PCET based copy-move forgery detection in images under geometric transforms

With the advent of the powerful editing software and sophisticated digital cameras, it is now possible to manipulate images. Copy-move is one of the most common methods for image manipulation. Several methods have been proposed to detect and locate the tampered regions, while many methods failed when the copied region undergone some geometric transformations before being pasted, because of the de-synchronization in the searching procedure. This paper presents an efficient technique for detecting the copy-move forgery under geometric transforms. Firstly, the forged image is divided into overlapping circular blocks, and Polar Complex Exponential Transform (PCET) is employed to each block to extract the invariant features, thus, the PCET kernels represent each block. Secondly, the Approximate Nearest Neighbor (ANN) Searching Problem is used for identifying the potential similar blocks by means of locality sensitive hashing (LSH). In order to make the algorithm more robust, morphological operations are applied to remove the wrong similar blocks. Experimental results show that our proposed technique is robust to geometric transformations with low computational complexity.     

A Replicated Survey of IT Software Project Failures

Despite various industry reports about the failure rates of software projects, there's still uncertainty about the actual figures. Researchers performed a global Web survey of IT departments in 2005 and 2007. The results suggest that the software crisis is perhaps exaggerated and that most software projects deliver. However, the overall project failure rate, including cancelled and completed but poorly performing projects, remains arguably high for an applied discipline.     

Comparative effects of gamma and microwave irradiation on the quality of black pepper

Powdered black pepper from Egyptian markets, was irradiated with different recommended doses of gamma rays (5.0 and 10.0 kGy) and with microwaves for different periods (20, 40 and 75 s) to improve its hygienic quality. The most common bacterial isolates were of three generaBacillus, Clostridium andMicrococcus (7.5 × 10⁶), whereas the predominant fungi (7.8 × 10⁴) wereAspergillus species,A. glaucus, A. flavus, A. niger andA. ochraceus. Doses of gamma irradiation used (5.0 and 10 kGy) were sufficient to decrease spore-forming bacteria (SFB) and to inhibit the fungal flora and coliforms which contaminated the black pepper powder. Microwave treatments for 40 s and 75 s were of the same effectiveness whereas treatment for 20 s was less so. GLC analysis proved the presence of 31 peaks, only 19 compounds were identified as monoterpene hydrocarbons (56.21%), the major one being -phellandrene and limonene. Sesquiterpenes were also present, mainly -caryollphyllene (3.69%) as well as oxygenated compounds such as terpenol, geraniol, Me-chavicol, eugenol and anisol. Gamma irradiation at 5 kGy and 10 kGy respectively decreased the numbers of identified compounds from 21 (86.58% concentration) in untreated pepper to 16 (59.22% concentration), 15 (54.06% concentration). In comparison, microwave treatments, particularly for 40 s and 75 s, increased the concentration of the same compounds. The results obtained indicate that microwave treatment, under these conditions, is a safe and suitable technique for decontamination of black pepper which does not result in a great loss of flavour compounds, as compared with recommended doses of gamma irradiation.     

Validating the ISO/IEC 15504 measure of software requirementsanalysis process capability

ISO/IEC 15504 is an emerging international standard on software process assessment. It defines a number of software engineering processes and a scale for measuring their capability. One of the defined processes is software requirements analysis (SRA). A basic premise of the measurement scale is that higher process capability is associated with better project performance (i.e., predictive validity). The paper describes an empirical study that evaluates the predictive validity of SRA process capability. Assessments using ISO/IEC 15504 were conducted on 56 projects world-wide over a period of two years. Performance measures on each project were also collected using questionnaires, such as the ability to meet budget commitments and staff productivity. The results provide strong evidence of predictive validity for the SRA process capability measure used in ISO/IEC 15504, but only for organizations with more than 50 IT staff. Specifically, a strong relationship was found between the implementation of requirements analysis practices as defined in ISO/IEC 15504 and the productivity of software projects. For smaller organizations, evidence of predictive validity was rather weak. This can be interpreted in a number of different ways: that the measure of capability is not suitable for small organizations or that the SRA process capability has less effect on project performance for small organizations     

Analysis of Polycyclic Aromatic Hydrocarbons in Egyptian Petroleum Condensate Oils

The polycyclic aromatic hydrocarbons (PAH) in Egyptian condensates are analyzed for the first. A solid phase extraction (SPE) followed by gas chromatography-mass selective detection was used for their analysis. The method was calibrated for optimal extraction conditions. Excellent recoveries were found (78–114%) for the PAHs that were identified using a variety of standards and GC-MS spectra. The solid-phase extracted PAH fraction was further separated by HPLC on a Ag(I) mercaptopropanosilica gel to reduce the complexity of the sample by separating the PAHs based on the number of aromatic rings. The analytes were quantified using GC with a flame ionization detector. For this kind of sample SPE is a more convenient separation technique than an open column. PAHs containing two to four rings in the concentration range 0.6–11 μg/L were measured. Some preliminary geochemical hypotheses based on the analyzed PAHs and the previously analyzed S-containing aromatic compounds were formed as to the depositional environment and source rock type.     

Computing Travel Time Reliability in Transportation Networks with Multistates and Dependent Link Failures

The measurement of transportation network travel time reliability is imperative to provide drivers with accurate route guidance information and to generate the shortest path (or alternative paths) connecting origins and destinations, especially under conditions of varying demands and limited capacities. Previous studies assumed that link failures in a road network are statistically independent and that reliability probabilities are perfectly determinable. In real life, these assumptions are dubious, because the failure of a link in one particular area does not necessarily result in the complete failure of the neighboring link, but may lead to deterioration of its performance. This paper presents a new methodology to study the multistate system reliability analysis of transportation networks for which one cannot formulate an “all or nothing” type of failure criterion and in which dependent link failures are considered. The methodology is presented, using a numerical example, for computing the probability that travel time between an origin and a destination may exceed a threshold.     

Software cost estimation with incomplete data

The construction of software cost estimation models remains an active topic of research. The basic premise of cost modeling is that a historical database of software project cost data can be used to develop a quantitative model to predict the cost of future projects. One of the difficulties faced by workers in this area is that many of these historical databases contain substantial amounts of missing data. Thus far, the common practice has been to ignore observations with missing data. In principle, such a practice can lead to gross biases and may be detrimental to the accuracy of cost estimation models. We describe an extensive simulation where we evaluate different techniques for dealing with missing data in the context of software cost modeling. Three techniques are evaluated: listwise deletion, mean imputation, and eight different types of hot-deck imputation. Our results indicate that all the missing data techniques perform well with small biases and high precision. This suggests that the simplest technique, listwise deletion, is a reasonable choice. However, this will not necessarily provide the best performance. Consistent best performance (minimal bias and highest precision) can be obtained by using hot-deck imputation with Euclidean distance and a z-score standardization     

Evaluating capture-recapture models with two inspectors

Capture-recapture (CR) models have been proposed as an objective method for controlling software inspections. CR models were originally developed to estimate the size of animal populations. In software, they have been used to estimate the number of defects in an inspected artifact. This estimate can be another source of information for deciding whether the artifact requires a reinspection to ensure that a minimal inspection effectiveness level has been attained. Little evaluative research has been performed thus far on the utility of CR models for inspections with two inspectors. We report on an extensive Monte Carlo simulation that evaluated capture-recapture models suitable for two inspectors assuming a code inspections context. We evaluate the relative error of the CR estimates as well as the accuracy of the reinspection decision made using the CR model. Our results indicate that the most appropriate capture-recapture model for two inspectors is an estimator that allows for inspectors with different capabilities. This model always produces an estimate (i.e., does not fail), has a predictable behavior (i.e., works well when its assumptions are met), will have a relatively high decision accuracy, and will perform better than the default decision of no reinspections. Furthermore, we identify the conditions under which this estimator will perform best