In this project we implemented Leak Finder, a tool for examining how Android applications use their granted permissions. Leak Finder instruments Android applications with custom log code, then it collects the logs from actual user application runs and uses these logs to create an execution graph. Auditors can use the executing graph to examine when an applications tends to use its permissions. ...

Objective: We studied finder needle use in Internal Jugular Vein (IJV) catheterization and complications rate in adult cardiac surgery. Methods: A prospective study was carried out for 3 month period from august to November 2007 and all patients older than 18 years who underwent elective cardiac surgery were studied. Data were collected about using finder needle, patient position, success rate,...

Role-playing games (RPG’s) use a variety of methods for rolling dice to add randomness to the game. In the simplest form, a small number of identical dice are rolled and added, but more advanced forms involve cumulative re-rolling of 6’s, doubling the value of doubles, removing the lowest or highest result or counting the number of dice that are below a threshold, and many other weird and wonde...

We introduce an adaptive learning environment named DALM (DICE adaptive learning model) based on DICE test-driven development (TDD) model that was implemented in a parse-tree based automatic on-line grader. In our opinion, there are three variables in DALM. The individual differences (I) classify the learners into several groups. The training method (T) that equivalent to TDD model in DICE can ...

In the biological domain, to extract the newly discovered functional features from massive literature is a major challenging issue. To automatically annotate GeneRIF in a new literature is the main goal in this paper. We try to find function words and introducers in the training corpus, and then apply such informative words to annotate the GeneRIF. The experiments showed that 48.15%, 49.78%, 32...

Thoracic and abdominal multi-organ segmentation has been a challenging problem due to the inter-subject variance of human thoraxes and abdomens as well as the complex 3D intra-subject variance among organs. In this paper, we present a preliminary method for automatically segmenting multiple organs using non-enhanced CT data. The method is based on a simple framework using generic tools and requ...

An algorithm is presented for fully automated brain tumor segmentation from only two magnetic resonance image modalities. The technique is based on three steps: (1) alternating different levels of automatic histogram-based multi-thresholding step, (2) performing an effective and fully automated procedure for skull-stripping by evolving deformable contours, and (3) segmenting both Gross Tumor Vo...