International Journal of Innovation in Engineering
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Classification of Mammogram Images by Using SVM and KNN
Get PDFBreast cancer is a fairly diverse illness that affects a large percentage of women in the west. A mammogram is an X-ray-based evaluation of a woman's breasts to see if she has cancer. One of the earliest prescreening diagnostic procedures for breast cancer is mammography. It is well known that breast cancer recovery rates are significantly increased by early identification. Mammogram analysis is typically delegated to skilled radiologists at medical facilities. Human mistake, however, is always a possibility. Fatigue of the observer can commonly lead to errors, resulting in intraobserver and interobserver variances. The image quality affects the sensitivity of mammographic screening as well. The goal of developing automated techniques for detection and grading of breast cancer images is to reduce various types of variability and standardize diagnostic procedures. The classification of breast cancer images into benign (tumor increasing, but not harmful) and malignant (cannot be managed, it causes death) classes using a two-way classification algorithm is shown in this study. The two-way classification data mining algorithms are utilized because there are not many abnormal mammograms. The first classification algorithm, k-means, divides a given dataset into a predetermined number of clusters. Support Vector Machine (SVM), a second classification algorithm, is used to identify the optimal classification function to separate members of the two classes in the training dat
Financial Deepening and Economic Growth in Nigeria: Evidence from 1982 โ 2019
Get PDFThis paper examines the impact of financial deepening on economic growth in Nigeria from 1982 โ 2019. The objective of the study is to look at the impact of credit to private sector, money supply and gross domestic savings on the economic growth in Nigeria. Secondary data were collected based on the model used in the research work and unit root test was conducted on the data to test their stationary, after which we perform co-integration test to analyze the long run relationship among the variables. The result obtained from our empirical analysis shows that all financial deepening variables possesses a significant impact on the economic growth in Nigeria, that is, money supply, credit to private sector and gross domestic savings financial deepening proxies has significant and positive effect on economic growth. The study therefore recommends that government and the monetary authorities should make policies which would help to boost the saving culture of the people. This could be done by increasing the deposit rate which would lure the people to deposit their money in banks thereby increasing the supply of loanable funds. This would lead to a fall in interest rate and eventually rise in investment
Prediction of Weld Strength in Power Ultrasonic Spot Welding Process Using Artificial Neural Network (ANN) and Back Propagation Method
Get PDFIn this presented work, the employment of artificial neural network (ANN) connected with back propagation method was performed to predict the strength of joining materials that carried out by using ultrasonic spot welding process. The models which created in this study were investigated and their process parameters were analysed. These parameters were classified and set as input variables like for example applying pressure, time of duration weld and trigger of vibrating amplitude while weld strength of joining dissimilar materials (Al-Cu) is set as output parameters. The identification from the process parameters are obtained using number of experiments and finite element analyses based prediction. The results of actual and numerical are accurate and reliability, however its complexity has significant effect due to sensitive to the condition variation of welding processes. Therefore, the needed for an efficient technique like artificial neural network coupled with back propagation method is required to use the experiments as an input data in simulation of ultrasonic welding process, finding the adequacy of modeling process in prediction of weld strength and to confirm the performance of using mathematical methods. The results of the selecting non-linear models show a noticeable potency when using ANN with back propagation method in providing high accuracy compared with other results obtained by conventional models
Occupational Risks of Firefighters in Jakarta: Job Safety Analysis Approach
Get PDFCity Administration Fire and Rescue Service sub-department East Jakarta. It is one of the public organizations which, in carrying out its duties, is very wide with high risk. If this is not handled properly, events caused by unsafe actions and unsafe conditions can harm officers, organizations, and environmental safety. This study aims to analyze and determine the work risks of firefighters at the City Administration Fire and Rescue Service sub-department East Jakarta. The method in this study uses qualitative analysis and quantitative combining methods (numerical data) as well as the facts presented by research informants and then analyzed using the Job Safety Analysis (JSA) method based on the theory of use techniques JSA. The results of this study show that there are four types of work identified as risks in the field assignment section. The conclusion stipulates that the work of firefighters has many potential fire hazards with high severity and a risk rating of 40% in the High-Risk category, 50% in the Moderate Risk category, and as much as 10% risk in the Low-Risk category. Organizations are recommended to evaluate the work process of firefighters by increasing the completeness of PPE and increasing the competence of officers
Treatment of cracking in rigid highway pavements using knowledge-based System
Get PDFHighway engineers encounter numerous problems in the quality of rigid pavements; cracking types are the most critical ones. Thus, deciding on appropriate controlling measures represents an essential mission. Normally, cracking problems affect the quality of pavements as well as increase initial cost. Although experts can control and solve these problems by using their tacit knowledge, novice engineers cannot. Transfer of expertise from experts to novices is difficult pavements domain. Therefore, a system which experts could use to share their experience with other engineers both during and after a project is necessary. Without such transfer of expertise and knowledge, novices may repeat mistakes that experts have already learned to avoid. Documentation, classification, and computerization of these problems, their causes, treatments, and preventive actions can be very helpful in controlling and preventing them. This study aims to describe the development of a knowledge-based system that can be used by novice engineers to overcome cracking of rigid pavements. The system can also be used as an instructional tool for prospective highway engineers. In addition, the system can archive and organize raw knowledge from experts to be utilized by engineers who work in this field. Domain experts can use the system to share their experiences. The knowledge includes problems encountered in the domain, their causes, preventive actions, treatments, and their effects, which were presented in a classified format. The knowledge was presented in the form of rules and coded in software by using Visual Basic. The system was tested by different users involved in highway engineering, including experts and novice engineers. The mean values of the overall system evaluation by the four types of users based on the 5-point Likert scale were 4 and 4.5 respectively. These values reflect high level of satisfaction by end-users
The problem of production-distribution under uncertainty based on Vendor Managed Inventory
Get PDFIn this paper, a problem of managed inventory by the vendor in the production-distribution supply chain is presented based on the scenario. The main purpose of presenting the model of maximizing producer profit in a three-level supply chain network consisting of various strategic and tactical decisions under uncertainty. Due to the nonlinearity and NP-Hardness of the problem, meta-heuristic genetic algorithms, Whale optimization algorithm and league champions algorithm have been used. The results of problem solving show the high efficiency of meta-heuristic algorithms compared to accurate methods in solving the above model. So that the maximum percentage of relative differences between the methods mentioned with GAMS is less than 1%.Also, by solving the sample problems in larger sizes, it was observed that the league champions algorithm has the highest efficiency in terms of achieving the optimal value of the target function in a shorter time than the other algorithms used, with a useful weight of 0.998
Recent Technology for Recycling of Used Diapers Waste
Get PDFThe purpose of this paper is to provide information related to waste technology processing. The study was conducted using a literature review technique. This review provides an in-depth discussion of the impact and the recent breakthrough in improving problems arising from the generation and disposal of soiled diapers. Various technologies were highlighted, especially the safer use and cleaner technology, such as biodegradation and composting to maximizing recycle process at a cheaper cost. Moreover, pyrolysis shows an opportunity to improve the efficiency of the recycling process used diapers. Finally, recycling is achievable with an economic incentive if the costs of a series of complicated processes are lower than the value of the end product. Therefore, the best technology for recycling becomes a big consideration. The consideration of which process to use may vary from national and industrial outlook in terms of rate of return, total cost, and environmental. The challenge of recycling is to reduce the cost of waste treatment while providing high-quality final products and need to focus on developing practical and environmentally friendly recovery methods
Energy Storage for High Speed Trains: Economical and Energy Saving Evaluation
Get PDFIncreasing the utilization rate of regenerative braking energy in rail systems is one of the ongoing applications increasing in significance in recent years. In rail systems, braking is made with two ways, mechanical and electrical. While the energy released due to mechanical braking cannot be recovered, the energy released due to electrical braking can be reused as regenerative braking energy. This regenerative braking energy varies according to the dynamics of the system and it can be given back to the grid, stored in storage devices or burned in resistors (it is not desired). This study develops a novelty algorithm within the scope of this objective and provides the calculation of the regenerative braking energy recovery rate and then making a decision for storage or back to grid of this energy. Afterwards, the regenerative braking energy was calculated with the help of this algorithm for Eskisehir-Ankara and Ankara-Eskisehir trips in two different passengers (load) scenarios, using the YHT 65000 high-speed train, which was chosen as a case study. Then, with a decision maker added to this classical regenerative braking energy algorithm, it will be decided whether this energy will be stored or forward back into the grid for the purpose of providing non-harmonic energy to the grid
Entrepreneurship Education and Entrepreneurial Intention of University Undergraduate Students in Benue State Nigeria
Get PDFThis study examined the effect of entrepreneurship education on entrepreneurial intention of university undergraduate students in Benue State, Nigeria. The study specifically examined the effect of entrepreneurship education on start-up intention and innovation intention among university undergraduate students in Benue State, Nigeria. The adopted the cross-sectional survey design involving university undergraduates in three universities in Benue State. The population of the study comprised of 957 final year students from Faculty of Management Sciences from JS Tarka University Makurdi (224), Benue State University Makurdi (631) and University of Mkar, Mkar (102). Applying Taro Yameneโs formula, a sample size of 282 was realized. The study employed questionnaire as the major instrument for data collection. The items on the questionnaire were all measured on a 5-point scale ranging from 1=strongly disagree to 5=strongly agree. Result of pilot study showed that the reliability for each of the constructs was above 0.70. Simple linear regression analysis was used in testing the data gathered from the survey. Analysis was done with the aid of Statistical Package for Social Sciences (SPSS 23). Findings revealed that entrepreneurship education has significant positive effect on start-up intention and innovation intention of university undergraduate students in Benue State, Nigeria. The study concludes that university undergraduate studentsโ intentions toward entrepreneurship can be enhanced using entrepreneurship education. This study is an initial call to elaborate an appropriate model of entrepreneurship education in universities in Benue State that will present a more practical and effective entrepreneurship educatio
Forecasting Startup Return using Artificial Intelligence Methods and Econometric Models and Portfolio Optimization Using VaR and C-VaR
Get PDFIn this paper, we have tried to study the main role of startups in economy, their characteristics, main goals and etc. The main goal of article is prediction of startup's return using artificial intelligence methods such as genetic algorithm (GA) and artificial neural network (ANN). Some global indices such as S&P500, DJAI, and economic indicators such as 10 years Treasury yield, Wilshire 5000 Total Market Full Cap Index along with some other special indicators in startups like team, idea, timing and etc. are used as input variables. GA is used as feature selection and finding the most important variables. ANN is used as an optimization model and prediction of startup's returns. We used econometric models such as regression analysis. We have estimated Value at risk (VaR) and Conditional Value at risk (C-VAR) for considered portfolios including three startups (public company) such as Dropbox, Inc. (DBX), Scout24 SE (G24.DE) and TIE.AS and optimal portfolio formation. The results show that AI based methods are more powerful in prediction of startup's return. On the other hand, VaR and C-VaR models are very beneficial approach in minimizing risk and maximizing return