Embedding 3-D Gaze Points on a 3-D Visual Field: A Case of Transparency

The paper seeks to demonstrates the likelihood of embedding a 3D gaze point on a 3D visual field, the visual field is inform of a game console where the user has to play from one level to the other by overcoming obstacles that will lead them to the next level. Complex game interface is sometimes difficult for the player to progress to next level of the game and the developers also find it difficult to regulate the game for an average player. The model serves as an analytical tool for game adaptations and also players can track their response to the game. Custom eye tracking and 3D object tracking algorithms were developed to enhance the analysis of the procedure. This is a part of the contributions to user interface design in the aspect of visual transparency. The development and testing of human computer interaction uses and application is more easily investigated than ever, part of the contribution to this is the embedding of 3-D gaze point on a 3-D visual field. This could be used in a number of applications, for instance in medical applications that includes long and short sightedness diagnosis and treatment. Experiments and Test were conducted on five different episodes of user attributes, result show that fixation points and pupil changes are the two most likely user attributes that contributes most significantly in the performance of the custom eye tracking algorithm the study. As the advancement in development of eye movement algorithm continues user attributes that showed the least likely appearance will prove to be redundant

Intrusion Detection through DCSYS Propagation Compared to Auto-encoders

In network settings, one of the major disadvantages that threaten the network protocols is the insecurity. In most cases, unscrupulous people or bad actors can access information through unsecured connections by planting software or what we call malicious software otherwise anomalies. The presence of anomalies is also one of the disadvantages, internet users are constantly plagued by virus on their system and get activated when a harmless link is clicked on, this a case of true benign detected as false. Deep learning is very adept at dealing with such cases, but sometimes it has its own faults when dealing benign cases. Here we tend to adopt a dynamic control system (DCSYS) that addresses data packets based on benign scenario to truly report on false benign and exclude anomalies. Its performance is compared with artificial neural network auto-encoders to define its predictive power. Results show that though physical systems can adapt securely, it can be used for network data packets to identify true benign cases

Emoji Essence: Detecting User Emotional Response on Visual Centre Field with Emoticons

User experience is understood in so many ways, like a one on one interaction (subjective views), online surveys and questionnaires. This is simply so get the user’s implicit response, this paper demonstrates the underlying user emotion on a particular interface such as the webpage visual content based on the context of familiarisation to convey users’ emotion on the interface using emoji, we integrated physiological readings and eye movement behaviour to convey user emotion on the visual centre field of a web interface. The physiological reading is synchronised with the eye tracker to obtain correlating user interaction, and emoticons are used as a form of emotion conveyance on the interface. The eye movement prediction is obtained through a control system’s loop and is represented by different color display of gaze points (GT) that detects a particular user’s emotion on the webpage interface. These are interpreted by the emoticons. Result shows synchronised readings which correlates to area of interests (AOI) of the webpage and user emotion. These are prototypical instances of authentic user response execution for a computer interface and to easily identify user response without user subjective response for better and easy design decisions

Modeling and Simulation of a DC Drive Integrated through a Demultiplexer

As expected, digital circuits are mostly ubiquitous and a necessary part of our modern and everyday life. Most of our electronics are formed from its configuration. Also new applications are now being designed almost all the time. This is fairly a most recent phenomenon. This chapter is aimed at integration of a DC motor to its demultiplexer encoders for the modeling of a complex system. Almost every mechanical movement that we come across is accomplished by an electronic motor, which are a means of converting energy to mechanical source. Almost all DC motors work on the same principles so the main objective is to apply direct current that operates through the interaction of magnetic flux and an electric current to produce rotational speed and configured torque to the demultiplexer encoders for the automation of a complex engine starter system. On several reruns, the result shows that the DC motor and DMF machine will be an important factor for mechanical device integration and composition of most demultiplexed machines

Detection of natural structures and classification of HCI-HPR data using robust forward search algorithm

Purpose – 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. Design/methodology/approach – 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. Findings – Results shows that the forward search method provides robust features that are capable of repelling over-fitting in physiological and eye movement data. Research limitations/implications – 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. Practical implications – The authors conducted some of the experiments at individual residence which may affect environmental constraints. Originality/value – 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

A Control System for Detecting Emotions on Visual Interphase Stimulus

Complex dynamic contents of visual stimuli induce implicit reactions in a user. This leads to changes in physiological processes of the user which is referred to as stress. Our goal is to model and produce a system that represents the mechanical interactions of the body and eye movement behavior. We are particularly concerned with the skin conductance response (SCR) and eye fixations to visual stimulus and build a dynamic system that detects stress and its correlates to visual widgets. The process consists of the following modules: (1) a hypothesis generator for suggesting possible structural changes that result from the direct interaction with visual stimulus, (2) an information source for responding to operator querying about users’ interactive and physiological processes, and (3) a continuous system simulator for simulating and illustrating physiological reactions during interaction. This model serves as an infrastructure for modeling physiological processes and could be of benefit in usability laboratory, web developers, and designers of interactive systems, enabling evaluators to visualize interface as a better access to identifying areas that cause stress to users

User Experience Adaptation of Complex Game Interface for User Behaviour Modeling Using RNN

In a video game review, the main focus is the narratives, characters, graphics, and mechanics in the gameplay. Some recent research mentions the user interface only when it comes into light as a creative platform for simple interactive narratives from a technical point of view; this narrative is mainly a software tool that requires traditionally modernized inputs from the user. The user needs to interact with the navigational controls or menus in order to start a basic game play. A complex game interface as stimulus is generally considered as having a feeling of immersion that allows for visual tracking of user behavioural patterns and use it to predict the next strategy of the user using robust computational models. A number of users have limited sensory perception in a gameplay and hence rely on complex game stimulus and an adaptive model is paramount when considering behavioural expectations that place the user in a digital environment with more expressive perceptions. We developed a custom based eye tracking and 3D object detection algorithm which was utilised by recruiting users to interact with visual 3D objects and trace their eye movement behaviour to generated data. We then applied the use of recurrent neural network (RNN) for direct tracing of user behavioural activities in a sequential manner to predict their behaviour for interface adaptation. Result indicates that redundant user attributes are flexible and flawless for identifying predicted response of the user in a controlled environment. This would lead to prototypical representation of user behavioural analytics as an embedded platform in the confined digital environment. One of the limitations of the project is its inability to basically specify the 3D gaze point at the inner boundaries of the visual field. Data visualisation is strictly based on combined object flow detection. The originality of the work is its ability to redefine fixation point to a rendered cascaded 3D gaze point and space-defined saccade which is indicated by the distance between one gaze points to the other. The 3D gaze point would be well suited for fixation generalisation on 3D as well as on 2D digital oriented environment

Impact of Coronavirus (COVID-19) Pandemic on Households’ Livelihood: Empirical Evidence from Sokoto State, North Western Nigeria

This study investigates the impact of coronavirus (covid-19) pandemic on households’ livelihood in Sokoto State, Nigeria using a survey dataset for a sample of two hundred and seventeen (217). The study applied mean and standard deviation in analyzing the data and finding suggests that covid-19 has negatively has negatively affected the household’s livelihood in terms of food security, market accessibility, and income generation activities and women and youths empowerment. The study further revealed that the pandemic put on negative influence on social activities of the households such as children education, social structure and gender relations. Furthermore, the study concludes that, covid-19 has negative effects on cultural activities of the households such as community events, funeral activities, ceremonies, sports activities and cultural values. In addition to covid-19 pandemic, this study also indicated that psychological behaviour of household such as sustainable behavior, uncertainty; infections fears and family relations were negatively affected. From the foregoing, this study recommends the needs for the government to create a window in fiscal policy that will accommodate any unforeseen health challenges in the future. Based on the previous experience, the study further recommends the need for the households to be on alert on the future pandemic and take precautions measures that would prevent the deterioration of socio-cultural activities and psychological behaviour. Keywords: covid-19, households, livelihood, Nigeria DOI: 10.7176/JESD/14-12-08 Publication date:June 30th 202

Gendered Dimensions of Accountability to Address Health Workforce Shortages in Northern Nigeria

Northern Nigeria has some of the worst health indices in sub‑Saharan Africa. Poor health outcomes are the result of multiple factors, including the lack of front-line health workers in rural and hard-to-reach areas. In 2012, funded by UK aid and DFID, the Women for Health programme was created to address the issue of gendered barriers of access to health education programmes and the subsequent dearth of nurses and midwives. It emerged that a different kind of ‘accountability’ was required to achieve improved maternal health outcomes: holding to account powerful actors within the community for their role in creating barriers of access to education for women and girls, as well as barriers to the retention of female health workers. This article, drawn directly from programme activities in Jigawa, Kano, Katsina, Yobe, and Zamfara states, documents strategies to shift gender norms that limit women’s professional choices and their access to quality maternal health services.Open Society Foundations, Vozes Desiguais/Unequal Voices, Future Health Systems consortium, the Impact Initiative and Health Systems Globa