An Overview of Machine Learning within Embedded and Mobile Devices-Optimizations and Applications.

Embedded systems technology is undergoing a phase of transformation owing to the novel advancements in computer architecture and the breakthroughs in machine learning applications. The areas of applications of embedded machine learning (EML) include accurate computer vision schemes, reliable speech recognition, innovative healthcare, robotics, and more. However, there exists a critical drawback in the efficient implementation of ML algorithms targeting embedded applications.

Large-scale radio propagation path loss measurements and predictions in the VHF and UHF bands.

For decades now, a lot of radio wave path loss propagation models have been developed for predictions across different environmental terrains. Amongst these models, empirical models are practically the most popular due to their ease of application. However, their prediction accuracies are not as high as required.

SMOTE-DRNN: A Deep Learning Algorithm for Botnet Detection in the Internet-of-Things Networks.

Nowadays, hackers take illegal advantage of distributed resources in a network of computing devices (i.e., botnet) to launch cyberattacks against the Internet of Things (IoT).

COVID-19 pandemic and emerging plastic-based personal protective equipment waste pollution and management in Africa.

The threat of plastic waste pollution in African countries is increasing exponentially since the World Health Organisation declared the coronavirus infection as a pandemic. Fundamental to this growing threat are multiple factors, including the increased public consumption for single-use plastics, limited or non-existence of adequate plastic waste management infrastructures, and urbanisation. Plastics-based personal protective equipment including millions of surgical masks, medical gowns, face shields, safety glasses, protective aprons, sanitiser containers, plastics shoes, and gloves have been widely used for the reduction of exposure risk to Severe Acute Respiratory Syndrome (SARS) Coronavirus 2 (SARS-CoV-2).

Analysis of key performance indicators of a 4G LTE network based on experimental data obtained from a densely populated smart city.

Key performance indicator (KPI) data provide candidate information required for effective network planning, performance analysis and optimization. However, inadequate KPI data could limit efficient network planning leading to escalating operational cost, and this could adversely affect the subscribers of the network. To this end, this article presents radio frequency (RF) measurements and evaluation of KPIs taken at 1876.

Nigeria's preparedness for internet of everything: A survey dataset from the work-force population.

The article presents statistical facts on Nigeria's preparedness for Internet of everything. Copies of structured questionnaire were administered to 163 workers in Lagos State. Using descriptive statistics and charts (bar chart and histogram), the paper revealed that most of the respondents are aware of the concept of internet of everything, perceive that Nigeria is prepared for an internet enabled society and already have devices that can help them access the internet from where they are.

Trends and patterns of broadband Internet access speed in a Nigerian university campus: A robust data exploration.

Efficient broadband Internet access is required for optimal productivity in smart campuses. Besides access to broadband Internet, delivery of high speed and good Quality of Service (QoS) are pivotal to achieving a sustainable development in the area of education. In this data article, trends and patterns of the speed of broadband Internet provided in a Nigerian private university campus are largely explored.

Gender disparity in admissions into tertiary institutions: Empirical evidence from Nigerian data (2010-2015).

Gender equality in access to higher education is an important factor in building a sustainable world. Although a good number of countries across the globe have achieved parity in primary education between boys and girls, the target is yet to be widely attained at tertiary level of education. In this data article, empirical data on yearly admissions into accredited tertiary institutions in Nigeria are extensively explored to reveal the existence of gender gaps in the national admission process.

Statistical analysis of frequencies of opponents׳ eliminations in Royal Rumble wrestling matches, 1988-2018.

The datasets and their analyses presented in this paper revealed some frequencies of opponents׳ eliminations by entrance or order of elimination in Royal Rumble wrestling matches from 1988 to 2018. The frequency of eliminations by the order of entrant is quite different from order of eliminations. Statistical methods, algorithms and machine learning methods can be applied to the raw data to obtain more hidden trend not included in this article.

Influence of talent retention strategy on employees׳ attitude to work: Analysis of survey data.

In this data article, an analysis on the strategies for talent retention in Covenant University and the corresponding effects on employees' attitude to work was presented. The study population included the academic staff of Covenant University, which has a population of 530 employees, but a sample size was determined using Yamen׳s formula. The data obtained through survey questionnaires were analysed using Statistical Package for Social Sciences (SPSS).

Exploration of daily Internet data traffic generated in a smart university campus.

In this data article, a robust data exploration is performed on daily Internet data traffic generated in a smart university campus for a period of twelve consecutive (12) months (January-December, 2017). For each day of the one-year study period, Internet data download traffic and Internet data upload traffic at Covenant University, Nigeria were monitored and properly logged using required application software namely: FreeRADIUS; Radius Manager Web application; and Mikrotik Hotspot Manager. A comprehensive dataset with detailed information is provided as supplementary material to this data article for easy research utility and validation.

Datasets linking ethnic perceptions to undergraduate students learning outcomes in a Nigerian Tertiary Institution.

This data article represents academic performances of undergraduate students in a select Nigerian Private Tertiary institution from 2008 to 2013. The 2413 dataset categorizes students with respect to their origins (ethnicity), pre-university admission scores and Cumulative Grade Point Averages earned at the end of their study at the university. We present a descriptive statistics showing mean, median, mode, maximum, minimum, range, standard deviation and variance in the performances of these students and a boxplot representation of the performances of these students with respect to their origins.

Comparative assessment of data obtained using empirical models for path loss predictions in a university campus environment.

Empirical models are most widely used for path loss predictions because they are simple, easy to use, and require less computational efficiency when compared to deterministic models. A number of empirical path loss models have been developed for efficient radio network planning and optimization in different types of propagation environments. However, data that prove the suitability of these models for path loss predictions in a typical university campus propagation environment are yet to be reported in the literature.

The role of gender on academic performance in STEM-related disciplines: Data from a tertiary institution.

This data article presents data of academic performances of undergraduate students in Science, Technology, Engineering and Mathematics (STEM) disciplines in Covenant University, Nigeria. The data shows academic performances of Male and Female students who graduated from 2010 to 2014. The total population of samples in the observation is 3046 undergraduates mined from Biochemistry (BCH), Building technology (BLD), Computer Engineering (CEN), Chemical Engineering (CHE), Industrial Chemistry (CHM), Computer Science (CIS), Civil Engineering (CVE), Electrical and Electronics Engineering (EEE), Information and Communication Engineering (ICE), Mathematics (MAT), Microbiology (MCB), Mechanical Engineering (MCE), Management and Information System (MIS), Petroleum Engineering (PET), Industrial Physics-Electronics and IT Applications (PHYE), Industrial Physics-Applied Geophysics (PHYG) and Industrial Physics-Renewable Energy (PHYR).

Datasets on demographic trends in enrollment into undergraduate engineering programs at Covenant University, Nigeria.

In this data article, we present and analyze the demographic data of undergraduates admitted into engineering programs at Covenant University, Nigeria. The population distribution of 2649 candidates admitted into Chemical Engineering, Civil Engineering, Computer Engineering, Electrical and Electronics Engineering, Information and Communication Engineering, Mechanical Engineering, and Petroleum Engineering programs between 2002 and 2009 are analyzed by gender, age, and state of origin. The data provided in this data article were retrieved from the student bio-data submitted to the Department of Admissions and Student Records (DASR) and Center for Systems and Information Services (CSIS) by the candidates during the application process into the various engineering undergraduate programs.

Incidence of cassava mosaic disease and associated whitefly vectors in South West and North Central Nigeria: Data exploration.

Cassava mosaic disease (CMD) is one of the most economically important viral diseases of cassava, an important staple food for over 800 million people in the tropics. Although several species associated with CMD have been isolated and characterized over the years, several new super virulent strains of these viruses have evolved due to genetic recombination between diverse species. In this data article, field survey data collected from 184 cassava farms in 12 South Western and North Central States of Nigeria in 2015 are presented and extensively explored.

Citation analytics: Data exploration and comparative analyses of of Open Access and Subscription-Based publications indexed in (2014-2016).

Citation is one of the important metrics that are used in measuring the relevance and the impact of research publications. The potentials of citation analytics may be exploited to understand the gains of publishing scholarly peer-reviewed research outputs in either Open Access (OA) sources or Subscription-Based (SB) sources in the bid to increase citation impact. However, relevant data required for such comparative analysis must be freely accessible for evidence-based findings and conclusions.

Smart campus: Data on energy generation costs from distributed generation systems of electrical energy in a Nigerian University.

This data article presents comparisons of energy generation costs from gas-fired turbine and diesel-powered systems of distributed generation type of electrical energy in Covenant University, Ota, Nigeria, a smart university campus driven by Information and Communication Technologies (ICT). Cumulative monthly data of the energy generation costs, for consumption in the institution, from the two modes electric power, which was produced at locations closed to the community consuming the energy, were recorded for the period spanning January to December 2017. By these, energy generation costs from the turbine system proceed from the gas-firing whereas the generation cost data from the diesel-powered generator also include data on maintenance cost for this mode of electrical power generation.

Path loss dataset for modeling radio wave propagation in smart campus environment.

Path loss models are often used by radio network engineers to predict signal coverage, optimize limited network resources, and perform interference feasibility studies. However, the propagation mechanisms of electromagnetic waves depend on the physical characteristics of the wireless channel. Therefore, efficient radio network planning and optimization requires detailed information about the specific propagation environment.

Learning analytics: Dataset for empirical evaluation of entry requirements into engineering undergraduate programs in a Nigerian university.

In Nigerian universities, enrolment into any engineering undergraduate program requires that the minimum entry criteria established by the National Universities Commission (NUC) must be satisfied. Candidates seeking admission to study engineering discipline must have reached a predetermined entry age and met the cut-off marks set for Senior School Certificate Examination (SSCE), Unified Tertiary Matriculation Examination (UTME), and the post-UTME screening. However, limited effort has been made to show that these entry requirements eventually guarantee successful academic performance in engineering programs because the data required for such validation are not readily available.

Learning analytics for smart campus: Data on academic performances of engineering undergraduates in Nigerian private university.

Empirical measurement, monitoring, analysis, and reporting of learning outcomes in higher institutions of developing countries may lead to sustainable education in the region. In this data article, data about the academic performances of undergraduates that studied engineering programs at Covenant University, Nigeria are presented and analyzed. A total population sample of 1841 undergraduates that studied Chemical Engineering (CHE), Civil Engineering (CVE), Computer Engineering (CEN), Electrical and Electronics Engineering (EEE), Information and Communication Engineering (ICE), Mechanical Engineering (MEE), and Petroleum Engineering (PET) within the year range of 2002-2014 are randomly selected.

Data on the key performance indicators for quality of service of GSM networks in Nigeria.

In this data article, the Key Performance Indicators (KPIs) for Quality of Service (QoS) of Global System for Mobile Communications (GSM) networks in Nigeria are provided and analyzed. The data provided in this paper contain the Call Setup Success Rate (CSSR), Drop Call Rate (DCR), Stand-alone Dedicated Channel (SDCCH) congestion, and Traffic Channel (TCH) congestion for the four GSM network operators in Nigeria (Airtel, Etisalat, Glo, and MTN). These comprehensive data were obtained from the Nigerian Communications Commission (NCC).

Received signal strength and local terrain profile data for radio network planning and optimization at GSM frequency bands.

The behaviour of radio wave signals in a wireless channel depends on the local terrain profile of the propagation environments. In view of this, Received Signal Strength (RSS) of transmitted signals are measured at different points in space for radio network planning and optimization. However, these important data are often not publicly available for wireless channel characterization and propagation model development.

Smart campus: Data on energy consumption in an ICT-driven university.

In this data article, we present a comprehensive dataset on electrical energy consumption in a university that is practically driven by Information and Communication Technologies (ICTs). The total amount of electricity consumed at Covenant University, Ota, Nigeria was measured, monitored, and recorded on daily basis for a period of 12 consecutive months (January-December, 2016). Energy readings were observed from the digital energy meter (EDMI Mk10E) located at the distribution substation that supplies electricity to the university community.