Over the years, the alarming growth of the internet and its wide acceptance has led to increase in security threats. In Nigeria today, several internet assisted crimes known as cybercrimes are committed daily in various forms such as fraudulent electronic mails, pornography, identity theft, hacking, cyber harassment, spamming, Automated Teller Machine spoofing, piracy and phishing. Cybercrime is a threat against various institutions and people who are connected to the internet either through their computers or mobile technologies. The exponential increase of this crime in the society has become a strong issue that should not be overlooked. The impact of this kind of crime can be felt on the lives, economy and international reputation of a nation. Therefore, this paper focuses on the prominent cybercrimes carried out in the various sectorsin Nigeria and presents a brief analysis of cybercrimes in tertiary institutions in Ekiti-State. In conclusion, detection and prevention techniques are highlighted in order to combat cybercrimes in Nigeria.

Translation is the transfer of the meaning of a text from one language to another. It is a means of sharing information across languages and therefore essential for addressing information inequalities. The work of translation was originally carried out by human translators and its limitations led to the development of machine translators. Machine Translation is a subfield of computational linguistics that investigates the use of computer software to translate text or speech from one natural language to another. There are different approaches to machine translation. This paper reviews the two major approaches (single vs. hybrid) to machine translation and provides critique of existing machine translation systems with their merits and demerits. Several application areas of machine translation and various methods used in evaluating them were also discussed. Our conclusion from the reviewed literatures is that a single approach to machine translation fails to achieve satisfactory performance resulting in lower quality and fluency of the output. On the other hand, a hybrid approach combines the strength of two or more approaches to improve the overall quality and fluency of the translation.

The soil is composed of several nutrients which are important for the effective growth of plants. Nitrogen, phosphorus, and potassium are micronutrients which are very important for plant growth. There have been several methods and soil tests developed to test the compositions of these nutrients in the soil. Interpreting the results gotten from such tests has been a herculean task for farmers. Employing the use of a soft computing method to interpret such result would be a noble idea. In this paper, we describe the use of fuzzy logic to interpret the values of nitrogen, phosphorus, and potassium (NPK) gotten from conventional soil test to know their levels in the soil and predict possible NPK inputs.

No abstract

One of the most crucial challenges that Nigeria banks have to face is in the jurisdiction of customers’ satisfaction. Customers’ satisfaction has become one of the most important factors of success in today’s banking industry in Nigeria. Today Nigeria banks customer’s increases every day, as it is essential for many Nigerian to have proper savings with any bank of their choice; if the performance of bank falls short of their expectations, the very survival of such bank would be difficult. In this paper, a   framework for customer relationship management for Nigeria banks using big data analytics approach was developed. Qualitative research was used to identify customer satisfaction through customer management system information publish annually.  The data were collected from complaint data for financial report 2017 from the Customer Relationship Management System for WEMA Bank Plc. The data were analyzed using excel spread sheet and later converted into CSV and ARFF file format respectively. Data were  exported into WEKA for data analytics which then generated results. The formulated hypotheses are subjected to empirical test using Logistic regression and Machine learning. This new strategy provided solution of these problems identified. Keywords: Data Analytics, Linear regression, Banking,  Customer Satisfaction