The research sought to analyze military housing provision and Soldiers' housing preferences at shadawanka barrack Bauchi, with the goal of meeting the military personnel's housing demands in the study region. The study collected data using a quantitative technique and survey strategy using a descriptive and exploratory research design and a questionnaire instrument. The study's population consisted of military personnel, with a sample frame of 248 dwellings, assuming one personnel per house. A sample size of 160 people was chosen. The questionnaire on a five-point Likert scale was self-administered. According to the findings, the factors with the greatest and fair conditions are security, wall condition, floor condition, and finishing, while the variables with the lowest and lowest condition rating are sewage and road networks within the barrack. The barrack's general or average level of housing conditions was rated fair. Water supply and security are the variables with the highest levels of adequacy, whereas drainage and road networks have the lowest levels of adequacy and reaction. The general degree of appropriateness of the barracks' residences was rated unsatisfactory. The quality of the floor, the walls, and the number of bedrooms have moderate levels of satisfaction, whereas solid waste disposal and sewage have low levels of satisfaction. The most common source of unhappiness is the insufficiency of housing provision, which has the highest standardized Beta coefficient of 0.285. The study recommended that the sewerage and solid waste disposal systems be improved. The service can be contracted out. Internal road networks and drainage systems within the barracks should be restored, and new ones created to give proper accessibility. There is a need for new dwellings to be built in order to relieve overcrowding in most homes. Because military personnel are dissatisfied with their housing owing to inadequacies, it is recommended that sufficient housing based on the demands of the soldiers be considered.
- Oyeleke, Oyediran Olufemi Department of Estate Management and Valuation, Federal Polytechnic Nassarawa, Nassarawa State, Nigeria
- Bala Ishiyaku Department of Estate Management and Valuation, Faculty of Environmental Technology, Abubakar Tafawa Balewa University, Bauchi. Nigeria
- Muhammad Maryam Salihu Department of Estate Management and Valuation, Faculty of Environmental Technology, Abubakar Tafawa Balewa University, Bauchi. Nigeria
- Sakariyau Jamiu Kayode Department of Estate Management and Valuation, Faculty of Environmental Technology, Abubakar Tafawa Balewa University, Bauchi. Nigeria
References
[1] Abdu, A., Bichi, A. M., Umar, Y. A., & Nadikko, B. J. (2019). An assessment of housing satisfaction in police barracks of Gombe State, Nigeria, International Journal of Recent Scientific Research, 10, (04A), 31647-31654. [2] Alabi, O., Kayode, S., Misbahu, A., & Olaifa, O. (2021). Effect of Physical Characteristics on Resident’s Satisfaction in a High-Density Area of Ilorin Metropolis. Path of Science, 7(9), 1001-1006. doi:http://dx.doi.org/10.22178/pos-74.1 [3] Akoh, H. O., Kibon, A. U., Abbas, S., &Daukere, B. E. (2020), Developing geo-database for housing and facilities management in Sobi Barracks Ilorin, Kwara state, Nigeria, Sahel Journal of Geography, Environment and Development, 1(1), 117-129. [4] Akomolede, K. (2007) Low Income Earners and the Burden of Home Ownership in Nigeria, Nigerian Guardian Newspaper of January, 29; p. 29. [5] Al-Habees, M. A. (2012). Determination of the Residential Housing Needs Expected for Cities of Jordan Within the Period of 2014-2024, Management Science and Engineering, 6(2): 130-139. [6] Cohen, E. A. (2017). The big stick: the limits of soft power and the necessity of military force. Hachette UK. [7] Cole, K. A. (2000). Prioritizing Quality of Life Issues: Laying a Vision for Tomorrow (Joint Vision 2010). Air Command And Staff Coll Maxwell Afb Al [8] Kayode, S. J., Muhammad, M. S., & Bello, M. U. (2021). Effect of Socio-Economic Characteristics of Households on Housing Condition in Bauchi Metropolis, Bauchi State, Nigeria. Traektoriâ Nauki= Path of Science, 7(7), 2001-2013 [9] Kelly, S. M. T. (2020). Suicide in the Barracks: Architecture and Social Connection in Military Housing (Doctoral dissertation, University of Oregon). [10] Krejcie, R.V. & Morgan, D. W. (1970). Determine sample size for research activities. Education Psychology Measures, 30(3). [11] Kurraz, H. A. and Ziara, M. (2007). Towards Lowering the Cost of Houses in Palestine: New Perspective. The Islamic University Journal (Series of Natural Studies and Engineering), 15(2): 1-12. [12] Musa, H. A., Bello, M. U., & Kayode, S. J. (2021). Effect of Neighbourhood Characteristics on Resident’s Satisfaction in Doya Area of Bauchi Metropolis. Traektoriâ Nauki= Path of Science, 7(4), 6001-6005. [13] Pallant, J. (2011). SPSS Manual, a step by step guide to data analysis using SPSS. (4th ed.), Berskhire: Open University Press. [14] Polit, D. F., & Beck, C. T. (2010). Generalization in quantitative and qualitative research: Myths and strategies. International journal of nursing studies, 47(11), 1451-1458. [15] Sakariyau, J. K., Uwaezuoke, N. I,, Olaoye, T K.,& Sani, G.S (2021). Housing affordability among civil servants in Ekiti state, Nigeria. International Journal of Research and Review. 2021; 8(10): 383-390. DOI: https://doi.org/10. 52403/ijrr.20211051 [16] Sean, S. L., & Hong, T. T. (2014). Factors affecting the purchase decision of investors in the residential property market in Malaysia. Journal of Surveying, Construction and Property, 5(2), 1-13. [17] UN Shelter Sector. (2011). Assessing Housing Needs in Gaza, June 2007–December 2011.
Oyeleke, Oyediran Olufemi, Bala Ishiyaku, Muhammad Maryam Salihu, Sakariyau Jamiu Kayode, "Effect of Military Housing Condition on Housing Preference and Adequacy in Shadawanka Barrack Bauchi, Bauchi State, Nigeria" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.10 issue 12, December 2021, pp.01-06 DOI: https://dx.doi.org/10.51583/IJLTEMAS.2021.101201
The inability of capital markets in Sub-Saharan Africa in fund mobilization has affected financial openness in the sub-continent. It has been vigorously argued that financial openness can still thrive without viable capital market but the intermediation function of capital market should not be overlooked. To this end, this study examined the nexus between capital market and financial openness in Sub-Saharan African Countries for 30 years period ranging from 1990 - 2019.The study proxied financial openness with capital account balance ratio, private capital inflow ratio, number of listed companies, external finance through foreign capital market and per capita income ratio while capital market development was measured with market capitalization ratio. The study employed secondary data collected from World Development Indicators, Securities and Exchange Commission statistical bulletin, and Stock Exchange fact books of the respective countries. The study adopted ex-post facto research design while the time series data were analyzed using descriptive statistics, correlation, unit root test, granger causality test, Johansen co-integration and error correction model via E-Views 10. The result revealed that there is no significant relationship between market capitalization ratio and capital account balance ratio in Nigeria; a significant negative relationship between capital account balance ratio and market capitalization ratio in Zimbabwe; a significant positive relationship between private capital inflow ratio and market capitalization ratio in South Africa and a significant positive relationship between private capital inflow ratio and market capitalization ratio in Nigeria. The study recommended that Sub-Saharan Countries should develop trade openness and liberalisation policy that would promote the international relationships necessary for increasing market opportunities and enhancing profitable investments. Therefore the country should continue to develop its capital market to achieve international standards and attract more investors.
- Martin Emeka Okafor Department of Banking and Finance, Nnamdi Azikiwe University, Awka, Nigeria
- Clement Nwakoby Department of Banking and Finance, Nnamdi Azikiwe University, Awka, Nigeria
- Gideon Kasie Ezu Department of Banking and Finance, Nnamdi Azikiwe University, Awka, Nigeria
References
[1] Abedana, V.N., & Gayomey, J. (2016). IFRS/IAS adoption and its tax challenges and management - views from Ghana. The International Journal of Business Management 4(5), 197-210. [2] Abedian, I. (2005). Fiscal and monetary policy management in South Africa 1994-2005. Pan African Investment and Research Services. Johannesburg, South Africa. [3] Brownbridge, M. & Gockel, A.F. (1996). The Impact of Financial Sector Policies on Banking in Ghana. Research Department of Bank of Ghana [4] Bryant, M. (2017). Taking stock: Johannesburg Stock Exchange - the first 100 years. Johannesburg: Jonathan Ball. [5] BSE (2013) Annual Report. Botswana Stock Exchange, Gaborone. [6] Bulut, U. (2017). Financial conditions index as a leading indicator of business cycles in Turkey. In Ü. Hacioğlu & H. Dinçer (Eds.), Global financial crisis and its ramifications on capital markets (pp. 225–239). Cham: Springer International Publishing.10.1007/978-3-319-47021-4 [7] Bundoo, S.K. (2017). Stock market development and integration in SADC (Southern African Development Community). Review of Development Finance, 7(1), 64-72 [8] Calvo G., Leiderman, L., & Reinhart, C. (2013). Capital flows and real exchange rate appreciation in Latin America, IMF Staff Papers, 40(1), 108–151. [9] Carmen, R.,& Kenneth, R. (2010). This time is different: Eight centuries of financial folly. Princeton University Press. 66, 92–94. [10] CBN, (2006). Central Bank of Nigeria annual report and statement of accounts. http://www.cenbank.org/out/publications/reports/rd/2002/areport-02.pdf. [11] Cerdeiro, D.A., & Komaromi, A. (2019). Financial openness and capital inflows to emerging markets: In search of robust evidence. IMF Working Paper, WP/19/194. [12] Dozie, P.G. (2015). Investing in the Nigerian stock market through the Nigerian stock exchange. A Paper Presented at the First Africa Europe Forum “Lets Trust Africa” at UNSCO Headquarters Paris, March 27-30. [13] Ductor, L., & Grechyna, D. (2015). Financial development, real sector, and economic growth. International Review of Economics & Finance, 37, 393-405. [14] Dzikiti, W. (2017). Banking sector, stock market development and economic growth in Zimbabwe: A multivariate causality framework. Thesis submitted University of South Africa, 1-124, [15] Edwards, S., & Tavlas, G. (2014). The order of liberalization of the external sector in developing countries. International Finance Section, Department of Economics, Princeton University. [16] Eichengreen, B., & Andrew, R. (2014). Capital controls in the 21st century. Journal of International Money and Finance, 48, 1-16. [17] Fasanya, I.O., & Olayemi, I.A. (2020). Modelling financial openness growth-nexus in Nigeria: Evidence from bounds testing to cointegration approach. Futur Bus J 6, 4 (2020). https://doi.org/10.1186/s43093-019-0008-2 [18] Fasanya, O.I., Onakoya, A., & Ofoegbu, I.D. (2013). Capital Market Development: A Spur to Economic Growth in Nigeria. Acta Universitatis Danubius. Œconomica, 9(5), 245-255. [19] Filler, R.K., Jan, H., & Nauro, F.C. (2009). Do stock market promote economic growth?, The William Davidson Institute (University of Michigan Business School). Working Paper Series, No. 267, September. [20] Gosh, A.R., Ostry, J.D., & Qureshi, M.S. (2018). Taming the tide of capital flows: A policy guide. MIT Press. [21] Goyal, A. (2012). The future of financial liberalization in South Asia. Asia pac. Dev. J. 19(1), 63-95. [22] Hsiao, C. (2009). Panel data analysis - advantages and challenges. Los Angeles: University of Southern California. [23] Ibrahim, S.S., & Nuruddeen, T. (2016). The linkages between trade openness, financial openness and economic growth in Nigeria. https://www.researchgate.net/publication/319352421. Retrieved 14-4-2018. [24] Jugurnath, B., Chuckun, N., & Fauzel, S. (2016). Foreign direct investment & economic growth in Sub-Saharan Africa: an empirical study. Theoretical Economics Letters, 6(4), 798-807. [25] Kannan, A. (2018). What is financial openness? https://www.enotes.com/homework-help/what-financial-openness-181567. [26] Korinek, A. (2018). Regulating capital flows to emerging markets: An externality view. Journal of International Economics, 111(61), 80. [27] Lane, P.R., & Milesi-Ferretti, G.M. (2020). The external wealth of nations mark II: Revised and extended estimates of foreign assets and liabilities, 19702004. Journal of International Economics, 73(2), 223-250. [28] Levine, R., & Zervos, S. (2016). Stock market development and long-run growth. World Bank Economic Review, 10, 323–339. [29] Nowbutsing, B. M. (2014). The impact of openness on economic growth: Case of Indian Ocean rim countries. Journal of Economics and Development Studies, 2(2), 407-427. [30] Omole, D.A., & Falokun, G.O. (2009). The impact of interest rate liberalization on corporate financing strategies of quoted companies in Nigeria. Proceedings of the Conference on African Economic Research Consortium, (AERC'09), Kenya, pp: 52-52. [31] Patrick, H.T. (2016). Financial development and economic growth in underdeveloped countries. Economic Development and Cultural Change, 14(1), 174-189. [32] Quinn, D., & Toyoda, A.M. (2018). Does capital account liberalization lead to growth. Review of Financial Studies, 21,1403-1449. [33] Rachdi, H., & Mensi, S. (2012). Does institutions quality matter for financial development and economic growth nexus? Another look at the evidence from Mena countries. Economic Research Forum, Working Paper 705. [34] Sabandi, M., & Noviani, L. (2015). The effects of trade liberalization, financial development and economic crisis on economic growth in Indonesia. Journal of Economics and Sustainable Development, 6(24), 120-128. [35] Shaw, E. (1973). Financial deepening in economic development. New York: Oxford University Press. [36] Woodruff, J. (2019). How to calculate a working capital balance sheet. https://smallbusiness.chron.com/calculate-working-capital-balance-sheet-11175.html. Retrieved 17/04/2020 [37] Zulfiqar, K. & Kausar, R. (2012). Trade liberalization, exchange rate and export growth in Pakistan. Far East Journal of Psychology and Business, 9(2), 32-47.
Martin Emeka Okafor, Clement Nwakoby, Gideon Kasie Ezu, "Capital Market Development and Financial Openness in Sub-Saharan Africa" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.10 issue 12, December 2021, pp.07-15 DOI: https://dx.doi.org/10.51583/IJLTEMAS.2021.101202
This paper developed model equations that aid in decision making process of selecting the optimum gas transportation medium using regression analysis as the method.In apply regression analysis, data generated from the economic analysis conducted were exported to Excel and with the aid of Excel data analysis toolpak, model equations in the forms of simple linear equations were developed. The gas monetization technologies considered were only gas to liquid (GTL) and liquefied natural gas (LNG). In the study, series of sensitivity analyses were performed, with each factor that impacts on the profitability of the considered gas monetization technologies, one at a time and the various data points gotten from the sensitivity analyses were exported to Excel for development of a correlation/model equation using regression analysis. For gas to liquid (GTL) technology, the factors affecting its profitability (NPV) include: capital expenditure (CAPEX), gas feedstock price, naphtha price and oil price. Whereas, for liquefied natural gas (LNG) technology, the factors affecting its profitability include: gas feedstock price, shipping cost and LNG price. From the results of the regression analyses, it was discovered that: for each unit increase in CAPEX, the profitability of the GTL technology increases with 0.1 units; for each unit increase in gas feedstock price, the GTL profitability decreases with 3.8 x 10-13 units; for each unit increase in naphtha price, the GTL profitability increases with 8.01 x 10-15 units and for a unit increase in oil price, the GTL profitability increases with 6.1 x 10-4 units. And for a unit increase in shipping cost, the LNG profitability increases with 1000 units and for a unit increase in LNG price, the LNG profitability increases with 1000 units. Gas feedstock price has zero effect on the profitability (NPV) of LNG technology.
- Page(s): 16-20
- Date of Publication: 11 January 2022
- Okoli Nnanna O Emerald Energy Institute, UNIPORT
- Nwaozuzu Chijioke Emerald Energy Institute, UNIPORT
- Nteegah Alwell Emerald Energy Institute, UNIPORT
- Onyejekwe Ifeanyi M. Department of Petroleum Engineering, FUTO
References
[1] Clarke, S. andGhaemmghami, B. (2003). Engineering a Gas-to-Liquids Project: Taking GTL Forward. Engineering Solutions. Offshore World. p. 55-62. [2] Garrouch, A. A. (2007). Economic Viability of Gas-to-Liquid Technology,” (presented at the 2007 SPE Hydrocarbon Economics and Evaluation Symposium in Dallas, Texas on April 1-3), pp. 1-8. [3] Ross, S.A., Westerfield, R.W., and Jordan, B.D. (1996). Essentials of Corporate Finance. Chicago: McGraw-Hill. 490 p. [4] Şeref, M. H. and Ahuja, R. K. (2008). A portfolio management and optimization spreadsheet DSS. In Burstein, Frad&Holsapple, Clyde W. (eds.). Handbook on Decision Support Systems 1: Basic Themes. Springer. [5] Şeref, M. H.; Ahuja, R. K. and Winston, W. L. (2007). Developing spreadsheet-based decision support systems: using Excel and VBA. Dynamic Ideas. ISBN 978-0-9759146-5-6.
Okoli Nnanna O, Nwaozuzu Chijioke, Nteegah Alwell, Onyejekwe Ifeanyi M., "Development of Model Equations for Comparative Analysis of the Profitability of Gas Monetisation Technologies: A Case Study of GTL and LNG" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.10 issue 12, December 2021, pp.16-20 URL: https://ijltemas.in/DigitalLibrary/Vol.10Issue12/16-20.pdf
An application of traffic sign recognition is proposed on the basis of the convolution neural network (CNN).A CNN is an artificial neural network that is used to process and recognize the image that focuses on processing pixel data. A dataset is trained, tested, and saved in order for the application to be able to detect and classify the image considered from the dataset. A Graphical User Interface (GUI) is designed for the user to try and use the application which will load the image from the dataset and classify the image as per its requirement. In the German traffic sign recognition criterion, an accuracy of 98% is obtained from the model used. Traffic Sign Recognition plays an integral part in the intelligent transportation system and has driverless vehicles and assisted driving systems are some of the applications of it [1]. The self-driving cars needed to identify each and every detail that are present on the road that includes vehicles on the road as well as pedestrians walking on the sidewalk with extreme accuracy and precision. There were no challenging and publicly available datasets in the domain for a period of time but the situations had changed in the year 2011 when Stallkamp et al [2] and Larsson and Felsberg [3] introduced datasets that includes demonstrations for traffic sign detection and classification of it.
- Pisati Mahipal Reddy Student, Department of Information Technology at Maturi Venkata Subba Rao Engineering College, Osmania University, Hyderabad, Telangana,India
- Arrabothu Vishal Reddy Student, Department of Information Technology at Maturi Venkata Subba Rao Engineering College, Osmania University, Hyderabad, Telangana,India
- Sowjanya Jindam Assistant Professor, Department of Information Technology at Maturi Venkata Subba Rao Engineering College, Osmania University, Hyderabad, Telangana,India
- Ubaidullah Mohammed Sayeed Student, Department of Information Technology at Maturi Venkata Subba Rao Engineering College, Osmania University, Hyderabad, Telangana,India
- Arrabothu Vivek Reddy Student, Department of Information Technology at Maturi Venkata Subba Rao Engineering College, Osmania University, Hyderabad, Telangana,India
References
[1] Suisui Tang. (2014) Research on Traffic Sign Recognition Algorithm. Beijing Jiaotong University, PP. 1-7. [2] Krizhevsky A., Ilya S., Geoffrey E.H. ImageNet Classification with Deep Convolutional Neural Networks; Proceedings of the Advances in Neural Information Processing Systems 25; Lake Tahoe, NV, USA. 3–6 December 2012; pp. 1097–1105. [Google Scholar] [3] Lecun Y., Bottou L., Bengio Y., Haffner P. Gradient-based learning applied to document recognition. Proc. IEEE. 1998;86:2278–2324. doi: 10.1109/5.726791. [CrossRef] [Google Scholar] [4] P. Sermanet and Y. LeCun, “Traffic sign recognition with multiscale convolutional networks,” in Neural Networks (IJCNN), The 2011International Joint Conference on, 31 2011-aug. 5 2011, pp. 2809 –2813. [5] K. Jarrett, K. Kavukcuoglu, M. Ranzato, and Y. LeCun, “What is the best multi-stage architecture for object recognition?” in Computer Vision, 2009 IEEE 12th International Conference on, 29 2009-oct. 2 2009, pp. 2146 –2153. [6] D. Ciresan, U. Meier, J. Masci, and J. Schmidhuber, “A committee of neural networks for traffic sign classification,” in IJCNN’11, 2011, pp. 1918–1921. [7] A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” in NIPS’12, 2012, pp. 1106–1114 [8] Lai, Y., Wang, N., Yang, Y., & Lin, L. (2018). Traffic signs recognition and classification based on deep feature learning. In 7th International Conference on Pattern Recognition Applications and Methods (ICPRAM), Madeira, Portugal (pp. 622-629). [9] Hoo-Chang, S., Roth, H. R., Gao, M., Lu, L., Xu, Z., Nogues, I., ... & Summers, R. M. (2016). Deep convolutional neural networks for computer-aided detection: CNN architectures, dataset characteristics and transfer learning. IEEE transactions on medical imaging, 35(5), 1285. [10] Dataset:GTSRB - German Traffic Sign Recognition Benchmark https://www.kaggle.com/meowmeowmeowmeowmeow/gtsrb-german-traffic-sign
Pisati Mahipal Reddy, Arrabothu Vishal Reddy, Sowjanya Jindam, Ubaidullah Mohammed Sayeed, Arrabothu Vivek Reddy, "Recognition of Traffic Sign Using CNN and Deep Learning" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.10 issue 12, December 2021, pp.21-25 DOI: https://dx.doi.org/10.51583/IJLTEMAS.2021.101203
This paper proposes a Microwave Head Imaging Platform (MHIP) based on MIT App Inventor application. One of crucial element in the Microwave Imaging (MWI) is the imaging platform which used to hold and control the movement of antenna in certain angle. In the MHI platform, the key challenge is to improve the efficiency of angle control for brain stroke detection in the head phantom. Thus, the principal contribution of this work is the smart stepper motor control using MIT APP Inventor application for MHI platform which integrated with Arduino UNO module and Bluetooth module. The movement of platform based on two directions (clockwise and anticlockwise) with 10⁰ step of angle or 36 unique positions. Overall, the proposed system offers the smart data collection using smartphone which MIH as an alternative technique for brain stroke diagnostic.
- Page(s): 26-30
- Date of Publication: 15 January 2022
- A. Salleh Center for Telecommunication Research & Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM), 76100, Durian Tunggal, Melaka, Malaysia
- M. Z. A. Abd. Aziz Center for Telecommunication Research & Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM), 76100, Durian Tunggal, Melaka, Malaysia
- M. H. Misran Center for Telecommunication Research & Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM), 76100, Durian Tunggal, Melaka, Malaysia
- N. R. Mohamad Fakulti Teknologi Kejuruteraan Elektrik dan Elektronik (FTKEE), Universiti Teknikal Malaysia Melaka (UTeM), 76100, Durian Tunggal, Melaka, Malaysia
References
[1] Islam, M. T., Islam, M. T., Samsuzzaman, M., Kibria, S., & Chowdhury, M. E. (2021). Microwave Breast Imaging Using Compressed Sensing Approach of Iteratively Corrected Delay Multiply and Sum Beamforming. Diagnostics, 11(3), 470. [2] Saied, I., Arslan, T., Ullah, R., Liu, C., & Wang, F. (2021, May). Hardware Accelerator for Wearable and Portable Radar-based Microwave Breast Imaging Systems. In 2021 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1-5). IEEE. [3] Khoshdel, V., Asefi, M., Ashraf, A., & LoVetri, J. (2020). Full 3D microwave breast imaging using a deep-learning technique. Journal of Imaging, 6(8), 80. [4] Wang, Y., Zhang, Y., Wang, W., Liu, X., Chi, Y., Lei, J., ... & Zhang, T. (2020). Effects of circadian rhythm disorder on the hippocampus of SHR and WKY rats. Neurobiology of learning and memory, 168, 107141. [5] J. M. Felicio, J. M. Bioucas-Dias, J. R. Costa, and C. A. Fernandes, “Microwave Breast Imaging Using a Dry Setup,” IEEE Trans. Comput. Imaging, vol. 6, pp. 167–180, 2019. [6] Hossain, A., Islam, M. T., Chowdhury, M. E., & Samsuzzaman, M. (2020). A grounded coplanar waveguide-based slotted inverted delta-shaped wideband antenna for microwave head imaging. IEEE Access, 8, 185698-185724. [7] Tobon Vasquez, J. A., Scapaticci, R., Turvani, G., Bellizzi, G., Rodriguez-Duarte, D. O., Joachimowicz, N., ... & Vipiana, F. (2020). A prototype microwave system for 3D brain stroke imaging. Sensors, 20(9), 2607. [8] Stancombe, A. E., Bialkowski, K. S., & Abbosh, A. M. (2019). Portable microwave head imaging system using software-defined radio and switching network. IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology, 3(4), 284-291. [9] Sohani, B., Tiberi, G., Ghavami, N., Ghavami, M., Dudley, S., & Rahmani, A. (2019, June). Microwave imaging for stroke detection: validation on head-mimicking phantom. In 2019 PhotonIcs & Electromagnetics Research Symposium-Spring (PIERS-Spring) (pp. 940-948). IEEE. [10] M. S. R. Bashri and T. Arslan, “Low-cost and compact RF switching system for wearable microwave head imaging with performance verification on artificial head phantom,” IET Microwaves, Antennas Propag., vol. 12, no. 5, pp. 706–711, 2018, doi: 10.1049/iet- map.2017.0486. [11] Hasan, M. M., Samsuzzaman, M., Talukder, M. S., Islam, M. T., Azim, R., & Masud, M. A. (2020, December). Wideband slotted patch antenna for Microwave Based Head Imaging Applications. In 2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI) (pp. 1-4). IEEE. [12] Arayeshnia, A., Amiri, S., & Keshtkar, A. (2020). Miniaturized on‐body antenna for small and wearable brain microwave imaging systems. International Journal of RF and Microwave Computer‐Aided Engineering, 30(4), e22133. [13] Alqadami, A. S., Zamani, A., Trakic, A., & Abbosh, A. (2021). Flexible Electromagnetic Cap for Three-Dimensional Electromagnetic Head Imaging. IEEE Transactions on Biomedical Engineering. [14] I. Saied and S. A. A. Hussainy (2019). Portable and Wearable Device for Microwave Head Diagnostic Systems. IEEE Healthc. Innov. Point Care Technol. HI-POCT 2019, pp. 45–48. [15] Islam, M. S., Islam, M. T., Hoque, A., Islam, M. T., Amin, N., & Chowdhury, M. E. (2021). A Portable Electromagnetic Head Imaging System Using Metamaterial Loaded Compact Directional 3D Antenna. IEEE Access, 9, 50893-50906. [16] B. J. Mohammed, A. M. Abbosh, S. Mustafa, and D. Ireland (2014). Microwave system for head imaging. IEEE Trans. Instrum. Meas., vol. 63, no. 1, pp. 117–123. [17] A. Salleh, C. C. Yang, T. Alam, M. S. J. Singh, M. Samsuzzaman, and M. T. Islam (2020). Development of Microwave Brain Stroke Imaging System using Multiple Antipodal Vivaldi Antennas Based on Raspberry Pi Technology Development of Microwave Brain Stroke Imaging System using Multiple Antipodal Vivaldi Antennas Based on Raspberry Pi Technology,” J. Kejuruter., vol. 32, no. February, p. 11. [18] A. Salleh, C. C. Yang, M. Singh, J. Singh, and M. T. Islam (2019). Development of antipodal Vivaldi antenna for microwave brain stroke imaging system,” Int. J. Eng. Technol., vol. 8, no. 3, pp. 162–168. [19] Mobashsher, A. T., & Abbosh, A. M. (2016). Performance of directional and omnidirectional antennas in wideband head imaging. IEEE Antennas and Wireless Propagation Letters, 15, 1618-1621. [20] Mobashsher, A. T., Bialkowski, K. S., Abbosh, A. M., & Crozier, S. (2016). Design and experimental evaluation of a non-invasive microwave head imaging system for intracranial haemorrhage detection. Plos one, 11(4), e0152351. [21] Ilja M, Andrea M, David V., Ondrej F., Marco S., Jan V. (2019). Microwave tomography system for methodical testing of human brain stroke detection approaches, International Journal of antennas and propagation, vol. 9 [22] Mobashsher, A. T., Mahmoud, A., & Abbosh, A. M. (2016). Portable wideband microwave imaging system for intracranial hemorrhage detection using improved back-projection algorithm with model of effective head permittivity. Scientific reports, 6(1), 1-16. [23] Mobashsher, A. T., & Abbosh, A. M. (2016). On-site rapid diagnosis of intracranial hematoma using portable multi-slice microwave imaging system. Scientific reports, 6(1), 1-17.
A. Salleh, M. Z. A. Abd. Aziz, M. H. Misran, N. R. Mohamad, "Smart Stepper Motor Control using MIT App Inventor for Microwave Head Imaging Platform" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.10 issue 12, December 2021, pp.26-30 URL: https://ijltemas.in/DigitalLibrary/Vol.10Issue12/26-30.pdf