School of Technology

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Evaluation of software visualization tools: Lessons learned
(Institute of Electrical and Electronics Engineers (IEEE), 2009) Ogao, Patrick; Sensalire, Mariam; Telea, Alexandru
Many software visualization (SoftVis) tools are continuously being developed by both researchers as well as software development companies. In order to determine if the developed tools are effective in helping their target users, it is desirable that they are exposed to a proper evaluation. Despite this, there is still lack of a general guideline on how these evaluations should be carried out and many of the tool developers perform very limited or no evaluation of their tools. Each person that carries out one evaluation, however, has experiences which, if shared, can guide future evaluators. This paper presents the lessons learned from evaluating over 20 SoftVis tools with over 90 users in five different studies spread on a period of over two years. The lessons covered include the selection of the tools, tasks, as well as evaluation participants. Other discussed points are related to the duration of the evaluation experiment, its location, the procedure followed when carrying out the experiment, as well as motivation of the participants. Finally, an analysis of the lessons learned is shown with the hope that these lessons will be of some assistance to future SoftVis tool evaluators.
Modeling and mapping crime in Eastern Nairobi, Kenya
(AGILE PhD School, 2013) Mburu, Lucy W.
This working paper provides a description of the phases of my PhD study. Drawing on assumptions from various theories of environmental criminology, this study applies various crime mapping methodologies to observe geographic and temporal patterns of crime in the eastern part of the Kenyan capital city, Nairobi. This paper outlines the first completed phase which employs criminal geographic profiling to predict offender abodes, and also briefly identifies the next two phases of the study that involve spatio-temporal analysis and a regression modeling respectively. Results from the completed study have potential implications on the prediction and ultimate reduction of criminality, both within the Nairobi capital and also in other cities with similar spatial patterns.
Enterprise Resource Planning (ERP) System Implementation : A case for User participation
(2013) Ogao, Patrick; Matende, Samuel
The introduction of an information system such as Enterprise Resource Planning (ERP) system in an organization brings with it changes on how users work. An ERP system cuts across the different functional units of an organization and therefore if not properly managed during its implementation may lead to resistance from the users. The different streams of research on ERP systems have mainly been on ERP adoption, success measurement, and critical success factors (CSFs). There is a paucity of studies on user participation and the contribution of users towards the successful implementation of ERP systems. This paper reviews literature on ERP implementation with an aim of building a case for involving users in this implementation.
3-Category pedagogical framework for context based ambient learning
(IEEE, 2013) Mwendia, Simon N.; Waiganjo, Peter; Oboko, Robert
Mobile phones have taken centre stage in transforming people’s lives in all sectors of African economies. With regard to Education sector, studies show that, there is high prevalence of mobile phones among learners in African universities but no computer prevalence. However, E-learning technologies are not readily available among learners. Learners are therefore forced to access content from few fixed locations with internet connectivity such as cyber cafes and workplace, eliminating access flexibility in learning. The ‘Mobile phone rich’ but ‘computer poor’ context prevailing in African universities presents an opportunity to establish an appropriate type of learning that utilizes mobile phones rather than computers. This paper explores existing categories of m-learning projects and proposes a 3-category framework to provide better understanding of ambient learning and allow integration of future ambient learning projects situated in different learning environments.
Importance of the Neutral Category in Fuzzy Clustering of Sentiments
(International Journal of Fuzzy Logic Systems, 2014) Nderu, Lawrence; Jouandeau, Nicolas; Akdag, Herman
Social media is said to have an impact on the public discourse and communication in the society. It is increasingly being used in the political context. Social networks sites such as Facebook, Twitter and other microblogging services provide an opportunity for public to give opinions about some issues of interest. Twitter is an ideal platform for users to spread not only information in general but also political opinions, whereas Facebook provides the capability for direct dialogs. A lot of studies have shown that a need exists for stakeholders to collect, monitor, analyze, summarize and visualize these social media views. Some authors have tended to categorize these comments as either positive or negative ignoring the neutral category. In this paper, we demonstrate the importance of the neutral category in the clustering of sentiments from the social media. We then demonstrate the use of fuzzy clustering for this kind of task.
Evaluating the accuracy and effectiveness of criminal geographic profiling methods: the case of Dandora, Kenya
(Taylor & Francis Group, 2014) Mburu, Lucy W.; Helbich, Marco
Criminal geographic profiling (CGP) prioritizes offender search, extensively reducing the resources expended in criminal investigations. The utility of CGP has, however, remained unclear when variations in environmental characteristics and offense type are introduced. This study evaluates several CGP strategies with data from Dandora, a small but densely populated suburb of Nairobi, Kenya. The research employs error distance and search-cost measures to determine CGP accuracy. Characterized by much shorter journeys to crime than those observed in Western cities, this study discovers significant applicability of CGP strategies in prioritizing offender searches. The negative exponential CGP strategy is identified to generate the most accurate geo-profiles.
Open mobile ambient learning(OMAL): The next generation of mobile learning for 'mobile-rich' but 'computer-poor' contexts
(DAAD, 2014) Mwendia, Simon N.; Buchem, Ilona
By the end of year 2011, Africa had over 620 million mobile connections, overtaking Latin America to become second largest mobile market after Asia. According to Ilona Buchem in 2012, since mobile devices and applications are used every day in order to interact, plan, work, play and orientate, mobile pedagogies in context of HE in Africa should focus more on ambient assisted learning to facilitate greater independence and improve quality of life, which is especially beneficial to learners with special needs (e.g. disabled people and people living in remote locations). African universities face challenges in their attempts to offer quality educations, including the lack of access to university educational facilities and scientific information, poor access to computers, scarce availability of qualified teachers and the irrelevance of formal education to African needs, according to research conducted in 2008 and 2009. This removes flexibility that is needed in personalized learning, according to a 2010 study. This calls for innovative learning approaches that facilitate flexible access of open education resources (OER) in settings with high prevalence of mobile devices (such as mobile phones) but poor prevalence of location dependent devices (such as computers) as it is the case in Africa. Current forms of mobile learning aim at enabling context-sensitive learning, e.g. interacting with learners by considering learner’s current context (e.g. location, activity, social relations), mixed reality learning, for example, enhancing the meaning of learning content by allowing learners to participate in a media-rich environment, as well as ambient learning, for example, delivering learning content at anytime, anywhere and anyhow by placing digital artefacts within the environment of the learner, according to a 2006 report. However, a number of European projects in this area assume availability of adequate infrastructures, such as location dependent devices, which are hard to implement in setting such as African based universities, given the lack of sophisticated technological infrastructures. This presentation focuses on mobile learning as a means for supporting advancement in the quality of education by addressing mobile pedagogies that provide flexible access to learning through consideration of learner’s current context. Based on the Mobile Interface Ambient Learning (MIAL) framework, according to a 2013 report, designed for contexts with high penetration of mobile devices (mobile rich) but low prevalence of location dependent devices (computer poor), we propose Open Mobile Ambient Learning (OMAL) as an approach to enhance adoption of ambient learning by integrating Open Educational Resources (OER) into Personal Learning Environments (PLE), e.g. individual collocations of distributed applications, services and resources, according to a 2011 study, in context of HE in Africa. OMAL targets to benefit university students with special needs (e.g. disabled, elderly) by improving their learning independence and digital marginalization (e.g. own phones but have poor access to computers) through enhancing access flexibility. OMAL combines mechanisms of embedding intelligent interface in mobile devices to monitor special learning needs and contexts (Mobile Ambient Intelligence), with mechanism of appropriating adaptable learning tools and services by learner through mobile devices Adaptable Mobile Personal Learning Environment (AMPLE) and mechanisms of dynamically discovering Personal Learning Networks (PLN) in OER driven environments.
Culture aware M-learning classification framework for African countries
(IGI Global, 2014) Mwendia, Simon N.; Wagacha, Peter W.; Oboko, Robert
African countries are currently experiencing proliferation of mobile phone subscriptions but no prevalence of personal computers or electricity (Parker, 2011). It is estimated that, by the end of 2015 in Sub-Saharan Africa, the percentage of people with mobile network access will surpass that of access to electricity in homes (Rao, 2011). This phenomenon is also experienced in learning institutions, particularly universi- ties, where almost every student owns a mobile phone (Kashorda & Waema, 2009). Although there is a great potential for Mobile Learning (M-Learning) in education, the formal integration of M-Learning in the education systems is in its infancy since there is limited number of M-Learning projects in the region. This is in contrast with the rapid increase and integration of mobile phones in the daily lives of the population in the region (Isaacs, 2012). According to Olaniran (2009), online learning needs to be culturally aware and investigate the dimensions of cultural variability as well as its influence on learning within global education. In an attempt to address this need, this chapter focuses on the African region in describing dimensions of cultural variability and proposes four categories for M-Learning projects as well as their influences on dimensions of cultural variability.
Supporting e-learning in computer-poor environments by combining oer, cloud services and mobile learning
(ICCE2014, 2014) Mwendia, Simon Nyaga; Hoppe, H. Ulrich
Abstract Research supervision is an important type of support for advanced students when engaged in study projects or in writing their final theses. One of the most common complaints from research students is erratic or infrequent contact with supervisors, who might be too busy with other responsibilities or are not present frequently enough . High proliferation of mobile phones(i.e. 'mobile-rich') but no computer prevalence (i.e. 'computer-poor') in African countries calls for using mobile technologies to address this challenge. However, limitations of mobile devices (such as usage cost, memory capacity and small screen) are some of the barriers for mobile learning adoption. In this paper, we combine mobile learning with OER and Cloud Computing Services to enhance supervisors’ availability to their research students, who are in 'mobile-rich' but 'computer-poor ' learning settings typical for African universities.
Ambient learning conceptual framework for bridging digital divide in higher education
(IGI Global, 2014) Mwendia, Simon N.; Wagacha, Peter W.; Oboko, Robert
According to ITU (2012), digital divide is the difference between countries in terms of levels of ICT development. This difference remains significant. In 2011, the ICT Development Index (IDI) value of developed countries (6.52) was twice as high as that of developing countries (3.24). The need to link the digital divide for universal broadband Internet access is within the key international development goals, which include World Summit on the Information Society (WSIS) goals and Millennium Development Goals (MDGs). Ambient learning is the next generation of M-learning (Bick, Kummer, Pawlowski, & Veith, 2007), which allows flexible content access by considering learner's current situation and learning context (Kofod-Petersen, et al., 2008). However, ambient learning has not yet attained a state of common understanding (Winker, Scharf, Hahn, & Herczeg, 2011) and is not widely used or adopted (Bick, et al., 2007). This chapter presents a theoretical conceptual framework to foster creativity for innovative ambient learning applications, which can be used to bridge the digital gap between universities in developed and developing countries.
Crime risk estimation with a commuter- harmonized ambient population
(Taylor & Francis Group, 2016) Mburu, Lucy W.; Helbich, Marco
Residential population data are frequently employed to link the crime incidence of an area with the number of residents to estimate the underlying risk. Human mobility patterns cause shifts in the baseline population, however, that can potentially influence the crime statistics. This study therefore employed an ambient population that combined residential population data with data depicting the commuting activity in small administrative areas. The effects of the commuter-harmonized ambient population on crime were then evaluated in a series of negative binomial regression models. The models also controlled for criminogenic factors and incorporated eigenvector spatial filtering to adjust for spatial effects. The results show significant effects of commuting patterns on crime outcomes. For certain crimes, such as violence, theft, and disorder, the inbound commuters are significantly associated with high risk. It was further discovered that an offset variable comprising the commuter-harmonized ambient population data models the crime outcomes more reliably than when residential population data are used. Spatial filtering was found to effectively eradicate residual spatial autocorrelation after accounting for effects of the predictor variables. We conclude that calculating crime rates using the residential population does not constitute an accurate risk measure and that the ambient population has crucial implications for realistic and reliable target representation and crime modeling.
A contextualized and personalized model to predict user interest using location-based social networks
(Elsevier Ltd., 2016) Mburu, Lucy W.; Li, Ming; Sagl, Günther; Fan, Hongchao
The accurate determination of user interest in terms of geographic information is essential to numerous mobile applications, such as recommender systems and mobile advertising. User interest is greatly influenced by the usage context and varies across individuals; therefore, a user interest model should incorporate these individual needs and propensities. In this paper, we present an approach to model user interest in a contextualized and personalized manner based on location-based social networks. Multinomial logistic regression is employed to quantify the relationship between user interest and usage context at both the aggregate and individual levels. The proposed approach is tested in a real-world application using Foursquare check-ins issued between February and June 2014 in the three major cities of Chicago, Los Angeles and New York. Results demonstrate the capability of the contextualization process for capturing contextual influences on user interest, and that such influences can be observed at a fine-grained scale at the individual level through the personalization process. The proposed approach therefore enables contextualized and personalized estimation of user interest, thereby contributing useful information to follow-up mobile applications.
Modeling spatial interactions between areas to assess the burglary risk
(MDPI, 2016) Mburu, Lucy W.; Bakillah, Mohamed
Abstract It is generally acknowledged that the urban environment presents different types of risk factors, but how the structural effects of areas influence the risk levels in neighboring areas has been less widely investigated. This research assesses the local effects of burglary contributory factors on burglary over small areas in a large metropolitan region. A comparative framework is developed for analyzing the effects of geographic dependence on burglary rates, and for assessing how such dependence conditions the community context and the urban land use. A local indicators spatial autocorrelation analysis assesses burglaries over five years (2011–2015) to identify risk clusters. Thereafter, effects of different variables (e.g., unemployment, building density) on burglary frequency are estimated in a series of regression models while controlling for changes in the risk levels of nearby surrounding areas. Results uncover strong evidence that the configuration of the surroundings influences risk. After controlling for area-based interaction, patterns are identified that contrast with the previous literature, such as lower burglary frequency in areas with higher tenancy in social housing units. Together the findings demonstrate that the spatial arrangement of areas is as crucial as contextual crime factors, particularly when assessing the risk for small areas.
Analysis of community properties and node properties to understand the structure of the bus transport network
(ScienceDirect, 2016) Mburu, Lucy W.; Sun, Yeran; Wang, Shaohua
Akin to most infrastructures, intraurban bus networks are large and highly complex. Understanding the composition of such networks requires an intricate decomposition of the network into modules, taking into account the manner in which network links are distributed among the nodes. There exists for each set of highly interlinked nodes little connectivity with the next set of highly interlinked nodes. This inherent property of nodes makes community detection a popular approach for analyzing the structure of complex networks. In this study, we attempt to understand the structure of the intraurban bus network of Ireland’s capital city, Dublin in a two-step approach. We first analyze the modular structure of the network by identifying potential communities. Secondly, we assess the prominence of each network node by examining the module-based topological properties of the nodes. Results of this empirical study reveal a clear pattern of independent communities, indicating thus, an implicit multi-community structure of the intraurban bus network. Examination of the geographic characteristics of the identified communities shows a degree of socio-economic divisions of the Dublin city. Furthermore, a large majority of the important nodes (vital transportation hubs) are located at the city center, implying that most of the bus lines in Dublin city tend to intersect the city’s core.
Dynamic heuristics greedy search: a mobile information retrieval algorithm for ambient learning systems
(ACM Digital Library, 2016) Mwendia, Simon N.; Oboko, Robert; Wagacha, Peter Waiganjo
Environmental risk factors influencing bicycle theft:
(PubMed Central, 2016) Mburu, Lucy W.; Helbich, Marco
Abstract Urban authorities are continuously drawing up policies to promote cycling among commuters. However, these initiatives are counterproductive for the targeted objectives because they increase opportunities for bicycle theft. This paper explores Inner London as a case study to address place-specific risk factors for bicycle theft at the street-segment level while controlling for seasonal variation. The presence of certain public amenities (e.g., bicycle stands, railway stations, pawnshops) was evaluated against locations of bicycle theft between 2013 and 2016 and risk effects were estimated using negative binomial regression models. Results showed that a greater level of risk stemmed from land-use facilities than from area-based socioeconomic status. The presence of facilities such as train stations, vacant houses, pawnbrokers and payday lenders increased bicycle theft, but no evidence was found that linked police stations with crime levels. The findings have significant implications for urban crime prevention with respect to non-residential land use.
Contextual factors and public value of e-government services in kenya
(Global Scientific Journals, 2017) Kamau, Gabriel; Wausi, Agnes; Njihia, James
Abstract E-government research has been skewed towards technological deterministic perspective mainly centering on technological issues. This provides no explicit guidance to the design and practice of e-government programs that result to increased uptake of e-government services. Theoretical discourse reveals undisputed consensus among e-government researchers that e-government uptake may be influenced by others contextual factors such as administrative and political consequences and should not be overlooked as they are valued. This study filled this gap by conducting an empirical investigated of the influence of contextual factors: ICT infrastructure, human capital and governance and the public value of e-government services. The study employed a mixed method exploratory, descriptive cross-sectional approach to realize the research objectives. Structural Equation Modeling was used to conduct statistical analysis of data collected. The study findings demonstrated that ICT infrastructure insignificantly contributed to public value of e-government services. However, the study revealed significantly contribution of human capital as well as governance to public value of e-government services.
Communities as neighborhood guardians: A spatio-temporal analysis of community policing in Nairobi's suburbs
(Springer, 2017) Mburu, Lucy W.; Helbich, Marco
The efficacy of citizens to participate in neighborhood-watch activities and report signs of trouble is important for safeguarding communities against crime. Community policing is a key policing strategy for utilizing the capability of residents to solve local crime-related problems. However, variability in social cohesion among communities profoundly affects the contribution of individuals towards policing. After 7 years of a community policing intervention in suburban Nairobi, Kenya, this study assesses the program as a state-initiated and community-sustained security venture. We compare micro-scaled concentrations of different property and violent crimes to identify geographic variations over time using kernel density estimates and spatio-temporal scan statistics. Multi-level regression models assess the direct and conditioned perceptions of individuals and their neighbors, and how these perceptions influenced crime variation during the pre- and post-intervention periods of community policing. Both the density estimates and the scan statistics pinpoint a disproportionate crime reduction across neighborhoods. The research findings also depict an interaction between the communal willingness to participate in neighborhood-watch activities and the relative crime decline. In particular, those communities that have good relations with the police are more inclined to involve themselves in community policing. The findings of this study are discussed in terms of their implications for policy.
Directing attention through gaze hints improves task solving in human-humanoid interaction
(pubMed, 2018) Mwangi, Eunice; Barakova, Emilia I; Díaz-Boladeras, Marta; Català Mallofré, Andreu; Rauterberg, Matthias
Abstract In this paper, we report an experimental study designed to examine how participants perceive and interpret social hints from gaze exhibited by either a robot or a human tutor when carrying out a matching task. The underlying notion is that knowing where an agent is looking at provides cues that can direct attention to an object of interest during the activity. In this regard, we asked human participants to play a card matching game in the presence of either a human or a robotic tutor under two conditions. In one case, the tutor gave hints to help the participant find the matching cards by gazing toward the correct match, in the other case, the tutor only looked at the participants and did not give them any help. The performance was measured based on the time and the number of tries taken to complete the game. Results show that gaze hints (helping tutor) made the matching task significantly easier (fewer tries) with the robot tutor. Furthermore, we found out that the robots' gaze hints were recognized significantly more often than the human tutor gaze hints, and consequently, the participants performed significantly better with the robot tutor. The reported study provides new findings towards the use of non-verbal gaze hints in human-robot interaction, and lays out new design implications, especially for robot-based educative interventions.
Ambient learning - knowledge as a service model: towards the achievement of sustainable development goal four
(IEEE, 2018) Mwendia, Simon N.; Karanja, Richard G.
Studies show that United Nations Sustainable Development Goal Four is yet to be achieved. This paper presents an artefact named “Ambient learning- Knowledge as a Service model” for describing how actionable knowledge can be extracted from ambient learning systems to support improvement and consequently facilitate the achievement of Sustainable Development Goal Four. A creative process was adopted to guide the development of the model. The process involved carrying out problem analysis through literature review, designing the model by combining ambient learning and Knowledge as a Service concept and demonstrating its application by developing a prototype. Evaluation results revealed that C4.5 algorithm that is implemented in Waikato Environment for Knowledge Analysis (WEKA) software is suitable for extracting knowledge from ambient learning systems while Swi-prolog software can be applied to create a tool for knowledge delivery.