A Three-Dimensional Evaluation Model for Network Management System

AbstractThe growing of network applications and the advances in network services demand for more complex and flexible network management systems. It becomes difficult to evaluate the performance of such a system using the traditional, simple and arbitrary evaluation methods especially when the system is designed for a specific purpose. Systematic evaluation models should be built to evaluate if a system meets the specified requirements while does not sacrifice much of the network performance. In this paper, we propose a three-dimensional evaluation model for network management system which takes cost, impact, as well as operation into consideration at the same time. We define evaluation index as a performance indicator, which is detailed elaboration for the proposed model. We believe that the three-dimensional evaluation for network evaluation can be better suited in nowadays network environment

Cloud Forensics Investigation: Tracing Infringing Sharing of Copyrighted Content in Cloud

Cloud Computing is becoming a significant technology trend nowadays, but its abrupt rise also creates a brand new front for cybercrime investigation with various challenges. One of the challenges is to track down infringing sharing of copyrighted content in cloud. To solve this problem, we study a typical type of content sharing technologies in cloud computing, analyze the challenges that the new technologies bring to forensics, formalize a procedure to get digital evidences and obtain analytical results based on the evidences to track down illegal uploader. Furthermore, we propose a reasoning model based on the probability distribution in a Bayesian Network to evaluate the analytical result of forensics examinations. The proposed method can accurately and scientifically track down the origin infringing content uploader and owner. Keywords: cloud forensics, peer to peer, file sharing, tracking, CloudFron

β-delayed particle decay of 9C and the A = 9, T = 1/2 nuclear system: Experiment, data, and phenomenological analysis

The β decay of 9C (T1/2 = 126.5 ms) has been studied in two experiments observing about 15 × 107 and 8 × 107 decays, respectively, at the TISOL facility at TRIUMF; different detector configurations were employed in the two experiments. In this first of two papers, the two experimental setups are described, as well as data analysis and a phenomenological approach to deducing branching ratios to and from states in 9B. In the experiments single spectra, and double and triple coincidence spectra, were recorded. Several states in 9B were observed; β-branching ratios to these states, and particle decay channels from these states, are reported. In particular, secondary decays into the 5Li and 8Be ground states were observed. With the inclusion of a considerable continuum and additional states, fair agreement with the reported 9Li logft values is found with a phenomenological approach for deducing the branching ratios. To extend the discussion, in a second, forthcoming paper, a multichannel, multistate R-matrix analysis of these data will be described

β-delayed particle decay of 17ne into p + α + 12C through the isobaric analog state in 17F

We have observed the breakup of the isobaric analog state at 11.193 MeV in 17F into three particles via three channels: proton decay to the α-unbound 9.585 MeV state in 16O; and α decay to the proton-unbound 2.365 and 3.502/3.547 MeV states in 13N. Laboratory α-particle spectra corresponding to these three modes have been generated in Monte Carlo simulations using single-channel, single- and multilevel R-matrix formulas. A fit of these spectra to the α spectrum resulting from a triple-coincidence measurement results in excellent agreement with the experimental spectrum and allows branching ratios to be deduced for these rare decay modes

Three-particle breakup of the isobaric analog state in 17F

We have studied the b-delayed particle decay of 17Ne to test the feasibility of determining both the E1 and E2 components of the 12C(a,g )16O cross section at energies relevant to helium burning in stars. In this context we have observed the breakup of the isobaric analog state in 17F at 11.193 MeV into three particles via three channels: proton decay to the 9.59 MeV state in 16O; and a decay to the 2.365 and 3.502/3.547 MeV states in 13N. This is the first reported observation of the decay of the IAS to the 12 state in 16O at 9.59 MeV and the first reported b-delayed proton-a decay. With straightforward improvements to our detection apparatus to improve angular resolution, b suppression, and solid angle coverage, we should be able to proceed to the measurement of the effect of the tail of the subthreshold state at 7.117 MeV in 16O on thea spectrum from the breakup of the 9.59 MeV state

Measurement of the 24Mg(p,t) 22Mg reaction and implications for the 21Na(p, γ) 22Mg stellar reaction rate

Levels in 22Mg between 4 and 7 MeV excitation energy have been populated in a high-resolution study of the 24Mg(p,t) 22Mg reaction. Two new states have been observed at energies Ex = 5090 and 6323 keV, while two states were observed at 5962 and 6046 keV. The precision in measured excitation energies for several other 22Mg levels has been improved substantially. In addition, a new state at 8141 keV was observed in 23Mg. Using spin and parity restrictions from the present and previous work, we discuss T = 1 analog state assignments of A = 22 nuclei below 7 MeV excitation energy. The implications for the rate of the stellar reaction 21Na(p, γ) 22Mg which takes part in hydrogen burning during nova outbursts are presented

Genomic analysis of diet composition finds novel loci and associations with health and lifestyle

We conducted genome-wide association studies (GWAS) of relative intake from the macronutrients fat, protein, carbohydrates, and sugar in over 235,000 individuals of European ancestries. We identified 21 unique, approximately independent lead SNPs. Fourteen lead SNPs are uniquely associated with one macronutrient at genome-wide significance (P < 5 × 10−8), while five of the 21 lead SNPs reach suggestive significance (P < 1 × 10−5) for at least one other macronutrient. While the phenotypes are genetically correlated, each phenotype carries a partially unique genetic architecture. Relative protein intake exhibits the strongest relationships with poor health, including positive genetic associations with obesity, type 2 diabetes, and heart disease (rg ≈ 0.15–0.5). In contrast, relative carbohydrate and sugar intake have negative genetic correlations with waist circumference, waist-hip ratio, and neighborhood deprivation (|rg| ≈ 0.1–0.3) and positive genetic correlations with physical activity (rg ≈ 0.1 and 0.2). Relative fat intake has no consistent pattern of genetic correlations with poor health but has a negative genetic correlation with educational attainment (rg ≈−0.1). Although our analyses do not allow us to draw causal conclusions, we find no evidence of negative health consequences associated with relative carbohydrate, sugar, or fat intake. However, our results are consistent with the hypothesis that relative protein intake plays a role in the etiology of metabolic dysfunction