Optimal security hardening on attack tree models of networks: a cost-benefit analysis

Researchers have previously looked into the problem of determining whether a given set of security hardening measures can effectively make a networked system secure. However, system administrators are often faced with a more challenging problem since they have to work within a fixed budget which may be less than the minimum cost of system hardening. An attacker, on the other hand, explores alternative attack scenarios to inflict the maximum damage possible when the security controls are in place, very often rendering the optimality of the controls invalid. In this work, we develop a systematic approach to perform a cost-benefit analysis on the problem of optimal security hardening under such conditions. Using evolutionary paradigms such as multi-objective optimization and competitive co-evolution, we model the attacker-defender interaction as an “arms race”, and explore how security controls can be placed in a network to induce a maximum return on investment.     

Facile Fabrication of PbS Nanocrystal:C60 Fullerite Broadband Photodetectors with High Detectivity

Hybrid PbS nanocrystal/C₆₀ fullerite photodetectors are fabricated using a simple one‐step drop casting procedure onto pre‐patterned interdigitated electrodes. The devices exhibit a broad spectral response from the near UV through to the near infrared yielding a detectivity, D*, of above 10¹⁰ Jones from 400 nm to ≈1050 nm. The ability to further extend the spectral response to wavelengths ≈1350 nm in the near infrared via tuning of the PbS nanocrystal diameter is also demonstrated. The dynamic responses of the devices are presented, exhibiting a fast photocurrent rise time (<40 ns) followed by a long bi‐exponential decay with characteristic lifetimes of τ₁ = 5.3 μs ± 0.1 μs and τ₂ = 37.8 μs ± 0.7 μs. These devices, which have a detectivity approaching that of commercial detectors, a broader spectral response, and a fast rise time, offer an attractive low‐cost solution for large‐area broadband photodetectors.     

SY－3C型氨合成塔内件特点及其温度分布

对三段冷激－冷管型氨合成塔内件的结构特点及其温度分布进行了讨论。理论计算和生产实践证明，该内件结构简单，温度分布合理，压降较低，运行平稳，催化剂装量增加，升温还原方便，是一种节能高产的氨合成塔内件。     

基于工程能力培养的桥梁工程毕业设计教学改革研究

根据国内高等工科院校的教育特点,结合国际CDIO工程教育理念,针对桥梁工程毕业设计的实践教学课程,研究并探讨了培养和提高学生的工程能力的教学改革途径和方法,以期为国内类似专业课程毕业设计实践教学提供借鉴和参考。     

Nanocharacterization in Dentistry

About 80% of US adults have some form of dental disease. There are a variety of new dental products available, ranging from implants to oral hygiene products that rely on nanoscale properties. Here, the application of AFM (Atomic Force Microscopy) and optical interferometry to a range of dentistry issues, including characterization of dental enamel, oral bacteria, biofilms and the role of surface proteins in biochemical and nanomechanical properties of bacterial adhesins, is reviewed. We also include studies of new products blocking dentine tubules to alleviate hypersensitivity; antimicrobial effects of mouthwash and characterizing nanoparticle coated dental implants. An outlook on future “nanodentistry” developments such as saliva exosomes based diagnostics, designing biocompatible, antimicrobial dental implants and personalized dental healthcare is presented.     

Miscibility of chitosan–hydroxyethylcellulose blends in aqueous acetic acid solutions at 35°C

The miscibility of blends of chitosan and hydroxyethylcellulose in a 2% acetic acid solution was studied by viscometry, densitometry, and refractometry at 35°C. The data suggest that the blends were completely miscible in all proportions. Further, the membranes were fabricated from concentrated blend solutions. The solid‐state compatibility of the blends was confirmed by scanning electron microscopy. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 96: 1996–1998, 2005     

Optimization of preparation conditions on the dielectric properties of polyaniline

The dielectric response in the microwave field of polyaniline prepared at different temperatures and using different inorganic and organic dopants was studied. Chemical oxidative polymerization of aniline was done at low temperature (0–5°C), at room temperature, and at high (60°C) temperature using different inorganic dopants like HCl, HNO₃, H₂SO₄, HClO₄, etc. Polyaniline was also prepared with different organic dopants like camphor sulfonic acid, Toluene sulfonic acid, and Naphthalene sulfonic acid. All polymers formed were characterized using IR, TGA, DSC, and SEM, etc. The dielectric responses of all polymers are studied using cavity perturbation technique in the microwave field. The studies indicates that the polyaniline prepared with perchloric acid at room temperature shows higher conductivity and absorption coefficient compared with all other samples. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009     

PtLiLa/γ-Al2O3催化剂上柴油水蒸气重整制氢实验研究

采用浸渍法制备了PtLiLa/γ-Al2O3催化剂。以－10号柴油为原料,在固定床管式反应器中研究了温度、水碳比、空速对PtLiLa/γ-Al2O3催化剂上柴油水蒸气重整制氢反应的影响,确定了适宜的反应条件。采用XRD和SEM方法对反应后的催化剂进行了表征。结果表明,PtLiLa/γ-Al2O3催化剂对柴油水蒸气重整制氢具有较好的催化性能,且稳定性良好。在温度680 oC,水碳摩尔比22,柴油空速0.3 h-1条件下,H2产率为28.66 mol/mol。     

COVID-19 Infected Lung Computed Tomography Segmentation and Supervised Classification Approach

The purpose of this research is the segmentation of lungs computed tomography (CT) scan for the diagnosis of COVID-19 by using machine learning methods. Our dataset contains data from patients who are prone to the epidemic. It contains three types of lungs CT images (Normal, Pneumonia, and COVID-19) collected from two different sources; the first one is the Radiology Department of Nishtar Hospital Multan and Civil Hospital Bahawalpur, Pakistan, and the second one is a publicly free available medical imaging database known as Radiopaedia. For the preprocessing, a novel fuzzy c-mean automated region-growing segmentation approach is deployed to take an automated region of interest (ROIs) and acquire 52 hybrid statistical features for each ROIs. Also, 12 optimized statistical features are selected via the chi-square feature reduction technique. For the classification, five machine learning classifiers named as deep learning J4, multilayer perceptron, support vector machine, random forest, and naive Bayes are deployed to optimize the hybrid statistical features dataset. It is observed that the deep learning J4 has promising results (sensitivity and specificity: 0.987; accuracy: 98.67%) among all the deployed classifiers. As a complementary study, a statistical work is devoted to the use of a new statistical model to fit the main datasets of COVID-19 collected in Pakistan.