The voting system in the world has been characterised with many fundamental challenges, thereby resulting to a corrupt contestant winning an election. Researchers have been emotionally, physically, socially and intellectually concerned about the election malpractices recorded at various levels of electing a representative. Questions on how corrupt stakeholders in elections could be prevented from fraudulent activities such as rigging and impersonation called for discussion and answers. Consequences of declaring a corrupt contestant as a winner are bad governance, insecurities and diversification of public funds for personal gains. There must be approaches to tackle the problems of voting systems. This paper focused on a comprehensive review of electronic voting systems by different scholars as a platform for identifying shortcomings or drawbacks towards the implementation of a highly secured electronic voting system. The methods used by different scholars were technically reviewed so as to identify areas that need improvement towards providing solutions to the identified problems. Furthermore, countries with history on the adoption of e-voting systems were reviewed. Based on the problems identified from various works, a novel for future work on developing a secured electronic voting system using fingerprint and visual semagram techniques was proposed.

Secondary schools as part of the foundational level of education cannot afford to lag behind in using multimedia to improve the intellectual and creative capabilities among the teachers and students. This study investigated multimedia technologies as modern pedagogical tools for strategic improvement on the teaching and learning process. The study adopted a descriptive survey design. The population was the senior secondary school students and teachers in Kuje Area Council of Federal Capital Territory (FCT), Nigeria. A simple random sampling technique was used to select 250 students and 100 teachers. Cronbach's alpha statistical tool was used to obtain a reliability coefficient of 0.83 on validated questionnaires which were distributed to collect data from the respondents. Statistically, mean, standard deviation, percentage and partial correlation were used to answer the research questions while t-test and Chi-Square were used to test the postulated hypotheses at 0.05 level of significance. The findings showed that television sets, projectors and computers were the major multimedia facilities used for teaching and learning in the council, multimedia facilities had a high influence on teaching and learning. It was gathered that multimedia enriched teaching cognitive skills and psychomotor skills and developed concretization of abstraction on any subject matter. Some recommendations were made which included the provision of financial support to procure multimedia facilities to schools towards the attainment of educational objectives, provision of subsiding policies by the government on the importation of multimedia facilities, employment of competent and experienced technical staff should be employed to solve a series of technical problems in using multimedia facilities. Experimental research design on the effectiveness of multimedia facilities as modern pedagogical tools for strategic improvement on teaching and learning was proposed for future work.

Allocation of Driving Licensing in Nigeria in the past was done haphazardly and as a result drivers with poor driving culture were usually allocated driving license. This probably was followed by unprecedented wave of road traffic accidents with attendant human and material losses. In other to reduce these losses, the federal road safety commission at its inception introduced some measures to curb the issue of licensing. This work, in line with the technological trend proposed an automated licensing scheme to improve on the efficiency of the previous system. The system was tested with 50 applicants and the result presented.

Security over the years remains a major concern of all especially the law enforcement agencies. One way of arresting this concern is to be able to reliably detecting deception. Detecting deception remains a difficult task as no perfect method has been found for the detection. Past researches made use of a single cue (verbal or nonverbal), it was found that examining combinations of cues will detect deception better than examining a single cue. Since no single verbal or nonverbal cue is able to successfully detect deception the research proposes to use both the verbal and nonverbal cues to detect deception. Therefore, this research aims to develop a KNN model for classifying the extracted verbal, nonverbal and VerbNon features as deceptive or truthful. The system extracted desired features from the dataset of Perez-Rosas. The verbal cues capture the speech of the suspect while the nonverbal cues capture the facial expressions of the suspect. The verbal cues include the voice pitch (in terms of variations), frequency perturbation also known as jitters, pauses (voice or silent), and speechrate (is defined as the rate at which the suspect is speaking). The Praat (a tool for speech analysis) was used in extracting all the verbal cues. The nonverbal features were extracted using the Active Shape Model (ASM). The work was implemented in 2015a MatLab. The classification was done using KNN model. KNN performed well with VerbNon dataset with a percentage score of 96.2%.