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Experimenting with resilience and scalability of wifi mininet on small to large SDN networks
Today everything is getting digitized where people want to be wireless by all aspects. There is a high demand of WiFi in every sector. Highest influence on network planning of newly developed network infrastructure is of SDN to meet the futuristic needs of upcoming technology. As a result, newly developed networks have become more adaptive to dynamic circumstances along with enhanced flexibility. Being globally connected, it is inevitable to obtain adequate services from data centers through Wi-Fi support on SDN Networks, which is still a dream. Thus, the target of the experiment performed and presented by the authors of this paper is to implement WiFi support on SDN. Further, authors have also demonstrated the scalability and resilience of SDN based WiFi Network on Mininet by testing performance parameters in various dynamic scenarios. This paper will have a high impact on the end users as SDN technology can be implemented as last mile technology using WiFi SDN. BEIESP. -
Experimenting with scalability of Beacon controller in software defined network
In traditional network, a developer cannot develop software programs to control the behavior of the network switches due to closed vendor specific configuration scripts. In order to bring out innovations and to make the switches programmable a new network architecture must be developed. This led to a new concept of Software Defined Networking(SDN). In Software defined networking architecture, the control plane is detached from the data plane of a switch. The controller is implemented using the control plane which takes the heavy lift of all the requests of the network. Few of the controllers used in SDN are Floodlight, Ryu, Beacon, Open Daylight etc. In this paper, authors are evaluating the performance of Beacon controller using scalability parameter on network emulation tool Mininet and IPERF. The experiments are performed on multiple scenarios of topology size range from 50 to 1000 nodes and further analyzing the controller performance. BEIESP. -
Experimenting with scalability of floodlight controller in software defined networks
Software Defined Network is the booming area of research in the domain of networking. With growing number of devices connecting to the global village of internet, it becomes inevitable to adapt to any new technology before testing its scalability in presence of dynamic circumstances. While a lot of research is going on to provide solution to overcome the limitations of the traditional network, it gives a call to research community to test the applicability and caliber to withstand the fault tolerance of the provided solution in the form of SDN Controllers. Out of existing multiple controllers providing the SDN functionalities to the network, one of the stellar controllers is Floodlight Controller. This paper is a contribution towards performance evaluation of scalability of the Floodlight Controller by implementing multiple scenarios experimented on the simulation tool of Mininet, Floodlight Controller and iPerf. Floodlight Controller is tested in the simulation environment by observing throughput and latency parameters of the controller and checked its performance in dynamic networking conditions over Mesh topology by exponentially increasing the number of nodes. 2017 IEEE. -
Explainable AI Method for Cyber bullying Detection
People of all ages and genders are using social media platforms to engage themselves in all sorts of activities. People create profiles on online social networks in order to communicate with one another in this virtual environment. Hundreds or thousands of friends and followers are split across many profiles. Along with the virtual communication in this social media life, cyber-crimes also creep in many distinguished forms to grab user's information and emotionally degrade them with harassment and arrogant behavior. A set of machine learning methods are proposed and used to detect such a bullying behavior. Along with the detection of such an act, the model should also provide the logical reasoning of the evidence extracted. The explain ability of the models classification will give us a view of the way towards portraying a suspect as a bullier. This paper illustrates a machine learning model that works on a twitter data set to suggest the tweets as category bullying or non-bullying. LIME a tool to predict the interpretability of the model is used to depict the performance of model and provides explainability. 2022 IEEE. -
Explainable Artificial Intelligence: Frameworks for Ensuring the Trustworthiness
The growing computer power and ubiquity of big data are allowing Artificial Intelligence (AI) to gain widespread adoption and applicability in a wide range of sectors. The absence of an explanation for the conclusions made by today's AI algorithms is a significant disadvantage in crucial decision-making systems. For example, existing black-box AI systems are vulnerable to bias and adversarial assaults, which can taint the learning and inference processes. Explainable AI (XAI) is a recent trend in AI algorithms that gives explanations for their AI conclusions. Many contemporary AI systems have been shown to be vulnerable to undetectable assaults, biased against underrepresented groups, and deficient in user privacy protection. These flaws damage the user experience and undermine people's faith in all AI systems. This study proposes a systematic way to tie the social science notions of trust to the technology employed in AI-based services and products. 2024 IEEE. -
Explainable IoT Forensics: Investigation on Digital Evidence
This research examines the relevance of digital forensics in the field of Internet of Things and describes how different forensics tools and software are used to investigate cybercrimes. It emphasizes the importance of IoT Forensics and how it's used to tackle cybercrimes. It also discusses on the challenges faced by IoT forensics and gives an insight into the recent advancements in the field. It gives a walkthrough about how digital forensics investigation is done in 'data stolen' or 'data deleted' scenario. An outline of research potential and problems in IoT forensics is given in this chapter. The main details of IoT forensics are described. In all stages of a forensic investigation, issues linked to IoT are highlighted along with the potential that IoT presents for forensics. An illustration of an IoT forensics case is given with appropriate analytics. A brief research overview is provided, with information on the important research directions and a review of relevant articles. Future research proposals are included in the chapter's conclusion. 2023 IEEE. -
Explaining Autism Diagnosis Model Through Local Interpretability Techniques - A Post-hoc Approach
In this era of machine learning and deep learning algorithms dominating the Artificial Intelligence (AI) world, the trustworthiness of these black box models is still questionable. Life-caring sectors like healthcare and banking make use of these black box models as assistance in critical decision-making processes, but the degree of reliability of these decisions is still uncertain. This is because these black box models will not reveal the causation of the predicted outcome. However, creating an interpretable model that can explain the internal workings of these black box models can provide some reliable insights and trustable justifications for the predicted outcome. This study aimed to create an interpretable model for autism diagnosis which can give some trustable explanations for its predicted outcome. Using local interpretability methods such as LIME, SHAP, and Anchors the predicted outcome for each instance is explained well with some standard visual representations. As a result, this study developed an interpretable autism diagnosis model with an accuracy rate of 91.37% and with good local model explanations. 2023 IEEE. -
Explaining the intention to uptake COVID-19 vaccination using the behavioral and social drivers of vaccination (BeSD) model
Background: The World Health Organization (WHO) has proposed a tool to measure behavioral and social drivers (BeSD) of vaccination uptake intentions of people across all countries. This study tests BeSD model to predict people's intentions to uptake COVID-19 vaccination in rural India. Methods: An online cross-sectional survey was developed for the purpose based on the components of the BeSD model, i.e., confidence, motivation, and behavioral intention. A convenient sampling technique was used to collect samples, amounting to a total of 625, from rural Bengaluru, in the Karnataka state of India. Structural equation modelling (SEM) was applied to examine the proposed model. All respondents for the survey were in the age category of 1868 years with a mean age of 35 years. Findings: The results showed that 85% of COVID-19 vaccine uptake intentions can directly or indirectly be attributed to the government's vaccine communication strategy, perceived threats about the vaccine, and their trust in the healthcare sector. The dimensions of the vaccine acceptance scale (motivation factors) act as a mediator between these factors and COVID-19 vaccination uptake (the behavioral factor). Conclusion: The study demonstrates that the BeSD framework is an efficient model for predicting the COVID-19 vaccination uptake in India. 2022 The Authors -
Explanations for anomalies in semi strong from of efficient market hypithesis
The tradition notion of efficient market described in the academic literature is quite strong and probably is unrealistic because of following factors: short selling, short covering, fresh buying and profit booking. After all, science is just a human idea about phenomena which can change over time. In real markets, traders can cause markets to be inefficient. According to verifiability newlinetheory of meaning, most of statements are meaningless such as prices reflect earning .in order to make a statement meaningful that statements have to be tested with all ideas related to it. Researcher is testing EMH under various conditions to make meaningful. In this study, researcher is testing so called semi strong under market condition and firm size which is based upon market capitalization. National stock exchange provides classification of companies based newlineupon market capitalization. This is an event study to study stock return to earning newlineannouncements in recession and post recession periods. In other words, testing so called semi strong under market conditions and firm size of market capitalization such as large cap, mid cap and small cap. Researcher uses AARs, CAARS and T-test to study the impact of earning announcements on stock returns. Result of this study shows its onerous to accept semi strong so Fama received the Nobel prize in economics for what? -
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Exploration and Analysis of Seizure Spikes Through Spectral Domain Transformation
Seizure detection is the most crucial area of investigation when it comes to understanding brain disorders. This proposed research study embarked on an automated model for epileptic seizure diagnosis by means of different kinds of Spectral transformation using EEG inputs from seizure sufferers and healthy subjects. This automated model accommodates non-invasive brain electrical activity monitoring. This method aims to facilitate the analysis and identification of epileptic seizure states since, monitoring and diagnosing such brain electrical activity is a complex task due to its numerous divisions and underlying features. The primary objective of this research study is to distinguish between EEG-based seizures and healthy individuals. To achieve this goal, a combination of spectral transformation and EEG analysis techniques is utilized. These techniques include examining the frequency spectrum, magnitude spectrum, correlation, and T-Distributed Stochastic Neighboring Embedding (T-SNE) analysis. This analysis yields valuable insights from EEG data, refining the input data and making it more suitable for prediction and identification. The models performance is evaluated using two distinct datasets: real-time EEG data from individuals experiencing epileptic seizures and EEG data from healthy subjects. These datasets are sourced from the Bangalore EEG Epilepsy Dataset (BEED), India and the BONN epilepsy dataset from the UCI repository. In a comparative study of spectral transformation methods, including Complex Fast Fourier Transform (CFFT) and Real-Valued Fast Fourier Transform (RFFT), it is discovered that reducing the data dimension by using feature extraction is not the optimal approach. This simplification leads to the loss of valuable information. Therefore, preserving the full spectrum of EEG characteristics is crucial for gaining valuable insights into brain neuronal functions, ultimately enabling more accurate seizure prediction. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Exploration of activation energy and binary chemical reaction effects on nano Casson fluid flow with thermal and exponential space-based heat source
Purpose: The purpose of this paper is to explore the effects of binary chemical reaction and activation energy on nano Casson liquid flow past a stretched plate with non-linear radiative heat, and also, the effect of a novel exponential space-dependent heat source (ESHS) aspect along with thermal-dependent heat source (THS) effect in the analysis of heat transfer in nanofluid. Comparative analysis is carried out between the flows with linear radiative heat process and non-linear radiative heat process. Design/methodology/approach: A similarity transformation technique is utilised to access the ODEs from the governed PDEs. The manipulation of subsequent non-linear equations is carried out by a well-known numerical approach called RungeKuttaFehlberg scheme. Obtained solutions are briefly discussed with the help of graphical and tabular illustrations. Findings: The effects of various physical parameters on temperature, nanoparticles volume fraction and velocity fields within the boundary layer are discussed for two different flow situations, namely, flow with linear radiative heat and flow with non-linear radiative heat. It is found that an irregular heat source/sink (ESHS and THS) and non-linear solar radiation play a vital role in the enhancement of the temperature distributions. Originality/value: The problem is relatively original to study the effects of activation energy and binary chemical reaction along with a novel exponential space-based heat source on laminar boundary flow past a stretched plate in the presence of non-linear Rosseland radiative heat. 2019, Emerald Publishing Limited. -
Exploration of carbon nano dots in hydro carbon soot and carbon black
Hydrocarbon soot, a prime component of particulate matter pollution, poses a great threat to the environment. In this study, we put forth a novel way of harnessing carbon nanodots from the soot particulates thereby converting an environmentally perilous component to an innocuous entity suitable for many applications such as biomedical tracers, gas detectors etc. Large scale production of pure carbon nanodots (PCN) was achieved via direct catalyst free thermal decomposition of kerosene and diesel. Nanostructure of carbon black and graphite is also investigated for comparative studies. In UV-Vis spectra, absorptions at 233, 232 and 229 nm are attributed to ?-?? transition of the C=C bonding. XRD of the samples shows a highly intense peak at ?24 and a slightly broadened peak around 42 due to (002) and (010) reflections of graphitic planes respectively. In IR spectra, peaks at 3431 and 1047 cm-1 were assigned to O-H and C-O stretching vibrations respectively. The band observed at 1619 cm-1 manifests the skeletal vibrations from graphitic domains and hence indicates the presence of crystalline graphitic carbon. The absorption bands at 2920 and 2850 cm-1 arise because of the existence of aliphatic groups in the soot sample. 2017, International Congress of Chemistry and Environment. All rights reserved. -
Exploration of Chemical Reaction Effects on Entropy Generation in Heat and Mass Transfer of Magneto-Jeffery Liquid
In many chemical engineering processes, a chemical reaction between a foreign mass and the fluid does occur. These processes find relevance in polymer production, oxidation of solid materials, ceramics or glassware manufacturing, tubular reactors, food processing, and synthesis of ceramic materials. Therefore, an exploration of homogeneous first-order chemical reaction effects on heat and mass transfer along with entropy analysis of Jeffrey liquid flow towards a stretched isothermal porous sheet is performed. Fluid is conducting electrically in the company of transverse magnetic field. Variations in heat and mass transfer mechanisms are accounted in the presence of viscous dissipation, heat source/sink and cross-diffusion aspects. The partial differential equations system governing the heat transfer of Jeffery liquid is reformed to the ordinary differential system through relevant transformations. Numerical solutions based on Runge-Kutta shooting method are obtained for the subsequent nonlinear problem. A parametric exploration is conducted to reveal the tendency of the solutions. The present study reveals that the Lorentz force due to magnetism can be used as a key parameter to control the flow fields. Entropy number is larger for higher values of Deborah and Brinkman numbers. It is also established that the concentration species field and its layer thickness of the Jeffery liquid decreases for a stronger chemical reaction aspect. To comprehend the legitimacy of numerical results a comparison with the existing results is made in this exploration and alleged an admirable agreement. 2018 Walter de Gruyter GmbH, Berlin/Boston 2018. -
Exploration of low heat rejection engine characteristics powered with carbon nanotubes-added waste plastic pyrolysis oil
Compression ignition (CI)-powered alternative energy sources are currently the main focus due to the constantly rising worldwide demand for energy and the growing industrialization of the automotive sector. Due to their difficulty of disposal, non-degradable plastics contribute significantly to solid waste and pollution. The waste plastics were simply dropped into the sea, wasting no energy in the process. Attempts have been made to convert plastic waste into usable energy through recycling. Waste plastic oil (WPO) is produced by pyrolyzing waste plastic to produce a fuel that is comparable to diesel. Initially, a standard CI engine was utilized for testing with diesel and WPO20 (20% WPO+80% diesel). When compared to conventional fuel, the brake thermal efficiency (BTE) of WPO20 dropped by 3.2%, although smoke, carbon monoxide (CO), and hydrocarbon (HC) emissions were reasonably reduced. As a result, nitrogen oxide (NOx) emissions decreased while HC and CO emissions marginally increased in subsequent studies utilizing WPO20 with the addition of 5% water. When combined with WPO20 emulsion, nanoadditives have the potential to significantly cut HC and CO emissions without impacting performance. The possibility of incorporating nanoparticles into fuel to improve performance and lower NOx emissions should also be explored. In order to reduce heat loss through the coolant, prevent heat transfer into the cylinder liner, and increase combustion efficiency, the thermal barrier coating (TBC) material is also coated inside the combustion chamber surface. In this work, low heat rejection (LHR) engines powered by emulsion WPO20 containing varying percentages of carbon nanotubes (CNT) are explored. The LHR engine was operated with a combination of 10 ppm, 20 ppm, and 30 ppm CNT mixed with WPO20. It was shown that while using 20 ppm of CNT with WPO20, smoke, hydrocarbons, and carbon monoxide emissions were reduced by 11.9%, 21.8%, and 22.7%, respectively, when compared to diesel operating in normal mode. The LHR engine achieved the greatest BTE of 31.7% as a result of the improved emulsification and vaporization induced by CNT-doped WPO20. According to the study's findings, WPO20 with 20 ppm CNT is the most promising low-polluting fuel for CI engines. 2023 The Institution of Chemical Engineers -
Exploration of non-linear thermal radiation and suspended nanoparticles effects on mixed convection boundary layer flow of nanoliquids on a melting vertical surface
In this paper, the significance of increasing nonlinear thermal radiation on boundary layer flow of some nanofluids is deliberated upon. The effects of magnetic field, melting and viscous dissipation are also considered. The numerical results are obtained for governing flow equations and compared with the previously published results for a special case and found to be in excellent agreement. The effects of various physical parameters such as melting parameter, thermal radiation parameter, temperature ratio parameter and Eckert number on velocity and temperature profiles are analyzed through several plots. The numerical results of physical quantities of engineering interest such as skin friction coefficient and local Nusselt number are presented and discussed in detail. It is found that the nonlinear thermal radiation effect is favourable for heating processes than linear thermal radiation effect. Additionally, the moving parameter and melting parameter can be used to reduce the friction or drag forces. 2018 by American Scientific Publishers All rights reserved. -
Exploration of Personal Identity Among Individuals with Multiple Inter-state Migration Experiences
Migration is an increasingly common phenomenon for various reasons like economic betterment and educational purposes. Migration is also considered a life-event causing psychological distress. Individuals who migrate multiple times, are faced with a challenge of adapting to a new environment multiple times, thus having to give up and incorporate certain elements from the environment into the self, in turn altering their personal identity. This research is focused on exploring the personal identity of individuals who have undergone multiple interstate migrations within India. Life histories of 12 individuals were taken and analysed using thematic analysis. The findings indicate that there are changes in various components of personal identity like certain changes within the family, development of a multicultural perspective, certain cognitive elements like divergent thinking and development of certain personal traits like acceptance. These individuals are highly adaptable to different kinds of environments. They do not have strong attachments with peers. Keywords: personal identity, multiple interstate migrations -
Exploration of the dual fuel combustion mode on a direct injection diesel engine powered with hydrogen as gaseous fuel in port injection and diesel-diethyl ether blend as liquid fuel
The present study explores the possibilities of the use of diesel-diethyl ether (DDEE) blends as pilot fuel, and hydrogen (H2) as inducted gaseous fuel in a diesel engine operated on dual fuel mode (DFM). DEE was added to diesel in ratios of 525% in increasing steps of 5%, to prepare the DDEE5, DDEE10, DDEE15, DDEE20, and DDEE25 blends that were used as pilot fuel. In this current study, for hydrogen gas generation, a hydrogen production kit was fabricated which was powered by solar energy. The hydrogen gas was produced from the electrolysis of water-KOH solution. During the experiment, hydrogen was inducted through the engine intake port employing an electronic gas injector. The quantity of hydrogen injection was set constant of 0.2 lpm for all the test cases. DDEE-hydrogen (DDEE+H2) blends accomplished overall good results compared to diesel. DDEE20+H2 furnished optimal results compared to diesel and other DDEE+H2 blends. Peak cylinder pressure for DDEE20+H2 was 66.91 bar at 5.2oCA aTDC, and the maximum HRR was 32.75 J/deg.CA. Compared to diesel, the BTE of engine for DDEE20+H2 was augmented by about 0.6% and the BSFC was diminished by about 3.7%, at maximum load conditions. A decline in CO and HC emissions of 29.6%, and 35% were observed for DDEE20+H2 at maximum load condition, but the NO and CO2 emanation was observed to be higher by around 29.4%, and 17.4% in comparison to diesel respectively. 2023 Hydrogen Energy Publications LLC -
Exploration of the effects of anisotropy and rotation on RayleighBard convection of nanoliquid-saturated porous medium using general boundary conditions
This paper presents an analysis of RayleighBard convection (RBC) of a Newtonian-nanoliquid-saturated anisotropic porous medium in the presence of rotation (RayleighBardTaylor convection). The investigation is performed using non-classical boundary conditions. The effect of various parameters on the onset of convection is presented graphically. The system sees stabilisation due to an increase in the rotation rate and thermal anisotropy parameter whereas the system destabilises due to an increase in the mechanical anisotropy parameter. The results of 82 limiting cases can be extracted from the current work. The results of free-free, rigid-free and rigid-rigid isothermal/adiabatic boundaries are obtained from the present study by considering appropriate limits. The results of the limiting cases of the present study are in excellent agreement with those observed in earlier investigations. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Exploration of Thermophoresis and Brownian motion effect on the bio-convective flow of Newtonian fluid conveying tiny particles: Aspects of multi-layer model
This research deals with the analysis of bioconvection caused by the movement of gyrotactic microorganisms. The multi-layer immiscible Newtonian fluid flowing through the vertical channel conveying tiny particles is accounted. The immiscible fluids are arranged in the form of a sandwich where the middle layer has a different base fluid that does not mix with the base fluid of the adjacent fluid layer. This separation of the fluid layers gives rise to the interface boundary conditions. Such flows have found applications in electronic cooling and solar reactors processes. Buongiornos model has been incorporated to design the mathematical model that describes the three-layer flows of Newtonian fluid conveying tiny (metal/oxide) particles under thermophoretic force and Brownian motion. The model thus formed is in the form of the ordinary differential system of equations that are solved using the DTM-Pade approximant after non-dimensionalization. The limited results have an excellent comparison with the existing literature results. The results are discussed through graphs and tables. It is seen that thermophoresis enhances the temperature and particle concentration of the fluid whereas, the Brownian motion is found to enhance the temperature and decrease the concentration. The presence of bioconvection helps in achieving enhanced energy and mass transportation. Moreover, the heat transfer occurring between the different base fluids helps to maintain the optimum temperature in the systems. IMechE 2022.