Data analytics in SDN and NFV: Techniques and Challenges

Software defined networking and network function virtualization are drawing huge attention from researchers both in industry and academia. NFV reduces the capital and opera- tional expenditure of the organization by decoupling the network functions from physical hardware on which they run, which poses new challenges in the perspective of network management such as data management, resource management and performance analysis. Consequentially, novel techniques and strategies are required to address these challenges in efficient way. This paper discusses the most widely used data analytics techniques like machine learning and time series data analysis. Further it describes the review of data mining tools and frameworks. Machine learning helps to overcome the challenges of network management by providing intelligence in network. Hence, in this paper we describe an overview of high level architecture of machine learning analysis framework, the challenges of applying machine learning algorithms in virtual environment and also some of the interesting problems of network management which can be solved by using machine learning

Machine Learning Defence Mechanism for Securing the Cloud Environment

A computer paradigm known as ”cloud computing” offers end users on-demand, scalable, and measurable services. Today’s businesses rely heavily on computer technology for a variety of reasons, including cost savings, infrastructure, development platforms, data processing, data analytics, etc. The end users can access the cloud service providers’ (CSP) services from any location at any time using a web application. The protection of the cloud infrastructure is of the highest  significance, and several studies using a variety of technologies have been conducted to develop more effective defenses against cloud threats. In recent years, machine learning technology has shown to be more effective in securing the cloud environment. In recent years, machine learning technology has shown to be more effective in securing the cloud environment. To create models that can automate the process of identifying cloud threats with better accuracy than any other technology, machine learning algorithms are  trained  on  a  variety  of  real-world  datasets. In this study, various recent research publications that used machine learning as a defense mechanism against cloud threats are reviewed

Supersensitive measurement of angular displacements using entangled photons

We show that the use of entangled photons having non-zero orbital angular momentum (OAM) increases the resolution and sensitivity of angular-displacement measurements performed using an interferometer. By employing a 4$\times$4 matrix formulation to study the propagation of entangled OAM modes, we analyze measurement schemes for two and four entangled photons and obtain explicit expressions for the resolution and sensitivity in these schemes. We find that the resolution of angular-displacement measurements scales as $Nl$ while the angular sensitivity increases as $1/(2Nl)$, where $N$ is the number of entangled photons and $l$ the magnitude of the orbital-angular-momentum mode index. These results are an improvement over what could be obtained with $N$ non-entangled photons carrying an orbital angular momentum of $l\hbar$ per photonComment: 6 pages, 3 figure

HD 12098 and other results from NainiTal-Cape survey

NainiTal-Cape Survey is a survey started with the aim of searching for new rapidly oscillating Ap stars in the northern hemisphere and has discovered one mono-periodic roAp star HD 12098. The frequency separation of HD 12098 suggests a rotation period of 5.5 day for the star. The discovery of roAp oscillations in HD 12098 and the results of the multi-site observation campaign organized to resolve the ambiguity in the determination of the rotation period of HD 12098 is presented. The results of non oscillating Ap stars discovered in the survey and two promising roAp candidates HD 17431 and HD 207561 are also presented. If confirmed, the variability in HD 207561 will make it the first Am star showing roAp type rapid variability.Comment: 10 pages, 10 figures, JAA sty, To appear in the proceedings of ARIES international workshop on Asteroseismolog

Pediatric surgical specialty in India: Sunset or in an eclipse? Current status: 2014-15

Background: Pediatric surgical specialty in India is more than 50-year-old. In spite of the advances made in pediatric surgical care, the specialty is still not being recognized as a “super specialty” and given importance in par with other super specialties. There is a decrease in the demand for pediatric surgical trainee posts. Aims: To assess the current status of pediatric surgical services in India and analyze the factors contributing to decrease in demand for pediatric surgical trainee posts. Materials and Methods: A web-based survey was conducted in January 2014. A questionnaire was sent to all members of Indian Association of Pediatric Surgeons via e-mail and the results were analyzed. Survey Monkey statistical software was used for analysis of data. Results: A total of 145 (24.5%) members responded to the survey. The majority of the members were practicing in metros and were dissatisfied because of the lesser remuneration as compared to other super specialties. However, the majority of the members were happy socially and professionally and expected a bright future for the specialty. Conclusion: Pediatric surgery, like any other surgical branch, has short comings. Pediatric surgical specialty in India is currently in an eclipse rather than in a sunset

Rectovestibular fistula: Is treatment always required?

The traditional teaching in the management of rectovestibular fistula involves corrective surgery, either in single or multiple stages.Usually, female children operated for the same are advised cesarean section during childbirth to prevent damage to the neoanus.Herein, we report a story of a 68-year-old woman with untreated rectovestibular fistula and has given birth to five children withoutany sequalae

Modeling of Bubble Growth Dynamics and Nonisothermal Expansion in Starch-Based Foams During Extrusion

A mathematical model was developed to describe expansion phenomena in starch-based foams during extrusion. The model was divided into three parts to describe the microbubble growth dynamics, to couple bubble growth with extrudate expansion, and to describe the macrotransport phenomena in the extrudate, respectively. The differential equations involved in the model were solved by finite element schemes. For validating the model, the predicted radius, density, and residual moisture of final extrudate were compared with experimental data. Standard deviations between the predicted and experimental radius, density, and residual moisture of final extrudates were 16.7%, 11.2%, and 39.3%, respectively. The model was used to predict the profiles of downstream velocity, expansion ratio, moisture content, and temperature of extrudate during expansion

U(1) Gauge Theory as Quantum Hydrodynamics

It is shown that gauge theories are most naturally studied via a polar decomposition of the field variable. Gauge transformations may be viewed as those that leave the density invariant but change the phase variable by additive amounts. The path integral approach is used to compute the partition function. When gauge fields are included, the constraint brought about by gauge invariance simply means an appropriate linear combination of the gradients of the phase variable and the gauge field is invariant. No gauge fixing is needed in this approach that is closest to the spirit of the gauge principle. We derive an exact formula for the condensate fraction and in case it is zero, an exact formula for the anomalous exponent. We also derive a formula for the vortex strength which involves computing radiation corrections.Comment: 15 pages, Plain LaTeX, final published versio

Intrinsic and extrinsic pathway signaling during neuronal apoptosis: lessons from the analysis of mutant mice

Trophic factor deprivation (TFD)-induced apoptosis in sympathetic neurons requires macromolecular synthesis–dependent BAX translocation, cytochrome c (cyt c) release, and caspase activation. Here, we report the contributions of other intrinsic and extrinsic pathway signals to these processes. Sympathetic neurons expressed all antiapoptotic BCL-2 proteins examined, yet expressed only certain BH3-only and multidomain proapoptotic BCL-2 family members. All coexpressed proapoptotic proteins did not, however, exhibit functional redundancy or compensatory expression, at least in the Bax−/−, Bak−/−, Bim−/−, Bid−/−, and Bad−/− neurons examined. Although the subcellular distribution or posttranslational modification of certain BCL-2 proteins changed with TFD, neither transcriptional nor posttranslational mechanisms regulated the expression or subcellular localization of BID, BAD, or BAK in this paradigm. Despite modest induction of Fas and FasL expression, Fas-mediated signaling did not contribute to TFD-induced apoptosis in sympathetic neurons. Similar findings were obtained with K+ withdrawal–induced apoptosis in cerebellar granule neurons, a model for activity-dependent neuronal survival in the CNS. Thus, expression alone does not guarantee functional redundancy (or compensation) among BCL-2 family members, and, at least in some cells, extrinsic pathway signaling and certain BH3-only proteins (i.e., BID and BAD) do not contribute to BAX-dependent cyt c release or apoptosis caused by TFD