-74813b3e17f460286df-6472 20220326064108301 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Recent Technology and Engineering (IJRTE) IJRTE 22773878 10.35940/ijrte.2277-3878 https://www.ijrte.org/ 03 30 2020 8 6 Assistant Professor, Department of Education in Science and Mathematics, Regional Institute of Education, Bhopal (M.P.), India. Dhirendra Kumar Shukla* Manoj Sharma Professor& Head, Department of Applied Sciences, Sagar Institute of Research and Technology, Bhopal (M.P.), India. This note explains about “Parkinson Disease which may be a long-term disorder of the central nervous system”. The research paper focuses on analysis of symptoms of “Parkinson Disease” to predict the disease in early stage. Concept of FCMs was used to interpret the diagnostic symptoms of “Parkinson Disease”. The target is to draw connection between the symptoms and provide likely explanation. 03 30 2020 1146 1149 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A1969.038620 https://www.ijrte.org/portfolio-item/A1969058119/ Lecturers and Researchers, Department of Architecture, College of Science and Technology, Covenant University, Canaanland, Km 10 Idiroko Road, Ota, Ogun State, Nigeria. Olatunde Daniel Babalola Wonders Nduka Eke Practitioner and Researcher, Department of Architecture, College of Science and Technology, Covenant University, Canaanland, Km 10 Idiroko Road, Ota, Ogun State, Nigeria. Akunnaya Pearl Opoko Lecturers and Researchers, Department of Architecture, College of Science and Technology, Covenant University, Canaanland, Km 10 Idiroko Road, Ota, Ogun State, Nigeria. Dr. Oladunni Izobo-Martins Lecturer, Department of Architecture, Covenant University, Ota, Ogun State, Nigeria. Dr. Osahon James Ediae Lecturer, Department of Architecture, College of Science and Technology, Covenant University, Ota, Nigeria Adedotun Oyebola Akinola Lecturers and Researchers, Department of Architecture, College of Science and Technology, Covenant University, Canaanland, Km 10 Idiroko Road, Ota, Ogun State, Nigeria. Accessibility of public buildings has been an issue of global interest and importance in the society in recent times. It has been promoted by the need to ensure universal equality and end discrimination of persons either based on size, ability and mobility disorder. Given the important role of water transportation in aiding mobility, movement of goods and services in coastal cities such as Lagos, this study reviewed the compliance of design, construction and operation of Ferry Terminals towards accessibility of users. The research adopts the case study approach and interviews in appraising the three existing Ferry Terminals in Lagos State, Nigeria for accessibility compliance. The case study involved observation and evaluation of the facilities, and the interviews focused on 18 of the ‘facilities operators and passengers’ about their experiences of associated facilities. Findings from the study revealed poor compliance to accessibility in both the external and internal environments. As such, there is a high degree of limitation in use of the facilities for all facets of water travel; from building approach; waiting, boarding and disembarking areas. Existing facilities have inadequate accessibility and are below standards to ensure use by all and without discrimination or segregation of users. It is therefore imperative for Ferry terminal buildings and amenities to be accessible in effectively enabling all users achieve true mobility in barrier-free environments that foster user-comfort through the adoption and application of universal design principles. 03 30 2020 2153 2167 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.B2278.038620 https://www.ijrte.org/portfolio-item/B2278078219/ Research Scholar, Department of ECE, Noorul Islam Centre for Higher Education, Kumaracoil, Tamil Nadu, India. C. Gangaiah Yadav K. S. Vijula Grace Assistant Professor, Department of ECE, Noorul Islam Centre for Higher Education, Kumaracoil, Tamil Nadu, India. An aggressive scaling in size and the increasing number of the transistor count are the important challenge of the design of Integrated Circuit (IC). In the same manner interconnection lines and resistive opens also became a major problem in present nanometer technology. The resistive open faults [ROFs] represent degradation [1] in connectivity’s within a circuit’s interconnections because of unavoidable manufacturing failures present in both current and future developing technologies. The resistive open fault [ROF] is an imperfect circuit connection that can be modelled as a defect resistors between two nodes of the circuit. The Resistive open faults [2] not causes the functionality of the circuit instantly. But, it causes the delay faults. In this research proposal, the impact of resistive open faults measured in 6-Transistors (6T) Static RAM memory cell design. The proposed 6T Static RAM memory cell implemented in 45nm technology by using Cadence Virtuoso library. The main goal of this proposed research work is to analise the effect of resistive open faults and how it reduce delay and power of 6T Static RAM cell. The resultant outputs of proposed 6T SRAM cell operation with and without ROFs will be compared. 03 30 2020 3531 3536 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.B3250.038620 https://www.ijrte.org/portfolio-item/B3250078219/ M.Tech Student, Department of Electronics and Communication Engineering, Mar Athanasius College of Engineering, Kothamangalam, India. Rincy Johnson Thomas Mohan Assistant Professor, Department of Electronics and Communication Engineering, Mar Athanasius College of Engineering, Kothamangalam, India. Sara Paul Assistant Professor, Department of Electronics and Communication Engineering, Mar Athanasius College of Engineering, Kothamangalam, India. Agriculture, although known as the backbone of the Indian economy, is facing crisis in terms of production. One of the major issues in the agriculture sector is the growth of weeds among the crops. They compete with the desired plants for various resources and hence their growth must be inhibited. At present weeds are removed either manually, which is a time consuming and labour intensive task, or herbicides are being sprayed uniformly all over the field to keep them under check. Spraying of herbicide is very inefficient as the chemical contributes less to weed control and cause contamination of the environment. The main objective of this work is a weed control system that differentiates the weed from crops and restricts weed growth alone by the precise removal of the weed. This is implemented by capturing the images of the field at regular intervals and processing them with a Raspberry Pi board by making use of an image processing algorithm to differentiate the desired plants from the weeds. This is based on various features like colour and size of the crop and weed. Once the weeds are identified and located correctly through image processing, a signal is transmitted from the Raspberry Pi board to turn on the weed cutting system. The selective activation of the weed removal system helps in the precise removal of the weeds and this provides a better environment for the desired plants to grow well. 03 30 2020 347 352 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.B3679.038620 https://www.ijrte.org/portfolio-item/B3679078219/ Department of Electronics and Communication Engineering, Mar Athanasius College of Engineering, Kothamangalam, India. Linet Rose A. S. Thomas Mohan Department of Electronics and Communication Engineering, Mar Athanasius College of Engineering, Kothamangalam, India. Dr. Vinodkumar Jacob Department of Electronics and Communication Engineering, Mar Athanasius College of Engineering, Kothamangalam, India. Aquaponics is a farming method, which is the combination of aquaculture and hydroponics, which grows fish and plants together in one integrated system. The fish waste provides an organic food source for the plants, and the plants naturally filter the water for the fish. The purpose of this project is to build an automatic fish feeder system for aquaponics using image processing technique with the help of Wireless Sensor Network (WSN). This helps the farmers to reduce manual effort and safeguard a balanced food delivery. The number of fish in the pond may vary over time, so the amount of fish feed provided need to be changed. As there will be a large number of fish moving randomly in a pond, the manual tracking and counting of fish is very difficult. It is a time consuming and erroneous process. This work focuses on developing a system that tracks and counts the fish in the pond for aquaponics. This automatic fish identification system processes the video of the entire pond and makes it easier to estimate the count of fish. The frames from the video are processed using Raspberry-Pi board and the count of fish is transmitted through Wi-Fi. Such a system would assist to feed the fish accordingly. Based on the count transferred, a fish feeder mechanism is controlled using NodeMCU at the other end of the Wi-Fi. The amount of fish feed remaining in the feeding box is informed to the user through mobile application. 03 30 2020 835 840 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.B3685.038620 https://www.ijrte.org/portfolio-item/B3685078219/ SCOPE, VIT, Vellore, India Bharat Gupta Shefali Bhardwaj SENSE, VIT, Vellore, India K. Govinda SCOPE, VIT, Vellore, India Rajkumar. R SCOPE, VIT, Vellore, India Stock market is an important part of the economy of any country. People generally use stocks as an investment and try to get a profit out of them. Investing in the stock market is a huge risk-return. One bad decision can lead to huge losses while one good decision can result in good profit. To make sure that our investment decisions are not bad, one must choose the right stock. In this project we have tried to do the same. We have incorporated the functions to view data like closing prices, highs, lows etc. Using this data one can know the general trend of some stock but how to know whether the stock is risky or not. In this paper, we implemented two algorithms, namely Bootstrap method and Monte Carlo simulation for risk analysis. 03 30 2020 2629 2633 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.C4193.038620 https://www.ijrte.org/portfolio-item/C4193098319/ Assistant Professor, Department of Computer Science and Engineering, Kongunadu College of Engineering and Technology, Trichy, Tami Nadu, India. Dhivya S Anguraju K Assistant Professor, Department of Computer Science and Engineering, Kongunadu College of Engineering and Technology, Trichy, Tami Nadu, India. Suvitha K Assistant Professor, Department of Computer Science and Engineering, Kongunadu College of Engineering and Technology, Trichy, Tami Nadu, India. Preethi P Assistant Professor, Department of Computer Science and Engineering, Kongunadu College of Engineering and Technology, Trichy, Tami Nadu, India. Saravanabhavan C Head of the Department , Department of Computer Science and Engineering, Kongunadu College of Engineering and Technology, Trichy, Tami Nadu, India. Medicinal services industry has become huge business. The medicinal services industry creates a lot of social insurance information day by day that can be utilized to separate data for foreseeing malady that can happen to a patie future while utilizing the treatment history and wellbeing information This concealed data in the human services information will be later utilized for full of feeling basic leadership for patient's wellbeing. Additionally, this region need improvement by utilizing the educational information social insurance. Significant test is the manner by which to extricate the data from these information on the grounds that the sum is enormous so a few information mining and machine learning systems can be utilized. Additionally, the normal result a-n extent of this venture is that in the event that malady can be anticipated, at that point lord y treatment can be given to the patients which can lessen the danger of life and spare existence of patient and cost t get treatment of ailments can be decreased up somewhat by duke acknowledgment. For this expert problem, a probabilistic displaying and profound learning approach will prepare a Long Short-Term Memory(LSTM) repetitive neural network and two convolutional neural systems for forecast of illness which is named as an upgraded half and half algorithm. The fast adoption of electronic wellbeing records has made an abundance of new information about patients, which is a goldmine for improving the understanding of human health. The above strategy is utilized to anticipate epidemic ailments utilizing quiet treatment history and wellbeing data. The parameter thought about is that this mode lessens test and train set blunder and increment information enlargement with better accuracy of 73.6%. 03 30 2020 353 359 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.C6450.038620 https://www.ijrte.org/portfolio-item/C6450098319/