Miracle-dz/UniFAR-FTUs huggingface dataset:
An evaluation of some systemic fungicides for the control of Septoria leaf spot of tomato

Three systemic fungicides viz. Thiophanate Methyl (Topsin M 70WP), Benomyl (Benlate 50WP) and Carbendazim (Bavistin 50WP) and a protectant, Mancozeb (Dithane M-45), were tested at Akomadan in Ghana for their efficacies and cost effectiveness against Septoria lycopersici Speg. , which causes Septoria leaf spot of tomato. The optimal spray schedule for themost cost effective and most readily-available fungicide was also studied. In the dry season, when leaf spot was generally absent, no differences in efficacies of the fungicides could be detected. In the wet season, Septoria leaf spot severity was high and the three systemic fungicides were generally superior to the protectant, Dithane M-45. Among the systemics, Benlate and Topsin M performed similarly and were generally more efficacious than Bavistin. The cost effectiveness of the systemic fungicides in the wet season (indicated by benefit:cost indices (BCI) was highest for Topsin M (0.22-0.32 per cent) followed by Bavistin (0.11-0.23 per cent) and lowest for Benlate (0.07-0.13 per cent). Use of Topsin M (413 g a.i. /ha) at 1, 2 and 3-weekly applications, commencing 5 weeks after transplanting and terminating in the 9th week, resulted in area under disease progress curve (AUDPC) values of 26.83, 29.16 and 31.82 per cent wk, respectively. These values were all significantly lower (P=0.05) than the value of 38.73 per cent wk associated with the no fungicide treatment. Judicious pesticide use and possible measures for increasing tomato yields in the area are discussed. (Ghana Journal of Agricultural Science, 1997, 30(1): 71-78)
El tiempo de compromiso motor en las sesiones de Educación Física del primer y segundo ciclo de Educación Primaria Commitment motor time in primary education first and second cycle physical education sessions

The main objectives of this study were to describe the most common type of sessions in physical education classes depending on the type of students groupings and to analyze the time available for practice (TCM) depending on the type of meeting, school year or when students practice the first, second and third year of primary education. This study involved 264 children who were studying in the first, second and third year of primary education. A total of 176 physical education sessions were recorded by observation tool TiPEF which showed excellent reliability (Cohen's Kappa = 0.95 to 0.99). The sessions where a cluster of large group used were the most used (33.5%) and sessions where the clusters were in groups of 4, 8 and 12 participants were the least used (5.7% each). The mean duration of TCM for all sessions analyzed was 21.4 ± 3.8 min / session, meaning that 67.2% of the time bound for other tasks that did not involve driving practice. The freshmen were the most TCM arranged by session and the third year the least (p <0.01). In sessions after recess and early in the afternoon TCM having students was higher (p <0.01) than in the last session of the morning and afternoon. It can be essential that educational institutions and physical education teachers perform specific actions to increase the TCM at these ages.
Participatory design of DIY digital assistive technology in Western Kenya

The participatory design, fabrication and customization of assistive technology can be an empowering experience for users with disabilities and their caregivers and teachers. These inherently creative activities can bring together multiple stakeholders and facilitate ongoing dialogues among them. We utilized a Do-It-Yourself assistive technology (DIY-AT) prototyping platform in a series of community-building activities to investigate the possibilities and challenges of maker approaches to the design and development of assistive technology in Western Kenya. We engaged a diverse group of stakeholders, including teachers, university students and representatives from governmental and non-governmental organizations working with people with disabilities. The results underline the importance of creating supportive local infrastructures, incorporating affordances for end-user technology appropriation, and identifying and engaging multiple stakeholders.
Evaluation of a New Kernel-Based Classifier in Eye Pupil Detection

Accurate pupil location is paramount to applications such as gaze estimation, assistive technologies and several man-machine interfaces as the ones found in smartphones and VR applications. We introduce a new classifier stemmed from the Inner Product Detector and investigate its features on the challenging task of pupil localization. IPD (Inner Product Detector) is a classifier with high potential in facial landmarks detection. It is robust to variations in the desired pattern while maintaining good generalization and computational efficiency. However, one possible limitation is its linear behavior, which could be overcome by aggregating non-linear techniques, such as kernel methods. Although kernel classifiers have been exhaustively studied in the past two decades, it was not analyzed or applied with IPD, yet. The proposed KIPD achieves in the worst case an accuracy of 97.41% on the BioID dataset and 93.71% in LFPW dataset both at 10% of the interocular distance. In this paper the KIPD is compared to the state of the art methods, including the ones using deep learning, being competitive in terms of accuracy as well as computational complexity.
A control scheme for monitoring process covariance matrices with more variables than observations

In this paper, we propose a new control chart that integrates a powerful high‐dimensional covariance matrix test with the exponentially weighted moving average procedure for monitoring high‐dimensional variability with individual observations. Design and implementation of the proposed chart are provided, including search algorithm and a table for the control limits, diagnostic aids after the signal, effect of misspecifying the in‐control distribution, and a bootstrap procedure. Monte Carlo simulation results show that the new chart, with its powerful inherited properties, provides satisfactory performance in various cases, especially for covariance shifts that involve diagonal components. The application of the proposed method is illustrated with a real data example from a white wine production process.
How Different homophily Preferences mitigate and spur ethnic and Value segregation: Schelling's Model Extended

In Schelling’s segregation model, agents of two ethnic groups reside in a regular grid and aim to live in a neighborhood that matches the minimum desired fraction of members of the same ethnicity. The model shows that observed segregation can emerge from people interacting under spatial constraints following homophily preferences. Even mild preferences can generate high degrees of segregation at the macro level. In modern, ethnically diverse societies, people might not define similarity based on ethnicity. Instead, shared tolerance towards ethnic diversity might play a more significant role, impacting segregation and integration in societies. With this consideration, we extend Schelling’s model by dividing the population of agents into value-oriented and ethnicity-oriented agents. Using parameter sweeping, we explore the consequences that the mutual adaptation of these two types of agents has on ethnic segregation, value segregation, and population density in the neighborhood. We examine for equally sized ethnic groups and for majority–minority conditions. The introduction of value-oriented agents reduces total ethnic segregation compared to Schelling’s original model, but the new value segregation appears to be more pronounced than ethnic segregation. Due to spillover effects, stronger ethnic homophily preferences lead not only to greater ethnic segregation, but also to more value segregation. Stronger value-orientation of the tolerant agents similarly leads to increased ethnic segregation of the ethnicity-oriented agents. Also, value-oriented agents tend to live in neighborhoods with more agents than ethnicity-oriented agents. In majority–minority settings, such effects appear to be more drastic for the minority than the majority ethnicity.
Automatic physical activity and in‐vehicle status classification based on GPS and accelerometer data: A hierarchical classification approach using machine learning techniques

Due to the advancement of tracking technology, a large quantity of movement data has been collected and analyzed in various research domains. In human mobility and physical activity (PA) research, GPS trajectories and the capabilities of geographic information systems (GIS) facilitate a better understanding of the associations between PA and various environmental factors taking individuals’ daily travels into account. PA research, however, needs to widen its focus from the intensity of PA to types of PA, which may provide useful clues for understanding specific health behaviors in particular geographic contexts. This study proposes and develops an algorithm to automatically classify PA types and in‐vehicle status using GPS and accelerometer data. Walking, standing, jogging, biking and sedentary/in‐vehicle statuses are identified through hierarchical classification processes based on machine learning and geospatial techniques. The proposed algorithm achieved high predictive accuracy on real‐world GPS and accelerometer data. It can greatly reduce participants’ and researchers’ burdens by automatically identifying PA types and in‐vehicle status for human mobility research, which is also known as travel mode imputation in transportation research.
Mobile persuasion: promoting clean and sustainable environment

Research has shown that most developing nations like Nigeria are increasingly confronting numerous environmental problems such as greenhouse gases, oil spills, and toxic waste management. However, the real problem has to do with peoples' negative attitudes and behaviors to the environment and resultant environmental problems. For instance, a high percentage of wastes generated in most developing countries in Africa are currently being disposed of via open dumping - which refers to a situation where people dump refuse on the streets. As responsible citizens, however, we should care more for the environment. We must take steps to reduce our personal ecological footprints, educate ourselves on what engenders environmental problems as well as change our attitudes towards our environment. In the last decade, computer-human interaction (CHI) research has evolved in response to the considerable increase in peoples' understanding of the influential roles that technology plays in everyday life. Technologies that are essentially designed for the purpose of influencing users to change their behaviors and attitudes, without using coercion or deception is referred to as Persuasive technology (PT). These behavioral and attitudinal changes are realized via the use of persuasive strategies. Persuasive strategies are techniques that are used in PT design to motivate behavior change and influence people to achieve specific goals in various domains like ecommerce, health and even in environmental management. As a first step towards contributing to research, this study focuses on how to design and implement a mobile persuasive system (a behavioral change support system BCSS) for waste management. This system when implemented could motivate users to change their attitudes and behaviors towards waste disposal and to care more for the environment.
Extreme Classification (Dagstuhl Seminar 18291)

Extreme classification is a rapidly growing research area within machine learning focusing on multi-class and multi-label problems involving an extremely large number of labels (even more than a million). Many applications of extreme classification have been found in diverse areas ranging from language modeling to document tagging in NLP, face recognition to learning universal feature representations in computer vision, gene function prediction in bioinformatics, etc. Extreme classification has also opened up a new paradigm for key industrial applications such as ranking and recommendation by reformulating them as multi-label learning tasks where each item to be ranked or recommended is treated as a separate label. Such reformulations have led to significant gains over traditional collaborative filtering and content-based recommendation techniques. Consequently, extreme classifiers have been deployed in many real-world applications in industry. Extreme classification has raised many new research challenges beyond the pale of traditional machine learning including developing log-time and log-space algorithms, deriving theoretical bounds that scale logarithmically with the number of labels, learning from biased training data, developing performance metrics, etc. The seminar aimed at bringing together experts in machine learning, NLP, computer vision, web search and recommendation from academia and industry to make progress on these problems. We believe that this seminar has encouraged the inter-disciplinary collaborations in the area of extreme classification, started discussion on identification of thrust areas and important research problems, motivated to improve the algorithms upon the state-of-the-art, as well to work on the theoretical foundations of extreme classification.
Digital services for entrepreneurs in informal settlements

In this poster, we examine the possibilities digital services may provide to entrepreneurs in informal settlements where traditional employment is scarce. The literature and our fieldwork shows that the entrepreneurs can be separated to two main categories based on their motivations; surviving and growing. The different entrepreneurs need different digital services for support. We collect these needs in the DSE-model, which is presented as our contribution. Also considered are the ethical ramifications of push to entrepreneurship.
Using augmented reality to enhance printed magazine articles about Namibian lodges

Information technology is an enabler of every business nowadays. IT is becoming a strategy and an integral part of marketing all kinds of businesses. This paper presents an approach to using Augmented Reality (AR) in order to advertise lodges in Namibia. It demonstrates the work undertaken during a one-week coding week held at Onjala Lodge near Windhoek in Namibia and the exemplary AR application that was developed. The coding week also included writing a magazine article supposed to be published about the lodge, with the images functioning as two-dimensional markers for the AR application. The AR content includes images and videos from around the lodge as well as three-dimensional animal models and should spark interest in the lodge within users of the application.
Reliability assessment models for dependent competing failure processes considering correlations between random shocks and degradations

This article develops reliability models for systems subject to two dependent competing failure processes, considering the correlation between additional damage size on degradation in soft failure process and stress magnitude of shock load in hard failure process, both of which are caused by the same kth random shock. The generalized correlative reliability assessment model based on copulas is proposed, which is then extended to three different shock patterns: (1) δ‐shock, (2) m‐shock, and (3) m‐run shocks. There are some statistical works to be introduced in reliability modeling, including data separation of total degradation amount, inferring the distribution of amount of aging continuous degradation at time t, and fitting copula to the specific correlation. The developed reliability models are demonstrated for an application example of a micro‐electro‐mechanical system.
Low-Cost Wireless Electrooculography Speller

While communication is an innate ability to most of us, individuals with severe motor disability such as amyotrophic lateral sclerosis (ALS) have difficulty in daily communication. Nowadays, with the help of human-computer interface (HCI), they can communicate using bio-signal which can be measured from the human body and monitored. Electrooculography (EOG) is one type of bio-signal, it can be measured as the electrical potential difference generated by eye movement. This project aims to develop a low-cost wireless EOG based speller. The EOG signal acquisition used 5 surface electrodes, which captures horizontal and vertical eye movement. A low cost wireless EOG signal acquisition circuit was designed and implemented. A real-time EOG classifying algorithm was developed on the Arduino to classify up to 10 different types of eye movement. This classified information is transmitted wirelessly to a virtual keyboard ona computer. A self-design keyboard was developed by placing the most frequently used alphabets closer initial point to increase the efficiency of the speller. A test was conducted on eight subjects to compare the accuracy and efficiency of the proposed low cost wireless EOG speller. The proposed system was able to outperform most of the spellers reported in literature by providing an average accuracy of 89 % and speed of 6.48 lpm.
The interplay between emotion and trust in technology

As technology evolves, exhibiting human-like characteristics, it is becoming a part of human daily activities with possibility of high degrees of dependency, due to its adaptation to users. For example, merely speaking to a smart phone to make a call or send a text. The new challenge of persuading users to change behavior such as low adoption of these technologies has emerged, because little effort is required to use them, but users know little or nothing about how they function. Trust is a key concept to study, as it can mitigate the presently discussed risk and uncertainty associated with present and future technologies. In addition to trust, emotion is also a key indicator for persuading users to changing behavior toward technical artifact. Therefore, this research focuses on unraveling the interplay between emotion and trust of users when interacting with human-like technologies. The contribution of this research is the development of conceptual mapping of various emotional affect and trust in technology, using psychometric and physiological evidences. This can further the understanding of persuasive application development by taking not just trust factors into account or emotional factors alone, but the relationship between these two indicators
Bifurcation Analysis of a Vibro-Impact Viscoelastic Oscillator with Fractional Derivative Element

To the best of authors’ knowledge, little work has been focused on the noisy vibro-impact systems with fractional derivative element. In this paper, stochastic bifurcation of a vibro-impact oscillator with fractional derivative element and a viscoelastic term under Gaussian white noise excitation is investigated. First, the viscoelastic force is approximately replaced by damping force and stiffness force. Thus the original oscillator is converted to an equivalent oscillator without a viscoelastic term. Second, the nonsmooth transformation is introduced to remove the discontinuity of the vibro-impact oscillator. Third, the stochastic averaging method is utilized to obtain analytical solutions of which the effectiveness can be verified by numerical solutions. We also find that the viscoelastic parameters, fractional coefficient and fractional derivative order can induce stochastic bifurcation.
Trustworthiness requirement‐oriented software process modeling

Trustworthy software is delivered by enacting trustworthy software processes. The purpose of this paper is to propose an approach to modeling trustworthiness requirement‐oriented software processes. First, based on the aspect‐oriented modeling techniques, separation of concerns is used to separate the crosscutting activities and the core activities according to the different trustworthiness requirements and functional requirements. A goal‐oriented modeling and reasoning method for trustworthiness requirements to find the crosscutting activities that satisfy multiple trustworthiness requirements is presented. Then, base processes are modeled for functional requirements. The crosscutting activities for trustworthiness requirements are decomposed into processes or tasks and encapsulated in aspects that are woven into the base processes. In the weaving procedure, correct weaving methods between multiple aspects and between aspects and base processes are designed. Errors or mistakes of aspect‐oriented process modeling are prevented. Finally, trustworthy third‐party certification authority software is studied systematically in a case study, and performance evaluations are conducted to show the cost and effect of the approach.
Online social networks risks to organisations: a literature review

The use of online social networks (OSNs) is increasing exponentially - leading to soaring risks for organisations. Organisations need to regulate employees' use of OSNs to minimise the impacts of OSNs related threats. The aim of this paper is to identify organisational security risks emanating from the use of OSNs by employees. A review and analysis of existing literature on OSNs was done to develop a taxonomy of OSNs' organisational risks. The review revealed that OSNs and employees are the current weakest security links in organisations and engender dreadful information security risks. In addressing OSNs security threats, there are challenges that organisations might encounter. For organisations to implement effective security management programs, it is recommended that future research should look at identifying critical success and failure factors for implementing OSNs security control mechanisms.
Edinburgh Research Explorer "What Is Optical Flow For?'': Workshop Results and Summary

Citation for published version: Güney, F, Sevilla-Lara, L, Sun, D & Wulff, J 2019, "What Is Optical Flow For? '': Workshop Results and Summary. in L Leal-Taixé & S Roth (eds), Computer Vision ECCV 2018 Workshops. vol. 11134, Lecture Notes in Computer Science, vol. 11134, Image Processing, Computer Vision, Pattern Recognition, and Graphics, vol. 11134, Springer International Publishing, Cham, pp. 731-739, European Conference on Computer Vision 2018, Munich, Germany, 8/09/18. https://doi.org/10.1007/978-3-030-11024-6_56