Refine your search
Co-Authors
Journals
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Gowri, S.
- Automated Nano-Technology Based Particulate Filters to a Clean Environment in Rooms of Biomedical Applications
Abstract Views :258 |
PDF Views:0
Authors
Affiliations
1 Department of Biomedical Instrumentation Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, IN
1 Department of Biomedical Instrumentation Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, IN
Source
ICTACT Journal on Microelectronics, Vol 7, No 3 (2021), Pagination: 1189-1192Abstract
The products or the process of production are highly sensitive to contamination on the environment. In this regard, manufacturing of semiconductors and their related application plays a major cause. The airborne concentration of particulates like chemical vapours or dust compounds can be found even an enclosed environment. This accounts for pollution in clean rooms for the purpose of biomedical applications. These rooms should be monitored highly and should be protected from harmful substances and contamination risks. In this paper, we clean the air that is entering the room that is filtered with nano-particle based filters to eliminate the dust. The air is recirculated via nano-particulate high efficiency particulate air filter. These filters connected with nano-materials absorbs the contaminants. The implantable particulate filters are the edges of the room enables a clean environment. The experimental testing is conducted using several nano-filters that is connected with power design circuits to automatically control the entire environment. The results achieved show that the presence of microbials in the room is cleaned effectively.Keywords
Airborne Particulates, Pollution, Nano-Particle Filters, Clean Environment.
References
- Kalpana, V. N., & Devi Rajeswari, V. (2018). A review on green synthesis, biomedical applications, and toxicity studies of ZnO NPs. Bioinorganic chemistry and applications, 2018.
- Teaima, M. H., Abdelnaby, F. A., Fadel, M., El-Nabarawi, M. A., & Shoueir, K. R. (2020). Synthesis of Biocompatible and Environmentally Nanofibrous Mats Loaded with Moxifloxacin as a Model Drug for Biomedical Applications. Pharmaceutics, 12(11), 1029.
- Arif, U., Haider, S., Haider, A., Khan, N., Alghyamah, A. A., Jamila, N., ... & Kang, I. K. (2019). Biocompatible polymers and their potential biomedical applications: A review. Current pharmaceutical design, 25(34), 3608-3619.
- Rastogi, S., Sharma, G., & Kandasubramanian, B. (2020). Nanomaterials and the Environment. The ELSI Handbook of Nanotechnology: Risk, Safety, ELSI and Commercialization, 1-23.
- Jiang, F., Yan, D., Lin, J., Kong, H., & Yao, Q. (2021). Implantation of multiscale silk fibers on poly (lactic acid) fibrous membrane for biomedical applications. Materials Today Chemistry, 21, 100494.
- Song, W., Wang, Y., Wang, B., Yao, Y., Wang, W., Wu, J., ... & Zou, Z. (2020). Super stable CsPbBr3@ SiO2 tumor imaging reagent by stress-response encapsulation. Nano Research, 13(3), 795-801.
- Sajjadi, M., Ahmadpoor, F., Nasrollahzadeh, M., & Ghafuri, H. (2021). Lignin-derived (nano) materials for environmental pollution remediation: Current challenges and future perspectives. International Journal of Biological Macromolecules.
- Liu, Z., Liu, Y., Shen, S., & Wu, D. (2018). Progress of recyclable magnetic particles for biomedical applications. Journal of Materials Chemistry B, 6(3), 366-380.
- Fu, X., Cai, J., Zhang, X., Li, W. D., Ge, H., & Hu, Y. (2018). Top-down fabrication of shape-controlled, monodisperse nanoparticles for biomedical applications. Advanced drug delivery reviews, 132, 169-187.
- Afsheen, S., Tahir, M. B., Iqbal, T., Liaqat, A., & Abrar, M. (2018). Green synthesis and characterization of novel iron particles by using different extracts. Journal of Alloys and Compounds, 732, 935-944.
- Gundo, S., Parauha, Y. R., Singh, N., & Dhoble, S. J. (2021, May). Eco-friendly synthesis route of silver nanoparticle: A review. In Journal of Physics: Conference Series (Vol. 1913, No. 1, p. 012052). IOP Publishing.
- Sakthivel, M., Franklin, D. S., Sudarsan, S., Chitra, G., Sridharan, T. B., & Guhanathan, S. (2019). Gold nanoparticles embedded itaconic acid-based hydrogels. SN Applied Sciences, 1(2), 146.
- Raipuria, V., Rani, N., Sharma, V. P., & Naiya, T. K. (2018). Use of nanoparticle derived from natural source and its application in drilling fluid. International Journal of Oil, Gas and Coal Technology, 19(3), 283-295.
- Demissie, M. G., Sabir, F. K., Edossa, G. D., & Gonfa, B. A. (2020). Synthesis of zinc oxide nanoparticles using leaf extract of lippia adoensis (koseret) and evaluation of its antibacterial activity. Journal of Chemistry, 2020.
- Osman, E. (2020). Nanofinished Medical Textiles and Their Potential Impact to Health and Environment. Nanoparticles and Their Biomedical Applications; Springer: Singapore, 127-145.
- An Improved Classification Of MR Images For Cervical Cancer Using Convolutional Neural Networks
Abstract Views :181 |
PDF Views:0
Authors
Affiliations
1 Department of Biomedical Instrumentation Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, IN
1 Department of Biomedical Instrumentation Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, IN
Source
ICTACT Journal on Image and Video Processing, Vol 12, No 2 (2021), Pagination: 2605-2609Abstract
Cervical cancer is the biggest cause of death in the field of women gynaecology. Patient treatment outcomes are influenced by the stage and nodal status of their cancers as well as their tumour size and histological classes. In this paper, we develop a classification model using a state-of-art heuristic mechanism that enables the use of deep learning algorithm to classify the MRI image from the input cervical images. The classification is conducted with highly dense network that helps to reduce the errors during the testing process. The simulation is conducted in matlab to test the efficacy of the model and the results of simulation shows that the proposed method achieves higher grade of classification accuracy than the other existing methods.Keywords
Classification, MR Image, Cervical Cancer, CNNReferences
- A. Ghoneim, G. Muhammad and H.S. Hossain, “Cervical Cancer Classification using Convolutional Neural Networks and Extreme Learning Machines”, Future Generation Computer Systems, Vol. 102, pp. 643-649, 2020.
- S. Karthick, P.A. Rajakumari and R.A. Raja, “Ensemble Similarity Clustering Frame work for Categorical Dataset Clustering using Swarm Intelligence”, Proceedings of International Conference on Intelligent Computing and Applications, pp. 549-557, 2021.
- N.V. Kousik and M. Saravanan, “A Review of Various Reversible Embedding Mechanisms”, International Journal of Intelligence and Sustainable Computing, Vol. 1, No. 3, pp. 233-266, 2021.
- A. Khadidos, A.O. Khadidos, S. Kannan and G. Tsaramirsis, “Analysis of COVID-19 Infections on a CT Image using Deep Sense Model”, Frontiers in Public Health, Vol. 8, pp. 1-20, 2020.
- X. Tan, K. Li, J. Zhang and W. Wang, “Automatic Model for Cervical Cancer Screening based on Convolutional Neural Network: A Retrospective, Multicohort, Multicenter Study”, Cancer Cell International, Vol. 21, No. 1, pp. 1-10, 2021.
- V. Maheshwari, M.R. Mahmood and S. Sravanthi, “Nanotechnology-Based Sensitive Biosensors for COVID-19 Prediction using Fuzzy Logic Control”, Journal of Nanomaterials, Vol. 2021, pp. 1-13, 2021.
- S.B. Sangeetha, R. Sabitha and B. Dhiyanesh, “Resource Management Framework using Deep Neural Networks in Multi-Cloud Environment”, Proceedings of International Conference on Operationalizing Multi-Cloud Environments, pp. 89-104, 2021.
- N. Bnouni, H.B. Amor and I. Rekik, “Boosting CNN Learning by Ensemble Image Preprocessing Methods for Cervical Cancer Segmentation”, Proceedings of 18th International Multi-Conference on Systems, Signals and Devices, pp. 264-269, 2021.
- T. Haryanto, I.S. Sitanggang, M.A. Agmalaro and R. Rulaningtyas, “The Utilization of Padding Scheme on Convolutional Neural Network for Cervical Cell Images Classification”, Proceedings of International Conference on Computer Engineering, Network, and Intelligent Multimedia, pp. 34-38, 2020.
- Y. Xiang, W. Sun, C. Pan and M. Yan, “A Novel Automation-Assisted Cervical Cancer Reading Method based on Convolutional Neural Network”, Biocybernetics and Biomedical Engineering, Vol. 40, No. 2, pp. 611-623, 2020.
- H. Akbar, N. Anwar, S. Rohajawati and A. Yulfitri, “Optimizing AlexNet using Swarm Intelligence for Cervical Cancer Classification”, Proceedings of International Symposium on Electronics and Smart Devices, pp. 1-6, 2021.
- K. Deepa, “A Journal on Cervical Cancer Prediction using Artificial Neural Networks”, Turkish Journal of Computer and Mathematics Education, Vol. 12, No. 2, pp. 1085-1091, 2021.
- L. Cao, J. Yang and Z. Rong, “A Novel Attention-Guided Convolutional Network for the Detection of Abnormal Cervical Cells in Cervical Cancer Screening”, Medical Image Analysis, Vol. 73, pp. 102197-102210, 2021.
- S. Murugan, C. Venkatesan, M.G. Sumithra and S. Manoharan, “DEMNET: A Deep Learning Model for Early Diagnosis of Alzheimer Diseases and Dementia from MR Images”, IEEE Access, Vol. 9, pp. 90319-90329, 2021.
- N. Dong, L. Zhao and C.H. Wu, “Inception V3 based Cervical Cell Classification Combined with Artificially Extracted Features”, Applied Soft Computing, Vol. 93, pp. 106311-106319, 2020.
- G. Liang, H. Hong and W. Zheng, “Combining Convolutional Neural Network with Recursive Neural Network for Blood Cell Image Classification”, IEEE Access, Vol. 6, pp. 36188-36197, 2018.
- B. Wang, Y. Zhang, C. Wu and F. Wang, “Multimodal MRI Analysis of Cervical Cancer on the Basis of Artificial Intelligence Algorithm”, Contrast Media and Molecular Imaging, Vol. 23, pp. 1-16, 2021.
- C. Zhang, C.W. Jia, H.R. Ge, “Quantitative Detection of Cervical Cancer based on Time Series Information from Smear Images”, Applied Soft Computing, Vol. 112, pp. 107791-107798, 2021.
- Biochips
Abstract Views :212 |
PDF Views:4
Authors
Source
Biometrics and Bioinformatics, Vol 7, No 5 (2015), Pagination: 126-129Abstract
“Biochips”-The most exciting future technology is an outcome of the fields of Computer science, Electronics & Biology. It’s a new type of bio-security device to accurately track information regarding what a person is doing, and who is to accurately track information regarding what he is doing, and who is actually doing it. It’s no more required with biochips the good old idea of remembering pesky PINs, Passwords, & Social security numbers .No more matters of carrying medical records to a hospital, No more cash/credit card carrying to the market place; everything goes embedded in the chip…. Everything goes digitalized. No more hawker tricks on the internet….! Biochip has a variety technique for secured E-money transactions on the net. The power of biochips exists in capability of locating lost children, downed soldiers, and wandering Alzheimer patients.
- Optimization of Micro Wire Electric Discharge Machining Process:A Response Surface Approach
Abstract Views :202 |
PDF Views:0
Authors
Affiliations
1 Dept of Manufacturing Engineering, College of Engineering Guindy, Anna University, Chennai, IN
1 Dept of Manufacturing Engineering, College of Engineering Guindy, Anna University, Chennai, IN
Source
Manufacturing Technology Today, Vol 12, No 10 (2013), Pagination: 13-19Abstract
This paper presents a systematic methodology for modeling and analysis of Material removal rate of micro wire EDM process using the Response Surface Methodology (RSM). The factors of micro WEDM process are voltage, capacitance and feed rate. The machining performance of material removal rate is response variable investigated. Experimental work carried out on metal matrix composite (LM 6- B4C /9%) with zinc coated copper wire by a standard RSM design called a Central Composite Design (CCD). To analysis the proposed second order mathematical model for material removal rate using CCD for estimating the model coefficients of three factors and it has found that influences the MRR in micro WEDM process. Based on ANOVA, the voltage, feed rate and capacitance significant effect on the MRR.Keywords
Micro EDM, Micro WEDM, ANOVA, Response Surface Methodology(RSM).- Modeling and Prediction of Surface Roughness in Micro Turning of Aluminium Using Regression
Abstract Views :193 |
PDF Views:0
Authors
Affiliations
1 Dept. of Manufacturing Engg., CEG, Anna University, Guindy, Chennai, IN
1 Dept. of Manufacturing Engg., CEG, Anna University, Guindy, Chennai, IN
Source
Manufacturing Technology Today, Vol 7, No 11 (2008), Pagination: 7-11Abstract
Micro-machining is the most basic technology for the production of miniaturized parts with micron level dimensions. One type of tool based micromachining technology is micro turning. It is a conventional metal removal mechanism that has been miniaturized. Surface roughness plays an important role in product quality in producing of micron scale structures and components. In this paper, the effect and prediction of machining parameters on surface roughness in a micro turning operation on Aluminium was investigated by using the multiple Regression modeling concepts. In the micro-turning process, cutting conditions determine the time and cost of production which ultimately affect the quality of the final product. So reliable models and methods are required for the prediction of the output performance of the process.- An Experimental Investigation of Superabrasive Grinding of Alumina Ceramics Using Molybdenum Disulphide as Solid Lubricant
Abstract Views :207 |
PDF Views:0
Authors
Affiliations
1 Dept. of Manufacturing Engg., CEG Campus, Anna University, Chennai, IN
1 Dept. of Manufacturing Engg., CEG Campus, Anna University, Chennai, IN
Source
Manufacturing Technology Today, Vol 7, No 3 (2008), Pagination: 10-17Abstract
Super abrasive grinding is a development in the precision grinding technology for producing high surface finish on the surfaces. Cooling and lubrication are especially important to ensure workpiece quality because of high friction and intense heat generation involved in the process. Conventionally, liquid coolants in flood form are employed in grinding. The large contact area between the wheel and workpiece causes as tiff boundary layer around the periphery, which restricts the flow of fresh cutting fluids in the grinding zone. Hence, the usage of fluid coolant is in effective. Minimization and possibly the elimination of fluid coolants can be done by substituting their functions through the use of solid lubricants. In this work, the possibility of using Molybdenum-di-Sulphide as a lubricating medium to reduce the heat generated at the grinding zone is investigated by the use of an experimental setup in the surface grinding machine. The study of effect of wheel parameters and grinding parameters on surface roughness, surface damage, specific energy and grinding forces are analyzed and the results are compared with the results obtained in the dry grinding.- Finite Element Analysis of Parts Fabricated by FDM
Abstract Views :199 |
PDF Views:0
Authors
Affiliations
1 Department of Manufacturing Engineering, College of Engineering, Anna University, Chennai-25, IN
1 Department of Manufacturing Engineering, College of Engineering, Anna University, Chennai-25, IN
Source
Manufacturing Technology Today, Vol 6, No 6 (2007), Pagination: 27-31Abstract
The high degree of automation of layered manufacturing process and its ability to create geometrically complex parts to precise dimensions provide it with a unique potential for low volume production of rapid tooling and functional components. As the rapid prototyping going towards rapid manufacturing in recent days, strength becomes the main factor which affected by many process parameters. In this study, stress analysis has been done on FDM (Fused Deposition Modeling) parts mesostructure by finite element method. In this Finite Element Analysis (FEA) models were designed with different mesostructural process parameters like road width, air gap and slice thickness, on this a linear orthotropic analysis was done to know the effect of each parameter on stress distribution. FEA results were compared with experimental yield strength results and they have better agreement with experimental results in knowing the effect of each parameter on strength.- Modeling of RP-FDM Using Response Surface Methodology to Predict the Influence of Process Parameters on Porosity
Abstract Views :193 |
PDF Views:0
Authors
Affiliations
1 Department of Manufacturing Engineering, College of Engineering, Anna University, Chennai-600025, IN
1 Department of Manufacturing Engineering, College of Engineering, Anna University, Chennai-600025, IN