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

Multidimensional CNN and LSTM for Predicting Epilepsy Seizure Activities

Epilepsy is a chronic neurological disease caused by sudden abnormal brain discharges, leading to temporary brain dysfunction. It can manifest in various ways, including paroxysmal movement, sensory, autonomic nerve, awareness, and mental abnormalities. It is now the second largest neurological disorder worldwide, affecting around 70 million people and increasing by approximately 2 million new cases each year. While about 70% of epilepsy patients can control their seizures with regular antiepileptic drugs, surgery, or nerve stimulation treatments, the remaining 30% suffer from intractable epilepsy without effective treatment, causing significant burden and potential danger to their lives. Early prediction and treatment are crucial to prevent harm to patients. Electroencephalogram (EEG) is a valuable tool for diagnosing epilepsy as it records the brain's electrical activity. EEG can be divided into scalp and intracranial types, and doctors typically analyze EEG signals of epileptic patients into four periods

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

New set of measures to analyze non-equilibrium structures

We introduce a set of statistical measures that can be used to quantify non-equilibrium surface growth. They are used to deduce new information about spatiotemporal dynamics of model systems for spinodal decomposition and surface deposition. Patterns growth in the Cahn-Hilliard Equation (used to model spinodal decomposition) are shown to exhibit three distinct stages. Two models of surface growth, namely the continuous Kardar-Parisi-Zhang (KPZ) model and the discrete Restricted-Solid-On-Solid (RSOS) model are shown to have different saturation exponents

Strategies developed on the modification of titania for visible light response with enhanced interfacial charge transfer process: An overview

The modification of titania by metal / non metal ion doping, coupling with narrow band gap sensitizer, surface flourination, metal deposition, and together with recent ventures on application of 001 facets of anatase titania for visible light response with enhanced charge carrier separation are briefly overviewed. © Versita Sp. z o.o

Influence of physicochemical-​electronic properties of transition metal ion doped polycrystalline titania on the photocatalytic degradation of Indigo Carmine and 4-​nitrophenol under UV​/solar light

To understand the role of dopant inside TiO2 matrix, anatase TiO2 was doped with transition metal ions like Mn2+, Fe3+, Ru3+ and Os3+ having unique half filled electronic configuration and their photocatalytic activity was probed in the degrdn. of Indigo Carmine (IC) and 4-​nitrophenol (NP) under UV​/solar light. For comparison, TiO2 was also doped with V5+, Ni2+ and Zn2+ metal ions having d0, d8 and d10 electronic configuration resp. Irresp. of excitation source UV​/solar light and nature of the org. pollutant, photocatalytic activities of doped photocatalysts followed the order: Mn2+-​TiO2 > Fe3+-​TiO2 > Ru3+-​TiO2 ≥ Os3+-​TiO2 > Zn2+-​TiO2 > V5+-​TiO2 > Ni2+-​TiO2 at an optimum concn. of dopant. Based on the exptl. results obtained, it is proposed that the existence of dopant with half filled electronic configuration in TiO2 matrix which is known to enhance the photocatalytic activity is not universal! Rather it is a complex function of several physicochem.-​electronic properties of doped titania. Enhanced photocatalytic activity of Mn2+ (0.06 at.​%)​-​TiO2 was attributed to the combined factors of high pos. redn. potential of Mn2+/Mn3+ pairs, synergistic effects in the mixed polymorphs of anatase and rutile, smaller crystallite size with high intimate contact between two phases and favorable surface structure of the photocatalyst. Despite the intense research devoted to transition metal ion doped TiO2, it is rather difficult to make unifying conclusion which is highlighted in this study

Safety and effectiveness of tranexamic acid in reduction of post-partum hemorrhage in patients undergoing caesarean section in tertiary care hospital of Southern India

Background: Obstetric haemorrhage is a leading cause of premature maternal mortality, accounting for at least 100,000 deaths each year worldwide. Tranexamic acid has been shown to reduce uterine blood loss in non-surgical aspect. The aim of the study is to evaluate the safety and effectiveness of TXA in prevention of post-partum hemorrhage in patients undergoing caesarean delivery and to compare the secondary clinical outcomes.Methods: In this prospective observational cross-sectional study, 50 pregnant women undergoing CD were selected in random pattern and divided into control and study group of 25 patients each, in the department of obstetrics and gynaecology in Sri. Siddhartha medical college, Tumakuru from November 2019 to October 2021. The study group were given 1 g of TXA intravenously and the control group did not receive TXA. All the pregnant women received 20 units of oxytocin following delivery.Results: Mean of the total blood loss in the study group was 67 % less than the control group. Secondary clinical outcomes such as need for blood transfusion, other surgical measures to stop bleeding were comparatively less in study group compared to control groups. To note, no significant difference in duration of hospital stay was found between two groups.Conclusions: Our study suggests that, a safe dose of 1g IV tranexamic acid prior to caesarean section has an effective role in reducing blood loss and significantly improved blood loss–related secondary clinical outcomes with fewer side effects.