Browse Items (14421 total)
Sort by:
-
Comparative Study of AI Models for Automated Tuberculosis Detection Using Image Processing Techniques
Tuberculosis is a critical global health issue, particularly in resource-limited regions where early and accurate diagnosis is important and is in need so that the treatment is effective and the control transmission is controlled. The known diagnostic methods, such as sputum smear microscopy and nucleic acid amplification tests are costly, time-consuming, and require trained professionals. Due this in some cases it is inaccessible in many regions. Deep learning-based automated TB detection offers a promising alternative by enhancing diagnostic efficiency through medical imaging analysis. This study presents a comparative evaluation of five deep learning models, InceptionResNetV2, DenseNet, VGG16, ANN, and a custom CNN, trained on a dataset of 3,008 chest radiograph images, evenly distributed between TB-positive and normal cases. The dataset underwent advanced preprocessing techniques, pixel normalization, and data augmentation. The hyperparameter tuning process was applied, which optimized the learning rates, dropout rates, convolutional filter sizes, and batch sizes to enhance model performance. The models were assessed using accuracy, precision, recall, F1-score, sensitivity, specificity.. Experimental results indicated that the custom CNN achieved the highest classification accuracy (99.51). The superior performance of the custom CNN over other models is attributed to optimized feature extraction, effective preprocessing, and structured hyperparameter tuning. A comparative analysis with previous studies highlights how this approach mitigates dataset limitations and improves model interpretability, and the potential of AI-driven TB detection, enhancing future diagnostic efficiency by improving model generalizability and deployment in real-world healthcare settings. 2025 IEEE. -
Comparative study of benchmarking models for higher education institutions
Benchmarking is a systematic and ongoing process of assessing an organisations business processes against those of business process leaders to obtain data that will enable the firm to take corrective action to enhance performance (Pattison, 1993). Eight benchmarking models, namely the European Foundation for Quality Management (EFQM) excellence model, American Productivity and Quality Centre (APQC) consortium framework, Commonwealth Higher Education Management Service (CHEMS) model, Mckinnon model, Henderson-Smart et al. model, educational development efficiency (EDE) model, Tee benchmarking model, and fourth generation balanced scorecard method are being studied, analysed, evaluated and compared. While most models effectiveness depends on the cooperation and participation of benchmarking partners, few depends on secondary data are an exception. Most benchmarking models lack the implementation and are fluid and flexible models. This comparative benchmarking study helps an institution understand which benchmarking model needs to be used, as the study details each models essential features, advantages, and limitations. Copyright 2025 Inderscience Enterprises Ltd. -
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 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 of Wi-Fi 6 and 5G for Residential Internet Services
Whereas Wi-Fi 6 and 5G briefly competed in the home internet space, 5G has since outpaced Wi-Fi 6 in speed and reliability. Wi-Fi 6 and 5G have detailed white papers outlining their protocols and specs. Initial home use and advanced Wi-Fi use should prioritize downloading, as Wi-Fi 6 offers a significant edge in download speed, latency, and efficiency in multi-device environments (most homes have a home intelligence system, phones, and PCs). 5G has no physical PC connection and must be provisioned by a carrier and covered by a cell tower. Hence, its advantages are for rural users and for users who typically work from home. Each has specific target markets, with the home as the primary focus, including streaming media and gaming, multiple smart home devices, and a home office. Install speed and cost, system-wide latency (total system, including devices), data retention and privacy, device lock (data retention), and scaling (to be sound). 5G uses cell towers with a large and covered geographic area and no physical restrictions. Each has target markets where advanced Wi-Fi has outpaced rural users and mobile users. This is where Wi-Fi has outpaced 5G (5G is a better solution for streaming, data retention, and scaling). Findings indicate that Wi-Fi 6 is excellent in environments with high-speed broadband. At the same time, 5G demonstrates its advantages in areas with low-quality broadband or when users require mobile Internet access. Because both technologies offer unique benefits, combining them may yield the best home connectivity. The document enables buyers, Internet Service Providers (ISPs), and community decision-makers to choose cutting-edge internet connectivity options. 2025, Innovative Information Science and Technology Research Group. All rights reserved. -
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. -
Comparing keyframe extraction for video summarization in CPU and GPU
Most of the information is captured through multimedia techniques. Videos contain many frames which might be redundant. Since processing of many frames is involved, these redundant frames must be removed for better and efficient results. Summarizing these frames by removing similar frames can speed up processing. In this paper video summarization is achieved by generating key frames. Key frames are generated using discrete wavelet transforms (DWT) technique and we subtract background from the keyframes to get region of interest. A video of 920&Times;720 resolution and length 120 second was used as test video and the run-time was 111 second in CPU and 60 second in GPU. The speed up is nearly 100%. A HD video which took 23 minutes in serial implementation to extract foreground object from key frames generated was reduced to 7 minutes using GPU acceleration. 2015 IEEE. -
Comparing machine learning and ensemble learning in the field of football
Football has been one of the most popular and loved sports since its birth on November 6th, 1869. The main reason for this is because it is highly unpredictable in nature. Predicting football matches results seems like the perfect problem for machine learning models. But there are various caveats such as picking the right features from an enormous number of available features. There have been many models which have been applied to various football-related datasets. This paper aims to compare Support Vector Machines a machine learning model and XGBoost an Ensemble learning model and how Ensemble Learning can greatly improve the accuracy of the predictions. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved. -
Comparing maritime piracy along the coasts of Africa: In search of a solution for the Gulf of Guinea
Merchant ships at sea have been under threat for centuries from criminal activities such as maritime piracy and armed robbery. Such acts have seen a rise in recent years, with new breeding grounds mushrooming across the globe. In Africa, such criminal activities are as old as maritime trade, with three severely affected regions, each with its own dynamics. While piracy on the eastern coast (Gulf of Aden) has been brought under control by international maritime forces and that on the south-eastern coast (Mozambique Channel) by local maritime forces, piracy on the western side (Gulf of Guinea) continues unabated and has become a matter of concern for the world's maritime fraternity. In an effort to find a solution for piracy in the Gulf of Guinea, this article aims to compare and analyse incidents of piracy along the coasts of Africa and understand whether the countermeasures adopted on the eastern coasts can be replicated on the western one. 2020 National Maritime Foundation. -
Comparing Strategies for Post-Hoc Explanations in Machine Learning Models
Most of the machine learning models act as black boxes, and hence, the need for interpreting them is rising. There are multiple approaches to understand the outcomes of a model. But in order to be able to trust the interpretations, there is a need to have a closer look at these approaches. This project compared three such frameworksELI5, LIME and SHAP. ELI5 and LIME follow the same approach toward interpreting the outcomes of machine learning algorithms by building an explainable model in the vicinity of the datapoint that needs to be explained, whereas SHAP works with Shapley values, a game theory approach toward assigning feature attribution. LIME outputs an R-squared value along with its feature attribution reports which help in quantifying the trust one must have in those interpretations. The R-squared value for surrogate models within different machine learning models varies. SHAP trades-off accuracy with time (theoretically). Assigning SHAP values to features is a time and computationally consuming task, and hence, it might require sampling beforehand. SHAP triumphs over LIME with respect to optimization of different kinds of machine learning models as it has explainers for different types of machine learning models, and LIME has one generic explainer for all model types. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.