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OpenStackDP: a scalable network security framework for SDN-based OpenStack cloud infrastructure
Network Intrusion Detection Systems (NIDS) and firewalls are the de facto solutions in the modern cloud to detect cyberattacks and minimize potential hazards for tenant networks. Most of the existing firewalls, perimeter security, and middlebox solutions are built on static rules/signatures or simple rule matching, making them inflexible, susceptible to bugs, and difficult to introduce new services. This paper aims to improve network management in OpenStack Clouds by taking advantage of the combination of software-defined networking (SDN), Network Function Virtualization (NFV), and machine learning/artificial intelligence (ML/AI) and for making networks more predictable, reliable, and secure. Artificial intelligence is being used to monitor the behavior of the virtual machines and applications running in the OpenStack SDN cloud so that when any issues or degradations are noticed, the decision can be quickly made on how to handle that issue, being able to analyze data in motion, starting at the edge. The OpenStackDP framework comprises lightweight monitoring, anomaly-detecting intelligent sensors embedded in the data plane, a threat analytics engine based on ML/AI algorithms running inside switch hardware/network co-processor, and defensive actions deployed as virtual network functions (VNFs). This network data plane-based architecture makes high-speed threat detection and rapid response possible and enables a much higher degree of security. We have built the framework with advanced streaming analytics technologies, algorithms, and machine learning to draw knowledge from this data that is in motion before the malicious traffic goes to the tenant compute nodes or long-term data store. Cloud providers and users will benefit from improved Quality-of-Services (QoS) and faster recovery from cyber-attacks and compromised switches. The multi-phase collaborative anomaly detection scheme demonstrates an accuracy of 99.81%, average latencies of 0.27 ms, and response speed within 9 s. The simulations and analysis show that the OpenStackDP network analytics framework substantially secures and outperforms prior SDN-based OpenStack solutions for Cloud architectures. 2023, The Author(s). -
Operational pattern forecast improvement with outlier detection in metro rail transport system
Transportation is an unavoidable part of every humans life. The mobility system handles the transport of humans from different places using various transport modes. According to a station in a populated area, the main problem is the presence of traffic in peak hours and wasting their valuable time on the road. The only medium which runs above the traffic is metro rails/subways. For these reasons, metro rails become a point of interest for each researchers prophecy and provide valuable recommendations for the smooth functioning of services. Even though, in many cases, the metro systems are affected by abnormal passenger flow. So, this study handles abnormal passenger flow detection and station clustering for the behavior study of a passenger flow system. The research compares outlier detection and anomaly identification for the behavioral analysis of the metro rail passenger flow. The study use data from Kochi Metro Rail Limited for the period 2017 to 2019. Outlier removal has used in passenger flow data before building a forecasting system. In pattern recognition algorithm those components which lie outside the patterns can be considered abnormal (anomaly).The outliers are the component falling apart from the region of interest. The effect of removing the outlier from the time-series pattern is studied against the outlier included pattern to show the improvement. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Operational plan on teaching-learning at departmental level /
Journal Of Education & Social Policy, Vol.1, Issue 2, pp.77-79, ISSN No: 2375-0790 (Online) 2375-0782 (Print). -
Opinion mining on newspaper headlines using SVM and NLP
Opinion Mining also known as Sentiment Analysis, is a technique or procedure which uses Natural Language processing (NLP) to classify the outcome from text. There are various NLP tools available which are used for processing text data. Multiple research have been done in opinion mining for online blogs, Twitter, Facebook etc. This paper proposes a new opinion mining technique using Support Vector Machine (SVM) and NLP tools on newspaper headlines. Relative words are generated using Stanford CoreNLP, which is passed to SVM using count vectorizer. On comparing three models using confusion matrix, results indicate that Tf-idf and Linear SVM provides better accuracy for smaller dataset. While for larger dataset, SGD and linear SVM model outperform other models. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved. -
Opportunistic mycoses in COVID-19 patients/survivors: Epidemic inside a pandemic
Being considered minor vexations, fungal infections hinder the life of about 15% of the world population superficially, with rare threats to life in case of invasive sepsis. A significant rise in the intrusive mycoses due to machiavellian fungal species is observed over the years due to increased pathology and fatality in people battling life-threatening diseases. Individuals undergoing therapy with immune suppressive drugs plus recovering from viral infections have shown to develop fungal sepsis as secondary infections while recovering or after. Currently, the whole world is fighting against the fright of Coronavirus disease (COVID-19), and corticosteroids being the primitive therapeutic to combat the COVID-19 inflammation, leads to an immune-compromised state, thereby allowing the not so harmful fungi to violate the immune barrier and flourish in the host. A wide range of fungal co-infection is observed in the survivors and patients of COVID-19. Fungal species of Candida, Aspergillus and Mucorales, are burdening the lives of COVID-19 patients/survivors in the form of Yellow/Green, White and Black fungus. This is the first article of its kind to assemble note on fungal infections seen in the current human health scenario till date and provides a strong message to the clinicians, researchers and physicians around the world non-pathological fungus should not be dismissed as contaminants, they can quell immunocompromised hosts. 2021 -
Oppositional Glowworm Swarm based Vector Quantization Technique for Image Compression in Fiber Optic Communication
In recent times, fiber optic communication networks have become commonly applied for commercial as well as military applications. Fiber optic networks have gained popularity owing to the high data rate. At the same time, the generation of huge quantity of data at a faster rate poses a major challenge in the storing and transmission process. To resolve this issue, data compression approaches have been presented to reduce the quantity of transmitted data and thereby minimizes bandwidth utilization and memory. Vector quantization (VQ) is a commonly employed image compression technique and Linde Buzo Gray (LBG) is used to construct an optimum codebook to compress images. With this motivation, this paper presents a new oppositional glowworm swarm optimization based LBG (OGSO-LBG) technique for image compression in fiber optic communication. The OGSO algorithm involves the integration of oppositional based learning (OBL) concept into the GSO algorithm to boost its convergence rate. The OGSO-LBG algorithm produces the codebook at a faster rate with minimal computation complexity. In order to highlight the enhanced compression performance of the OGSO-LBG technique, a series of experiments were carried out and the results are examined under different dimensions. 2021 IEEE -
Optical and electrical properties of SnS semiconductor crystals grown by physical vapor deposition technique
Tin sulfide (SnS) is a material of interest for use as an absorber in low cost solar cells. Single crystals of SnS were grown by the physical vapor deposition technique. The grown crystals were characterized to evaluate the composition, structure, morphology, electrical and optical properties using appropriate techniques. The composition analysis indicated that the crystals were nearly stoichiometric with Sn-to-S atomic percent ratio of 1.02. Study of their morphology revealed the layered type growth mechanism with low surface roughness. The grown crystals had orthorhombic structure with (0 4 0) orientation. They exhibited an indirect optical band gap of 1.06 eV and direct band gap of 1.21 eV with high absorption coefficient (up to 103 cm-1) above the fundamental absorption edge. The grown crystals were of p-type with an electrical resistivity of 120 ? cm and carrier concentration 1.52015 cm-3. Analysis of optical absorption and diffuse reflectance spectra showed the presence of a wide absorption band in the wavelength range 3001200 nm, which closely matches with a significant part of solar radiation spectrum. The obtained results were discussed to assess the suitability of the SnS crystal for the fabrication of optoelectronic devices. 2011 Elsevier B.V. All rights reserved. -
Optical and Electrochromic Properties of CeO2/WO3 Hybrid Thin Films Prepared by Hydrothermal and Sputtering
Innovative chromogenic nanostructures like hybrids but also composite materials can be increased electrochromic efficiency because of their prospective application values in low-power displays, smart windows, electronic papers, and car anti-reflect mirrors. We used a hydrothermal approach to make Cerium oxide Nanorods have various ratios in this report. DC magnetron sputtering procedures cover the generated cerium oxide nanorods of various diameters with a tungsten oxide layer in one step. the surface plasmon effect varies depending on the size of Ce Nanorods, and this phenomenon impacts electrochromic results. the electrochromic performances of CeO2/WO3 nanorods on FTO-coated glass slides are examined using a 0.5 M solution of H2SO4 as the electrolyte in the visible range. These structures produce considerable optical modulation (47 %, 45 %, and 41 % at 700 nm) and coloration efficiency (11.6, 7.57, and 10.84 cm2C-1 at 700 nm). 2022 Seventh Sense Research Group -
Optical Character Recognition (OCR) based Vehicle's License Plate Recognition System Using Python and OpenCV
License Platform Detection is a computer technology that enables us to identify digital images on the platform automatically. Different operations are covered in this system, such as imaging, number pad locations, alphanumeric character truncation and OCR. The final objective of the system is to construct and create efficient image processing procedures and techniques to position a licensing platter on the Open Computer View Library picture. It was used and implemented the K-NN algorithm and python programming language. The technology can be used in different industries such as security, highway speed detection, lighting violations, manuscript documents, automatic charging system, etc. Auto plate recognition is an integrated technology which identifies the auto licence plate. Auto plate auto recognition. Multiple applications include complex safety systems, public spaces, parking and urban traffic control. Automatic Vehicle License Plate Recognition (AVLPR) has undesirable aspects because of many effects, such as light and speed. This work presents an alternative technique to leverage free software for the implementation of AVLPR systems including Python and the Open Computer Vision (openCV). 2021 IEEE. -
Optical Character Recognition system with Projection Profile based segmentation and Deep Learning Techniques
Optical character recognition is the solution to convert text from printed or scanned documents into editable data. This project is aimed at building a Optical character recognition system that recognizes digital text. A document is first detected using contour-based detection technique without altering the angle of the image and is segmented into lines, once the lines are segmented the words embedded in them are extracted. This segmentation is done using projection profiling method. Characters are then segmented words with vertical projection profiling from the extracted words. These characters are fed into an image recognition model for recognition. The recognition model is CNN based deep learning model. Modified VGG16 architecture is used here to extract maximum features from the images and then classify them. To train the model a dataset is created from a repository of digital character dataset. The dataset consists of images of 153 font variants. 2022 IEEE. -
Optical characterization of oxadiazoles analogues doped PMMA film for photonic application
In the present study, newly synthesized nitrobenzene derivatives (PBT and PBF) doped poly(methyl methacrylate) films were prepared using spin coating techniques, and their optical properties were analyzed. The absorption spectra of various weight percentages (0.02%, 0.1%, 0.2%, and 0.3%) of nitrobenzene derivative-doped polymer films were recorded using a UVvisible spectrometer. From the absorption spectra, optical properties such as refractive index, band gap energy, extinction coefficient, and dielectric constant were calculated. The effect of doping on the optical properties of PMMA was investigated, with results revealing normal dispersive behavior from the refractive index and extinction coefficient. Atomic force microscopy and scanning electron microscopy images indicated that the synthesized films have a low degree of roughness and a smooth surface. Additionally, the nonlinear optical properties of the PBF-doped polymer film were investigated, and the ? value was determined to be 7.403cm/W. Overall, the findings suggest that PBF-doped polymer films are promising candidates for photonic applications. Indian Association for the Cultivation of Science 2024. -
Optical design studies for national large optical-IR telescope
A 1012 m class national large optical-IR telescope (NLOT) is envisaged to meet the growing scientific requirements in astronomy and astrophysics. Telescopes of such dimensions can only be made by segmenting the primary mirror, as it eases a more prominent primary mirrors fabrication, transportation, operation, and maintenance process. This paper presents the various optical designs analyzed for NLOT that can be fabricated using the India TMT Optics Fabrication Facility (ITOFF) at the Centre for Research and Education in Science and Technology (CREST) campus. We present the primary mirror segmentation details, its ideal optical performance, and study each designs advantages and technical complexities. Based on the above analysis, we have narrowed it down to an optimal design, and its performance analysis is also discussed. Indian Academy of Sciences 2024. -
Optical Properties of Magnetic Quantum Dots
The delta-like dispersion of the density of states (DoS) enable quantum dots (QD) to display optical and electronic properties comparable with those of real atoms. The discrete electronic structure of QDs akin to that of atoms is formed due to the effect of quantum confinement (QCE). In the case of magnetic quantum dots (MQD), the QDs are incorporated with magnetic impurities such as Mn atom, rare earth elements etc., by which the QDs undergo significant changes in optical and electronic properties by lifting their degeneracies (Zeeman effect). The combination of fluorescent and magnetic entities opens up opportunities for synthesizing two-in-one nanocomposites beneficial for multi-functional, multi-targeting, and multi-theranostic tools. Optical properties of QDs consisting of magnetic impurities, such as the absorption coefficient, oscillator strength, and refractive index are discussed in this chapter. 2023 selection and editorial matter, Amin Reza Rajabzadeh, Seshasai Srinivasan, Poushali Das, and Sayan Ganguly. -
Optical properties of MnTe2 few-layer quantum dots
Quantum dots (QDs) are gaining attention as a possible emissive material that might be used in flexible optoelectronic and photonic systems. In the present work, the temperature-dependent photoluminescence (TDPL) property of manganese di-telluride (MnTe2) QDs was investigated. The room-temperature PL is attributed to the abrupt breakage of the large-area MnTe2 nanosheets by ultrasonication, which integrates defect-mediated localized trap states inside the electronic bandgap. As a result, deliberately generated defect states ultimately generate such PL emission of QDs. Density functional theory (DFT) results further validate the experimental interpretations of the origin of TDPL. In addition, through an in-situ liquid diffusion approach, the QDs were also integrated into a NaCl matrix. Due to light scattering properties, the hybrid crystals exhibit fluorescence centres at various excitation wavelengths. These results suggest that these MnTe2 QDs can be used as an effective basis for future flexible optoelectronic applications. 2024 Elsevier B.V. -
Optical Resonator-Enhanced Random Lasing using Atomically Thin Aluminium-based Multicomponent Quasicrystals
Photon trapping inside a gain medium using a dispersed two-dimensional (2D) passive scatterer is an impetus to obtain incoherent random lasing (ic-RL) emission due to non-resonant feedback. An optical resonator (OR) can be used to influence such lasing thresholds. Non-noble nanomaterials-based quasicrystals (QCs) are an intriguing research prospect due to their potential surface plasmon resonance (SPR) property and ability to be exfoliated into 2D. In this work, an aluminium-based multicomponent alloy (Al70Co10Fe5Ni10Cu5) has been synthesized via the arc melting method. Thereafter, ultrasonication-based liquid phase exfoliation was used to obtain 2D quasicrystals (2D-QCs). The SPR-induced light scattering properties of synthesized 2D-QCs were exploited to obtain ic-RL from DCM dye gain medium under 532 nm, 10 ns, 10 Hz pulsed laser pumping. The plasmonic field enhancement property of 2D-QCs which enables the gain medium to absorb photons outside its peak absorption band has been demonstrated. The transition from ic-RL to OR-enhanced ic-RL and vice versa in the presence of resonator walls has been achieved by tweaking the device architecture. In this way, the ability of 2D-QCs to be potential passive scatterers and the controllability of lasing thresholds in the presence of an OR has been demonstrated. 2024 Elsevier Ltd -
Optical Spectroscopy of Classical Be Stars in Old Open Clusters
We performed the optical spectroscopy of 16 classical Be stars in 11 open clusters older than 100 Myr. Ours is the first spectroscopic study of classical Be stars in open clusters older than 100 Myr. We found that the H? emission strength of most of the stars is less than 40 in agreement with previous studies. Our analysis further suggests that one of the stars, [KW97] 35-12, might be a weak H? emitter in nature, showing H? equivalent width of ?0.5 Interestingly, we also found that the newly detected classical Be star LS III +47 37b might be a component of the possible visual binary system LS III +47 37, where the other companion is also a classical Be star. Hence, the present study indicates the possible detection of a binary Be system. Moreover, it is observed that all 16 stars exhibit a lesser number of emission lines compared to classical Be stars younger than 100 Myr. Furthermore, the spectral type distribution analysis of B-type and classical Be stars for the selected clusters points out that the existence of CBe stars can depend on the spectral type distribution of B-type stars present in these clusters. 2023. National Astronomical Observatories, CAS and IOP Publishing Ltd. -
Optical spectroscopy of Gaia detected protostars with DOT: Can we probe protostellar photospheres?
Optical spectroscopy offers the most direct view of the stellar properties and the accretion indicators. Standard accretion tracers, such as H ? , H ? and Ca II triplet lines, and most photospheric features fall in the optical wavelengths. However, these tracers are not readily observable from deeply embedded protostars because of the large line of sight extinction (Av? 50 100 mag) toward them. In some cases, however, it is possible to observe protostars at optical wavelengths if the outflow cavity is aligned along the line-of-sight that allows observations of the photosphere, or the envelope is very tenuous and thin, such that the extinction is low. In such cases, we not only detect these protostars at optical wavelengths, but also follow up spectroscopically. We have used the HOPS catalog (Furlan et al. in 2016) of protostars in Orion to search for optical counterparts for protostars in the Gaia DR3 survey. Out of the 330 protostars in the HOPS sample, an optical counterpart within 2 ? ? is detected for 62 of the protostars. For 17 out of 62 optically detected protostars, we obtained optical spectra (between 5500 and 8900 using nt Object Spectrograph and Camera (ADFOSC) on the 3.6-m Devasthal Optical Telescope (DOT) and Hanle Faint Object Spectrograph Camera (HFOSC) on 2-m Himalayan Chandra Telescope (HCT). We detect strong photospheric features, such as the TiO bands in the spectra (of 4 protostars), hinting that photospheres can form early in the star-formation process. We further determined the spectral types of protostars, which show photospheres similar to a late M-type. Mass accretion rates derived for the protostars are similar to those found for T-Tauri stars, in the range of 10 - 7 10 - 8M? yr - 1 . 2023, Indian Academy of Sciences. -
Optical spectroscopy of Galactic field classical Be stars
In this study, we analyse the emission lines of different species present in 118 Galactic field classical Be stars in the wavelength range of 3800-9000 We re-estimated the extinction parameter (AV) for our sample stars using the newly available data from Gaia DR2 and suggest that it is important to consider AV while measuring the Balmer decrement (i.e. D34 and D54) values in classical Be stars. Subsequently, we estimated the Balmer decrement values for 105 program stars and found that ?20 per cent of them show D34 ? 2.7, implying that their circumstellar disc are generally optically thick in nature. One program star, HD 60855 shows H? in absorption - indicative of disc-less phase. From our analysis, we found that in classical Be stars, H? emission equivalent width values are mostly lower than 40 which agrees with that present in literature. Moreover, we noticed that a threshold value of ?10of H? emission equivalent width is necessary for FeII emission to become visible. We also observed that emission line equivalent widths of H?, P14, FeII 5169, and OI 8446for our program stars tend to be more intense in earlier spectral types, peaking mostly near B1-B2. Furthermore, we explored various formation regions of Ca II emission lines around the circumstellar disc of classical Be stars. We suggest the possibility that Ca II triplet emission can originate either in the circumbinary disc or from the cooler outer regions of the disc, which might not be isothermal in nature. 2021 Oxford University Press. All rights reserved. -
Optimal allocation algorithm of marketing resources based on improved random forest
Random Forest algorithm is an ensemble learning algorithm that classifies data by combining multiple decision trees. It has a wide range of applications and is not easy to overfit. It has a wide range of applications in medicine, bioinformatics, management and other fields. By studying the Cobb-Douglas sales function, it is found that it can only analyze the static allocation of marketing resources, but cannot describe the dynamic changes. Enterprise marketing resource management runs through the enterprise management from beginning to end. The research on marketing resource management is helpful for enterprises to grasp and control the whole process of marketing resource management from the overall and overall level, and has important theoretical value and reality for enterprise marketing management activities. significance. In the vast majority of enterprises in our country, the size of advertising promotion expenses and the number of salesmen is often determined based on the experience and subjective assumptions of decision makers, so it is difficult to say that they are optimized. This paper starts with determining the optimal advertising budget and the number of salespeople, and conducts applied research on the optimal allocation of marketing resources. 2023 IEEE. -
Optimal Allocation of Renewable Sources with Battery and Capacitors in Radial Feeders for Reliable Power Supply Using Pathfinder Algorithm
Allocating renewable energy systems (RESs) in an electrical distribution system (EDS) is crucial to achieving various objectives. However, their intermittency presents several challenges. In this connection, an efficient meta-heuristic pathfinder algorithm (PFA) is employed to determine the optimal location and size of photovoltaic (PV) and wind turbine (WT) systems, along with energy storage systems (ESS) and capacitor banks (CB) for both grid and islanding modes of operations. An objective function was formulated for loss reduction, greenhouse gas (GHG) emissions, and voltage profile improvement. The simulation results for the IEEE 33-bus EDS system are shown for two cases: grid-connected and islanding. The computational effectiveness of the PFA was compared with that reported in the literature. The PFA results showed an outstanding ability to resolve difficult optimisation problems. In addition, the optimal size of the RES when the network operates in the grid-connected mode can significantly improve the performance. The real power losses and GHG emissions were reduced by 48.49 % and 67.75% with PV systems and the other, respectively, whereas WT systems they are reduced to 69.68 % and 67.85 %, respectively. However, a combination of ESS, CB, and PV/WT can render the EDN sustainable for the islanding mode of operations. The Author(s).