credit scoring is a kind of binary classification problem that contains important information for manager to make a decision in particularly in banking authorities. obtained scores provide a practical credit decision for a loan officer to classify clients to reject or accept for payment loan. for this sake, in this paper a data envelopment analysis- discriminant analysis (dea-da) approach is us...

abstract is not available.

concerning the population growth and urban development, significant growth in the rate of personal car usage has caused more transportation and thus growth in occupying the street areas for parking vehicles. this has caused much transporting problems and traffic. hence concerning the parking issue is crucial in traffic and municipal management.the important issue is the suitable place for the p...

this paper presents a comprehensive review of the works done, during the 2000–2012, in the application of data mining techniques in credit scoring. yet there isn’t any literature in the field of data mining applications in credit scoring. using a novel research approach, this paper investigates academic and systematic literature review and includes all of the journals in the science direct onli...

Confident peptide identification is one of the most important components in mass-spectrometry-based proteomics. We propose a method to properly combine the results from different database search methods to enhance the accuracy of peptide identifications. The database search methods included in our analysis are SEQUEST (v27 rev12), ProbID (v1.0), InsPecT (v20060505), Mascot (v2.1), X! Tandem (v2...

The effectiveness of database search algorithms, such as Mascot, Sequest and ProteinPilot is limited by the quality of the input spectra: spurious peaks in MS/MS spectra can jeopardize the correct identification of peptides or reduce their score significantly. Consequently, an efficient preprocessing of MS/MS spectra can increase the sensitivity of peptide identification at reduced file sizes a...