Predicting Multi-class Customer Profiles Based on Transactions: a Case Study in Food Sales

Predicting the class of a customer profile is a key task in marketing, which enables businesses to approach the right customer with the right product at the right time through the right channel to satisfy the customer's evolving needs. However, due to costs, privacy and/or data protection, only the business' owned transactional data is typically available for constructing customer profiles. Predicting the class of customer profiles based on such data is challenging, as the data tends to be very large, heavily sparse and highly skewed. We present a new approach that is designed to efficiently and accurately handle the multi-class classification of customer profiles built using sparse and skewed transactional data. Our approach first bins the customer profiles on the basis of the number of items transacted. The discovered bins are then partitioned and prototypes within each of the discovered bins selected to build the multi-class classifier models. The results obtained from using four multi-class classifiers on real-world transactional data from the food sales domain consistently show the critical numbers of items at which the predictive performance of customer profiles can be substantially improved

Winners’ notes. Using Multi-Resolution Clustering for Music Genre Identification

Article describing a less technical version of our winning entry in the ISMIS 2011 Music Genre competitio

Resilience of the Internet of Things (IoT) from an Information Assurance (IA) Perspective

Internet infrastructure developments and the rise of the IoT Socio-Technical Systems (STS) have frequently generated more unsecure protocols to facilitate the rapid intercommunication between the plethoras of IoT devices. Whereas, current development of the IoT has been mainly focused on enabling and effectively meeting the functionality requirement of digital-enabled enterprises we have seen scant regard to their IA architecture, marginalizing system resilience with blatant afterthoughts to cyber defence. Whilst interconnected IoT devices do facilitate and expand information sharing; they further increase of risk exposure and potential loss of trust to their Socio-Technical Systems. A change in the IoT paradigm is needed to enable a security-first mind-set; if the trusted sharing of information built upon dependable resilient growth of IoT is to be established and maintained. We argue that Information Assurance is paramount to the success of IoT, specifically its resilience and dependability to continue its safe support for our digital economy

Have Usability and Security Trade-offs in Mobile Financial Services (MFS) become Untrustworthy?

The trade-off between Usability and Security has been well researched with various models proposed on how best to improve Usability without jeopardizing Security and vice visa. Usable Security has become a key factor in Mobile Financial Services (MFS), the new frontier for mobile phones utilisation. However, have the compromises gone too far? The trustworthiness of MFS system has already slowed down new adoption and impacted ongoing security trust issues and user confidence in spite of potential MFS benefits for its users. To understand this growing lack of trust with MFS, we need to comprehend the nature of Usable Security in assuring the behaviours of MFS users and determine the right trade-off to improve trust whilst facilitating future uptake. We conducted an empirical survey of 698 user’s experience of MFS and here present our findings of this investigation for further synthesis towards proposing practical control elements to assure Usable Security in MFS

Design and simulation of an effective backup power supply for academic institutions in Nigeria: A case study of NDA postgraduate school

This research work is aimed to mitigate the adverse effect of numerous portable generators used in academic environments due to the unstable power supply experienced in Nigeria. Data for the study on the existing backup, availability hours from the national grid, and load demand for the area of study were obtained from the residents of the campus, facility managers, and Kaduna Distribution Company as the grid supplier from August 2017 to December 2020. The average load of the campus was obtained to be 80kW. These were used as a baseline to obtain the required size and quantity of material to generate the backup power needed. A total ampere-hour requirement of the battery to be used was obtained to be 4,278.07Ah considering the average battery depth of discharge of 80%. This resulted in a total number of cells required to be 134 considering a battery with a 200Ah rating and a nominal voltage rating of 48V. A solar photovoltaic (PV) system rating of 166.4kW is required to sufficiently charge the battery bank and also serve the load. This amounts to a minimum of 5 panels per string connected in series and 34 number panels per string connected in parallel based on which the total number of panels required summed up to 666. The inverter rating for the load was obtained to be 150 kVA with a total load of 100 kVA, an efficiency of 80%, and an average future expansion of 20 %. A diesel generator rating of 100kVA with a starting kVA rating of 113.64kVA is required to efficiently serve the load considering future expansion of 1.1 and operating efficiency of 80 %. These obtained parameters were simulated using MATLAB/Simulink to test the feasibility of the backup systems. The generation cost of each backup was calculated based on which solar PV with battery bank has an initial energy generation cost of 81.9 ₦/kWh and a future energy generation cost of 0.27 ₦/kWh while diesel generator has an initial energy generation cost of 1602.04 ₦/kWh and a future energy generation cost of 8.07 ₦/kWh as such, PV has the least energy cost and more economical for the academic environment

Mathematical Modelling of Leachate Production from Waste Contained Site

In this work, mathematical models of leachate production from Waste Contained Site (WCS) was developed and validated using the existing experimental data with aid of MATLAB, 2007a. When the leachate generation potentials (Lo) were 100m3, 80m3 and 50m3, the maximum amount of leachate generated were about 2920m3, 2338m3 and 1461m3 for about 130 days respectively. It was noted that as the leachate percolates through a selected distance, the concentration keeps decreasing for one dimensional flow in all the cases considered. Decreasing in concentration continues until a point was reached when the concentration was almost zero and later constant. The effects of diffusivity, amount of organic content present within the waste and gravity, as cases, were also considered in various occasions during the percolation. Comparison of their effects was also taken into account. In case of gravity at constant diffusivity, decrease in concentration was not rapid but gradually while much organic content in the waste caused the rate of leachate production to be rapid; hence, giving rise to a sharp sloped curve. It can be concluded that gravity influences the rate of change in the concentration of the leachate generation as the leachate percolate downward to the underground water. When the diffusivity and gravity are put into consideration, the concentration of the leachate decreases gradually and slowly

Design of experiments platform for online simulation model validation and parameter updating within digital twinning

The process of developing a virtual replica of a physical asset usually involves using standardized parameter values to provide simulation of the physical asset. The parameters of the virtual replica are also continuously validated and updated over time in response to the physical asset's degradation and changing environmental conditions. The parametric calibration of the simulation models is usually made with trial-and-error using data obtained from manual survey readings of designated parts of the physical asset. Digital Twining (DT) has provided a means by which validating data from the physical asset can be obtained in near real time. However, the time-consuming process of calibrating the parameters so the simulation output of the virtual replica matches the data from physical asset persists. This is even more so when the calibration of the simulator is performed manually by analysing the data received from the physical system using expert knowledge. The manual process of applying domain knowledge to update the parameters is error prone due to incompleteness of the knowledge and inconsistency of the validation/calibration data. To address these shortcomings, an experimental platform implemented by integrating a simulator and a scientific software is proposed. The scientific software provides for the reading and visualisation of the simulation data, automation of the simulation running process and provide interface of the relevant validation and adaptive algorithmics. This comprehensive integrated platform provides an automated online model validation and adaptation environment. The proposed platform is demonstrated using BEASY - a simulator designed to predict protection provided by a cathodic protection (CP) system to an asset, with MATLAB as the scientific software. The developed setup facilitates the task of model validation and adaptation of the CP model by automating the process within a DT ecosystem

Factors Affecting Ballability of Mixture Iron Ore Concentrates and Iron Oxide Bearing Wastes in Metallurgical Processing

Iron oxide bearing wastes (IOBS) are produced at every part of processing stage of sinter, molten iron and steel production. They are hard to handle and in many cases are stockpiled only to be a source of environmental pollution. However, they can be balled into pellets. Pellets characterized by good ballability values are transportable and recyclable as they can withstand stress without disintegrating back to dust. Yet, ballability is affected by certain factors like the grain sizes of the materials, the moisture and binder contents of the ball mix, wettability of the balled materials and the processing perimeters of the granulator. The objective of this research work is to investigate the factors affecting ballability of mixture of iron ore concentrates and iron oxide bearing wastes in metallurgical processing. The parameters under consideration were: grain size of materials, the moisture contents, speed of balling disc, IOBS and bentonite (binder) contents of the balled mix. The investigation was carried out by balling different volume fractions of mix containing iron oxide concentrate and IOBS using a balling disc and testing the resulting balls for green compressive strength using an universal testing machine. It was found that the ballability of the mixture of iron ore concentrate and IOBS increases as grain sizes of the materials reduce but increases as the moisture contents and IOBS content increase up to an optimum value of moisture content in the mix before it starts to reduce. The ballability also increases along with the speed of the granulator (balling disc) within the limit of this work. An increase in ballability with a slight raise in bentonite content in the mix was observed as well

An approach for adaptive model performance validation within digital twinning

The validation of the operationality of models is considered a crucial step in the model development process. Recent developments in Digital Twinning (DT) enable the online availability of operational data from the physical asset required for operational validation. The benefits of DT in situations where operational validation has formed a basis for model adaptation has also been demonstrated. However, these benefits within DT have not been fully utilized due to the lack of an approach for benchmarking the required quantity, quality and diversity of validation data and performance metrics for online model validation and adaptation. Therefore, there is a need for a framework for benchmarking validation data and metrics requirements during model validation in different domains. An approach for benchmarking the required quantity, quality and variability of validation data and performance metric(s) for online model adaptation within DT is proposed. The approach is focused on addressing the problem of parameter(s) uncertainty of a predictive model within its uncertainty boundary. It involves generating virtual test models, a primary and another reference model for the performance evaluation of one compared to the another with the benchmarked validating data and metrics within DT. This process is repeated until the dataset and/or metric(s) are promising enough to validate primary model against the reference model. The proposed approach is demonstrated using BEASY - a simulator designed to predict protection provided by a cathodic protection system to an asset. In this case, a marine structure is the focus of the study, where the protection potentials to prevent corrosion are predicted over the life of the structure. The algorithm(s) for the approach are provided within a Scientific Software (MATLAB) and integrated to the simulator-based cathodic-protection model

DEVELOPMENT OF A WEARABLE PRESSURE BANDAGE SYSTEM FOR SCORPION STING

This paper presents a wearable pressure bandage system (ScorpioBand) to discourage unsafe first aid practices by scorpion sting victims. A pressure bandage is utilized to apply pressure over the entire surface around the sting point to reduce the likelihood of scorpion envenomation and pressure transducers were used to acquire bandage pressure signals. A Flexiforce pressure sensor interfaced with a PIC16F873A microcontroller based embedded device are the core components of the wearable system. A real-time simulation using myRIO embedded device and LabVIEW software was used to design the developed system. The developed ScorpioBand prototype was implemented as a waistband and it triggers a visual signal when a safe pressure limit is exceeded during application of the pressure bandage. The performance of the developed system was evaluated experimentally and an average bandage pressure of 48.96 mmHg was achieved with three layers of the bandage in 90% of the trial cases conducted by first-time users. The implication of the results is that inexperienced users in rural communities can apply the developed wearable bandage system to achieve the required bandage pressure for scorpion sting