Threshold cryptography based on Asmuth-Bloom secret sharing

In this paper, we investigate how threshold cryptography can be conducted with the Asmuth-Bloom secret sharing scheme and present three novel function sharing schemes for RSA, ElGamal and Paillier cryptosystems. To the best of our knowledge, these are the first provably secure threshold cryptosystems realized using the Asmuth-Bloom secret sharing. Proposed schemes are comparable in performance to earlier proposals in threshold cryptography.     

Classification of brain hemorrhage computed tomography images using OzNet hybrid algorithm

Classification of brain hemorrhage computed tomography (CT) images provides a better diagnostic implementation for emergency patients. Attentively, each brain CT image must be examined by doctors. This situation is time-consuming, exhausting, and sometimes leads to making errors. Hence, we aim to find the best algorithm owing to a requirement for automatic classification of CT images to detect brain hemorrhage. In this study, we developed OzNet hybrid algorithm, which is a novel convolution neural networks (CNN) algorithm. Although OzNet achieves high classification performance, we combine it with Neighborhood Component Analysis (NCA) and many classifiers: Artificial neural networks (ANN), Adaboost, Bagging, Decision Tree, K-Nearest Neighbor (K-NN), Linear Discriminant Analysis (LDA), Naïve Bayes and Support Vector Machines (SVM). In addition, Oznet is utilized for feature extraction, where 4096 features are extracted from the fully connected layer. These features are reduced to have significant and informative features with minimum loss by NCA. Eventually, we use these classifiers to classify these significant features. Finally, experimental results display that OzNet-NCA-ANN excellent classifier model and achieves 100% accuracy with created Dataset 2 from Brain Hemorrhage CT images.     

Investigation of Ant System parameter interactions by using design of experiments for job-shop scheduling problems

In recent years, one of the most important and promising research fields has been metaheuristics to find optimal or near-optimal solutions for NP-hard combinatorial optimization problems. Improving the quality of the solution or the solution time is basic research area on metaheuristics. Modifications of the existing ones or creation of hybrid approaches are the focus of these efforts. Another area of improving the solution quality of metaheuristics is finding the optimal combination of algorithm control parameters. This is usually done by design of experiments or one-at-a-time approach in genetic algorithms, simulated annealing and similar metaheuristics. We observe that, in studies which use Ant Colonies Optimization (ACO) as an optimization technique; the levels of control parameters are determined by some non-systematic initial experiments and the interactions of the parameters are not studied yet.In this study, the parameters of Ant System have been investigated on different sized and randomly generated job-shop scheduling problems by using design of experiments. The effects and interactions of the parameters have been interpreted with the outputs of the experiments. Referring to the statistical analysis it is observed that none of the interactions between the Ant System parameters has a significant effect on makespan value. A specific fractional experimental design is suggested instead of the full factorial design. Depending on the findings from the benchmark problems it will be a reliable approach to use the suggested design for saving time and effort in experiments without sacrificing the solution quality.     

Cost-conscious comparison of supervised learning algorithms over multiple data sets

In the literature, there exist statistical tests to compare supervised learning algorithms on multiple data sets in terms of accuracy but they do not always generate an ordering. We propose Multi²Test, a generalization of our previous work, for ordering multiple learning algorithms on multiple data sets from “best” to “worst” where our goodness measure is composed of a prior cost term additional to generalization error. Our simulations show that Multi²Test generates orderings using pairwise tests on error and different types of cost using time and space complexity of the learning algorithms.     

Comparing alternative classifiers for database marketing: The case of imbalanced datasets

There are various algorithms used for binary classification where the cases are classified into one of two non-overlapping classes. The area under the receiver operating characteristic (ROC) curve is the most widely used metric to evaluate the performance of alternative binary classifiers. In this study, for the application domains where the high degree of imbalance is the main characteristic and the identification of the minority class is more important, we show that hit rate based measures are more correct to assess model performances and that they should be measured on out of time samples. We also try to identify the optimum composition of the training set. Logistic regression, neural network and CHAID algorithms are implemented for a real marketing problem of a bank and the performances are compared.     

A Review of Dehydration of Various Industrial Sludges

Wastewater characteristics and sludge generation potential of point source categories are reviewed critically. Novel industry-specific sludge dewatering/drying solutions necessary to establish a sustainable model are examined through a detailed literature survey. Knowledge of sludge properties is one of the most critical issues needed to design dewatering/drying equipment. This study focuses on industrial wastewater/sludge characterization. In addition, a comprehensive review of current drying models and technologies is also presented. A summary of the results derived from a novel thin-film-based photonic sludge dewatering/drying study is outlined as an alternative approach for industrial sludge control. Sludge was dried in a tubular quartz reactor (TQR), the inner surface of which was coated with a TiO₂ thin film. The TQR was irradiated with UV A, UV B, and UV C lamps. The consumed and generated energy fluxes through endergonic and exergonic reactions driven by photolysis and photocatalysis were investigated. In addition, the variations in sludge dewatering/drying characteristics were also examined and compared with conventional methods to evaluate the energy requirements.     

A review of the day-ahead natural gas consumption in Denmark:starting point towards forecasting accuracy improvement

Natural gas consumption forecasting is crucial for transmission system operators,distribution system operators,traders,and other players in the market.This work...     

The effect of replacing fat with oat bran on fatty acid composition and physicochemical properties of meatballs

Oat bran was used as a fat substitute in the production of meatballs. The effect of oat bran addition on the fatty acid composition, trans fatty acids, total fat, some physicochemical and sensory properties of the samples was studied. Meatballs were produced with four different formulations; the addition of 5, 10, 15 and 20% oat bran. Control samples were formulated with 25% fat addition as in commercial production. The major fatty acids were cis-oleic, palmitic and stearic acid in all the meatball samples, those with oat bran added as well as the control. Meatballs containing oat bran had lower concentrations of total fat and total trans fatty acids than the control samples. Meatballs made with 20% oat bran had the highest protein, salt and ash contents, L value (lightness), b value (yellowness), and the lowest moisture content and a value (redness). There was no significant difference among the meatball samples with respect to sensory properties, and all samples had high acceptability.     

Increasing single-lap joint strength by adherend curvature-induced residual stresses

Single-lap joint (SLJ) geometry is the most widely used type of adhesive joint geometry. In this joint, peel stresses occur at the overlap ends due to load eccentricity and the presence of shear-free adhesive termination surfaces. These peel stresses, along with the transverse tensile stresses which occur along the overlap longitudinal axes, and adhesive shear stresses, ultimately cause joint failure. Obviously, reductions in these stresses should result in higher joint strength and increased load capacity. To this end, we exploited elastic spring-back capability of (steel) metal adherends by initially forming curved segments of varying arc lengths and radii at overlap ends. These adherends with curved-end sections were then bonded in single-lap configuration, simply by applying sufficient bonding pressure to elastically flatten the curved segments to result in typically flat overlap sections subsequent to adhesive cure and the removal of bonding pressure. Since the elastic adherend overlap ends tend to revert back to their initial curved form, they exert compressive residual stresses on the adhesive layer in the overlap end regions. We determined that the compressive residual stresses induced in this fashion considerably increased the load capacity of SLJs subjected to tension.