.5% and 92.6% respectively. About 81.5% were females compared to 18.5% of their counterparts. Patients (38.9%) and their relatives (61.1%) were the main sources of the violence respectively. More than half (57.0%) of students exposed to violence at outpatient services and 25.9% at the emergency room and 16.7% at inpatient wards. Few of them (22, 14.7%) thought that they will get support if they make a complaint. Conclusion: Being a medical student and has direct contact with patients and their relative is not always safe practice. Our results suggested a high prevalence of verbal and physical abuse against medical students. Health sector authorities should adopt a restrictive and clear strategy to protect medical students and other healthcare providers

DIMENSION AND COLOR CLASSIFICATION OF OLIVE FRUIT WITH IMAGE PROCESSING TECHNIQUES

DIMENSION AND COLOR CLASSIFICATION OF OLIVE FRUIT WITH IMAGE PROCESSING TECHNIQUESAbstractThe development of image processing technology appears in agriculture as well as in many other fields. Various classifications are carried out for fruits and vegetables. These are processes such as determining the harvest time according to their degree of maturity, deciding the way of collection and performing packaging operations according to their dimension. This study aims to classify the fruit according to its intended use in order to benefit more from the olive fruit that is important in industrial terms. In this study, olive fruit is classified as big, medium, and small according to its dimensions. Also classified as black and green according to their colors. This classification process was made in MATLAB environment and the KNN algorithm and decision trees was used. The results are obtained with Euclid and Manhattan methods used with the KNN algorithm and are given comparatively. According to the application results, 100% success was achieved in both methods in color classification. In dimension classification, 89.2% classification success was achieved in KNN algorithm and 86.7% in decision tree method.Keywords: Image processing, olive classification, KNN classification algorithm, decision tree

Rule based segmentation and subject identification using fiducial features and subspace projection methods

This paper describes a framework for carrying out face recognition on a subset of standard color FERET database using two different subspace projection methods, namely PCA and Fisherfaces. At first, a rule based skin region segmentation algorithm is discussed and then details about eye localization and geometric normalization are given. The work achieves scale and rotation invariance by fixing the inter ocular distance to a selected value and by setting the direction of the eye-to-eye axis. Furthermore, the work also tries to avoid the small sample space (S3) problem by increasing the number of shots per subject through the use of one duplicate set per subject. Finally, performance analysis for the normalized global faces, the individual extracted features and for a multiple component combination are provided using a nearest neighbour classifier with Euclidean and/or Cosine distance metrics. © 2007 ACADEMY PUBLISHER

Performance analysis of turbo codes over Rician fading channels with impulsive noise

The statistical characteristics of impulsive noise differ greatly from those of Gaussian noise. Hence, the performance of conventional decoders, optimized for additive white Gaussian noise (AWGN) channels is not promising in non-Gaussian environments. In order to achieve improved performance in impulsive environments the decoder structure needs to be modified in accordance with the impulsive noise model. This paper provides performance analysis of turbo codes over fully interleaved Rician fading channels with Middleton's additive white Class-A impulsive noise (MAWCAIN). Simulation results for the memoryless Rician fading channels using coherent BPSK signaling for both the cases of ideal channel state information (ICSI) and no channel state information (NCSI) at the decoder are provided. An eight state turbo encoder having (1, 13/15, 13/15) generator polynomial is used throughout the analysis. The novelty of this work lies in the fact that this is an initial attempt to provide a detailed analysis of turbo codes over Rician fading channels with impulsive noise rather than AWGN. ©2007 IEEE

Sequential left internal mammary artery grafting in combination with the aortic no-touch technique

Aim: This study aimed to investigate the short-term outcomes achieved with off-pump bypass combined with the aortic no-touch technique where sequential anastomoses between the left internal mammary artery (LIMA), left anterior descending (LAD) and diagonal artery were employed. Material and methods: A total of 583 patients (mean age 63, 80% male) who underwent off-pump bypass (LIMA-diagonal-LAD sequential) were enrolled in this retrospective analysis. Data regarding the frequency of in-hospital postoperative complications, intra-aortic balloon pump (IABP) and inotropic agent requirement, re-exploration for bleeding, and length of hospital stay were collected. Anastomosis patency was evaluated in 49 patients who underwent angiography. Results: 2.6% of the participants received inotropic agents and 0.5% required IABP. Frequency of acute renal failure, sternal wound infection, cerebrovascular event, respiratory failure, and hemodialysis was less than 1% in total. Among the 49 patients undergoing angiography at an average 41 ±17 months after bypass, the LIMA-LAD was patent in 98% and the LIMA-diagonal was patent in 84% of the subjects. Preoperative left ventricle ejection fraction (LVEF) and recent myocardial infarction (MI) prior to bypass were significantly correlated with postoperative IABP and inotropic agent requirement (r = 0.165, p < 0.01 for LVEF, p = 0.021 for recent MI). Conclusions: Off-pump bypass in combination with the aortic no-touch technique is associated with favorable postoperative outcomes including reduced postoperative stroke, renal dysfunction, IABP, and inotropic agent requirement compared to the results of previous randomized prospective studies published in the literature. © 2022 Termedia Publishing House Ltd.. All rights reserved

Prediction of Rebound Amount in Dry Mix Shotcrete by a Fast Adaboosting Neural Network

In this study, a new machine learning approach has been proposed to predict the rebound causing loss of material in shotcrete using the ensemble learning method. In shotcrete application, the amount of rebound material was obtained for use in a dataset. In this study, the shotcrete mixes that contain an additive of fly-ash, silica fume, and polypropylene fiber were produced besides simple shotcrete. Each mix was sprayed onto 2 wooden panels measuring 45 × 45 × 15 cm in size. The rebound material resulting from the spraying process was collected, weighed and recorded as data. The highest rebound was observed for the plain sample and the lowest for samples with substituted silica fume. Dependent and independent parameters were identified in the dataset produced as a result of experimental studies. Hyperparameters producing optimum results in the training of the model were identified for the model and boosting method. The dataset was split into training and testing sets by 80% and 20%, respectively. As a result, the model achieved a prediction performance of 84.25%. To test the performance of the proposed model, traditional machine learning algorithms were compared on the same dataset. Consequently, the proposed model was observed to have the highest accuracy

Peritoneal tuberculosis and granulomatous hepatitis secondary to treatment of bladder cancer with Bacillus Calmette-Guérin

Intravesical administration of Bacillus Calmette-Guérin is used as a treatment method in superficial bladder cancer. While it is generally well tolerated, serious side effects may develop. Granulomatous hepatitis cases have been previously reported; however, only one case with tuberculous peritonitis exists in the current literature. We hereby present two cases, one of which is the second tubercular peritonitis case following Bacillus Calmette-Guérin treatment to be reported, and the other a case with granulomatous hepatitis. Complete cure was achieved in both cases with specific therapy. In the patient who developed peritonitis, intravesical Bacillus Calmette-Guérin therapy was recommenced after antituberculosis treatment, and completed without further complications