Parametric timed model checking for guaranteeing timed opacity

Information leakage can have dramatic consequences on systems security. Among harmful information leaks, the timing information leakage is the ability for an attacker to deduce internal information depending on the system execution time. We address the following problem: given a timed system, synthesize the execution times for which one cannot deduce whether the system performed some secret behavior. We solve this problem in the setting of timed automata (TAs). We first provide a general solution, and then extend the problem to parametric TAs, by synthesizing internal timings making the TA secure. We study decidability, devise algorithms, and show that our method can also apply to program analysis.Comment: This is the author (and extended) version of the manuscript of the same name published in the proceedings of ATVA 2019. This work is partially supported by the ANR national research program PACS (ANR-14-CE28-0002), the ANR-NRF research program (ProMiS) and by ERATO HASUO Metamathematics for Systems Design Project (No. JPMJER1603), JS

3D-conformal-intensity modulated radiotherapy with compensators for head and neck cancer: clinical results of normal tissue sparing

BACKGROUND: To investigate the potential of parotic gland sparing of intensity modulated radiotherapy (3D-c-IMRT) performed with metallic compensators for head and neck cancer in a clinical series by analysis of dose distributions and clinical measures. MATERIALS AND METHODS: 39 patients with squamous cell cancer of the head and neck irradiated using 3D-c-IMRT were evaluable for dose distribution within PTVs and at one parotid gland and 38 patients for toxicity analysis. 10 patients were treated primarily, 29 postoperatively, 19 received concomittant cis-platin based chemotherapy, 20 3D-c-IMRT alone. Initially the dose distribution was calculated with Helax (® )and photon fluence was modulated using metallic compensators made of tin-granulate (n = 22). Later the dose distribution was calculated with KonRad (® )and fluence was modified by MCP 96 alloy compensators (n = 17). Gross tumor/tumor bed (PTV 1) was irradiated up to 60–70 Gy, [5 fractions/week, single fraction dose: 2.0–2.2 (simultaneously integrated boost)], adjuvantly irradiated bilateral cervical lymph nodes (PTV 2) with 48–54 Gy [single dose: 1.5–1.8]). Toxicity was scored according the RTOG scale and patient-reported xerostomia questionnaire (XQ). RESULTS: Mean of the median doses at the parotid glands to be spared was 25.9 (16.3–46.8) Gy, for tin graulate 26 Gy, for MCP alloy 24.2 Gy. Tin-granulate compensators resulted in a median parotid dose above 26 Gy in 10/22, MCP 96 alloy in 0/17 patients. Following acute toxicities were seen (°0–2/3): xerostomia: 87%/13%, dysphagia: 84%/16%, mucositis: 89%/11%, dermatitis: 100%/0%. No grade 4 reaction was encountered. During therapy the XQ forms showed °0–2/3): 88%/12%. 6 months postRT chronic xerostomia °0–2/3 was observed in 85%/15% of patients, none with °4 xerostomia. CONCLUSION: 3D-c-IMRT using metallic compensators along with inverse calculation algorithm achieves sufficient parotid gland sparing in virtually all advanced head and neck cancers. Since the concept of lower single (and total) doses in the adjuvantly treated volumes reduces acute morbidity 3D-c-IMRT nicely meets demands of concurrent chemotherapy protocols

Pattern Recognition in Macroscopic and Dermoscopic Images for Skin Lesion Diagnosis

Pattern recognition in macroscopic and dermoscopic images is a challenging task in skin lesion diagnosis. The search for better performing classification has been a relevant issue for pattern recognition in images. Hence, this work was particularly focused on skin lesion pattern recognition, especially in macroscopic and dermoscopic images. For the pattern recognition in macroscopic images, a computational approach was developed to detect skin lesion features according to the asymmetry, border, colour and texture properties, as well as to diagnose types of skin lesions, i.e., nevus, seborrheic keratosis and melanoma. In this approach, an anisotropic diffusion filter is applied to enhance the input image and an active contour model without edges is used in the segmentation of the enhanced image. Finally, a support vector machine is used to classify each feature property according to their clinical principles, and also for the classification between different types of skin lesions. For the pattern recognition in dermoscopic images, classification models based on ensemble methods and input feature manipulation are used. The feature subsets was used to manipulate the input feature and to ensure the diversity of the ensemble models. Each ensemble classification model was generated by using an optimum-path forest classifier and integrated with a majority voting strategy. The performed experiments allowed to analyse the effectiveness of the developed approaches for pattern recognition in macroscopic and dermoscopic images, with the results obtained being very promising

Association between XPF Polymorphisms and Cancer Risk: A Meta-Analysis

Background: Xeroderma pigmentosum complementation group F (XPF or ERCC4) plays a key role in DNA repair that protects against genetic instability and carcinogenesis. A series of epidemiological studies have examined associations between XPF polymorphisms and cancer risk, but the findings remain inconclusive. Methodology/Principal Findings: In this meta-analysis of 47,639 cancer cases and 51,915 controls, by searching three electronic databases (i.e., MEDLINE, EMBASE and CNKI), we summarized 43 case-control studies from 29 publications on four commonly studied polymorphisms of XPF (i.e., rs1800067, rs1799801, rs2020955 and rs744154), and we did not find statistical evidence of any significant association with overall cancer risk. However, in stratification analyses, we found a significant association of XPF-rs1799801 with a reduced cancer risk in Caucasian populations (4,845 cases and 5,556 controls; recessive model: OR = 0.87, 95% CI = 0.76–1.00, P = 0.049, P = 0.723 for heterogeneity test, I2 = 0). Further genotype-phenotype correlation analysis showed that the homozygous variant CC genotype carriers had higher XPF expression levels than that of the TT genotype carriers (Student’s t test for a recessive model: P = 0.046). No publication bias was found by using the funnel plot and Egger’s test. Conclusion: This meta-analysis suggests a lack of statistical evidence for the association between the four XPF SNPs and overall risk of cancers. However, XPF-rs1799801 may be associated with cancer risk in Caucasian populations, which needs to be further validated in single large, well-designed prospective studies

ICAR: endoscopic skull‐base surgery

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Computational Methods for Pigmented Skin Lesion Classification in Images: Review and Future Trends

Skin cancer is considered as one of the most common types of cancer in several countries, and its incidence rate has increased in recent years. Melanoma cases have caused an increasing number of deaths worldwide, since this type of skin cancer is the most aggressive compared to other types. Computational methods have been developed to assist dermatologists in early diagnosis of skin cancer. An overview of the main and current computational methods that have been proposed for pattern analysis and pigmented skin lesion classification is addressed in this review. In addition, a discussion about the application of such methods, as well as future trends, is also provided. Several methods for feature extraction from both macroscopic and dermoscopic images and models for feature selection are introduced and discussed. Furthermore, classification algorithms and evaluation procedures are described, and performance results for lesion classification and pattern analysis are given

The affects of demographics differentiations on authorship identification

There is lots of previous studies concern the language difference in text regarding the demographics attribute. This investigation is different by presenting a new question: is male style more consistent than female or the opposite? Furthermore, we study the style differentiation according to age. Hence, this investigation presents a novel analysis of the proposed problem by applying authorship identification across each category and comparing the identification accuracy between them. We select personal blogs or diaries, which are different from other types of text such as essays, emails, or articles based on the text properties. The investigation utilizes couple of intuitive feature sets and studies various parameters that affect the identification performance. The results and evaluation show that the utilized features are compact while their performance is highly comparable with other larger feature sets. The analysis also confirmed the usefulness of the common users’ classifier, based on common demographics attributes, in improving the performance for the author identification task. Web mining - information extraction - psycholinguistic - machine learning - authorship identification - demographics differentiatio