Students in this modern age find engineering courses taught in the university very abstract and difficult, and cannot relate theoretical calculations to real life scenarios. They consequently lose interest in their coursework and perform poorly in their grades. Simulation of classroom concepts with simulation software like MATLAB, were developed to facilitate learning experience. This paper involves the development of a virtual laboratory simulation package for teaching data communication concepts such as coding schemes, modulation and filtering. Unlike other simulation packages, no prior knowledge of computer programming is required for students to grasp these concepts.

Accurate energy metering and billing is a challenge in some developing countries. In Nigeria, the issues of inadequate power generation, transmission and distribution infrastructure are recurrent problems, coupled with inefficient energy metering which is a major problem that results in residential energy consumers being billed unfair energy charges by the Electricity Distribution Companies (DISCOs) for unused energy, and this has been termed “crazy bill”. For the energy sector to be effective, energy bills should be based on the actual energy usage and likewise customers must pay for used energy. To achieve this, the Nigerian Electricity Regulatory Commission (NERC) recommended the installation of prepaid meters for all customers, but as at today, there is no full compliance with this regulation. Power supply is grossly unreliable, and this has affected power quality due to frequent load shedding and power outages. The dataset presented in this article captures the type of apartment, the type of electrical appliances used by occupant, the average monthly energy bill paid for electricity, the use or non-use of alternative energy sources, the type of alternative energy sources used, and the type of energy meter used by sampled residents of the Ota community in Ogun State, Nigeria. The dataset was acquired using an investigative questionnaire to survey the residential consumers within the sampled space.

The technology, Long Term Evolution (LTE) developed by 3rd Generation Partnership Project is considered an improved standard in mobile communications when compared to previously attained network standards. LTE with prospects of decreased latency levels and support of downlink and uplink transmission at data rates exceeding 100Mbps and 50Mbps, an effective handover framework needs to be put in place to improve quality of service rendered to the network users and decrease wastage of network resources. This study examines several works carried out on a handover criteria (hysteresis margin) needed for designing an effective handover framework. This margin is based on the received signal strength between both target and serving eNodeBs, and its proper determination amongst other advantages mitigates the rate of unnecessary and repeated handover (ping-pong effect). The model presented in this research integrates the artificial neural network (ANN) mechanism into the determination of hysteresis margin in the LTE handover process which is to minimize handover delay and ping-pong taking into consideration the speed of the user equipment (UE).

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Abstract-Handover is the process of achieving Continuous service as the user moves in-between cells. Handover is needed during cell-crossing or/and signal quality degradation in the current channel. During handover, there is switching among networks and thereby transfer users to another network or BS [45]. The fundamental of 5G is heterogeneous networks and in such networks, seamless handover in non-negotiable [46]. Phases of handover are: discovery, decision and execution. Network discovery finds appropriate network that satisfies user desired QoS. Decision phase is when the handover should take place (also known as a handover initiation phase). These phases determine seamlessness of the handover. Wrong time of initiation leads to unnecessary handover or call drop rate is increased and thereby result to poor QoS. Therefore, handover should take place at the right time by trigger handover decision considering all the parameters properly to ensure QoS is not affected and unnecessary handover is avoided.