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Comparative optimization studies (Isp 4 vs isp 3 vs isp 2 media) of mangrovian streptomyces pluripotens anukcjv1 for its ?-amylase production and geographical correlation of mangrovian actinomycetes strains
Streptomyces pluripotens ANUKCJV1 was isolated from Coringa Mangroves which was located along the South Indian Delta. The Current work which was in continuation to our previously reported work which suggests that Streptomyces pluripotens ANUKCJV1 was the potential strain and the same has been subjected to comparative optimization studies in the current work by employing three media: ISP 4; ISP 3; ISP 2 media for enhanced ?-Amylase Production. Physico-Chemical variables viz Incubation period, PH, Temperature, Carbon and Nitrogen sources with respect to three different media (ISP 4, ISP 3 and ISP 2) were tested and cumulative analysis of three different media for differential bioactivity of ?-Amylase was done. Results suggest that ISP 4 found to be the best medium with cumulative value of 24.2 U/mL, where as the cumulative value of ISP 3 and ISP 2 were 19.3 U/mL and 19.4 U/mL respectively. Peptone as Nitrogen source of ISP 4 found to be the favourite Individual variable among all with production value of 8.0 U/mL. Geographical correlation with respect to number of Actinomycetes strains and ?-Amylase Bioactivity depicts that Distant geographical soil samples from the shore found to be favourable for higher number of Actinomycetes strains: A1 soil samples (~ 500 m)-33 %; A2 samples (~ 400 m)-22 %. With regard to ?-Amylase Bioactivity, A5 samples (~ 100 m) analysed to be the potential geographical bioactive zone for ?-Amylase Production. From the study it can be concluded that since ISP 4 found to be the favourite medium of the potential strain, by employing the same large scale exploration of the Streptomyces pluripotens ANUKCJV1 of the Coringa Mangroves may be done to tap the industrial benefits of ?-Amylase. EM International. -
Comparative Performance Analysis of Deep Learning Models in Cervical Cancer Detection
Cervical cancer one of the four most common malignancies worldwide and poses a significant threat, particularly in resource-constrained regions. Automated diagnostic approaches, leveraging colposcope image analysis, hold great promise in curbing the impact of this disease. In this paper, we deploy a range of deep learning methods, including DenseNet 121, ResNet 50, AlexNet and VGG 16 to classify the cervical intraepithelial neoplasia. Our methodology is deployed on a dataset sourced from a Cancer Research institute in India. The current experiment aims to establish the execution of the state-of-the-art pretrained frameworks in deep learning. This will be a baseline experiment for researcher who aim to develop further deep learning models for cervical cancer diagnosis. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Comparative Performance Analysis of Machine Learning and Deep Learning Techniques in Pneumonia Detection: A Study
Pneumonia is a bacterial or viral infection that inflames the air sacs in one or both lungs. It is a severe life-threatening disease, making it increasingly necessary to develop accurate and reliable artificial intelligence diagnosis models and take early action. This paper evaluates and compares various Machine Learning and Deep Learning models for pneumonia detection using chest X-rays. Six machine learning models -Logistic Regression, KNN, Decision Tree, Random Forest, Naive Bayes, and Support Vector Machines - and three deep learning models - CNN, VGG16, and ResNet - were created and compared with each other. The results exhibit how just the model choice can significantly affect the quality and inerrancy of the final diagnostic tool. 2023 IEEE. -
Comparative Performance of LSTM and ARIMA for the Short-Term Prediction of Bitcoin Prices
This research assesses the prediction of Bitcoin prices using the autoregressive integrated moving average (ARIMA) and long-short-term memory (LSTM) models. We forecast the price of Bitcoin for the following day using the static forecast method, with and without re-estimating the forecast model at each step. We take two different training and test samples into consideration for the cross-validation of forecast findings. In the first training sample, ARIMA outperforms LSTM, but in the second training sample, LSTM exceeds ARIMA. Additionally, in the two test-sample forecast periods, LSTM with model re-estimation at each step surpasses ARIMA. Comparing LSTM to ARIMA, the forecasts were much closer to the actual historical prices. As opposed to ARIMA, which could only track the trend of Bitcoin prices, the LSTM model was able to predict both the direction and the value during the specified time period. This research exhibits LSTM's persistent capacity for fluctuating Bitcoin price prediction despite the sophistication of ARIMA. 2023, University of Wollongong. All rights reserved. -
Comparative Study Analysis on News Articles Categorization using LSA and NMF Approaches
Due to exponentially growing news articles every day, most of their important data goes unnoticed. It is important to come up with the ability to automatically analyse these articles and segregate them based on the context and related to their particular domain. This paper applies topic modelling which is one of the most growing unsupervised machine learning fields on a million headlines articles in order to produce topics to describe the context of the news article. There are various generative models but we specifically focusing on the non-negative matrix factorization (NMF) and Latent Semantic Analysis (LSA) for implementing and evaluating news dataset. Furthermore, the findings reveal that both NMF and LSA are useful topic modelling tools and classification frameworks, but based on the experimental results the LSA model performed well to identify the hidden data with better mean coherence values and also consumes lesser execution time than NMF. 2022 IEEE. -
Comparative study of Breakdown Phenomena and Viscosity in Liquid Dielectrics
Liquid dielectrics are extensively used in electrical apparatus which are operating in distribution and transmission systems. The function of electrical equipment strongly depends on the conditions of liquid dielectric. Liquid dielectrics used are the most expensive components in power system apparatus like transformers and circuit breakers. A failure of these equipment would causes a heavy loss to the electrical industry and also utilities. Insulation failures are the leading cause of transformer failures and thus the liquid dielectrics plays a major role in the safe operation of transformers. One of the main causes for the failure of transformers is due to the presence of moisture. In this work, the life of insulating medium is estimated by comparing the Breakdown strength and Viscosity of different pure oils with that of the contaminated oils (which contains moisture) and also finding the alternative for mineral oil. vegetable oils which are reliable, cost-effective and environmental friendly even when they are contaminated. 2019 IEEE. -
Comparative Study of Graph Theory for Network System
The historical background of how graph theory emerged into world and gradually gained importance in different fields of study is very well stated in many books and articles. Some of the most important applications of graph theory can be seen in the field network theory. Its significance can be seen in some of the complex network systems in the field of biological system, ecological system, social systems as well as technological systems. In this paper, the basic concepts of graph theory in terms of network theory have been provided. The various network models like star network model, ring network model, and mesh network model have been presented along with their graphical representation. We have tried to establish the link between the models with the existing concepts in graph theory. Also, many application-based examples that links graph theory with network theory have been looked upon. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Comparative study of phytoremediation of chromium contaminated soil by Amaranthus viridis in the presence of different chelating agents
Chromium is a harmful heavy metal to the environment due to the toxicity induced by it to plants and other living organisms. High concentration of Cr in soil poses severe toxicological problems ecosystem. Phytoremediation using different plants is an economical and environment-friendly method for removing Cr from soil. The addition of chelating agents augments the phytoex-traction using plants.The present study aimed to augment the Cr phytoremediation capacity of Amaranthus virdis, a predomi-nant plant species in the Cr-contaminated open dumpsites of Bangalore.. Phytoextraction of Cr by Amaranthus viridis was studied in the presence of different chelating agents viz. ethylenediaminetetraacetic acid (EDTA), citric acid (CA), growth pro-moting hormone-indoleacetic acid (IAA) and NPK fertiliser. A. viridis grown under different concentrations (5, 10 and 20 mg/Kg) of Cr were treated with 0.5g EDTA/Kg of soil, 0.5g CA/Kg of soil, 1mg IAA/Kg of soil and NPK (125 mg of nitrogen, 45 mg of phosphorous and 156 mg of potassium per Kg of soil). Results indicated that CA, at 10 mg/kg Cr supply, induced the highest uptake (up to 29.25 g/plant). Furthermore, the study revealed that CA amendment induced maximum Cr uptake in A. viridis at all levels of Cr supply as compared to other amendments. This was due to the increased solubility of Cr in the presence of citric acid and the amelioration of oxidative stress due to Cr to plants by citric acid. This study inferred that the non-hyperaccumulating plant, A. virdis could be used as a phytoremediator for Cr in the presence of citric acid in the places where it is grown abundantly. Author (s). Publishing rights @ ANSF. -
Comparative Study of Product Liability and Data Confidentiality in Case of Intermediaries with Special Reference to India and The European Union
Technology has played a major role in human development. The advent and invention of wheel and fire changed the coverage of human society. On a similar note in 90 s a technology called internet was developed and it changed all rules of the game. This technology removed all hindrances of place and time. It created faceless market place wherein; consumer not only have huge choices and varieties but also, they can create goods and services on their own. This was the origin of Electronic Business and it gave birth to new breed of middleman / intermediaries to facilitate it. These intermediaries are application provider, ISP, network service provider etc. The mantras of success were wide choices and data. But this mantra created a new legal challenge of data handling and liability for defects in goods and services. Researcher has studied and analysed all dimensions of intermediaries newlineand how they handled the two new legal challenge of data confidentiality and newlineproduct liability. In addition, researcher has examined the legal framework of India and compared it with legal framework of European Union and finally concluded on the coverage and effectiveness of Indian legal structure and what India learn and implement from European Union. This thesis mainly focusing on generic business model used by intermediaries. Issues like IPR, industry specific domain like financial systems and medical domain are excluded. Researcher followed the doctrinal research methodology to understand the evolution of intermediaries, product liability, data confidentiality in India by various primary resources like the Indian Laws i.e., Consumer newlineProtection Act, 2019, Indian Contract Act, 1872, Information Technology Act, 2000 and other various statutes. This thesis compares Indian legal framework with European Union and test the hypothesis of coverage and effectiveness of Indian legal structure with European Union. -
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Comparative study of recommender systems
Recommendation System is a quickly progressing study area. Many new approaches are offered so far. In this particular paper we have researched on various applications of recommender system and various techniques used in recommender system like collaborative filtering, content-based filtering and hybrid filtering. Collaborative filtering is amongst the common methods utilized in recommending process. So comparative study on various collaborative filtering is done and the results are plotted graphically. 2016 IEEE. -
Comparative study of sinusoidal and non-sinusoidal two-frequency internal heat modulation in a Rayleigh-Bard system
A linear stability analysis is assented to investigate the effect of two-frequency internal heat modulation at the onset of convection in a Newtonian liquid. The correction Rayleigh number and wave number for small amplitudes is calculated using the Venezian approach. Under two-frequency internal heat modulation, the motion is found to be subcritical. To quantify heat transfer in the system, the three-mode Lorenz model is solved numerically. Various combinations of sinusoidal and non-sinusoidal waveforms influence the onset of convection and heat transfer in the system due to two-frequency internal heat modulation. The parameters' influence on heat transfer is seen to be dependent on the presence of a heat source or sink. 2021 Wiley Periodicals LLC. -
Comparative study of soil properties and vegetation at various open dump and non-dumpsites in the Bengaluru city of Karnataka, India
A comparative field studies on seven municipal dumpsites namely Agara 1 (12.917N, 77.639E), Agara 2 (12.922N, 77.639E), HSR depot (12.919N, 77.644E), Koraman-gala Church (12.934N, 77.626E), Koramanagla BDA (12.931N, 77.625E), Garvebhayipalya (12.897N, 77.638E) and Sanjay Gandhi hospital (12.891N, 77.601 E), and its adjoining non-dump sites were conducted to understand their soil characteristic features and the vegetation pattern. Soil characteristics were presented in terms of the physicochemical parameters and the vegetation patterns were presented in terms of the dominance using the ecological parameter Important Value Index (IVI). Soils at the dump sites showed higher mean electrical conductivity and pH values as compared to the non-dump sites. Though the mineral content showed higher mean value in the dump sites (except chloride), there is no significant variation in the higher total soluble solutes between dump and non-dump sites(P>0.05) As per ANNOVA there was highly significant variation in the heavy metal content between dump and non dumpsites (P<0.01).. With respect to vegetation analysis though 50 different species found across locations only 10 species viz Alternatheria sessile, Amaranthus spinose, Caesalpinia pulcherima, Ipomea acumilanata, Ipomea evolvulus, Parthenium hysterophorous Pisum sativum, Ricinis communis, Sida rombifolia and Solanum lycopersicum were found consistent across all locations irrespective of the seasons. Among these, A. sessile, R. communis and A. spinosa were found dominant based on the IVI values across seven locations which further can be studied for their potential for phyto remediating the land pollutants such as heavy metals. 2019, Applied and Natural Science Foundation. All rights reserved. -
Comparative study of various metals in the sewage samples of three major drains of the city-Patna, Bihar, India /
Mapana Journal Of Science, Vol.16, Issue 4, pp.23-35, ISSN: 0975-3303. -
Comparative Study on GANs and VAEs in Credit Card Fraud Detection
In today's world, the major issue credit card sectors encounter is fraud. This comparative study deals with how GANs and VAEs detect fraudulent transactions. The dataset comprised 284807 transactions, of which 492 were fraudulent. These two models, GANs and VAEs, are trained on this dataset, during which, in the training process, the models are learned to deal with the imbalance in the dataset. VAEs are trained so that fraud transactions are considered anomalies, and only legitimate transactions are passed onto the model for training. Conversely, GANs generate synthetic data of fraud by addressing the problem of data imbalance and passed on to the ML model for classification. We can observe that Both the models have very good AUC-ROC scores of around 96%, which indicates their distinguishing capability between the classes. In all other aspects, GANs outperformed VAEs, which makes GANs a better option for fraud detection. 2024 IEEE. -
Comparative Study on Gasoline and Methanol in a Twin Spark IC Engine
In search of a viable alternative to petrol and diesel, methanol, ethanol and biodiesel play an important role. Methanol and ethanol are traditional alternatives to petrol(gasoline) because of better engine performance and reduced emission of carbon monoxide, oxides of nitrogen (NOx), unburnt hydrocarbon (UBHC) and other harmful gases. This work represents the result of four sets of spark timings on engine performance and engine emissions when run on methanol and petrol. Exhaustive investigations are carried out on a variable compression ratio DTSi engine for both methanol and gasoline. Engine was run at full throttle and at a constant speed of 1600RPM. Theefficiency of the engine found to be enhanced with methanol fuel which has higher octane number and high laminar flame speed. Maximum efficiency was found to be ~25.45% and ~28.7% at compression ratio 10 for gasoline and methanol fuel, respectively. This is observed at 2624 BTDC (before top dead center) spark advance combination. Optimum compression ratio for gasoline and methanol is found to be 6.8 and 7.4, respectively, at this spark advance angle combination. Moreover, methanol fuel eventually emits lesser amount of CO, UBHC and NOx than gasoline under all experimental combinations. 2021, Springer Nature Singapore Pte Ltd. -
Comparative Study on Load Balancing Techniques in Distributed Systems
International Journal of Information Technology and Knowledge Management, Vol-6 (1), pp. 53-60. ISSN-0973-4414 -
Comparative Study on the Experimental Results on Low-Velocity Impact Characteristics of GLARE Laminates with Simulation Results from LS Dyna
Fiber reinforcement with metallic face sheets is one of the recently implemented materials for distinctive applications in automotive and aerospace sectors. While the reinforcement enhances the sustenance property of the laminate, the face sheets provide resistance to impact force. In most automotive sectors, drop weight analysis at varying velocity ranges is performed to evaluate the damage characteristics of the vehicle body. The present work is aimed at studying the influence of low-velocity impact (LVI) on Glass Laminate Aluminum-Reinforced Epoxy (GLARE) laminate. Three distinct thicknesses of Al-2024 T3 aluminum alloy (0.2, 0.3 and 0.4mm) were chosen as the face sheet and E-glass fiber was used as intermediate layers. Epoxy resin LY556 with a HY951 hardener was used to fabricate the GLARE structure and the overall thickness was maintained at 2.0mm for all the cases. Energy absorbed by GLARE laminates for different energy was determined using Drop weight Impact test experimentally and analytically. The laminate and the dart were modeled by ANSYS ACP tool and the simulation was performed using LS Dyna software. It was evident that laminate can sustain impact at a velocity of 3.13m/s and beyond which leads to surface delamination. The simulation results were in close agreement with the experimental values for the absorbed energy, with less than 10% error. 2022, The Institution of Engineers (India). -
Comparing Developmental Approaches for Game-Based Learning in Cyber-Security Campaigns
Digital game-based learning (DGBL) has been viewed as an effective teaching strategy that encourages students to pick up and learn a subject. This paper explores its viability to help increase the reach and efficiency of the existing cybersecurity awareness spreading campaigns that find adolescent students as their demographic. This work intends to reinforce the benefits of multimedia learning in schools and universities with the use of video games and further find the ideal type and genre of game that can be developed to spread awareness about cybersecurity to students in grades 8th to 12th (tailored towards the Indian context). Game genres were compared on the basis of having a simple gameplay loop, being easy for instructors to train themselves in, being inclusive to special needs children, being able to be published as an independent title, and having very low hardware specification requirements. Ideally, the paper proposes that this game would be a single-player experience that would follow a game-based learning approach to maximize the game's reach. Once identified, the model of the game was assessed using already existing implementations. Finally, the ideal model, a single-player visual novel is proposed. A future iteration of the paper will implement the proposed model of game design and perform an analysis of the effects the video game had on the learning experience of the students surveyed. 2023 IEEE. -
Comparing Influence of Depression and Negative Affect on Decision Making
The current study aimed to explore differential value-based decision-making patterns across three groupsindividuals diagnosed with mild-to-moderate depression, a healthy matched control group, and a negative mood induction group. In the current study, drug- and therapy-nae individuals diagnosed with first episode of mild-to-moderate depression (n = 40), healthy individuals matched on age, gender, and education (n = 40), and healthy individuals with no current, past, or family history of any psychiatric conditions in a negative mood-induced state (n = 40) were administered the IOWA Gambling Task (IGT) and the Balloon Analog Risk Task (BART). Results indicated that individuals with depression showed heightened punishment sensitivity on both the IGT and the BART (p < 0.05 on the BART and p < 0.05 on the IGT), andperformed poorly on the IGT indicating poor and slow learning (p < 0.01). A similar, less severe, pattern was observed in the negative mood induction group. Individuals with mild-to-moderate depression performed poorly on tasks of value-based decision making. The significance of process factors in decision making, such as reward and punishment sensitivity, valuation of outcomes and learning, was highlighted in this study. The study also demonstrated how a negative affective state, without the other clusters of depressive symptomatology, can also lead to a less severe, but impaired decision making. 2023, The Author(s) under exclusive licence to National Academy of Psychology (NAOP) India.