Emerging Trends in Electrical, Electronic and Communications Engineering

Decision support is required for effective planning on all kinds of scheduling scenarios. The stochastic scenarios and uncertainty in demands make the scheduling task complex. Multiple objectives in terms of cost, timing window, priorities and travel routes are the driving factors in the scheduling task. These objectives are often associated with given constraints like time, cost, resource limit etc. To meet all these objectives with the given constraints, it requires effective scheduling methods. Among different application areas of scheduling, emergency relief and staff scheduling are two domains which present major challenges for the scheduling research. These two areas provide analogy with many other areas of scheduling. Issues like finding appropriate locations and establishing them in appropriate group, discovering effective path for routing and making efficient plan for distribution and servicing are major challenges for these two and related scheduling cases. This paper covers a survey study on some of the recent papers of these areas that highlights the problem formulations, technologies, methods and algorithms applied. It provides a literature review on technologies and algorithms applied in the area of emergency case relief scheduling and staff scheduling.

5G is now the next generation of wireless communication systems. The general demonstration of one technology vision for fifth generation mobile networks is presented in this work. The vision of 5G technology provides guidance for the definition of requirements, architecture, and other aspects. By expanding the performances limits of mobile networks, it is necessary for the 5G to include a flexible designing which can optimize network utilization with large range of examples for partnership and business models. The 5G should include flexibility to optimize the network usage by design. Modular network functions with the ability of on demand deployment and scaling capabilities need to be included in the architecture. The purpose of this inclusion would be to handle the accommodation of various demands in a cost-effective and agile manner. Direct communication in D2D services is one of the new 5G networks characteristics. Advanced technologies such as massive MIMO and millimeter-wave radio systems have significant impact on design of cellular architecture. It is crucial for 5G technology to maintain a massive traffic volume owing to increase efficiency of radio link and density of cells. Also, it is necessary for the network to be transformed in a cloud architecture, which coordinates radio resources of multi-radio access, and inter-cell interference during network deployment. Research trends in 5G tell us that using an aggregation of technologies, it is possible to realize numerous goals. Our use case study for the perspective period post-2020 shows extremely broad variety of applications and their attributes performance.

Cloud radio access network (C-RAN) has been considered as one of the enabling network architectures towards the implementation of fifth generation (5G) wireless systems. Combining with advanced radio, wireless and computing techniques, C-RAN provides great potential to improve the network capacity, spectrum efficiency, energy efficiency and operational flexibility. Therefore, C-RAN has attracted considerable attention from both academia and industry. In this paper, we review the architecture and some of the key physical (PHY) layer signal processing issues of C-RAN. The functional split and limited-capacity fronthaul impose PHY layer issues and signal processing opportunities, e.g., channel state information acquisition, effective compress-and-forward methods and intelligent resource allocation schemes. Moreover, some emerging 5G techniques which can be supported by or integrated with C-RAN architecture, such as software-defined networking, heterogeneous networking, communication at millimeter wave frequencies and full-duplex radio are discussed. The challenges and future research directions are also presented, where mobile edge computing and caching, multi-dimensional resource management and PHY layer security and energy-efficient designs are highlighted.

Resonance allows a wireless power transfer (WPT) system to operate at greater distances compared to a non-resonant one. However, frequency splitting is observed which has the effect of limiting the maximum power transferred. This paper proposes a simple impedance matching algorithm to eliminate the frequency splitting phenomenon and maximise the output power which is cheaper to implement than other impedance matching methods. The WPT system is first converted into an equivalent circuit. Then the necessary conditions to satisfy the critically coupled condition using L matching circuits are formulated, from which the impedance matching algorithm is developed. The latter is verified from simulation and experimental results which are compared, analysed and improvements are also proposed.

System losses are important metrics for power utilities. The addition of distributed generation (DG) in the network can either improve or worsen system losses depending on the network configuration, placement of the DG or other factors. The impact that the integration of Small Scale Distributed Generation (SSDG) has on the losses in a low voltage distribution network in a highly residential has been presented in this paper. The model has been drawn in DIgSILENT Power Factory® using actual network parameters, load profile and photovoltaic (PV) generation data. The transformer losses and losses in the low voltage cables make up for the losses in the low voltage network and these components have been observed separately with increasing penetration of SSDG. The key contribution of this paper is the determination of that penetration of SSDG which results in the most optimum effect on network losses.

Due to the harsh environment of the power line, data transmission is greatly affected by noise, signal attenuation, interference, multiple reflections and varying impedance and loads. The noise channel at the University of Mauritius has been studied and the types of noise have been identified and modeled in Simulink. Results show that the noise with the highest impact on data transmission is impulsive noise. Narrowband noise has the least effect.

Web labs provides the opportunity to work from a computer connected to the internet anywhere and at any convenient time. In this work, a web lab for the study of a specific earthing or grounding arrangement has been conceived and implemented. Students are able to investigate different scenarios and understand why proper sizing of the protective device is critical to avoid any electrical accident. The main aims of this research work were to formulate a model for electrical installations of the TT (Terra Terra) earthing configurations, design and develop a test bed using LabVIEW (Laboratory Virtual Instrument Engineering Workbench) front panel as a user interface for conducting the lab experiments remotely. To assess the effectiveness of the web controlled lab a pre-test and a post-test evaluation were carried out. It was found from the results that their understanding of the subject improved substantially.

In this paper, the impact of different types of leaks on the excess pumping energy required in a distribution pipe is investigated. It is now well established that leakage is directly proportional to the pressure at the leak point in a pipe such that a pressure drop is inevitable. In order to compensate this drop in pressure, the pumping energy required to supply demand at a constant pressure has to be increased. How much more energy is required depends on the type and extent of the leak. For the 3 types of simulated leaks namely: orifice, circumferential and longitudinal slits with the same area of discharge, it is found that the excess pumping energy required for a circumferential crack in the pipe is the highest, followed by the orifice and then longitudinal slit as a result of the discharge to sustain customer demand and pressure head. The results of this research can be used to design a more robust control system or pump rescheduling strategy in order to save energy and water with regard to design, operation, and rehabilitation of old water distribution system.

The increasing penetration of renewable energy sources into the ac grid has brought several challenges for the power utilities, especially in the fields of power quality, stability, reliability, protection and control. In this paper, we present the design and implementation of a power flow control scheme for a photovoltaic to low voltage ac grid interface. The control algorithm is based on instantaneous tracking of the power reference signal by current regulation of the grid connected inverter. The proposed control and graphical user interface are implemented using LabVIEW. The ability of the developed system to control both the real and reactive powers injected into the grid is validated using both computer simulations and experimental tests.

Power loss reduction by Distribution Network Reconfiguration (DNR) is the process of finding the network topology offering the least losses. In this paper, an efficient hybrid algorithm is presented for the DNR problem. Through the addition of 3 deterministic refinements (a ‘warm start’, elitism and the hill climbing strategy), in any heuristic algorithm, both time efficiency and reliability of convergence can be achieved. Testing was done on 6 standard test systems: 16, 33, 70, 118, 135 and 880 bus systems. The results obtained revealed better network configurations that provided lesser power loss than other reported results.

Voltage stability maximization by Distribution Network Reconfiguration (DNR) is the process of finding a network configuration offering the least voltage deviation at the buses. Through the use of an Improved Voltage Deviation Index (IVDI) the stability of the entire distribution network has been studied. Using a hybrid algorithm, the DNR problem was tested on 6 standard test systems: 16, 33, 70, 118, 135 and 880 bus systems. The results showed that DNR using the IVDI can indeed lead to the improvement of the entire system stability.

Photovoltaic (PV) systems have played a key role over the last decade in the evolution of the electricity sector. Solar trackers are commonly used to increase the energy output from PV panels. However less focus have been laid on the security of the panels. It has been reported that the past few years has seen a significant increase in solar panel robbery. To address this issue, a microcontroller based, anti-theft, dual axis solar tracking prototype was designed and implemented. A comparative analysis was then performed between the dual-axis solar tracking system, and a fixed photo module. Results show that, on average the dual axis solar tracker produced 25.1% more energy than the stationary photo module, for the tropical island of Mauritius. An inexpensive microcontroller was used which enabled Short Message Service (SMS) text messages to and from the tracker, for control and signaling of tampering and/or theft of PV panels.

In recent years, installation of photovoltaic arrays has increased significantly worldwide driven by attractive incentives and reduced prices. However, the efficiency of the photovoltaic panels is negatively impacted by deposits of dust and dirt on their surface. Manual cleaning is highly labor-intensive, costly and uses excessive amounts of water. To address these shortcomings, an autonomous system is proposed to clean photovoltaic panels. It is based on two interconnected motorized structures that move along the surface of the PV panels to ensure that all sections are cleaned. A sensor network provides feedback on various aspects of the cleaning process. Tests showed that the proposed system can result in a gain of about 22% in daily average power output after three weeks of operation compared to a normal photovoltaic system.

This paper presents the control of voltage of a saturated power system using an Automatic Voltage Regulator (AVR) model. An unsaturated model of the system is first considered and then, this initial model is altered to include the effects of exciter and generator saturations. Since the amplifier has saturation limits in practice, these are also considered in the saturated system. The individual effect of the two types of saturations are analysed followed by an analysis of their combined effect. In order to obtain satisfactory responses in terms of settling time, percentage overshoot and steady state error, three types of compensating schemes were implemented, namely, Proportional Integral Derivative (PID), Fuzzy controller and PI-Fuzzy controller.

The interest towards solar Photovoltaic (PV) based power generation has increased worldwide due to climate change and depletion of fossil fuels. This has led to the need for accurate solar PV modelling under different environmental conditions. Since solar PV shows nonlinear characteristics, optimization technique is the best tool for modelling and estimation of PV parameters. Thus, in this paper, a Pattern Search (PS) algorithm is proposed to optimize the parameters of solar photovoltaic panels. The objective is to identify the parameters of single diode model based PV, in such a way that the difference between PV experimental current and simulated current is minimal. The effectiveness of the algorithms is investigated through simulation in MATLAB/Simulink environment at different solar irradiance and temperature and it is compared with the experimental data of solar module Kyocera – KC200GT 215. Results clearly reveal that the proposed technique shows better results in terms of its accuracy, convergence and CPU execution time.

In this paper, an improved Compressively Sampled Magnetic Resonance Imaging (CS-MRI) method that suppresses reconstruction noisy artifacts is proposed. The algorithm involves random undersampling of the k-space data of an MR image followed by reconstruction of the k-space data coefficients in a wavelet sparsifying domain. The high frequency noise in the reconstructed coefficients is suppressed in the Fourier transform domain by an adaptive Gaussian low pass filter. The reconstructed MR image is finally obtained by Inverse Discrete Fourier Transformation (IDFT) of the denoised k-space data. Experimental results demonstrate the robustness of the proposed method to sub-Nyquist sampling associated artifacts in terms of terms of Structural SIMilarity (SSIM) index and Peak Signal to Noise Ratio (PSNR) assessments.

Finite-difference time-domain (FDTD) is a versatile modeling technique which employs finite differences as approximations to both spatial and temporal derivatives. It is a numerical analysis technique used for modeling electrodynamics. The FDTD modeling is applied in wide range of applications such as biomedical imaging and biomedical treatment. In investigating the propagation, scattering and radiation of electromagnetic waves, the FDTD is used as a powerful tool. In this paper, we implemented 2D FDTD algorithm in Xilinx ISE platform by using Absorbing Boundary Conditions and Sinusoidal input as an exciting source. We have developed Synthesizable 2D-FDTD algorithm using fixed-point arithmetic. Synthesis and simulation are carried out on Virtex-5 FPGA and Analog Devices -BLACKFIN-533 target devices. It is experimentally found that proposed FPGA realization is 55.55% faster than that of DSP implementation.

High resolution images obtained from single image super resolution often suffer from excessive smoothness which blurs edges and gives smooth areas an un-natural texture. This paper proposes a super resolution method that combines wavelet super resolution and an edge enhancing back-projection filter to produce a super resolution image with sharp edges and natural texture. The low resolution image is first up-sampled using the discrete wavelet transform. High frequency sub-bands are derived from DWT of a bicubic interpolated low resolution image. The up-sampled image is then subjected to iterative back projection using a back-projection filter based on the Laplacian of Gaussian. The proposed method is tested on RGB colour images. It is found to produce better results than bicubic interpolation and selected edge directed interpolation methods in terms of PSNR and SSIM. It is also found to approximate the edge sharpness of edge directed interpolation while giving a more natural texture in smooth areas. The proposed method also eliminates spurious colours that have been observed in most edge-directed methods.

The PADK is a highly versatile DSP platform for implementing real-time audio applications. It features the Texas Instruments TMS320C6727, a powerful floating-point DSP processor and can process audio from eight input channels simultaneously. This makes it an ideal platform for developing multi-channel active acoustic noise control algorithms. This paper demonstrates results of system identification and feedback control using this kit. Using the Least Mean Square (LMS) algorithm, the filter coefficients are updated in real time to obtain an accurate impulse response. Potential applications of this particular platform are in the implementations of active acoustic noise control (ANC) systems in real time.

Wireless Communication and Signal Processing have become areas of flourishing research and innovation. Mathematical Modeling and Computational Simulations emerge as powerful ways to describe, analyze and control situations, solve problems and then interpret the results. The aim of this paper is to analyze the optimal sensing time made by cognitive radio secondary users during cooperative spectrum sensing in the Distributed Spectrum Utilization. The optimal time made by each cognitive radio user participating in cooperative spectrum sensing is modelled as a stochastic differential equation. The combination of all these sensing of the spectrum leads to a system of stochastic differential equations which is solved using a Runge-Kutta method. Computational simulations are provided to show that the total spectrum sensing time made by cognitive radios in the cooperative spectrum sensing is less than the total time they made in the spectrum sensing without cooperation.

In massive MIMO technology the channel is estimated using uplink training by sending an orthogonal pilot sequence from users to the base station. These sequences are re-used in the cell and also outside the cell. This gives rise to a channel estimation error referred to as pilot contamination. Large scale fading precoding which is based on the cooperation between cells has been proposed to mitigate pilot contamination. However this approach is known to limit in data transmission rate. In this paper, we propose a novel uplink training scheme to mitigate pilot contamination using a large scale fading precoding without the need of cooperation between cells. This achieves a higher transmission rate over existing method. The simulation results show that the proposed scheme improves 5% outage rate 10 times, over the existing method.

Standards like Long Term Evolution (LTE) employ Turbo coded QAM systems in order to achieve high data rates. Despite the fact that several mechanisms have been proposed in order to enhance the error performance of Turbo coded QAM systems, there is still the need to come up with novel or hybrid systems which can contribute towards further improved error performances. In this paper, a comparative analysis has been performed between symmetric and asymmetric LTE Turbo codes with the incorporation of techniques such as prioritization and regression based extrinsic information scaling. Results demonstrate that significant enhancement in the error performance throughout the whole E_b/N₀ range can be obtained with high order modulation when these techniques are used. With both symmetric and asymmetric LTE Turbo codes employing 64-QAM and a code-rate of 1/3, an average gain of 0.3 dB below BERs of 10−1 is obtained over symmetric and asymmetric LTE Turbo codes.

Technological advancement in Wireless Body Area Networks (WBANs) has gained much interest and became an emerging technology in the remote healthcare monitoring as WBANs are a collection of low-power, intelligent, miniaturized, lightweight, invasive or non-invasive bio sensors that operate in the proximity of a human body through wireless communication. They offer innovative and promising healthcare applications to improve the quality of life of patients by continuously monitoring human’s physiological vital signs. Based on existing literature on WBANs, technologies and standards, this paper proposes a WBAN to support remote healthcare monitoring of diabetic patients by ensuring higher degree of confidence in Quality of Information (QoI) through real-time data. The proposed architecture includes several features which enables better patient monitoring. Moreover, a qualitative approach is used to evaluate the systems’ architecture. Finally, the open research challenges and future works associated with WBANs design are discussed and evaluated.

Technical advances of Online Social Networking (OSN) have promoted new types of social interactions such as Proximity Based Social Networking (PBSN) where proximate users interact with each other using their mobile devices. However, personal details users share on these networks are not secured and messages exchanged are prone to different attacks and eavesdropping. Qualcomm introduces AllJoyn, which eases the development of such applications discovering with nearby devices and establishing a secure communication. In this paper, a secure device and service discovery protocol is introduced leveraging the AllJoyn framework. It allows mobile users to perform secure device advertising and discovery, authentication, encryption and decryption of exchanged messages. The security and performance of the proposed architecture are thoroughly analyzed and evaluated by using penetration tools and scenarios. Results showed that exchanged messages could not be captured and the system is not prone to attacks such as man-in-the-middle attacks.

This paper performs a comparative analysis of Unequal Error Protection (UEP) schemes for audio transmission over Asymmetric Digital Subscriber Line (ADSL). The proposed UEP scheme exploits three different levels of protection. First at the Discrete Multi-tone Modulation (DMT) layer, second with prioritized retransmissions and finally by using different code rates. A comparative analysis between Reed-Solomon (RS) codes and Turbo Codes is performed using two different block sizes. For the Turbo codes, Sign Division Ratio (SDR)-based extrinsic information scaling is also applied to further enhance the performance. Results show that when UEP is applied at three different levels, a gain of 11 dB is obtained over a scheme which applies UEP at only two levels.

The 3GPP (Third Generation Partnership Project) introduced Long Term Evolution (LTE), which is a 4G wireless technology used for broadband, derived from the 2G and 3G data technologies. LTE provides augmented capacity and speed. Among the different methods used for enhancing the performance of an LTE system is link adaptation, whereby the modulation, coding and other signal and protocol parameters are matched to the radio link conditions, leading to an improvement in transmission rates and/or bit error rates. This paper performs a comparative analysis of Link Adaptation with transmit diversity using 2 × 2 Multiple Input Multiple Output (MIMO) as well as different Channel Estimation Techniques. Link Adaptation is performed at the modulation level where a particular modulation index is selected based on the Signal-to-Interference Noise Ratio (SINR) value to obtain the maximum possible data rate for a target BER. Results show that a better performance is achieved using slot average algorithm.

Mobile technologies nowadays contribute to greater options to how learners can enhance their learning styles, leaving behind the traditional learning setup. Indeed mobile learning has become an integral part of our everyday life. Mobile learning refers to the use of mobile devices whereby learning is supported independent of the location and activity of the learner. This learning concept considers continual changes of contexts such as locations and the time available to learn within the mobile environment. Given that the current state of the use of contextual information in mobile learning is not extended, this paper put forward a context aware mobile learning system upon which parameters such as intrinsic and extrinsic context are used in order to improve mobile learning experience of the users. This work aims to synthesize a context-aware mobile learning system using dynamic content adaptation to establish personalized learning contents delivery on portable devices.

The recent increase in the number of security attacks by cyber-criminals on small businesses meant that security remained a concern for such organizations. In many such cases, detecting the attackers remained a challenge. A common tool to augment existing attack detection mechanisms within networks involves the use of honeypot systems. A fundamental feature of low-interaction honeypots is to be able to lure intruders, but the effectiveness of such systems has nevertheless been affected by various constraints. To be able to secure honeypots systems, it is important to firstly determine its requirements, before taking appropriate actions to ensure that the identified requirements have been achieved. This paper critically examines how existing low-interaction honeypot systems abide to major requirements before recommending how their security could be improved.

Driver drowsiness has become a major cause of traffic accidents. As a matter of fact, studies show that around one quarter of all serious motorway accidents are attributable to sleepy driver. One of the common ways to detect sleepy driver is by tracking the eye region since the major symptoms of fatigue such as frequent eye blinks and difficulty keeping eyes open, are visible through the driver’s eyes. Hence, it has become a necessity to proffer an investigation about the development of a mobile application system to detect the driver’s tiredness through Real-Time Eye. Naïve Bayes classifier algorithm and an alarm system have been implemented to proactively predict if there is any sign of drowsiness symptoms. The assessment of a population of 25 people were assessed which shows young people are mostly vulnerable to falling asleep on the wheel and that the notification alarm has also proved to be effective.

Requirement elicitation is one of the most important activities in requirement engineering and allocating limited amount of time in this activity is considered to significantly contribute towards failure of software projects. Having quality requirements is also greatly influenced by the techniques utilized during requirement elicitation process. The adoption of a single requirement elicitation technique within software development projects has various drawbacks. As solution, hybrid techniques are being considered as the way towards comprehensive requirements engineering. This paper investigates the hybrid requirement elicitation technique to tackle the challenges developers are facing in the process of software development. In this paper, the combination of 3 requirement elicitation techniques, namely use of questionnaire, interview and prototyping in a unified framework is investigated during the implementation of an online educational system.

Nowadays, with the ever-increasing demand for a wide range of mobile applications, mobile test automation is required to provide cost-effective, high quality and reliable mobile applications. Compared to manual testing which is time consuming and requires more resources in terms of people and time, automation aims at improving the test process. There are several mobile automation applications available on the market but there no proper mechanisms or guidelines that define the steps or best practices to adopt when performing mobile application development with the view of improving the testing process in terms of time taken. This research work investigates latest mobile application testing tools and guidelines, and proposes a framework to reduce the testing time of an android mobile application. In the proposed framework, five mobile application development guidelines that are common to android applications have been considered and tested using an automated testing tool.