iosr-JEEE   Volume-15 ~ Issue-6 ~ Nov. – Dec. 2020

Abstract: Various composite systems have been used on sensitizers for solar cell fabrication for electricity generation. In this study, Fluorine doped tin oxide (FTO), Indium tin oxide (ITO), Titanium oxide (TiO2) and Zinc oxides (ZnO) were chosen for its outstanding properties in the aspect of increased surface area of absorbtivity and current-voltage performance. Natural dye from Laali (Lawsonia inermis) stem bark was chosen as the sensitizer. The extracted dye was deposited on these composite systems. The SEM, XRD and EDS were carried out in the solar energy laboratory situated in South Africa. It was observed that ITO emerges the best over FTO while, TiO2 enhanced the shapes of the dye structure and ZnO enhanced the surface area of absorption..

Keywords: FTO: Fluorine doped tin oxide, ITO: Indium tin oxide, ZnO: Zinc Oxide, TiO2: Titanium oxide, sensitizers and Absorbitivity

[1]. K. E. Lee, M. A. Gomez, S. Elouatik and G. P. Demopoulos." Further understanding of the adsorption mechanism of N719 sensitizer on anatase TiO2 films for DSSC applications using vibration spectroscopy and confocal Raman imaging". Langmuir v 26, pp. 9575–9583, 2010
[2]. S.M. Rajaram, J.H. Won, M.P. Habib and H. Sung-Hwan. "Nanocrystalline TiO2/ZnO Thin films: Fabrication and Application to Dye-Sensitized Solar Cells" Journal of Physical Chemistry B: 109, pp. 24254 – 24259, 2005.
[3]. K. Dong-Joo, M. Byung-Ho, L. Don-kyu, P. Cha-Soo and S. Youl-Moon. "Comparison of transparent conductive indium tin oxide, titanium-doped indium oxide, and fluorine-doped tin oxide films for dye-sensitized solar cell application" Journal of Electrical Engineering and Technology, 6(5), pp. 684-687, 2011. [4]. Y. Beomjin, K. Kyungkon, L .Doh-Kwon, K. Min Jae, L. Hyunjung, K. Yong Hyun, K. Won Mok and P. Nam-Gyu. Enhanced charge collection efficiency by thin-TiO2-film deposition on FTO-coated ITO conductive oxidein dye-sensitized solar cells" Journal of material chemistry. 20, pp, 4392-4398, 2010
[5]. R Mamta and S.K. Tripathi "A Comparative study of Nanostructured TiO2, ZnO and Bilayer TiO2/ZnO Dye sensitized solar cell" Journal of Electronic Materials, 44(4) pp.1151-1159, 2015.

Abstract: Nigeria has a huge proven gas reserve of about 187 tscf (scf) (BP, 2013; NNPC, 2015). This makes Nigeria the world's ninth largest. These gas reserves can increase to 600 trn (scf) with intensive gas exploration. Nigeria, being the most populous country in Africa and having the largest gas reserves in the continent, the need to invest and diversify in power plant project in imperative. The total final energy consumption in Nigeria as at 2012 was 121 Million tons of oil equivalent (Mtoe), which will increase by 64% in year 2040. This signifies significant increase in energy demand in the country in the future, which justifies the need for more investment and diversification in power plant project in the country. The study objective is to determine optimal investment needed on gas for power plant project in Nigeria. The study employed mathematical programming. The paper employs this approach by....

Keywords: Optimal Investment, Profitability, Gas, Power Plant

[1]. Avram E. L. et al., 2009. Investment decision and its appraisal, DAAAM International, Vienna, Austria, EU, 2009, Vol. 20, No. 1, p. 1905-1906. Barberis, N. & Thaler, R. (2003) A survey of behavioral finance in G.M. Constantinides, M. Harris and R.M. Stulz (Eds) Handbook of the
[2]. BP, BP Statistical Review of World Energy,2015.
[3]. Chavas, Jean Paul, 2004. Risk analysis in theory and practice, Elsevier Academic Press, USA
[4]. Energy Information Administration (EIA) 2015
[5]. EIA, 2014. Energy Outlook for the year with predictions to 2035, "National Energy Information Centre, EI-30, Forrestal Building, Washington, DC 20585, April..

Abstract: The concept of integrated renewable energy has been a necessity for our fast-growing economies. However, most of the experimented integrated systems are facing large data management problems and this necessitates the need for smart configuration with Internet of Things (IOT). On an estate with houses that operate independent power systems, this research designed and implemented a 24-hour simulation of an integrated system that employed big data techniques for monitoring and controlling real time energy data from collaborative supplies with load priority selection options. It used Proteus software, Arduino uno, android app designed with HTML, CSS and JavaScript, and the web-based designed with PHP, MongoDB and JavaScript. Within a 3-hour schedule, the system underwent energy and load priority check to select preferred supply and suitable load. The operational level was displayed on both a mobile device and a hardware panel. Further research will be physical implementation.

Keywords: Real Time, Energy Data, Model, Integration Renewable Energy, Collaborated Supply

[1]. D. Gielen, F. Boshell, D. Saygin, M. D. Bazilian, N. Wagner, and R. Gorini, "The role of renewable energy in the global energy transformation," Energy Strateg. Rev., vol. 24, no. June 2018, pp. 38–50, 2019.
[2]. N. H. Motlagh, M. Mohammadrezaei, J. Hunt, and B. Zakeri, "Internet of things (IoT) and the energy sector," Energies, vol. 13, no. 494, pp. 1–27, 2020.
[3]. M. Ceci et al., "Innovative power operating center management exploiting big data techniques," ACM Int. Conf. Proceeding Ser., vol. 2, no. 2019, pp. 326–329, 2019.
[4]. V. Marinakis, "Big data for energy management and energy-efficient buildings," Energies, vol. 13, no. 7, pp. 1–18, 2020.
[5]. R. Karoly and C. D. Dumitru, "The Monitoring and Control Processes of a Renewable Energy Management System," Procedia Technol., vol. 19, no. 2015, pp. 689–694, 2015.

Abstract: Lung cancer could be a condition that causes cells to divide within the lungs uncontrollably with the exception of Non-small cell carcinoma and tiny cell carcinoma, there are a unit several alternative sorts like respiratory organ tumor, adenoid cystic carcinomas, lymphomas etc. which may result in the death of patient if not detected early. Concerning thirteen of all carcinoma area unit tiny cell carcinoma and concerning eighty four area unit non-small cell carcinoma. The aim is to implement unvaried fuzzy c mean (IFCM) clump rule on CT pictures of carcinoma so calculate the world of the respiratory organ affected region. During this classification Artificial Neural Network (ANN) rule area unit applied to stimulate the behavior of biological system composed of neurons. In MATLAB version 2016 the aroused image would be processed to induce result the output of whether or not the cancer is gentle or moderate or significant.

Keywords: Lung cancer, image processing, segmentation, Iterative Fuzzy C-mean, artificial neural networks.

[1]. M Sharma, S Kumar Singh, P Agrawal, and V Madaan, "Classification of clinical dataset of cervical cancer using KNN". Indian Journal of Science and Technology, 9(28):1-5, 2019.
[2]. ParinazEskandarian, Jamshid Bagherzadeh, "Computer-Aided Detection of Pulmonary Nodules based on SVM in Thoracic CT Images", IKT2015 7th International Conference on Information and Knowledge Technology.978-1-4673-7485- 9/15/$31.00 ©2015 IEEE
[3]. Imran FareedNizami*, SaadUlHasan†, Ibrahim Tariq Javed, "A Wavelet Frames + K-means based Automatic Method for Lung Area Segmentation in Multiple Slices of CT Scan "ISBN: 978-1-4799-5754-5/14/$26.00 ©2014 IEEE 245
[4]. Hao Han, Lihong Li, "Fast and Adaptive Detection of Pulmonary Nodules in Thoracic CT Images Using a Hierarchical Vector Quantization Scheme", IEEE Journal of Biomedical and Health Informatics 2168-2194 (c) 2013 IEEE.
[5]. Ashwin S, Kumar SA, Ramesh J, Gunavathi K, "Efficient and reliable lung nodule detection using a neural network-based computer aided diagnosis system". In Emerging Trends in Electrical Engineering and Energy Management (ICETEEEM), 2012 International Conference on Chennai; 2012:135–142

Abstract: Background: Breast cancer is one of the biggest killers in the world, and early diagnosis is essential for improved prognosis. Mammograms are X-ray images of the breast which are used to early detect breast cancer. Also, Mammography is specialized medical imaging for scanning the breasts. Computer aided diagnosis systems (CAD) play a major role in the early diagnosis of breast cancer. Extracting the breast region precisely from a mammogram is an essential component of CAD for mammography. The purposesin this work arepresenting automaticallyenhance of the mammogram image to helping the physician's to detect the cancer in the breast and proposed limited area in the breast body to find thenipple location in it.
Methods:The proposed methodof nipple location detection employs a threshold technique withpixelscontrast enhancementto analysis all.....

Key Word: mammography, mammogram enhancement , breast cancer, nipple location, nipple segmentation

[1]. Omar M. Sallabi,TawfikEzatTawfik, KenzA.Bozed," Computer-Aided Detection of the External Borders of the Breast in Digital Mammogram Images ", International Journal of Computer Science, Communication & Information Technology – CSCIT, Vol.4 pp.1-3,2017.
[2]. K. Pardhi and K. H. Wanjale ," Survey on Techniques Involved in Image Segmentation", International Journal of Computer Science Trends and Technology (I JCS T) –4 (3), May - Jun 2016.
[3]. N. Shrivastava and J. Bharti, Empirical Analysis of Image Segmentation Techniques. In International Conference on Smart Trends for Information Technology and Computer Communications , 2016, August , (pp. 143- 150). Springer, Singapore.
[4]. C. R. Gonzalez and R.E. Woods, and S. L. Eddins. "Morphological image processing." Digital Image Processing 3 (2008): 627-688.
[5]. R. Salem and A. Jasem, "Use of hybrid systems as filters for images one color", Journal of Research Maysan, Iraq,2011.

Abstract: Background: Breast cancer occurs with high frequency among the world's population and its one of the main reasons of death, but in middle-aged women since it is very difficult to early identify. Mammography is the most effective method for detection of breast diseases and specialized medical imaging for scanning the breasts. Moreover helps in the early detection and diagnosis of breast tumors. Materials and Methods: In this paper, the work is initiated with basic pre-processing steps using removing objects outside the breast and reducing noise in the mammogram image . In the next stage we applied double thresholding technique based approach for Mammograms image segmentation. also, we added the borders to the final segmented image as a contour on the original image to helping to easily detect the breast cancer in different Mammogram images......

Key Word: Digital mammogram, Breast region extraction ,Thresholding segmentation , Breast cancer

[1]. Lisa Hutchinson, " Breast cancer: Challenges, controversies, breakthroughs" , Nature Reviews Clinical Oncology, Vol. (7), pp. 669-670, December 2010. Doi:10.1038/nrclinonc.2010.192. URL: https://www.nature.com/nrclinonc/journal/v7/n12/pdf/nrclinonc.2010.192.pdf.
[2]. Cancer Net Home Page of the National Cancer Institute http://biomed. nus.sg, 2002.
[3]. Benjamin O. Anderson, ―Breast Cancer—Thinking Globally‖, Science, Vol. 343, Issue 6178, pp. 1403, 28 March 2014.
[4]. K. Nico, T. Martin, H. Jan, V.E. Leon, Digital Mammography: Computational Imaging and Vision, Kluwer Academic Publication, Hingham, MA, 1998.
[5]. Radiologyinfo.org, " Mammography" , URL: https://www.radiologyinfo.org/en/info.cfm?pg=mammo#overview.