Deciphering a novel image cipher based on mixed transformed Logistic maps

Since John von Neumann suggested utilizing Logistic map as a random number generator in 1947, a great number of encryption schemes based on Logistic map and/or its variants have been proposed. This paper re-evaluates the security of an image cipher based on transformed logistic maps and proves that the image cipher can be deciphered efficiently under two different conditions: 1) two pairs of known plain-images and the corresponding cipher-images with computational complexity of $O(2^{18}+L)$; 2) two pairs of chosen plain-images and the corresponding cipher-images with computational complexity of $O(L)$, where $L$ is the number of pixels in the plain-image. In contrast, the required condition in the previous deciphering method is eighty-seven pairs of chosen plain-images and the corresponding cipher-images with computational complexity of $O(2^{7}+L)$. In addition, three other security flaws existing in most Logistic-map-based ciphers are also reported.Comment: 10 pages, 2 figure

An optimal data service providing framework in cloud radio access network

Much work has been conducted to design effective and efficient algorithms for quality of service (QoS)-aware service computing in the past several years. The wireless mobile computing and cloud computing environments have brought many challenges to QoS-aware service providing. Mobile cloud computing (MCC) and cloud radio accessing networks (C-RANs) are the new paradigms arising in recent years. This work proposes a wireless data service providing framework in C-RAN aiming to provide data service in C-RAN by a more efficient way. The efficiency is measured by cost with time constraint. An abstract formal model is built on the proposed framework, and the corresponding optimal solution is deduced theoretically using queuing theory and convex optimization. The simulation results show that the proposed optimal strategy on the optimal solution works well and has a better performance than compared one

Effect of recombinant human brain natriuretic peptide on myocardial enzymes and cardiac function after percutaneous coronary intervention in patients with acute myocardial infarction

Purpose: To study the effect of recombinant human brain natriuretic peptide rhBNP on myocardial enzymes and cardiac function following percutaneous coronary intervention (PCI) in acute myocardial infarction (AMI) subjects.Methods: Patients with AMI (124 cases) subjected to PCI for 2 years were used as subjects in this investigation. Two groups of patients were used (62 patients per group). One group received rhBNP while the other group served as control. The patients consisted of 76 males and 48 females (mean age, 63.54 ± 12.31 years). The two groups of patients received 75 mg/kg body weight of clopidogrel orally and aspirin (300 mg/kg) 2 h before PCI. The peaks of creatine kinase (CK), creatine kinase MB (CKMB), and the levels of troponin I (cTnI) were assayed at pre-determined intervals with an automated biochemical analyzer, and changes in the enzyme levels were recorded. Echocardiography (ECG) parameters were also measured.Results: Lower peaks of CK, CK-MB and levels of cTnI were seen in rhBNP-treated patients, when compared with controls (p < 0.05). Total effectiveness was markedly higher in rhBNP-treated group than in control group (p < 0.05). Moreover, myocardial infarct size was significantly lower in rhBNP treatment group than in control group (p < 0.05).Conclusion: Treatment with rhBNP before PCI in patients with AMI increases coronary blood flow, ameliorates perfusion injury, inhibits left ventricular remodeling, reduces myocardial cell necrosis, and improves cardiac function and prognosis.Keywords: Recombinant human brain natriuretic peptide (rhBNP), Acute myocardial infarction, percutaneous coronary intervention, Myocardial enzymes, Cardiac functio