Locational analysis for regionalization of Turkish Red Crescent blood services

After a series of earthquakes in 1999, Turkish Red Crescent (TRC) has engaged in a restructuring for all of its activities, including the blood services. Our study on the blood management system had been started as part of this initiative to restructure the blood services and improve both their effectiveness and efficiency. In the current system of TRC, not much consideration has been given to how the locational decisions affect the performance of blood centers, stations and mobile units. In recent years, however, there has been much discussion regarding the regionalization of the blood management system in Turkey. In this study, we develop several mathematical models to solve the location–allocation decision problems in regionalization of blood services. We report our computational results, obtained by using real data, for TRC blood services.     

A new dosage regimen for topical application of ciprofloxacin in the management of chronic suppurative otitis media

The clinical and bacteriologic efficacy of topically applied ciprofloxacin was studied in 60 patients with chronic suppurative otitis media. Two hundred fifty and 125 microg/ml concentrations of ciprofloxacin solutions were given to two groups of patients. The duration of therapy was determined according to the clinical cure at follow-up. More than 21 days of therapy was not needed in any patient. The clinical cure rate with 250 microg/ml ciprofloxacin was 78.1% at 14 days and with 125 microg/ml it was 83.3%. However, a 100% clinical cure rate and complete bacteriologic eradication was obtained in 21 days in both groups. In each group only one patient had otomycosis by the fourteenth day of therapy, although ear discharge had ceased. It was concluded that 125 microg/ml ciprofloxacin could be applied as successfully as 250 microg/ml, and the duration of therapy had to be at least 14 days. This new dosage regimen can be adopted as an optimal dosage for ototopical application of ciprofloxacin in chronic suppurative otitis media. It will also obviously decrease the expense of therapy.     

Prediction of software vulnerability based deep symbiotic genetic algorithms: Phenotyping of dominant-features

The detection of software vulnerabilities is considered a vital problem in the software security area for a long time. Nowadays, it is challenging to manage software security due to its increased complexity and diversity. So, vulnerability detection applications play a significant part in software development and maintenance. The ability of the forecasting techniques in vulnerability detection is still weak. Thus, one of the efficient defining features methods that have been used to determine the software vulnerabilities is the metaheuristic optimization methods. This paper proposes a novel software vulnerability prediction model based on using a deep learning method and SYMbiotic Genetic algorithm. We are first to apply Diploid Genetic algorithms with deep learning networks on software vulnerability prediction to the best of our knowledge. In this proposed method, a deep SYMbiotic-based genetic algorithm model (DNN-SYMbiotic GAs) is used by learning the phenotyping of dominant-features for software vulnerability prediction problems. The proposed method aimed at increasing the detection abilities of vulnerability patterns with vulnerable components in the software. Comprehensive experiments are conducted on several benchmark datasets; these datasets are taken from Drupal, Moodle, and PHPMyAdmin projects. The obtained results revealed that the proposed method (DNN-SYMbiotic GAs) enhanced vulnerability prediction, which reflects improving software quality prediction.

     

HihO: accelerating artificial intelligence interpretability for medical imaging in IoT applications using hierarchical occlusion

Neural Computing and Applications - In the medical imaging domain, nonlinear warping has enabled pixel-by-pixel mapping of one image dataset to a reference dataset. This co-registration of data...     

Corrosion inhibition of stainless steel by polyaniline,poly(2-chloroaniline), and poly(aniline-co-2-chloroaniline) in HCl

Polyaniline (PANi), poly(2-chloroaniline) (PClANi), and poly(aniline-co-2-chloroaniline) (co-PClANi) films were synthesized by electrochemical deposition on 304-stainless steel (SS) from an acetonitrile solution. The structural properties of these polymer films were characterized by spectroscopic (FTIR and UV–vis) and electrochemical (cyclic voltammetry) methods. Open circuit potential–time (E_ocp–time) curves, potentiodynamic polarization, and electrochemical impedance (EIS) measurements showed that these films have significant protective performance against corrosion of SS in 0.5 M HCl solution. It was found that co-PClANi film has acted as a passivator as well as barrier for cathodic reduction reaction in a similar manner as PANi film. However, PClANi film has behaved only as barrier for corrosion protection of SS in 0.5 M HCl.     

Modeling and solving mixed-model assembly line balancing problem with setups. Part I: A mixed integer linear programming model

This paper is the first one of the two papers entitled “modeling and solving mixed-model assembly line balancing problem with setups”, which has the aim of developing the mathematical programming formulation of the problem and solving it with a hybrid meta-heuristic approach. In this current part, a mixed-integer linear mathematical programming (MILP) model for mixed-model assembly line balancing problem with setups is developed. The proposed MILP model considers some particular features of the real world problems such as parallel workstations, zoning constraints, and sequence dependent setup times between tasks, which is an actual framework in assembly line balancing problems. The main endeavor of Part-I is to formulate the sequence dependent setup times between tasks in type-I mixed-model assembly line balancing problem. The proposed model considers the setups between the tasks of the same model and the setups because of the model switches in any workstation. The capability of our MILP is tested through a set of computational experiments. Part-II tackles the problem with a multiple colony hybrid bees algorithm. A set of computational experiments is also carried out for the proposed approach in Part-II.     

Prioritized Mobile Robot Exploration Based on Percolation Enhanced Entropy Based Fast SLAM

The major aim in search and rescue using mobile robots is to detect and reach trapped survivors and to support rescue operations through disaster environments. Our motivation is based on the fact that a search and rescue (SAR) robot can navigate within and penetrate a disaster area only if the area in question possesses connected voids. Traversability or penetrability of a disaster area is a primary factor that guides the navigation of a search and rescue (SAR) robot, since it is highly desirable that the robot, without hitting a dead end or getting stuck, keeps its mobility for its primary task of reconnaissance and mapping when searching the highly unstructured environment. We propose a novel percolation guidance that collaborates with entropy based SLAM under a switching control setting the priority to either position or map accuracy. This newly developed methodology has proven to combine the superiority of both percolator guidance and entropy based prioritization so that the active SLAM becomes speedy, with high coverage rate of the area as well as increased accuracy in localization. Our percolator guidance stems from a frontier based conditioning of a-posteriori occurrences of upcoming connected voids that uses the fact that every obstacle partially seen at the frontier of the explored domain has a spatial continuity into the unexplored area. The developed modular architecture is introduced in details and demonstrative examples are provided and discussed.     

Verifying anonymity in voting systems using CSP

We present formal definitions of anonymity properties for voting protocols using the process algebra CSP. We analyse a number of anonymity definitions, and give formal definitions for strong and weak anonymity, highlighting the difference between these definitions. We show that the strong anonymity definition is too strong for practical purposes; the weak anonymity definition, however, turns out to be ideal for analysing voting systems. Two case studies are presented to demonstrate the usefulness of the formal definitions: a conventional voting system, and Prêt à Voter, a paper-based, voter-verifiable scheme. In each case, we give a CSP model of the system, and analyse it against our anonymity definitions by specification checks using the Failures-Divergences Refinement (FDR2) model checker. We give a detailed discussion on the results from the analysis, emphasizing the assumptions that we made in our model as well as the challenges in modelling electronic voting systems using CSP.     

Prediction of suspended sediment concentration from water quality variables

This study investigates use of water quality (WQ) variables, namely total chromium concentration, total iron concentration, and turbidity for predicting suspended sediment concentration (SSC). For this purpose, the artificial neural networks (ANNs) and regression analysis (RA) models are employed. Seven different RA models are constructed, considering the functional relation between measured WQ variables and SSC. The WQ and SSC data are fortnightly obtained from six monitoring stations, located on the stream Harsit, Eastern Black Sea Basin, Turkey. A total of 132 water samples are collected from April 2009 to February 2010. Model prediction results reveal that ANN is able to predict SSC from WQ data, with mean absolute error (MAE) of 10.30 mg/L and root mean square error (RMSE) of 13.06 mg/L. Among seven RA models, the best one, which has the form including all independent parameters, produces results comparable to those of ANN, with MAE = 14.28 mg/L and RMSE = 15.35 mg/L. The sensitivity analysis results reveal that the most effective parameter on the SSC is total chromium concentration. These results have time- and cost-saving implications.