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Basic capturing of emotion on user experience of web applications and browsing is important in many ways. Quite often, online user experience is studied via tangible measures such as task completion time, surveys and comprehensive tests from which data attributes are generated. Prediction of users’ emotion and behaviour in some of these cases depends mostly on task completion time and number of clicks per given time interval. However, such approaches are generally subjective and rely heavily on distributional assumptions making the results prone to recording errors. This paper aims to propose a novel method – a window dynamic control system – that addresses the foregoing issues.

Primary data were obtained from laboratory experiments during which 44 volunteers had their synchronized physiological readings – skin conductance response, skin temperature, eye movement behaviour and users activity attributes taken by biosensors. The window-based dynamic control system (PHYCOB I) is integrated to the biosensor which collects secondary data attributes from these synchronized physiological readings and uses them for two purposes: for detection of both optimal emotional responses and users’ stress levels. The method’s novelty derives from its ability to integrate physiological readings and eye movement records to identify hidden correlates on a webpage.

The results from the analyses show that the control system detects basic emotions and outperforms other conventional models in terms of both accuracy and reliability, when subjected to model comparison – that is, the average recoverable natural structures for the three models with respect to accuracy and reliability are more consistent within the window-based control system environment than with the conventional methods.

Graphical simulation and an example scenario are only provided for the control’s system design.

The novelty of the proposed model is its strained resistance to overfitting and its ability to automatically assess user emotion while dealing with specific web contents. The procedure can be used to predict which contents of webpages cause stress-induced emotions to users.

The dependence on the use of information systems for nearly every activity and functions in the internet is increasingly high. This form of interconnectedness has bolstered national economies, enhanced how governments interact with their citizens and how ordinary people connect with friends and family. However, this dependence has equally resulted to a high rise in vulnerability, threat and risk associated with more use of information and communication technology. Cyber-attacks that have the potential to disrupt or damage information system infrastructure are getting more complex with some level of sophistication. Traditional protection of information system infrastructure is no longer sufficient; systems have proven to be immune to failure or incidents. This paper aims to ensure that there is a continuous availability of services through a fail-safe proof.

MYSQL replication technique was used to develop a model based on three-tier layers using the principle of network interdependency and the replication techniques. Tier 1 depicts a Telecom organization serving as service provider that provides internet service to Tier 2 organization – a Bank; Tier 3 is the financial App that can be used by bank staff and customers. The fail-safe mode integrated mechanism enables Tier 3 to continue to render its services in the event of an attack on Tier 1 such as DDoS without disruption.

This technique succeeded in mitigating the loss of data if cyber incident occurred or reception of uninterrupted services is countered, which give rise to future master-to-master architecture.

The study conducted is limited to the design and development of a fail-safe system for interdependent networks or systems using MYSQL replication technique.

In an interdependent environment such as the cyberspace, the sectors are interdependent for optimal results. The originality of the work ensures that there is availability of services which is sustained and that data integrity is assured using the fail-safe technique based on MySQL replication method.

Detecting emotion on user experience of web applications and browsing is important in many ways. Web designers and developers find such approach quite useful in enhancing navigational features of webpages, and biomedical personnel regularly use computer simulations to monitor and control the behaviour of patients. On the other hand, law enforcement agents rely on human physiological functions to determine the likelihood of falsehood in interrogations. Quite often, online user experience is studied via tangible measures such as task completion time, surveys and comprehensive tests from which data attributes are generated. Prediction of users' emotion and behaviour in some of these cases depends mostly on task completion time and number of clicks per given time interval. However, such approaches are generally subjective and rely heavily on distributional assumptions making the results prone to recording errors.

The authors propose a novel method-a window dynamic control system that addresses the foregoing issues. Primary data were obtained from laboratory experiments during which forty-four volunteers had their synchronised physiological readings, skin conductance response (SCR), skin temperature (ST), eye movement behaviour and users’ activity attributes taken using biosensors. The window-based dynamic control system (PHYCOB I) is integrated to the biosensor which collects secondary data attributes from these synchronised physiological readings and uses them for two purposes. For both detection of optimal emotional responses and users' stress levels. The method's novelty derives from its ability to integrate physiological readings and eye movement records to identify hidden correlates on a webpage.

Results show that the control system detects basic emotions and outperforms other conventional models in terms of both accuracy and reliability, when subjected to model comparison that is, the average recoverable natural structures for the three models with respect to accuracy and reliability are more consistent within the window-based control system environment than with the conventional methods.

The paper is limited to using a window control system to detect emotions on webpages, while integrated to biosensors and eye-tracker.

The originality of the proposed model is its resistance to overfitting and its ability to automatically assess human emotion (stress levels) while dealing with specific web contents. The latter is particularly important in that it can be used to predict which contents of webpages cause stress-induced emotions to users when involved in online activities.

One of the contributions of artificial intelligent (AI) in modern technology is emotion recognition which is mostly based on facial expression and modification of its inference engine. The facial recognition scheme is mostly built to understand user expression in an online business webpage on a marketing site but has limited abilities to recognise elusive expressions. The basic emotions are expressed when interrelating and socialising with other personnel online. At most times, studying how to understand user expression is often a most tedious task, especially the subtle expressions. An emotion recognition system can be used to optimise and reduce complexity in understanding users' subconscious thoughts and reasoning through their pupil changes.

This paper demonstrates the use of personal computer (PC) webcam to read in eye movement data that includes pupil changes as part of distinct user attributes. A custom eye movement algorithm (CEMA) is used to capture users' activity and record the data which is served as an input model to an inference engine (artificial neural network (ANN)) that helps to predict user emotional response conveyed as emoticons on the webpage.

The result from the error in performance shows that ANN is most adaptable to user behaviour prediction and can be used for the system's modification paradigm.

One of the drawbacks of the analytical tool is its inability in some cases to set some of the emoticons within the boundaries of the visual field, this is a limitation to be tackled within subsequent runs with standard techniques.

The originality of the proposed model is its ability to predict basic user emotional response based on changes in pupil size between average recorded baseline boundaries and convey the emoticons chronologically with the gaze points.

The purpose of this paper is to proposes a forward search algorithm for detecting and identifying natural structures arising in human-computer interaction (HCI) and human physiological response (HPR) data.

The paper portrays aspects that are essential to modelling and precision in detection. The methods involves developed algorithm for detecting outliers in data to recognise natural patterns in incessant data such as HCI-HPR data. The detected categorical data are simultaneously labelled based on the data reliance on parametric rules to predictive models used in classification algorithms. Data were also simulated based on multivariate normal distribution method and used to compare and validate the original data.

Results shows that the forward search method provides robust features that are capable of repelling over-fitting in physiological and eye movement data.

One of the limitations of the robust forward search algorithm is that when the number of digits for residuals value is more than the expected size for stack flow, it normally yields an error caution; to counter this, the data sets are normally standardized by taking the logarithmic function of the model before running the algorithm.

The authors conducted some of the experiments at individual residence which may affect environmental constraints.

The novel approach to this method is the detection of outliers for data sets based on the Mahalanobis distances on HCI and HPR. And can also involve a large size of data with p possible parameters. The improvement made to the algorithm is application of more graphical display and rendering of the residual plot.