An exploratory study on how an accelerator program influences entrepreneurial learning: case of the Sri Lankan government accelerator

Entrepreneurs navigate through various phases of their new venture, starting with an idea, leading towards exploiting an opportunity and finally, for some managing the growth of the new venture or for others exiting the venture through harvest or closure. For first time entrepreneurs in particular, it is important to learn the multi-disciplinary skills of entrepreneurship during this process. While a body of literature on entrepreneurial learning exists, learning the implications and applications of these discrete learning constructs has not been explored in the context of the entrepreneur’s learning journey. However, the entrepreneurial journey and the resulting entrepreneurial learning during the journey must be seen as a continuum not as a series of isolated entrepreneurial learning constructs. This research examines how entrepreneurial learning is influenced in the context of a government accelerator program. This entrepreneurship program is vital, in the context of Sri Lanka, where the government is placing priority on the Information and Communication Technology (ICT) sector as the nation recovers economically from a 30 year civil war and the tragic effects of a tsunami. ICT is already among the top (five) 5 foreign exchange earners in Sri Lanka and the government actively focuses on supporting ICT entrepreneurs. The research methodology adopts an exploratory research design, using the case of the “one and only” government ICT entrepreneur accelerator in Sri Lanka. The primary means of data collection in this study was through semi-structured and open-ended interviews with stakeholders and texts from an on-going learning journal maintained by the participants in the accelerator program. Data was then analysed through concept mapping and thematic analysis following a perspective on theory building Entrepreneurial learning is relatively recent research area, in which publications on empirical and conceptual approaches began to appear from around the late 1990’s. While there is a body of knowledge available on entrepreneurial learning, researchers have called for further qualitative research in order to better understand the entrepreneurial learning process empirically. The study is the first of its kind to analyse and document the influence of a government accelerator on entrepreneurial learning. Firstly, the study findings reveal how the entrepreneurs perceive entrepreneurial learning in the given context. Secondly, the findings discuss how the entrepreneurial learning constructs are intervened during the temporal entrepreneurial process. Lastly, the thesis establishes the evidence that the government accelerator influences to strengthen the entrepreneurial mindset of entrepreneurs, supports building learning networks for entrepreneurs and facilitates the creation of a learning culture in their respective infant organisations. Based on these findings, the thesis identifies seven (7) propositions embedded in the government accelerator program when researching to seek the answers for the two research questions. The study contributes towards the theory of entrepreneurial learning on how government accelerators shape and influence entrepreneurial learning, particularly in the developing world. The study also integrates entrepreneurial learning theories by developing a conceptual model of how the facets of entrepreneurial learning are inter-related. This study makes recommendations on how future researchers could replicate, extend, and modify the findings. It also makes specific recommendations to governments and policy makers wishing to establish entrepreneurial accelerator programs.Thesis (Ph.D.) -- University of Adelaide, Entrepreneurship, Commercialisation and Innovation Centre, 201

Evolutionary algorithms and weighting strategies for feature selection in predictive data mining

The improvements in Deoxyribonucleic Acid (DNA) microarray technology mean that thousands of genes can be profiled simultaneously in a quick and efficient manner. DNA microarrays are increasingly being used for prediction and early diagnosis in cancer treatment. Feature selection and classification play a pivotal role in this process. The correct identification of an informative subset of genes may directly lead to putative drug targets. These genes can also be used as an early diagnosis or predictive tool. However, the large number of features (many thousands) present in a typical dataset present a formidable barrier to feature selection efforts. Many approaches have been presented in literature for feature selection in such datasets. Most of them use classical statistical approaches (e.g. correlation). Classical statistical approaches, although fast, are incapable of detecting non-linear interactions between features of interest. By default, Evolutionary Algorithms (EAs) are capable of taking non-linear interactions into account. Therefore, EAs are very promising for feature selection in such datasets. It has been shown that dimensionality reduction increases the efficiency of feature selection in large and noisy datasets such as DNA microarray data. The two-phase Evolutionary Algorithm/k-Nearest Neighbours (EA/k-NN) algorithm is a promising approach that carries out initial dimensionality reduction as well as feature selection and classification. This thesis further investigates the two-phase EA/k-NN algorithm and also introduces an adaptive weights scheme for the k-Nearest Neighbours (k-NN) classifier. It also introduces a novel weighted centroid classification technique and a correlation guided mutation approach. Results show that the weighted centroid approach is capable of out-performing the EA/k-NN algorithm across five large biomedical datasets. It also identifies promising new areas of research that would complement the techniques introduced and investigated

Phytomedicinal properties of Hygrophila schulli (Neeramulliya)

Hygrophila schulli which is known as “Neermulli’’ in the vernacular is an herbaceous plant native to Sri Lanka. Ancient medicinal literature suggests the use of H. schulli whole plant or its parts for the treatment of different communicable and non-communicable diseases including diabetes mellitus and tuberculosis. Active constituents and secondary metabolites including alkaloids, tannins, steroids, proteins, flavonoids, and glycosides are identified to possess antimicrobial, antitumor, antioxidant, hepatoprotective, anthelmintic, nephroprotective, antidiabetic, anticataract, anti-inflammatory, anti-nociceptive, hematopoietic, diuretic, antiurolithiatic, antipyretic, neuroprotection, and anti-endotoxin activities. In this review, we reviewed clinical studies, patents, and analytical studies from the earliest found examples from 1886 to the end of 2021. We critically analyzed and attempt to summarize the information based on bioactivities and chemical composition of H. schulli plant extracts which will be of future use for researchers in this field

Geospatial Analysis of Horizontal and Vertical Urban Expansion Using Multi-Spatial Resolution Data: A Case Study of Surabaya, Indonesia

Urbanization addresses urban expansion, and it leads conversion of the green space into the built-up area. However, previous studies mainly focused on two-dimensional (2D) urban expansion rather than three-dimensional (3D) growth. Here, the purpose of this study is to examine the urban expansion, including built-up and green space for both horizontal and vertical dimensions using geospatial analysis including remote sensing (RS) and Geographic Information System (GIS) in the sub-Central Business District (CBD) area of Surabaya, Indonesia. The medium resolution remote sensing data for both image and Digital Surface Model (DSM) acquired by Advanced Land-Observing Satellite (ALOS) were applied for time-1 (2010). The orthophoto and DSM derived by LiDAR were used for time-2 (2016). We quantified the built-up and green expansions in 2D (area), which were extracted from land use/land cover (LU/LC) by applying hybrid classification. The built-up and green expansions in 3D (volume) were estimated by generating a surface feature model. The spatial configuration of area expansion was investigated using patch metric, while the volume growth was examined using the volume expansion rate. We got three findings. (1) The built-up and green area had expanded about 11.54% and 95.61%, respectively, from 2010 to 2016. The expansion of green area presented in a notable portion, which was mainly contributed by the conversion of bareland to playground or park. However, the expansion of built-up area was less than the volume expansion of 20.6%. It revealed that built-up growth led to vertical rather than horizontal development. (2) The built-up area expansion tended to scatter configuration, whereas, the green area expansion tended to aggregate in a linear pattern. (3) The ratio of built-up volume expansion to green volume expansion showed a mean of 3.7, indicating that the development of built-up and green volume was imbalanced. The built-up growth presented higher than the green growth, mainly in the areas with more vertical building establishment. The pressing need for higher green volume in the study area was identified in several sites located at surrounding artery and toll roads. Overall, our approach can be applied as a reference in monitoring neighborhood environment through greening programs for sustainable urban development

Orchestration of renewable generation in low energy buildings and districts using energy storage and load shifting

There is increasing penetration of renewable generation in buildings and districts. There are challenges in making the effective use of this generation. The objective of the ORIGIN project (Orchestration of Renewable Integrated Generation In Neighborhoods) is to shape loads so that the fraction of energy consumed that is from local renewable generation is maximized, and energy imported from outside sources is minimized. This paper presents the overall approach taken in the ORIGIN project and explores building physics aspects of solar thermal storage system orchestration. The case study districts are briefly introduced and characteristics of their generation, buildings, districts and shiftable loads described. The orchestration approach taken in ORIGIN is then presented. At the core of the ORIGIN system is the orchestration algorithm which generates informational and control outputs to shape future loads to best meet the objectives. The model based approach used to quantify thermal and electrical load shifting opportunities for pre-charging, coasting or avoiding loads, while meeting thermal comfort and other demands, is described using a solar thermal storage system as an example. The future steps for the ORIGIN project; retrofit of the ORIGIN system into existing districts and potential for other future applications is briefly discussed

Impact of Landscape Structure on the Variation of Land Surface Temperature in Sub-Saharan Region: A Case Study of Addis Ababa using Landsat Data (1986–2016)

Urbanization has bloomed across Asia and Africa of late, while two centuries ago, it was confined to developed regions in the largest urban agglomerations. The changing urban landscape can cause irretrievable changes to the biophysical environment, including changes in the spatiotemporal pattern of the land surface temperature (LST). Understanding these variations in the LST will help us introduce appropriate mitigation techniques to overcome negative impacts. The research objective was to assess the impact of landscape structure on the variation in LST in the African region as a geospatial approach in Addis Ababa, Ethiopia from 1986–2016 with fifteen-year intervals. Land use and land cover (LULC) mapping and LST were derived by using pre-processed Landsat data (Level 2). Gradient analysis was computed for the pattern of the LST from the city center to the rural area, while intensity calculation was facilitated to analyze the magnitude of LST. Directional variation of the LST was not covered by the gradient analysis. Hence, multidirectional and multitemporal LST profiles were employed over the orthogonal and diagonal directions. The result illustrated that Addis Ababa had undergone rapid expansion. In 2016, the impervious surface (IS) had dominated 33.8% of the total lands. The IS fraction ratio of the first zone (URZ1) has improved to 66.2%, 83.7%, and 87.5%, and the mean LST of URZ1 has improved to 25.2 °C, 26.6 °C, and 29.6 °C in 1986, 2001, and 2016, respectively. The IS fraction has gradually been declining from the city center to the rural area. The behavior of the LST is not continually aligning with a pattern of IS similar to other cities along the URZs. After the specific URZs (zone 17, 37, and 41 in 1986, 2001, and 2016, respectively), the mean LST shows an increasing trend because of a fraction of bare land. This trend is different from those of other cities even in the tropical regions. The findings of this study are useful for decision makers to introduce sustainable landscape and urban planning to create livable urban environments in Addis Ababa, Ethiopia

Impact of Urban Surface Characteristics and Socio-Economic Variables on the Spatial Variation of Land Surface Temperature in Lagos City, Nigeria

The urban heat island (UHI) and its consequences have become a key research focus of various disciplines because of its negative externalities on urban ecology and the total livability of cities. Identifying spatial variation of the land surface temperature (LST) provides a clear picture to understand the UHI phenomenon, and it will help to introduce appropriate mitigation technique to address the advanced impact of UHI. Hence, the aim of the research is to examine the spatial variation of LST concerning the UHI phenomenon in rapidly urbanizing Lagos City. Four variables were examined to identify the impact of urban surface characteristics and socio-economic activities on LST. The gradient analysis was employed to assess the distribution outline of LST from the city center point to rural areas over the vegetation and built-up areas. Partial least square (PLS) regression analysis was used to assess the correlation and statistically significance of the variables. Landsat data captured in 2002 and 2013 were used as primary data sources and other gridded data, such as PD and FFCOE, were employed. The results of the analyses show that the distribution pattern of the LST in 2002 and 2013 has changed over the study period as results of changing urban surface characteristics (USC) and the influence of socio-economic activities. LST has a strong positive relationship with NDBI and a strong negative relationship with NDVI. The rapid development of Lagos City has been directly affected by conversion more green areas to build up areas over the time, and it has resulted in formulating more surface urban heat island (SUHI). Further, the increasing population and their socio-economic activities including industrialization and infrastructure development have also caused a significant impact on LST changes. We recommend that the results of this research be used as a proxy tool to introduce appropriate landscape and town planning in a sustainable viewpoint to make healthier and livable urban environments in Lagos City, Nigeria

Quantifying Surface Urban Heat Island Formation in the World Heritage Tropical Mountain City of Sri Lanka

Presently, the urban heat island (UHI) phenomenon, and its adverse impacts, are becoming major research foci in various interrelated fields due to rapid changes in urban ecological environments. Various cities have been investigated in previous studies, and most of the findings have facilitated the introduction of proper mitigation measures to overcome the negative impact of UHI. At present, most of the mountain cities of the world have undergone rapid urban development, and this has resulted in the increasing surface UHI (SUHI) phenomenon. Hence, this study focuses on quantifying SUHI in Kandy City, the world heritage tropical mountain city of Sri Lanka, using Landsat data (1996 and 2017) based on the mean land surface temperature (LST), the difference between the fraction of impervious surfaces (IS), and the fraction of green space (GS). Additionally, we examined the relationship of LST to the green space/impervious surface fraction ratio (GS/IS fraction ratio) and the magnitude of the GS/IS fraction ratio. The SUHI intensity (SUHII) was calculated based on the temperature difference between main land use/cover categories and the temperature difference between urban-rural zones. We demarcated the rural zone based on the fraction of IS recorded, <10%, along with the urban-rural gradient zone. The result shows a SUHII increase from 3.9 °C in 1996 to 6.2 °C in 2017 along the urban-rural gradient between the urban and rural zones (10 < IS). These results relate to the rapid urban expansion of the study areas from 1996 to 2017. Most of the natural surfaces have changed to impervious surfaces, causing an increase of SUHI in Kandy City. The mean LST has a positive relationship with the fraction of IS and a negative relationship with the fraction of GS. Additionally, the GS/IS fraction ratio shows a rapid decline. Thus, the findings of this study can be considered as a proxy indicator for introducing proper landscape and urban planning for the World Heritage tropical mountain city of Kandy in Sri Lanka

ICSECM 2015 - Facilities Management Approaches for Sustainability

In its most general sense sustainability is the capacity to endure. Sustainability has emerged as a result of significant concerns about the unintended social, environmental, and economic consequences of rapid population growth, economic growth and consumption of natural resources. Sustainability depends on three basic pillars; environmental, social and economical sustainability. In order to be sustainable, these three areas of sustainability must be achieved throughout the life cycle of a facility. The facility manager is in a unique position to view the entire process and is often the leader of the only group that has influence over the entire life cycle of a facility. Therefore, the facility manager often becomes the proponent of sustainable and green practices. Armed with the proper approaches, the Facility Manager can create long‐lasting value to the organisation by developing, implementing and maintaining sustainable facility practices. Therefore, this study attempts to pinpoint the Facilities Management approaches to achieve and maintain environmental, social and economical sustainability. A comprehensive literature review was carried out on a broader perspective with the purpose of getting familiarize with the research phenomena. Interview guidelines were developed based on the findings of the literature review. In order to validate and further the literature findings five expert interviews were carried out with experienced industry practitioners. Research findings revealed that in Sri Lankan context, a Facility Manager’s involvement for maintaining sustainability is most crucial in the operational phase of a facility. FM should have a clear view of environmental, social and economical aspects of sustainability. He / She should equally value the three pillars and a balanced approach needs to be taken in order to maintain a facility that is sustainable

The Impacts of Landscape Changes on Annual Mean Land Surface Temperature in the Tropical Mountain City of Sri Lanka: A Case Study of Nuwara Eliya (1996–2017)

Although urbanization has contributed to improving living conditions, it has had negative impacts on the natural environment in urbanized areas. Urbanization has changed the urban landscape and resulted in increasing land surface temperature (LST). Thus, studies related to LST in various urban environments have become popular. However, there are few LST studies focusing on mountain landscapes (i.e., hill stations). Therefore, this study investigated the changes in the landscape and their impacts on LST intensity (LSTI) in the tropical mountain city of Nuwara Eliya, Sri Lanka. The study utilized annual median temperatures extracted from Landsat data collected from 1996 to 2017 based on the Google Earth Engine (GEE) interface. The fractions of built-up (BL), forested (FL) and agricultural (AL) land, were calculated using land use and cover maps based on urban–rural zone (URZ) analysis. The urban–rural margin was demarcated based on the fractions of BL (&lt;10%), and LSTI that were measured using the mean LST difference in the urban–rural zone. Besides, the mixture of land-use types was calculated using the AL/FL and BL/FL fraction ratios, and grid-based density analysis. The results revealed that the BL in all URZs rapidly developed, while AL decreased during the period 1996 to 2017. There was a minimal change in the forest area of the Nuwara Eliya owing to the government’s forest preservation policies. The mean temperature of the study area increased by 2.1 °C from 1996 to 2017. The magnitude of mean LST between urban–rural zones also increased from 1.0 °C (1996) to 3.5 °C (2017). The results also showed that mean LST was positively correlated with the increase and decrease of the BL/FL and AL/FL fraction ratios, respectively. The grid-based analysis showed an increasing, positive relationship between mean LST and density of BL. This indicated that BL density had been a crucial element in increasing LST in the study area. The results of this study will be a useful indicator to introduce improved landscape and urban planning in the future to minimize the negative impact of LST on urban sustainability