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Author(s):
Robinson Mbato, Kabari Ledisi G..
Page No : 1-11
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Predicting Foreign Exchange Using Digital Signal Processing
Abstract
The forex market is one associated with so much volatility and can lead to grave financial losses if not properly understood. To understand the market is to study the price patterns from previous years or months and make predictions from the rate of falling and rising. There have been so much researches aimed at developing a predictive model for the FOREX market, however, no model has been able to handle the market volatility while predicting future rates accurately. In this work, we have developed a digital processing model for predicting foreign exchange using ARIMA and Artificial Neural Network algorithms. We used price datasets for five currencies namely: USD, Swiss Pounds, Yen, Euro and Franc, gotten from the Central Bank of Nigeria (CBN) website. The data ranged from a period of 20 years. The model was simulated using MATLAB software. The study performed excellently in terms of time (26 seconds) and minimal errors (0.7). This work could be beneficial to FOREX traders and to the entire research community.
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Author(s):
Bello Abdulazeez Omeiza, Kabari Ledisi G..
Page No : 12-21
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Digital Signal Processing for Predicting Stock Prices
Abstract
With the exponential growth of big data and data warehousing, the amount of data collected from various stock markets around the world has increased significantly. It is now impossible to process and analyze data using mathematical techniques and basic statistical calculations to forecast trends such as closing and opening prices, as well as daily stock market lows and highs. The development of smart and automated stock market forecasting systems has made significant progress in recent years. Digital signal processing is required for analysis and preprocessing because of the accuracy and speed with which these large amounts of data must be processed and analyzed. In this paper, we evaluate some of these predictive algorithms based on three parameters such as speed, accuracy and complexity, we analyze the data using the dataset from kaggle.com and we implement these algorithms using pythons. The results of our analysis in this paper shows a significant correlation between the yearly prices until the year 2018 where there is a significant increase in stock price.
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Author(s):
Olubukola D. Adekola, Stephen O. Maitanmi, Funmilayo A. Kasali, Ayokunle Omotunde, Oyebola Akande, Oduroye Ayorinde, Wumi Ajayi, Yaw Mensah.
Page No : 22-30
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Movie Success Prediction Using Data Mining
Abstract
The movie industry is arguably one of the biggest entertainment sectors. Nollywood, the Nigerian movie industry produces tons of movies for public consumption, but only a few make it to box-office or end up becoming blockbusters. The introduction of movie success prediction can play an important role in the industry not only to predict movie success but to help directors and producers make better decisions for the purpose of profit. This study proposes a movie prediction model that applies data mining techniques and machine learning algorithms to predict the success or failure of an upcoming movie (based on predefined parameters). The parameters needed for predicting the success or failure of a movie include dataset needed for the process of data mining such as the historical data of actors, actresses, writers, directors, marketing and production budget, audience, location, release date, and competing movies on same release date. This model also helps movie consumers to determine a blockbuster, hit, success rating and quality of upcoming movies before deciding on a movie ticket. The data mining techniques was applied to Internet Movie Database MetaData which was initially passed through cleaning and integration process.
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Author(s):
Ayokunle A. Omotunde, Martin Ejenobor, Ernest E. Onuiri, Izang Aaron, Ajayi Wumi, Adekola Olubukola.
Page No : 31-41
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Automated Teller Machine-Based Voting System
Abstract
Voting is a critical element of any election which involves the processes of electing leaders or representatives into positions of authority in a democratic system of government. In most developing countries of the world, this process is usually marred with challenges of confidentiality, Integrity, availability and auditability such as falsification of results, identity theft, theft of ballot boxes, multiple voting problems, over voting, and electoral fraud. This paper presents a framework for Automated Teller Machine-based voting system that solves the aforementioned challenges of the current voting system by using the existing Automated Teller Machines and debit cards issued for voting. Going further to implement the solution proposed in this paper will enhance and guarantee the credibility of the electoral processes and show a true reflection of the wishes of the people.
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Author(s):
Edison Kagona, Fahadi Bakaki, Makanto Mary Ngubteino, Djenny Bakwanamaha, Mayaza Issa Sarah.
Page No : 42-79
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Poultry Farm Management Information System (A Case Study of Biyinzika Poultry International Limited)
Abstract
This report discusses a Poultry Farm Management Information System of Biyinzika Poultry Farm International Limited. The software is sectioned into the sales management section, Purchase management section, Product management section.
This system was designed to overcome the problems identified with the current Poultry Farm Management information system of Biyinzika Poultry Farm International Limited. The Problems with the current system include: lack of information sharing in real-time, manual report generation on sales, purchases and the products, slow in information delivery especially in the determination of stock levels after transaction processes, a lot of time consumption, increasing the company costs, and lack of effective data recovery in case of any disaster such as fire outbreak, flood, damages among others.
Literature relating to the Poultry Information Management Systems were reviewed. The legacy system used in the company was also studied in more details. With this, more requirements for the Poultry Farm Management Information System were obtained and the system was designed and implemented. The interfaces for the new system were implemented using HTML, Bootstrap and Java Script. MYSQL was also used for implementing the system database while PHP was used to create interactivity with the database. After the implementation, the new system was then tested and validated.
When developing the system, the focus was on making the whole process of Information management in the poultry farm faster, more convenient and efficient for the company. This system automates the current poultry farm management information system in the organization.