Source identification for mobile devices, based on wavelet transforms combined with sensor imperfections

One of the most relevant applications of digital image forensics is to accurately identify the device used for taking a given set of images, a problem called source identification. This paper studies recent developments in the field and proposes the mixture of two techniques (Sensor Imperfections and Wavelet Transforms) to get better source identification of images generated with mobile devices. Our results show that Sensor Imperfections and Wavelet Transforms can jointly serve as good forensic features to help trace the source camera of images produced by mobile phones. Furthermore, the model proposed here can also determine with high precision both the brand and model of the device

Association of Over-The-Counter Pharmaceutical Sales with Influenza-Like-Illnesses to Patient Volume in an Urgent Care Setting

We studied the association between OTC pharmaceutical sales and volume of patients with influenza-like-illnesses (ILI) at an urgent care center over one year. OTC pharmaceutical sales explain 36% of the variance in the patient volume, and each standard deviation increase is associated with 4.7 more patient visits to the urgent care center (p<0.0001). Cross-correlation function analysis demonstrated that OTC pharmaceutical sales are significantly associated with patient volume during non-flu season (p<0.0001), but only the sales of cough and cold (p<0.0001) and thermometer (p<0.0001) categories were significant during flu season with a lag of two and one days, respectively. Our study is the first study to demonstrate and measure the relationship between OTC pharmaceutical sales and urgent care center patient volume, and presents strong evidence that OTC sales predict urgent care center patient volume year round. © 2013 Liu et al

A comparison of the Accuracy of Ultrasound and Computed Tomography in common diagnoses causing acute abdominal pain

Head-to-head comparison of ultrasound and CT accuracy in common diagnoses causing acute abdominal pain. Consecutive patients with abdominal pain for > 2 h and <5 days referred for imaging underwent both US and CT by different radiologists/radiological residents. An expert panel assigned a final diagnosis. Ultrasound and CT sensitivity and predictive values were calculated for frequent final diagnoses. Effect of patient characteristics and observer experience on ultrasound sensitivity was studied. Frequent final diagnoses in the 1,021 patients (mean age 47; 55% female) were appendicitis (284; 28%), diverticulitis (118; 12%) and cholecystitis (52; 5%). The sensitivity of CT in detecting appendicitis and diverticulitis was significantly higher than that of ultrasound: 94% versus 76% (p <0.01) and 81% versus 61% (p = 0.048), respectively. For cholecystitis, the sensitivity of both was 73% (p = 1.00). Positive predictive values did not differ significantly between ultrasound and CT for these conditions. Ultrasound sensitivity in detecting appendicitis and diverticulitis was not significantly negatively affected by patient characteristics or reader experience. CT misses fewer cases than ultrasound, but both ultrasound and CT can reliably detect common diagnoses causing acute abdominal pain. Ultrasound sensitivity was largely not influenced by patient characteristics and reader experience

Profiles of US and CT imaging features with a high probability of appendicitis

To identify and evaluate profiles of US and CT features associated with acute appendicitis. Consecutive patients presenting with acute abdominal pain at the emergency department were invited to participate in this study. All patients underwent US and CT. Imaging features known to be associated with appendicitis, and an imaging diagnosis were prospectively recorded by two independent radiologists. A final diagnosis was assigned after 6 months. Associations between appendiceal imaging features and a final diagnosis of appendicitis were evaluated with logistic regression analysis. Appendicitis was assigned to 284 of 942 evaluated patients (30%). All evaluated features were associated with appendicitis. Imaging profiles were created after multivariable logistic regression analysis. Of 147 patients with a thickened appendix, local transducer tenderness and peri-appendiceal fat infiltration on US, 139 (95%) had appendicitis. On CT, 119 patients in whom the appendix was completely visualised, thickened, with peri-appendiceal fat infiltration and appendiceal enhancement, 114 had a final diagnosis of appendicitis (96%). When at least two of these essential features were present on US or CT, sensitivity was 92% (95% CI 89-96%) and 96% (95% CI 93-98%), respectively. Most patients with appendicitis can be categorised within a few imaging profiles on US and CT. When two of the essential features are present the diagnosis of appendicitis can be made accuratel

Bodemschematisatie; opschaling door aggregatie van bodeminformatie voor modelsimulaties op nationale en regionale schaal

Dit rapport beschrijft de ontwikkeling van geautomatiseerde methoden voor opschaling van bodeminformatie door ruimtelijke en gegevensaggregatie voor modeltoepassingen, bodemschematisatie genoemd. Ze bestaan uit de selectie van bodemgegevens, ruimtelijke aggregatie van kaarteenheden van de bodemkaart, gegevensaggregatie door definiëring van rekenprofielen met procesparameters en het genereren van bodemkundige modelinvoer. Met statistische analyse van twaalf verschillende modeluitvoervariabelen is nagegaan welke van de ontwikkelde methoden voor bodemschematisatie het geringste informatieverlies gaf uitgaand van de ruimtelijke structuur op de Bodemkaart van Nederland, schaal 1: 50 000. De voorspelfout binnen kaarteenheden bedroeg minimaal 45. Het algoritme voor de ruimtelijke aggregatiemethode waarbij het studiegebied Beerse-Reuzel van 203 naar 23 ruimtelijke eenheden werd teruggebracht, gaf het meest representatieve beeld van de variabiliteit tussen de oorspronkelijke kaarteenheden. De toename vande voorspelfout door gegevensaggregatie werd door twee van de vier hiervoor ontwikkelde methoden het kleinst gehouden