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We investigate the effect of passivation contouring, surface roughness, and sidewall etch tapering on the FEM modelling accuracy of mm-wave couplers in CMOS BEOL. It is found that accurate passivation contouring leads to a marginal improvement of 0.15 dB in peak coupling prediction accuracy, but introducing a sidewall taper of 104ᵒ can improve the prediction of peak coupling by up to 0.37 dB. Including surface roughness of 5 % and 10 % of metal thickness did not have a notable improvement on prediction of peak coupling.

This paper presents recent radio frequency (RF) engineering work performed for the Ghana Radio Telescope, specifically concerning receiver and electromagnetic component design and analysis. An upgraded so-called Mark II receiver, currently nearing the end of its development phase, improves the bandwidth by approximately 100% and 30% for the 5 and 6.7 GHz bands, respectively. A proposed new wideband orthomode transducer (OMT) design is presented to replace the existing Intermediate Circular Orbit (ICO) satellite system components, which are known to add extra noise. Also contributing to the system noise temperature is the antenna and spillover temperatures. Electromagnetic simulation data is used to determine these parameters, showing that the antenna can contribute up to 32 K to the system noise temperature near the horizon. The resulting predicted sensitivity of the telescope is presented and is in the range of 4.6 to 5 m2/K assuming a receiver temperature of 90 K and an aperture efficiency of 70%.

Protecting power and distribution equipment from major faults will aid in preventing infrastructure damage and unnecessary power supply losses. Battery operated tripping units are used to open (trip) or re-close HT breakers in a substation during power supply failures. Short bursts of high currents from a battery bank in the substation switch room is used to energize open and close coils of HT breakers. A proposed 30 V, 10 A charger with an adequate battery bank can be an ideal sized unit for HT breaker tripping applications in a space constrained substation container (750 mm x570 mm x280 mm), placed in remote areas. To ensure easy unit access and serviceability, the batteries, control system and battery charger power module are all integrated into a single enclosed mountable cabinet unit. The dimensions and mass of the proposed housing cabinet was minimized to optimize space utilization and easy mobility. The housing cabinet can then be wall mounted or even placed on the floor, allowing it to be easily moved in the substation from one location to another. The PC board is also conformal coated to protect against corrosion due to humidity and a properly designed solder mask avoids unintentional short circuits. The battery charger makes use of a thyristor controlled full-wave bridge rectifier to charge the battery bank and will also include appropriate diagnostic faultfinding warning alarms. The proposed 30 V, 10 A battery charger system addresses some shortcomings of current battery charger implementations at remote substations, especially when the system is required to operate at higher ambient temperatures. This proposed battery charger system makes it possible to use up to 25 nickel cadmium cells or 15 lead acid cells to continuously supply 30 V at 10 A for fast charging and/or standing loads or both. In addition, several features have been added to assist technicians in determining potential battery charger faults in order to reduce breakdown times.

The COVID-19 outbreak has been declared as one of the worst global disasters. The impact of COVID-19 is visible in many sectors, such as health, logistics, and many other critical aspects of our daily lives. Due to the continuous rapid spread of COVID-19, many countries have imposed lockdown measures. As a result of the lockdown, many organizations are devising measures to remain operational during this period and beyond. One of the visible challenges of the lockdown to organizations lies in their technological readiness strategies, to operate this period. One of the feasible responses, many organizations are implementing is allowing workers to work from home and long-distance learning. Technologies such as Virtual Private Networks (VPNs) and Video Conferencing can enable workers to work from home. During this period cloud service providers have also noticed a big rise in the usage of cloud-based solutions. On the other hand, due to cost-effectiveness and usability, the concept of Mobile Cloud Computing (MCC) is rapidly gaining ground in the cloud and mobile computing communities. Cloud-based solutions, such as MCC can be deemed a possible solution to the damage that can be caused by the lockdown and beyond, to many organizations. Currently, however, there is no feasible MCC adoption model that guides the process of its adoption, thus the need to propose one. In this paper, an MCC adoption model is proposed, as well as a case scenario to which MCC can be useful is demonstrated.

A soft robotic actuator of modular construction has been designed where multiple repeated asymmetric deforming units are connected in series to alter the final deformed shape. Using a Genetic Algorithm that can change the orientation of each articulating unit by 180°, a combination of orientations is calculated to yield what best resembles the desired profile that is specified by means of a continuous function. To improve simulation run times for the finite element analyses, a reduced order model is presented where the 3D model is simplified to that of a 2D plane strain approximation. This preliminary work shows that by using an advanced computational design tool interesting behaviour can be achieved whilst using only a very simple asymmetric deforming modular unit. A physical actuator was manufactured and the deformation compared to the numerical models.

Computer programming courses are an essential facet of STEM education, confronted by many pressing challenges. Higher education (HE) students struggle to master programming principles resulting in unsatisfactory pass rates, student retention and low levels of student engagement. Gamification in programming courses has been recognized as a prospective technique that could improve student participation as well as impact learning in a positive way. There is currently a shortage of review studies published in the last two years (2018-2019) that focus specifically on the gamification of programming courses in HE. The aim of this paper is to bridge this gap and to provide a comprehensive review of literature concerning studies that focused on the usage of gamification systems in the teaching of programming courses in HE from 2014 until 2019. Results indicate that the most popular gamification elements that were used in the reviewed studies were leaderboards, followed by points, badges and levels. Additionally, in terms of the tools or instruments that were used to implement gamification solutions, it was discovered that the development of a new gamification platform and the usage of existing gamification tools were the most wide-spread method for gamification implementation. Lastly, from the studies that were reviewed, it was evident that gamification of HE programming courses had a very positive impact on student engagement, student programming knowledge and student motivation. This review paper fills a void in existing literature and could therefore serve as a valuable resource for academe that consider gamifying HE programming courses.

The relationship between negative and positive connotations with regard to malware in the cloud is rarely investigated according to the prevailing literature. However, there is a significant relationship between the use of positive and negative connotations. A clear distinction between the two emanates when we use the originally considered malicious code, for positive connotation like in the case of capturing keystrokes in a proactive forensic purpose. This is done during the collection of digital evidence for Digital Forensic Readiness (DFR) purposes, in preparation of a Digital Forensic Investigation (DFI) process. The paper explores the problem of having to use the keystrokes for positive reasons as a piece of potential evidence through extraction and digitally preserving it as highlighted in ISO/IEC 27037: 2012 (security approaches) and ISO/IEC 27043: 2015 (legal connotations). In this paper, therefore, the authors present a technique of how DFR can be achieved through the collection of digital information from the originally considered malicious code. This is achieved without modifying the cloud operations or the infrastructure thereof, while preserving the integrity of digital information and possibly maintain the chain of custody at the same time. The paper proposes that the threshold of malicious code intrusion in the cloud can be transformed to an efficacious process of DFR through logical acquisition and digitally preserving keystrokes. The experiment-tested keystrokes have shown a significant approach that could achieve proactive forensics.

Techniques applied in response to detrimental digital incidents vary in many respects according to their attributes. Models of techniques exist in current research but are typically restricted to some subset with regards to the discipline of the incident. An enormous collection of techniques is actually available for use. There is no single model representing all these techniques. There is no current categorisation of digital forensics reactive techniques that classify techniques according to the attribute of function and nor is there an attempt to classify techniques in a means that goes beyond a subset. In this paper, an ontology that depicts digital forensic reactive techniques classified by function is presented. The ontology itself contains additional information for each technique useful for merging into a cognate system where the relationship between techniques and other facets of the digital investigative process can be defined. A number of existing techniques were collected and described according to their function – a verb. The function then guided the placement and classification of the techniques in the ontology according to the ontology development process. The ontology contributes to a knowledge base for digital forensics – essentially useful as a resource for the various people operating in the field of digital forensics. The benefit of this that the information can be queried, assumptions can be made explicit, and there is a one-stop-shop for digital forensics reactive techniques with their place in the investigation detailed.

In past years, cryptography has been considered a difficult task to achieve on sensor nodes for the Internet of Energy (IoE) owing to the resource-constrained nature of 8- and 16-bit microcontroller units (MCUs). Previous attempts at implementing cryptographic services on wireless sensor nodes have resulted in high power consumptions, long operating times, and the depletion of memory resources. Over the last decade, however, processors for the IoT and IoE have improved; with increased operating power and memory resources, longer data bus widths and low-power consumption. With the improvements made to processors suitable for building IoT devices, the question remains whether endpoint nodes should still be considered capable of only supporting the most lightweight of cryptographic mechanisms. We evaluate the capabilities of a device family (Cortex-M series processors) commonly found in programmable logic controllers to implement standard, verified software cryptographic libraries in terms of execution times, memory occupation, and power consumption in order to determine their adequacy for use in smart grid applications. It was seen that the MCUs were easily capable of running standard cryptographic algorithms. However, the use of public key cryptography may still require the inclusion of a hardware crypto accelerator or the use of a secure MCU implementing public key cryptography; as the relatively long execution times seen during the operation of ECDSA, for example, could be intolerable within a real time IoE application.

Climate control is an everyday challenge. With the rapid surge in electricity prices over the past few years, air conditioning operating expenses necessarily increased. The effects, furthermore, of global warming result in increased cooling, and therefore, energy demand. The purpose of this paper is to propose two models that simulate a natural air cooling system. The first model simulates cooling through an earth to air heat exchanger, utilising the soil as a heat sink. The second model simulates the transient cooling of a control volume, which receives cooled air and is open to the environment. A scale model of an earth-to-air heat exchanger system was designed, constructed and used to verify results from the proposed models. Following verification, a real-life size heat exchanger was simulated in order to cool down a room of 60 m3 within one hour, using only the underground soil as a heat sink. Results showed that a room at an initial 30 °C can be cooled down to 20.5 °C with a 1.2 m underground heat exchanger and down to 17.8 °C if the length is increased to 2.0 m. Only fan power is needed to increase the air's dynamic pressure, resulting in flow conditions. As a result a coefficient of performance between 60 and 80 can be achieved.

The main objective of this paper is to determine the requirements for IoT forensics. The development of requirements for Internet of Things (IoT) forensics will make a groundbreaking contribution to the current body of knowledge. The secondary objective of the paper is the formulation of a Digital Forensic Readiness (DFR) model for the implementation of IoT forensics. The model aims to address the shortfalls of the requirements, as well as incorporate various Digital Forensic (DF) techniques that can be used in IoT environments. The model is presented in theoretical as well as graphical form. The model is then discussed to highlight various areas of possible new research. The model is furthermore evaluated to determine the level of contribution it makes to the current body of research.

The ability for the smart microgrid to allow for the independent generation and distribution of electrical energy makes it an attractive solution towards enabling universal access to electricity within developing economies. Distributed Ledger Technologies (DLTs) are being considered as an enabling technology for the secure energy trade market however the high processing, energy and data exchange requirements may make them unsuitable for the Industrial Internet of Things technologies used in the implementation of the microgrid and the limited connectivity infrastructure in developing technologies. This work serves to assess the suitability of DLTs for IIoT edge node operation and as a solution for the microgrid energy market by considering node transaction times, operating temperature, power consumption, processor and memory useage, in addition to mining effort and end user costs.

Internet of Things (IoT) is a relatively new wave of technology that is increasingly becoming popular in many different organisations globally. In essence, IoT is synonymous to networking technology, which allows individuals to connect to different devices in order to facilitate easy sharing of resources as well as communication. However, the one major difference between computer networking technology and IoT is the heterogeneity of data involved and distributed nature of IoT that involves self-actuating devices. Furthermore, the heterogeneity and distributed nature of IoT further brings complexity of the IoT ecosystem. For this reason, IoT ecosystem presents a big challenge to both Digital Forensic (DF) investigators and Law Enforcement Agencies (LEAs) when trying to implement DF techniques. What makes digital forensic investigations even harder in IoT ecosystem is its vastness and the rapidity with which it is expanding globally. This paper, thus, proposes an Integrated Digital Forensic Investigation Framework (IDFIF-IoT) for an IoT ecosystem which is an extension of an initially proposed generic Digital Forensic Investigation Framework for Internet of Things (DFIF-IoT). Note that, the main emphasis in this paper is on proposing an integrated framework with acceptable digital forensic techniques that are able to analyse Potential Digital Evidence (PDE) from the IoT-based ecosystem that may be used to prove a fact.

This paper provides a Common Vulnerability Scoring System (CVSS) metric-based technique for classifying and analysing the prevailing Computer Network Security Vulnerabilities and Threats (CNSVT). The problem that is addressed in this paper, is that, at the time of writing this paper, there existed no effective approaches for analysing and classifying CNSVT for purposes of assessments based on CVSS metrics. The authors of this paper have achieved this by generating a CVSS metric-based dynamic Vulnerability Analysis Classification Countermeasure (VACC) criterion that is able to rank vulnerabilities. The CVSS metric-based VACC has allowed the computation of vulnerability Similarity Measure (VSM) using the Hamming and Euclidean distance metric functions. Nevertheless, the CVSS-metric based on VACC also enabled the random measuring of the VSM for a selected number of vulnerabilities based on the [Ma-Ma], [Ma-Mi], [Mi-Ci], [Ma-Ci] ranking score. This is a technique that is aimed at allowing security experts to be able to conduct proper vulnerability detection and assessments across computer-based networks based on the perceived occurrence by checking the probability that given threats will occur or not. The authors have also proposed high-level countermeasures of the vulnerabilities that have been listed. The authors have evaluated the CVSS-metric based VACC and the results are promising. Based on this technique, it is worth noting that these propositions can help in the development of stronger computer and network security tools.

Proper management of electronic waste is becoming a major challenge for many developing countries, particularly African countries. This paper reviews the movement of e-waste between nations, and primarily to African countries. It also focuses on the challenges and issues that these countries then face to manage the e-waste in a safe manner, i.e. so that it does not harm the environment and human health. The researchers argues that, in most African countries, e-waste is often improperly managed—this is due to lack of knowledge and awareness on how e-waste impacts upon the environment and people's health. They conclude that people must be educated on the harmful effects posed by e-waste on the environment and human health.

This paper reviews electronic waste and its disposal methods. It also explores hazardous effects that e-waste have on human health, animals and the environment; it contains, for example, toxic metals. The ever-increasing growth of e-waste is one of the biggest threats of the 21st century; it is therefore a priority worldwide. There is no single best method to eradicate e-waste and related problems. Lack of suitable education, resulting in low levels of awareness, drives improper management of e-waste. This study therefore concludes that awareness and suitable education is the most important aspect that influences appropriate and proper management of e-waste, i.e. good (“green”) information technology practices.

Web based training software has been used extensively as one of the instruction methods to train users in basic digital literacy skills. One such example is the simulated online learning environment. Due to the fact that students are able to interact with real time simulations, these environments are referred to as Interactive Online Learning Environments (IOLEs). At most universities in South Africa, students from all faculties are obligated to take an introductory digital literacy course during their first year of study. Due to the large numbers of students in these introductory courses, universities are predominantly making use of IOLEs to assist with the teaching and assessment of MS Office skills. Limited research has been conducted on the constructs that may contribute to the continuous use intention of MS Office IOLEs by students in higher education. The main objective of this paper is to propose a model for the continuous use intention of IOLEs. Three theoretical models were combined in order to develop this model, and include Flow Theory, Information System Expectation-Confirmation Model and the DeLone and McLean Information Systems Success Model. Results reveal that the following constructs should be included in the model to predict continuous use intention: satisfaction, perceived usefulness, perceived enjoyment, perceived ease of use and focused immersion. In addition, students' satisfaction toward MS Office IOLEs was determined by information quality, perceived usefulness and perceived enjoyment. Understanding the constructs that influence students continuous use towards MS Office IOLEs could be used by institutions, businesses and instructors to focus their efforts on improving specific aspects of these platforms that would lead to higher levels of student engagement with them. This, in turn, could lead to higher levels of academic success as students engage more with the course content and improve their MS Office skills, one of the most important skills required by all types of employers today.

Analysing memory can be a daunting task. This is especially apparent for a digital forensic investigator that may not have the technical expertise to perform the memory analysis. A solution to this is a one-click tool that can scan and analyze a memory image and produce useful information in a digital forensic investigation. Such a tool can be created as a plug-in for the well-known investigative tools. This study, therefore, developed a tool that can be used as a plug-in for Autopsy (or any python-based forensic tool). The developed tool is evaluated based on the existing metrics of tool evaluation, and the result shows the applicability of the tool for memory analysis. By automating the analysis of a memory image, this study asserts that the number of mistakes made during an investigation can be reduced. Furthermore, the study asserts that the time and task complexity required for a memory forensics can be reduced by the automated process.

The task of autonomously gripping delicate objects such as fresh produce remains a challenge even in modern robotics. Current robotics grippers are mostly made of mechanical linkages and actuators which follow very structured trajectories. As these exhibit little mechanical compliance they can readily apply too much pressure as a point load, leading to blemishing or bruising of produce (eg. kiwifruit). In order to overcome this, this paper proposes a soft-robotic approach, which has the ability to morph and conform around the grasped object. This increases the contact area between the object and the gripper, resulting in a more equal distribution of force, and a lower effective contact pressure. Additionally, this allows for a more secure grip to be achieved. The proposed gripper design is inspired by the soft-touch of the human hand, which is presently the most suitable manipulator for fruit-picking tasks. The soft robotic device is manufactured from a composite of Ecoflex 00–30 Room Temperature Vulcanisation Rubber and polymer mesh. This paper describes the specification, design, manufacture and validation of the novel soft robotic gripper as it emerged from the conceptual phase into its application domain (kiwifruit gripping and manipulation). The physical results are crossexamined with those from FEA analysis.

This work considers a combined structural-electromagnetic analysis of large dish reflector antennas typically used in radio astronomy. The effect of gravitational deformation on the radio telescope is quantified by a structural analysis conducted with a finite element solver. The deformed geometry is then analysed using a computational electromagnetic package from which the performance degradation can be assessed. This offers key insights into the operation of the radio telescope under the influence of external forces, such as gravity.

We present a novel full-band W-band capacitively loaded transmission line phase shifter. A classical slow-wave microstrip (S-MS) transmission line is loaded with tunable FET capacitors to enable continuous phase tuning. The design is implemented in GlobalFoundries US 8HP 130 nm SiGe BiCMOS process with the 7 metal layer option. A maximum phase shift of 95.59° is achieved with an insertion loss of −5 dB ± 1.5 dB across the band, yielding a FoM of 17.3. The design occupies a chip area of 0.67 mm2. This solid-state solution presents a suitable alternative to micro-electromechanical systems (MEMS) loaded line phase shifters without the need for high tuning voltages.

This paper presents the electromagnetic modelling and supporting results of the African VLBI Network (AVN) Ghana radio telescope at the operating frequencies of 5 and 6.7 GHz. Working from limited technical data, we establish suitable geometrical parameters for the unshaped version of the Cassegrain system, including modelling and rotation of the four mirrors within the slanted beam-waveguide (BWG). The geometry implemented in GRASP (General Reflector Antenna Software Package) produces several performance values including the effects of the BWG, struts and mechanical tolerances. It is shown that the theoretical maximum gain and aperture efficiency at 5 GHz are 63.09 dBi and 72.56%, respectively. The corresponding values at 6.7 GHz are 65.80 dBi and 75.42%, respectively.

The use of slender tool holders is inherent to boring and turning operations. As a result, large vibrations, known as chatter, may arise, resulting in poor surface finishing and decrease in the tool life. Therefore, chatter is a recurring issue that is in need of modeling and controlling in order to improve the industry's productivity. The nonlinear and cutting friction forces, together with the mode coupling that arises from a symmetric tool holder, can lead to these extreme vibrations and possibly chaotic motion under a certain set of parameters. These nonlinearities must be studied and experimentally analyzed to be considered in chatter control mechanisms in turning. It is well known that passive shunt circuits increase the system's damping and can be used to control chatter. This paper presents a simple lumped nonlinear model of the tool holder embedded to a piezoelectric patch and an analysis of such model with and without the passive shunt circuit. The set of parameters is chosen in order to simulate a chatter condition. The resulting phase diagrams are qualitatively compared to experimental data obtained from a real turning operation made using a CNC lathe. The results show that the model is capable of appropriately simulating the chatter vibration.

Cloud computing paradigm continues to revolutionize the way business processes are being conducted through the provision of massive resources, reliability across networks and ability to offer parallel processing. However, miniaturization, proliferation and nanotechnology within devices has enabled digitization of almost every object which eventually has seen the rise of a new technological marvel dubbed Internet of Things (IoT). IoT enables self-configurable/smart devices to connect intelligently through Radio Frequency Identification (RFID), WI-FI, LAN, GPRS and other methods by further enabling timeously processing of information. Based on these developments, the integration of the cloud and IoT infrastructures has led to an explosion of the amount of data being exchanged between devices which have in turn enabled malicious actors to use this as a platform to launch various cybercrime activities. Consequently, digital forensics provides a significant approach that can be used to provide an effective post-event response mechanism to these malicious attacks in cloud-based IoT infrastructures. Therefore, the problem being addressed is that, at the time of writing this paper, there still exist no accepted standards or frameworks for conducting digital forensic investigation on cloud-based IoT infrastructures. As a result, the authors have proposed a cloud-centric framework that is able to isolate Big data as forensic evidence from IoT (CFIBD-IoT) infrastructures for proper analysis and examination. It is the authors' opinion that if the CFIBD-IoT framework is implemented fully it will support cloud-based IoT tool creation as well as support future investigative techniques in the cloud with a degree of certainty.

The need to interconnect devices over the Internet has led to the development of smart devices, home automation and the Internet of Things (IoT), which at the time of writing this paper is still an emerging phenomenon. As a result of IoT explosion, home appliances are able to be fully connected and controlled through an Intelligent Digital Network (IDN). Nevertheless, futuristic refrigerators will be able to connect to the Internet, which in turn will be able to accept a number of applications. While this brings effectiveness and convenience of connecting household appliances to the Internet, the threat level that is posed by interconnecting these appliances is high because a number of vulnerabilities exist that have potential to be exploited. In this paper, the authors show how a “smart refrigerator” can be used as an instrument that is able to propagate digital crimes like identity theft, spamming, privacy, data loss and so forth through creation of IoT bot. IoT bot is a robot network that can target connected multimedia centres. As a result, the authors have proposed a Smart Refrigerator Crime Propagation (SRCP) Model that shows how vulnerabilities are able to be exploited. Additionally, the authors have identified possible countermeasures as a route that can help to protect sensitive and critical information in an IoT-based environment. The proposed approaches/countermeasures have digital forensic capabilities that are able to filter periodic communication to and from the refrigerator in a forensic readiness approach. It is the authors' opinion that if the approaches are adhered to fully they may help to proactively prevent propagation of IoT-based digital crimes using connected home appliances.

So much research that has been done concerning eGovernment (eGov) frameworks. However, little focus has been put towards the use of Digital Forensics (DF) to conduct a proper Digital Forensic Investigation (DFI) in eGovernment frameworks. One reason for this may be because current DF tools were not developed to handle different eGov frameworks and their setup specifically. Therefore, gathering, examining and the general analysis of potential digital evidence when presented in courts of law becomes a great challenge to law enforcement officers/agencies and DF investigators (DFi). The problem addressed in this paper is, at the time of writing this paper, there exists no properly acceptable DFI framework that can be used to carry out a standard DFI in an eGovernment platform specifically for the case of the Republic of Uganda. Therefore, the author of this paper proposes a digital forensic investigation framework for eGov structure specifically focussing on Uganda. The proposed framework is based on the international standard for digital forensic investigation ISO/lEC 27043:2015. The author of this paper is of the belief that in future, the proposed framework can easily be incorporated into future DF tools development thereby facilitating the design of effective DFI tools in eGov platforms. Also, this research is meant to capture the attention of government officials in Uganda so as to fully develop and adopt a standard eGov forensic investigation process for Uganda.

This paper offers the design and prototype technology of a tactile sensor, based on the principle of surface texture recognition, capable of monitoring slip in robotic grasping. The sensor has been mounted onto a parallel gripper jaw of a robot. The integrated system of tactile sensor, gripper, robot and the system control, in real life experiments, has proven itself capable of slip detection and adjusting adequate grasping force preventing objects from falling down. Several experiments have been carried out with the newly developed system for grasping a number of various object-samples. Success rate of the system for testing in slip detection and adjusting adequate grasping force in experiments was about 85% in average.

User attribution process based on human inherent dynamics and preference is one area of research that is capable of elucidating and capturing human dynamics on the Internet. Prior works on user attribution concentrated on behavioral biometrics, 1-to-1 user identification process without consideration for individual preference and human inherent temporal tendencies, which is capable of providing a discriminatory baseline for online users, as well as providing a higher level classification framework for novel user attribution. To address these limitations, the study developed a temporal model, which comprises the human Polyphasia tendency based on Polychronic-Monochronic tendency scale measurement instrument and the extraction of unique human-centric features from server-side network traffic of 48 active users. Several machine-learning algorithms were applied to observe distinct pattern among the classes of the Polyphasia tendency, through which a logistic model tree was observed to provide higher classification accuracy for a 1-to-N user attribution process. The study further developed a high-level attribution model for higher-level user attribution process. The result from this study is relevant in online profiling process, forensic identification and profiling process, e-learning profiling process as well as in social network profiling process

Coal ore isn't a uniform material. In order to optimize the coal liberation process it is necessary to classify a coal ore sample into its constituent components as quickly and cheaply possible. This paper investigates whether it is feasible to employ image processing and pattern recognition to segment a photographic image of coal ore into its various mineral components prior to the sample being crushed. The key to solving this classification problem is to model the visual texture of the various coal components by means of a low-dimensional texture space consisting of two main dimensions, namely: roughness and regularity. The regularity of each texture is estimated by means of a novel model-based approach. The distribution of the various coal components in the resultant feature space is modelled by means of a mixtures model and a simple nearest-neighbour decision rule is used to classify each pixel in the image. The performance of the classification system is encouraging and shows the feasibility of our idea.

Proliferation and mobility trends on digital devices has seen a significant realization of Bring Your Own Device (BYOD) which is a phenomenon that allows employees in an organizational enterprise network to access computing resources through their personal mobile devices irrespective of their location. This technology has enabled cost effectiveness in organizations through increased accessibility of digital devices in daily business activities. However, the development of this technology faces a number of security challenges due to lack of effective proactive security model with digital forensic capability that is able to plan and prepare before potential security incidents occur in an organization that has allowed BYOD. It is on this premise that the authors have proposed a generic Digital Forensic Readiness (DFR) model that uses honeypot technology to detect and trap potential security incidents. In this paper, therefore, a significant security model with DFR capability has been proposed. The model is aimed at harvesting, encrypting and digitally preserving potential digital evidence (PDE) based on the DFR processes and guidelines that have been highlighted in the ISO/IEC 27043: 2015 international standard for information technology, security techniques, incident investigation principles and processes. Finally, the proposed model is meant to reduce the effort required to conduct Digital Forensic Investigation (DFI) by capturing potential digital evidence and make it available when needed by digital forensic investigators which eventually saves cost and time. A generic DFR model for BYOD using honeypot technology is the main focus of this paper.

With the advent of cloud computing systems it has become possible to provision large scale systems in a short time with little effort. The systems underpinning these cloud systems have to deal with massive amounts of data in order to function. Should an indecent occur that requires some form of forensic investigation it can be very challenging for an investigator to conduct the investigation. This is due, in large part, to the volatility of data in cloud systems.

The most commonly used pixel structure in integrated circuit technologies is the three-transistor pixel structure (3-T). This structure consists of a pixel, a reset transistor, a source follower and a pixel select transistor. An extension to this is the 4-T pixel structure where an extra transistor is included to enable current steering in the readout phase and reset phase. This greatly reduces current consumption compared to the conventional 3-T pixel structure. Simulation results depicting this optimization is provided to support the technical contribution of this paper.

A report published in 2014 by the World Economic Forum ranked the quality of South Africa's mathematics and science education in the last place out of 148 countries. Educational experts believe that learners can benefit from educational mathematical applications. Senior post-graduate students at the Central University of Technology in South Africa, therefore, embarked on a socio-constructivist project to develop appropriate educational mathematics applications for primary school learners in their community. This paper focuses on the first stage of this project where the aim was to investigate the use of mobile mathematics applications by primary school learners within the South African context. Quantitative and qualitative data was collected by using a survey targeting mathematics teachers and parents of children in grade 1 to 3 in the Free State province of South Africa. The results indicate that 64% of grade 1 to 3 learners have access to mobile devices and that both teachers and parents have a very positive perception towards the use of mathematics applications by their learners and children. In addition 30% of parents have downloaded mobile mathematics applications for learners to use at home. The most important reason why parents are not downloading mobile mathematics applications is because they do not know where to find them, or they do not have time to search for appropriate applications. High costs associated with Internet connectivity and the fact that not all learners have access to mobile devices were two key obstacles mentioned by teachers involved with the use of mobile mathematics applications in primary school education.

During post-event response, proactive forensics is of critical importance in any organisation when conducting digital forensic investigations in cloud environments. However, there exist no reliable event reconstruction processes in the cloud that can help in analysis and examination of Digital Evidence (DE) aspects, during Digital Forensic Readiness (DFR) process, as defined in the standard of ISO/IEC 27043:2015. The problem that this paper addresses is the lack of an easy way of performing digital event reconstruction process when the cloud is forensically ready in preparation of a Digital Forensic Investigation (DFI). During DFR approaches, event reconstruction helps in examination and pre-analysis of the characteristics of potential security incidents. As a result, the authors have proposed an Enhanced Cloud Forensic Readiness (ECFR) process model with event reconstruction process that can support future investigative technologies with a degree of certainty. We also propose an algorithm that shows the methodology that is used to reconstruct events in the ECFR. The main focus of this work is to examine the addition of event reconstruction to the initially proposed Cloud Forensic Readiness (CFR) model, by providing a more enhanced and detailed cloud forensic readiness model.

Engineering plants typically have a variety of interlinked production chains, where process flows are dependent on upstream events and operated by default or manual settings. Burnable off-gasses are mostly utilized as energy sources. Raw material feeds may fluctuate over time, resulting in fluctuating off-gas production and potentially in inefficient energy resource usage.

The internet has had a major impact on how information is shared within supply chains, and in commerce in general. This has resulted in the establishment of information systems such as e-supply chains amongst others which integrate the internet and other information and communications technology (ICT) with traditional business processes for the swift transmission of information between trading partners. Many organisations have reaped the benefits of adopting the eSC model, but have also faced the challenges with which it comes. One such major challenge is information security. Digital forensic readiness is a relatively new exciting field which can prepare and prevent incidents from occurring within an eSC environment if implemented strategically. With the current state of cybercrime, tool developers are challenged with the task of developing cutting edge digital forensic readiness tools that can keep up with the current technological advancements, such as (eSCs), in the business world. Therefore, the problem addressed in this paper is that there are no DFR tools that are designed to support eSCs specifically. There are some general-purpose monitoring tools that have forensic readiness functionality, but currently there are no tools specifically designed to serve the eSC environment. Therefore, this paper discusses the limitations of current digital forensic readiness tools for the eSC environment and an architectural design for next-generation eSC DFR systems is proposed, along with the system requirements that such systems must satisfy. It is the view of the authors that the conclusions drawn from this paper can spearhead the development of cutting-edge next-generation digital forensic readiness tools, and bring attention to some of the shortcomings of current tools.

The advent of cloud computing has brought new challenges to digital forensics. To address these challenges, new approaches in conducting digital forensic are required. In this paper, challenges that are faced by digital forensic investigator when faced with cloud based incident scenes are presented. The presented challenges are obtained from survey articles that explore outstanding and future challenges in digital forensics in general. In this paper we zoom in into cloud forensics as it is the main focus of the paper. Based on the challenges brought to light by the considered survey articles, we present requirements that should be met by digital forensic systems that aim to investigate cloud environments. Existing architectures and implementations of digital forensic systems are evaluated based on these requirements. Through this evaluation, gaps that are left out by the evaluated architectures are brought to light.

Mobile phone's short message services technology is being leveraged to provide branchless banking in developed countries. These SMS-based services reach areas where bank branches or auto telling machines would not be feasible thereby enabling financial inclusion among the unbanked and low-income earners. However, the vulnerability of its service delivery platform makes it attractive to fraudsters. Lack of digital forensic readiness (DFR) scheme, specifically designed for BB, to capture and preserve potential evidence for further investigation of fraud remains a challenge in this domain. The availability of digital evidence maximises the potential of an organisation to successfully conduct investigation at a reduced cost. Therefore, branchless banking service providers should consider incorporating digital forensic readiness in their security strategies. In this paper, the authors propose a digital forensic readiness scheme that addresses the problem of fraud in branchless banking.

Renewable energy generation is achieving ever deeper penetration into the power grid because of its advantages. Renewable power sources are becoming more and more popular and renewable energies have many advantages including reduced environmental impact. This paper presents a design framework to implement a DC powered house. Different aspects of this solution will be described. A possible standard voltage for a DC house will be determined as well as the amount of power used by a small household. As the prices on renewable energy generators such as photovoltaic panels' decreases, it makes DC power systems more attractive. The paper also covers the design and simulation of a DC-DC converter used in the solution to provide DC power to a household. Load tests are simulated and show the effects of load changes on the stability of the DC network.

The cloud has made digital forensic investigations exceedingly difficult due to the fact that data may be spread over an ever-changing set of hosts and data centres. The normal search and seizure approach that digital forensic investigators tend to follow does not scale well in the cloud because it is difficult to identify the physical devices that data resides on. In addition, the location of these devices is often unknown or unreachable. A solution to identifying the physical device can be found in data provenance. Similar to the tags included in an email header, indicating where the email originated, a tag added to data, as it is passed on by nodes in the cloud, identifies where the data came from. If such a trace can be provided for data in the cloud it may ease the investigating process by indicating where the data can be found. In this research the authors propose a model that aims to identify the physical location of data, both where it originated and where it has been as it passes through the cloud. This is done through the use of data provenance. The data provenance records will provide digital investigators with a clear record of where the data has been and where it can be found in the cloud.

Semiconductor power devices have a growing popularity in industrial, scientific and medical (ISM) band applications, such as microwave-heating, drying and plasma generation. A distinguishable property of these applications is the relentless pursuit of reliability, ruggedness, or the ability to withstand a mismatched loading condition without failure. Mismatch detection right at device output, preferably integrated in package, could provide critical information to avoid device breakdown and to enable performance optimization. In this work, the in-package mismatch detection and load monitoring is enabled by a specially designed six-port reflectometer. Compared with conventional reflection measurement techniques based on heterodyne receivers, the proposed design is passive, simple, compact and inexpensive. A hardware prototype is implemented with a size of 36 mm2. Loading conditions over the entire Smith chart are generated by a calibrated active-load-pull system and measured by the proposed system, yielding a root-mean-square error below -32 dB full-scale. This compact reflectometer enables the in-package accurate mismatch detection for the first time. The result of this study has been accepted for publication in the 2014 International Microwave Symposium, and nominated to be a finalist for its annual best paper award.

Although cloud computing is maturing, security issues are still prevalent. Most of the security issues that are in the cloud have existed since the advent of the Internet. These issues are escalated in a cloud environment due to its distributed nature, multi-tenancy and the sensitive and large amount of data that is transmitted over the Internet and hosted by third parties. The security aspect that this paper focuses on concerns digital forensics. The cloud spans over multi-jurisdictions. As such, service providers hosting the data that may be required for digital forensic investigation may be reluctant to comply with foreign law enforcement agencies. Even if they comply, this may be a costly and time-consuming exercise, given the amount of hosted data that belongs to multi-tenants. In this paper we present a forensic readiness model that makes use of a Forensic Service hosted in the cloud. The model is aimed at minimizing costs associated with conducting a digital forensic investigation in a distributed cloud environment. The scope of this paper however is limited to examining the impact that a forensic readiness mechanism put in place may have on other hosted cloud services. Preliminary results have shown a negligible effect in performance of cloud services by a having our proposed digital forensic readiness mechanism in place.

The traditional digital forensic investigation process has always had a post-event driven focus. This process is perhaps too long for the cloud. This paper investigates how digital forensic readiness can be used to quicken and update the traditional digital forensic investigation process to better suit cloud computing environments. John Tans states that centralized logging is the key to efficient forensic strategies. The author proposes a model that considers centralised logging of all activities of all the participants within the cloud in preparation of an investigation. This approach will quicken the acquisition of evidential data when an investigation is required, allowing the investigator to start the analysis and examination almost immediately.

Cloud computing is a new computing paradigm which presents challenges for digital forensic investigators. Digital forensics is a branch of computer security that makes use of electronic evidence to build up a criminal case or for troubleshooting purposes. Advances have been made since the advent of Cloud computing in addressing issues that came with the Cloud including that of security. However, not all aspects of security are advancing. Developments in digital forensics still leave a lot to be desired in terms of standards and appropriate digital forensic tools that are applicable in the Cloud. To achieve that, standards as well as standard tools are required for successful evidence collection, preservation, analysis and conviction in case of a criminal case. This paper contributes towards addressing issues in digital forensics by presenting an algorithm that can be used in the evidence identification phase of a digital forensic process. Data in Cloud environments exist in the Internet or in networked environments and data is always accessed remotely. There is therefore at least one connection to a host that exists in a Cloud environment. In a case of a computer system that hosts a Cloud service, the number of connections from clients can be very large. In such a scenario it is very hard to identify an attacker from both active and recently disconnected connections to a host. This may require an investigator to probe all individual IP addresses connected to the host which can be time consuming and costly. There is therefore a need for a mechanism that can identify and rank remote hosts that are connected to a victim host and that may be associated with a malicious activity. In this paper we present an algorithm that uses probabilities to identify and rank suspicious remote hosts connected to a victim host. This algorithm helps minimize the effort required of investigators to probe each IP address that is connected to a victim as connected IP addresses will be prioritized according to their rank.

For certain VT connections and unknown consumer earthing practices, metering errors will occur during unbalanced loading. Because of the small load offered by modern numerical tariff meters and relays, VT burden ratings may be inappropriate and the VT may not operate within its accuracy range. This can give rise to the ferroresonance phenomenon and neutral inversion for certain system and VT conditions. VTs used for tariff metering were investigated based on limb design, parameters, earthing and connection methods. To compare the accuracy, case studies were created and calculations performed with the aid of an Excel iterative program. The calculations compared the actual real power supplied to a load with the real power seen by the voltage and current transformers. From the results and theoretical research, optimum VT earthing, connections, ratings and standards were determined and compiled in a concise Code of Practice.

Induction motors have been the workhorse of industry since decades. With the rapid advancement in industry and transport the need exists for machines with higher power per volume, efficient and better reliability to widen the application range and drive bigger and crucial loads. Higher phase order machines have been identified as a viable solution to meet these needs. This paper is on the concept of using a six phase machine as different devices consisting of three or six phases. A study is done using a symmetrical six phase structure and configuring it to operate as a three phase motor, six phase motor and three phase motor with reactive compensation. Some parts of mathematical modeling are presented as well as Matlab/Simulink simulation results.

Digital forensics gained significant importance over the past decade, due to the increase in the number of information security incidents over this time period, but also due to the fact that our society is becoming more dependent on information technology. Performing a digital forensic investigation requires a standardised and formalised process to be followed. There is currently no international standard formalising the digital forensic investigation process, nor does a harmonised digital forensic investigation process exist that is acceptable in this field. This paper proposes a harmonised digital forensic investigation process model. The proposed model is an iterative and multi-tier model. The authors introduce the term “parallel actions”, defined as the principles which should be translated into actions within the digital forensic investigation process (i.e. principle that evidence's integrity must be preserved through the process and that chain of evidence must be preserved). The authors believe that the proposed model is comprehensive and that it harmonises existing state-of-the-art digital forensic investigation process models. Furthermore, we believe that the proposed model can lead to the standardisation of the digital forensic investigation process.

Semantic similarity between different terminologies is becoming a generic problem that extends across numerous domains, touching applications developed for computational linguistics, artificial intelligence, cognitive science and, in the case of this paper, digital forensics. Despite the usefulness of semantic similarity measures in different domains, accurately measuring semantic similarity between any two terms remains a challenging task. The main difficulty lies in developing a computational method with the ability to generate satisfactory results close to how human beings perceive these terminologies, especially when used in their domain of expertise.