I. Andonovic

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• Doctor of Philosophy
• Professor (Full) at University of Strathclyde

Computational analysis of infant movement has significant potential to reveal markers of developmental health. We report two studies employing dynamic analyses of motor kinematics and motor behaviours, which characterise movement at two levels, in 9-month-old infants. We investigate the effect of preterm birth (< 33 weeks of gestation) and the effe...

Existing methods to obtain position from inertial sensors typically use a combination of multiple sensors and orientation modeling; thus, obtaining position from a single inertial sensor is highly desirable given the decreased setup time and reduced complexity. The dead reckoning method is commonly chosen to obtain position from acceleration; howev...

There are several image inverse tasks, such as inpainting or super-resolution, which can be solved using deep internal learning, a paradigm that involves employing deep neural networks to find a solution by learning from the sample itself rather than a dataset. For example, Deep Image Prior is a technique based on fitting a convolutional neural net...

This paper reports on the use of estimates of individual animal feed intake (made using time spent feeding measurements) to predict the Feed Conversion Ratio (FCR), a measure of the amount of feed consumed to produce 1 kg of body mass, for an individual animal. Reported research to date has evaluated the ability of statistical methods to predict da...

Feasibility study to explore the use of on farm sensors for monitoring positive welfare in dairy cows.

Following the publication of the article [...]

The use of supervised Machine Learning (ML) to enhance Intrusion Detection Systems (IDS) has been the subject of significant research. Supervised ML is based upon learning by example, demanding significant volumes of representative instances for effective training and the need to retrain the model for every unseen cyber-attack class. However, retra...

Long Range Wireless Area Network (LoRaWAN) provides desirable solutions for Internet of Things (IoT) applications that require hundreds or thousands of actively connected devices (nodes) to monitor the environment or processes. In most cases, the location information of the devices arguably plays a critical role and is desirable. In this regard, th...

With the great capabilities of deep classifiers for radar data processing come the risks of learning dataset-specific features that do not generalize well. In this work, the robustness of two deep convolutional architectures, trained and tested on the same data, is evaluated. When standard training practice is followed, both classifiers exhibit sen...

Deep learning (DL) enables the creation of computational models comprising multiple processing layers that learn data representations at multiple levels of abstraction. In the recent past, the use of deep learning has been proliferating, yielding promising results in applications across a growing number of fields, most notably in image processing,...

Movement sonification is emerging as a useful tool for rehabilitation, with increasing evidence in support of its use. To create such a system requires component considerations outside of typical sonification design choices, such as the dimension of movement to sonify, section of anatomy to track, and methodology of motion capture. This review take...

Movement is prospective. It structures self-generated engagement with objects and social partners and is fundamental to children's learning and development. In autistic children, previous reports of differences in movement kinematics compared to neurotypical peers suggest its prospective organisation might be disrupted. Here, we employed a smart ta...

Deep learning techniques are subject to increasing adoption for a wide range of micro-Doppler applications, where predictions need to be made based on time-frequency signal representations. Most, if not all, of the reported applications focus on translating an existing deep learning framework to this new domain with no adjustment made to the object...

Monitoring and classification of dairy cattle behaviours is essential for optimising milk yields. Early detection of illness, days before the critical conditions occur, together with automatic detection of the onset of oestrus cycles is crucial for obviating prolonged cattle treatments and improving the pregnancy rates. Accelerometer-based sensor s...

Cloud cover remains a significant limitation to a broad range of applications relying on optical remote sensing imagery, including crop identification/yield prediction, climate monitoring, and land cover classification. A common approach to cloud removal treats the problem as an inpainting task and imputes optical data in the cloud-affected regions...

The integration of Information and Communication Technology (ICT) tools into mechanical devices in routine use within the aviation industry has heightened cyber-security concerns. The extent of the inherent vulnerabilities in the software tools that drive these systems escalates as the level of integration increases. Moreover, these concerns are be...

High levels of supplementation with cereal increases production rates in cattle but can increase incidence of disease, ranging from mild indigestion to acute ruminal acidosis and death. Therefore, there is motivation to determine biological markers which can be used to identify whether animals have been, or are being fed, sufficient or excessive ce...

The rich, complementary data provided by Sentinel-1 and Sentinel-2 satellite constellations host considerable potential to transform Earth observation (EO) applications. However, a substantial amount of effort and infrastructure is still required for the generation of analysis-ready data (ARD) from the low-level products provided by the European Sp...

Utilising deep learning image classification to automatically annotate subsea pipeline video surveys can facilitate the tedious and labour-intensive process, resulting in significant time and cost savings. However, the classification of events on subsea survey videos (frame sequences) by models trained on individual frames have been proven to vary,...

The motor system is becoming increasingly recognized as an important site of disruption in autism spectrum disorders (ASD). However, the precise nature of this motor disruption remains unclear with some conflicting reports. We employed a smart tablet serious game approach, which did not require verbal instruction. Children's movements on the touch...

The paper presents a classification of cyber attacks within the context of the state of the art in the maritime industry. A systematic categorization of vessel components has been conducted, complemented by an analysis of key services delivered within ports. The vulnerabilities of the Global Navigation Satellite System (GNSS) have been given partic...

A variety of compression methods based on encoding images as weights of a neural network have been recently proposed. Yet, the potential of similar approaches for video compression remains unexplored. In this work, we suggest a set of experiments for testing the feasibility of compressing video using two architectural paradigms, coordinate-based ML...

A variety of compression methods based on encoding images as weights of a neural network have been recently proposed. Yet, the potential of similar approaches for video compression remains unexplored. In this work, we suggest a set of experiments for testing the feasibility of compressing video using two architectural paradigms, coordinate-based ML...

Movement is prospective. It structures self-generated engagement with objects and social partners and is fundamental to children’s learning and development. In autistic children, previous reports of differences in movement kinematics compared to neurotypical peers suggest its prospective organisation might be disrupted. Here, we employed a smart ta...

Conditions that lead to undesired fouling events in oscillatory flow crystallisers are investigated. The moving fluid oscillatory baffled crystalliser is used to mimic the operating conditions of continuous oscillatory baffled crystallisers, while reducing materials and energy consumption. A non-invasive imaging method is deployed to determine foul...

Coordinate-based Multilayer Perceptron (MLP) networks, despite being capable of learning neural implicit representations, are not performant for internal image synthesis applications. Convolutional Neural Networks (CNNs) are typically used instead for a variety of internal generative tasks, at the cost of a larger model. We propose Neural Knitwork,...

Utilising deep learning image classification to automatically annotate subsea pipeline video surveys can facilitate the tedious and labour-intensive process, resulting in significant time and cost savings. However, the classification of events on subsea survey videos (frame sequences) by models trained on individual frames have been proven to vary,...

Current techniques for measuring feed intake in housed cattle are both expensive and time-consuming making them unsuitable for use on commercial farms. Estimates of individual animal intake are required for assessing production efficiency. The aim of this study was to predict individual animal intake using parameters that can be easily obtained on...

The monitoring of diver health during emergency events is crucial to ensuring the safety of personnel. A non-invasive system continuously providing a measure of the respiration rate of individual divers is exceedingly beneficial in this context. The paper reports on the application of short-range radar to record the respiration rate of divers withi...

Monitoring cattle behaviour is core to the early detection of health and welfare issues and to optimise the fertility of large herds. Accelerometer-based sensor systems that provide activity profiles are now used extensively on commercial farms and have evolved to identify behaviours such as the time spent ruminating and eating at an individual ani...

The treatment of interfering motion contributions remains one of the key challenges in the domain of radar-based vital sign monitoring. Removal of the interference to extract the vital sign contributions is demanding due to overlapping Doppler bands, the complex structure of the interference motions and significant variations in the power levels of...

The motor system is becoming increasingly recognized as an important site of disruptions in autism spectrum disorders (ASD). However, the precise nature of this motor disruption remains unclear with some conflicted reports between papers. A bottleneck in kinematic studies of children with ASD has been the use of laboratory-based motion tracking sys...

Delaminations within aerospace composites are of particular concern, presenting within composite laminate structures without visible surface indications. Transmission based thermography techniques using contact temperature sensors and surface mounted heat sources are able to detect reductions in thermal conductivity and in turn impact damage and la...

Cyber situational awareness has been proven to be of value in forming a comprehensive understanding of threats and vulnerabilities within organisations, as the degree of exposure is governed by the prevailing levels of cyber-hygiene and established processes. A more accurate assessment of the security provision informs on the most vulnerable enviro...

Automated methods for detecting defects within composite materials are highly desirable in the drive to increase throughput, optimise repair program effectiveness and reduce component replacement. Tap-testing has traditionally been used for detecting defects but does not provide quantitative measurements, requiring secondary techniques such as ultr...

Sandwich panels consisting of two Carbon Fibre Reinforced Polymer (CFRP) outer skins and an aluminium honeycomb core are a common structure of surfaces on commercial aircraft due to the beneficial strength–weight ratio. Mechanical defects such as a crushed honeycomb core, dis-bonds and delaminations in the outer skins and in the core occur routinel...

Cyber situational awareness has been proven to be of value in forming a comprehensive understanding of threats and vulnerabilities within organisations, as the degree of exposure is governed by the prevailing levels of cyber-hygiene and established processes. A more accurate assessment of the security provision informs on the most vulnerable enviro...

The growth in wirelessly enabled sensor network technologies has enabled the low cost deployment of sensor platforms with applications in a range of sectors and communities. In the agricultural domain such sensors have been the foundation for the creation of decision support tools that enhance farm operational efficiency. This Research Reflection i...

We study means of extracting quantitative information about particle attributes using state-of-art in-line and off-line particle measurements and analysis techniques. The approach comprises a combination of image analysis, laser diffraction, inversion of chord length distribution, and multivariate analysis. Polystyrene particle suspensions are used...

Fibre orientation within composite structures dictates the material properties of the laminate once cured. The ability to accurately and automatically assess fibre orientation of composite parts is a significant enabler in the goal to optimise the established processes within aftermarket aerospace industries. Incorrect ply lay-up results in a struc...

The use of supervised Machine Learning (ML) to enhance Intrusion Detection Systems has been the subject of significant research. Supervised ML is based upon learning by example, demanding significant volumes of representative instances for effective training and the need to re-train the model for every unseen cyber-attack class. However, retraining...

Collar-based activity sensors are in common use as a means of detecting oestrus to optimise farm fertility and, hence, productivity. Recently, the same acceleration-derived signals have been processed to detect the time spent ruminating and eating, which, together, give an insight into animal welfare. Here, the use of neck-mounted accelerometers to...

Regulatory requirements for sub-sea oil and gas operators mandates the frequent inspection of pipeline assets to ensure that their degradation and damage are maintained at acceptable levels. The inspection process is usually sub-contracted to surveyors who utilize sub-sea Remotely Operated Vehicles (ROVs), launched from a surface vessel and piloted...

Worldwide, there is a trend towards increased herd sizes, and the animal-to-stockman ratio is increasing within the beef and dairy sectors; thus, the time available to monitoring individual animals is reducing. The behaviour of cows is known to change in the hours prior to parturition, for example, less time ruminating and eating and increased acti...

Inspection of rice seeds is a crucial task for plant nurseries and farmers since it ensures seed quality when growing seedlings. Conventionally, this process is performed by expert inspectors who manually screen large samples of rice seeds to identify their species and assess the cleanness of the batch. In the quest to automate the screening proces...

Sub-acute ruminal acidosis ( SARA ) can reduce the production efficiency and impair the welfare of cattle, potentially in all production systems. The aim of this study was to characterise measurable postmortem observations from divergently managed intensive beef finishing farms with high rates of concentrate feeding. At the time of slaughter, we ob...

The paper centres on an assessment of the modelling approaches for the processing of signals in CW and FMCW radar-based systems for the detection of vital signs. It is shown that the use of the widely adopted phase extraction method, which relies on the approximation of the target as a single point scatterer, has limitations in respect of the simul...

Contamination of rice seeds affects the crop quality, yield and price. Inspection of rice seeds for purity is a very important step for quality assessment. Promising results have been achieved using hyperspectral imaging (HSI) for classification of rice seeds. However, the relatively high number of spectral features in HSI data continues to pose pr...

Carbon fibre reinforced polymer (CFRP) is increasingly used for aero-structure applications due to their high strength-to-weight ratio. The integration of the on-board electrical power system (EPS) with CFRP is challenging due to the requirement to thermally and electrically isolate these systems to meet existing safety standards. By capturing the...

Maintenance Repair and Overhaul (MRO) of composite aerospace components requires rigorous stress and strain analysis, including mechanical and thermal, as part of the repair process. Finite Element Analysis (FEA) as a standard and robust method of determining the transfer of transient thermal results of materials is well established for remanufactu...

The reticuloruminal function is central to the digestive efficiency in ruminants. For cattle, collar- and ear tag-based accelerometer monitors have been developed to assess the time spent ruminating on an individual animal. Cattle that are ill feed less and so ruminate less, thus, the estimation of the time spent ruminating provides insights into t...

The application of pH observations to clinical practice in dairy cattle is based on criteria derived primarily from single time-point observations more than 20 years ago. The aims of this study were to evaluate these criteria using data collected using continuous recording methods; to make recommendations that might improve their interpretation; an...

Size and shape distributions are among critical quality attributes of particulate products and their inline measurement is crucial for monitoring and control of particle manufacturing processes. This requires advanced tools that can estimate particle size and shape distributions from multi-sensor data captured in situ across various processing step...

Besides size and polymorphic form, crystal shape takes a central role in engineering advanced solid materials for pharmaceutical and chemical industry. This work demonstrates how multiple cycles of growth and dissolution can manipulate the habit of an acetylsalicylic acid crystal population. Considerable changes of the crystal habit could be achiev...

Particle processing industries, such as pharmaceutical, food processing and consumer goods sectors, increasingly require strategies to control and engineer particle attributes. In both traditional batch and continuous processes, particle size and shape need to be effectively monitored through in-line measurements from Process Analytical Technologie...

The in situ measurement of the particle size distribution (PSD) of a suspension of particles presents huge challenges. Various effects from the process could introduce noise to the data from which the PSD is estimated. This in turn could lead to the occurrence of artificial peaks in the estimated PSD. Limitations in the models used in the PSD estim...

In recent years, the pharmaceutical industry is seeing a movement towards the implementation of more efficient continuous manufacturing. This shift requires the development of in-line process analytical technologies to monitor and control the process at any given time. However, extracting reliable information from these sensors is a challenge. Amon...

Digitisation of manufacturing processes under the umbrella of Industry 4.0 is a multi-faceted challenge, with requirements ranging from ensuring all relevant data is captured and has meaning, to combining and analysing data streams correctly, through to creating useful and intuitive real-time user interfaces.One such data stream that has more recen...

The success of the various secondary operations involved in the production of particulate products depends on the production of particles with a desired size and shape from a previous primary operation such as crystallisation. This is because these properties of size and shape affect the behaviour of the particles in the secondary processes. The si...

Farmers worldwide are facing intense commercial pressure to optimise operational efficiency. This in turn is driving an uptake in the use of technology as farm sizes grow through consolidation to maintain profitability. The ready availability of cost-effective wirelessly enabled micro-electromechanical devices has enabled a range of technical solut...

Energy consumption, traffic adaptability, fast data collection, etc are the major issues in wireless sensor networks (WSNs). Most existing WSN protocols are able to handle one or two of the above issues with the other(s) being compromised. In order to reduce the energy consumption of wireless sensor nodes while having fast data collection under dif...

Mitigation of atmospheric turbulence effects on the bit-error rate performance for both asymmetrically clipped optical orthogonal frequency-division multiplexing (ACO-OFDM) and modified ACO-OFDM is studied using a single-input multiple-output configuration.

A conventional method to inspect the varietal purity of rice seeds is based on human visual inspection where a random sample is drawn from a batch. This is a tedious, laborious, time consuming and extremely inefficient task. This paper presents an automatic rice seed inspection method using Hyperspectral imaging and machine learning, to automatical...

When distributing rice seed to farmers, suppliers strive to ensure that all seeds delivered belong to the species that was ordered and that the batch is not contaminated by unhealthy seeds or seeds of a different species. A conventional method to inspect the varietal purity of rice seeds is based on manually selecting random samples of rice seed fr...

In Vehicular Delay Tolerant Networks (VDTN) connection from source to destination at any required period is not necessarily available. Therefore, the node with the message, save it in its own buffer and carry it until an opportunity comes across for forwarding. Fix nodes enhances the performance of VDTN. It helps in message storage and relaying mes...

Wireless heterogeneous network (HetNet) with small cells presents a new backhauling challenge that differs from those of experienced by conventional macro-cells. In practice, the choice of backhaul technology for these small cells whether fibre, xDSL, point-to-point and point-to-multipoint wireless, or multi-hop/mesh networks, is often governed by...

Graphics Processing Units (GPUs) have become the focus of much interest with the scientific community lately due to their highly parallel computing capabilities, and cost effectiveness. They have evolved from simple graphic rendering devices to extremely complex parallel processors, used in a plethora of scientific areas. This paper outlines experi...

Graphics Processing Units (GPUs) have become the focus of much interest with the scientific community lately due to their highly parallel computing capabilities, and cost effectiveness. They have evolved from simple graphic rendering devices to extremely complex parallel processors, used in a plethora of scientific areas. This paper outlines experi...

The Internet of Things (IoT) and the number of sensors integrated within safety critical environments is increasing exponentially. System designers employ off-the-shelf hardware to reduce development time and cost, however, the early adoption of consumer hardware and software raises numerous security questions. Several successful attacks and threat...

In this paper, the research focus on the development of energy saving schemes with roots in sleep modes that support the evolution of greener core optical IP networks. The cornerstone of the adopted strategy is partition-lightpath schemes underpinned by the hibernation state implemented through a modification of the intelligent control plane, in pa...

The Internet of Things (IoT) and the number of sensors integrated within safety critical environments is increasing exponentially. System designers employ off-the-shelf hardware to reduce development time and cost, however, the early adoption of consumer hardware and software raises numerous security questions. Several successful attacks and threat...

Behavioural scientists track animal behaviour patterns through the construction of ethograms which detail the activities of cattle over time. To achieve this, scientists currently view video footage from multiple cameras located in and around a pen, which houses the animals, to extract their location and determine their activity. This is a time con...