Philip Owende - Academia.edu (original) (raw)

Papers by Philip Owende

Frontiers in sustainability, Aug 3, 2022

Frontiers in Education, 2022

As a consequence of the COVID-19 pandemic, many college courses have pivoted to complete online d... more As a consequence of the COVID-19 pandemic, many college courses have pivoted to complete online delivery and colleges are also tasked with providing student supports online. It is likely this transition will last beyond any COVID-19 specific restrictions, therefore this small-scale, exploratory study examined the efficacy and impact of the provision of a 5 week online emotional intelligence (EI) coaching programme to a cohort of Irish university students (n = 19) studying at Technological University Dublin (TU Dublin). Results revealed that the average overall level of EI increased for participants following the coaching programme. Students reported that they believed the programme provided emotional support and that it also enabled them to manage academic stress more effectively and ultimately that engagement with the programme had a positive impact on their academic engagement. Taken collectively, the results of this study suggest that whilst EI coaching can be successfully delive...

Sentiment analysis and opinion mining have become emerging topics of research in recent... more Sentiment analysis and opinion mining have become emerging topics of research in recent years but most of the work is focused on data in the English language. A comprehensive research and analysis are essential which considers multiple languages, machine translation techniques, and different classifiers. This paper presents, a comparative analysis of different approaches for multilingual sentiment analysis. These approaches are divided into two parts: one using classification of text without language translation and second using the translation of testing data to a target language, such as English, before classification. The presented research and results are useful for understanding whether machine translation should be used for multilingual sentiment analysis or building language specific sentiment classification systems is a better approach. The effect...

Part of the Environmental Engineering Commons This Article is brought to you for free and open ac... more Part of the Environmental Engineering Commons This Article is brought to you for free and open access by the Energy at

Abstract. The core concepts, or threads, of Biosystems Engineering (BSEN) are variously understoo... more Abstract. The core concepts, or threads, of Biosystems Engineering (BSEN) are variously understood by those within the discipline, but have never been unequivocally defined due to its early stage of development. This makes communication and teaching difficult compared to other well established engineering subjects. Biosystems Engineering is a field of Engineering which integrates engineering science and design with applied biological, environmental and agricultural sciences. It represents an evolution of the Agricultural Engineering discipline applied to all living organisms not including biomedical applications. The basic key element for the emerging EU Biosystems Engineering program of studies is to ensure that it offers essential minimum fundamental engineering knowledge and competences. A core curriculum developed by Erasmus Thematic Networks is used as benchmark for Agricultural and Biosystems Engineering studies in Europe. The common basis of the core curriculum for the discip...

Learning analytics is an evolving discipline with capability for educational data analysis to ena... more Learning analytics is an evolving discipline with capability for educational data analysis to enable better understanding of learning processes. This paper reports on learning analytics research at Institute of Technology Blanchardstown, Ireland, that indicated measureable factors can identify first year students at risk of failing based on data available prior to commencement of first year of study. The study was conducted over three years, 2010 to 2012, on a student population from a range of academic disciplines (n=1,207). Data was gathered from both student enrolment data maintained by college administration, and an online, self-reporting tool administered during induction sessions for students enrolling into the first year of study. Factors considered included prior academic performance, personality, motivation, selfregulation, learning approaches, learner modality, age and gender. A k-NN classification model trained on data from the 2010 and 2011 student cohort, and tested on ...

This paper discusses the challenges to extraction of wood on low gradient harvesting sites that a... more This paper discusses the challenges to extraction of wood on low gradient harvesting sites that are classified as ‘sensitive’ and therefore have limitations on the use of forwarders and skidders for ground based wood extraction. Although the discussion is centred on plantation forests on peat soils in Ireland, the same may be generalised for forests on other soft soils that restrict the envirogentle use of forwarders and skidders. Wood extraction by cable systems is important for sustainable harvesting operations on such sites. Background Ireland’s forest area comprises approximately 9% (626,000 ha) of the total land area (Forest Service 2000). The Irish Forestry Board (Coillte) manages 70% (450,000 ha) of the forest area, of which about 80% is under commercial timber crop. The main commercial tree species include Sitka spruce, Lodgepole pine, Norway Spruce, Larch, Scots pine and Douglas fir, and these are established on five major soil categories, with 44% on peat soils (Figure 1)....

The characteristic response of flexible pavements under traffic load depict a delayed lateral str... more The characteristic response of flexible pavements under traffic load depict a delayed lateral strain relaxation (Viscoelasticity), a phenomenon that may be more accurately and expeditiously analysed using finite element (FE) viscoelastic response models. In this study a flexible pavement was modelled using ANSYS/ED finite element software suite. The pavement model was subjected to cyclic loading that simulated three levels of truck loads on 10R20 tyres at four tyre inflation pressures (viz. 350,490,630 and 770 kPa). The modelled results were in good agreement with the measured in-situ full-scale test data. Therefore, for known pavement material characteristics and tyre-pavement contact regime, finite element method could be used to efficiently estimate the fatigue life of flexible pavement with thin bituminous surfacing layers. * Corresponding author. Tel: +35318851194; Fax: +353-1-8851001 Email address: rachel.mulungye@itb.ie Introduction Characteristic response of in-situ bitumino...

Increasing college participation rates, and a more diverse student population, is posing a challe... more Increasing college participation rates, and a more diverse student population, is posing a challenge for colleges in facilitating all learners achieve their potential. This paper reports on a study to investigate the usefulness of data mining techniques in the analysis of factors deemed to be significant to academic performance in first year of college. Measures used include data typically available to colleges at the start of first year such as age, gender and prior academic performance. The study also explores the usefulness of additional psychometric measures that can be assessed early in semester one, specifically, measures of personality, motivation and learning strategies. A variety of data mining models are compared to assess the relative accuracy of each.

The increasing numbers enrolling for college courses, and increased diversity in the classroom, p... more The increasing numbers enrolling for college courses, and increased diversity in the classroom, poses a challenge for colleges in enabling all students achieve their potential. This paper reports on a study to model factors, using data mining techniques, that are predictive of college academic performance, and can be measured during first year enrolment. Data was gathered over three years, and focused on a diverse student population of first year students from a range of academic disciplines (n≈1100). Initial models generated on two years of data (n=713) demonstrate high accuracy. Advice is sought on additional analysis approaches to consider.

The purpose of this study was to evaluate differential global positioning system (DGPS) positiona... more The purpose of this study was to evaluate differential global positioning system (DGPS) positional accuracy on Irish forest roads with typical peripheral canopies. The peripheral canopy obstruction at 20 forest road sites in Roundwood State Forest, was determined using a handheld clinometer and magnetic compass. This simple field technique permitted quantification of the canopy obstruction using graphical means and resulted in a graphical skyplot of each site. The equipment, one Trimble ProXRS DGPS unit and two Trimble 4000SSi units permitted determination of the DGPS accuracy (average of 2.9 m) and precision (average of 2.1 m) with a range of peripheral canopies. DGPS performance was quantified in terms of the average absolute error in positional dilution of precision (PDOP) (DPDOP = 1.6). The relationship between DPDOP and percentage of open sky was found to be statistically significant (r = 0.706, r = 0.001). Statistical analysis also indicated a strong relationship between relat...

International Journal of Forest Engineering

... A model for estimating the productivity and cost of mechanized harvesting-debarking process i... more ... A model for estimating the productivity and cost of mechanized harvesting-debarking process in fast-growing Eucalyptus globulus plantations. For. Prod. ... Ownership costs: Interest on capital (I) in $/year, I= (in × Y), 8640, 7488, 18432, 10080, 12096, 33184, 30464. ... Operating costs: ...

International Journal of Forest Engineering

This paper describes the development of a quantitative method of classifying forest canopy that c... more This paper describes the development of a quantitative method of classifying forest canopy that can be related to degradation in Differential GPS (DGPS) performance. Using digital images taken vertically skywards at 20 sites within a forest on the east coast of Ireland, canopy cover was described using percentage sky obstruction (O p), largest hole (DT max), and the fragmentation of sky view (DT p) using pixel count and distance transform data. Statistical methods were used to produce three clusters which related to canopy cover in stands of Picea sitkensis and Picea contorta. DGPS data were then collected on 10 separate dates at the 20 sites, every two seconds for five minutes, and the two-dimensional standard deviation of the position fix was used to represent DGPS precision. The standard deviations ranged from 0.5 m to 9.7 m (compared to the manufacturer's specification of approximately 1 m in the horizontal). Precision was found to be related to the total obstruction, the size of the largest hole in the canopy, and the fragmentation of the sky view. Where there was little obstruction (<20%) or fragmentation, the DGPS performance was effectively the same as outside the forest, open canopy caused a 2-3 fold degradation in precision, and closed canopy a 5-7 fold degradation. It is suggested that the methods presented could be used to rapidly relate DGPS performance to forest canopy, and therefore may be useful in pre-planning inventory mapping and future machine operations using guidance systems.

Journal of Learning Analytics

Increasing college participation rates, and diversity in student population, is posing a challeng... more Increasing college participation rates, and diversity in student population, is posing a challenge to colleges in their attempts to facilitate learners achieve their full academic potential. Learning analytics is an evolving discipline with capability for educational data analysis that could enable better understanding of learning process, and therefore mitigate these challenges. The outcome from such data analysis will be dependent on the range, type, and quality of available data and the type of analysis performed. This study reviewed factors that could be used to predict academic performance, but which are currently not systematically measured in tertiary education. It focused on psychometric factors of ability, personality, motivation, and learning strategies. Their respective relationships with academic performance are enumerated and discussed. A case is made for their increased use in learning analytics to enhance the performance of existing student models. It is noted that la...

Journal of Learning Analytics, 2016

This paper reports on a study to predict students at risk of failing based on data available prio... more This paper reports on a study to predict students at risk of failing based on data available prior to commencement of first year of study. The study was conducted over three years, 2010 to 2012, on a student population from a range of academic disciplines, n=1,207. Data was gathered from both student enrolment data maintained by college administration, and an online, self-reporting, learner profiling tool administered during first-year student induction. Factors considered included prior academic performance, personality, motivation, self-regulation, learning approaches, age and gender. Models were trained on data from the 2010 and 2011 student cohort, and tested on data from the 2012 student cohort. A comparison of eight classification algorithms found k-NN achieved best model accuracy (72%), but results from other models were similar, including ensembles (71%), support vector machine (70%) and a decision tree (70%). Models of subgroups by age and discipline achieved higher accura...

Non-cognitive Skills and Factors in Educational Attainment, 2016

This paper reports on an application of classification and regression models to identify college ... more This paper reports on an application of classification and regression models to identify college students at risk of failing in first year of study. Data was gathered from three student cohorts in the academic years 2010 through 2012 (n=1207). Students were sampled from fourteen academic courses in five disciplines, and were diverse in their academic backgrounds and abilities. Metrics used included noncognitive psychometric indicators that can be assessed in the early stages after enrolment, specifically factors of personality, motivation, self regulation and approaches to learning. Models were trained on students from the 2010 and 2011 cohorts, and tested on students from the 2012 cohort. Is was found that classification models identifying students at risk of failing had good predictive accuracy (> 79%) on courses that had a significant proportion of high risk students (over 30%).

Encyclopedia of Forest Sciences, 2004

2009 Reno, Nevada, June 21 - June 24, 2009, 2009

ABSTRACT Miscanthus, straw and willow from short rotation coppice are promising biofuels for Irel... more ABSTRACT Miscanthus, straw and willow from short rotation coppice are promising biofuels for Ireland. However there is relatively little experience with their gasification. This work aims at optimizing and identifying the limits of their gasification in an atmospheric air blown, bubbling fluidized bed gasifier. The technical feasibility of co-gasification with wood to overcome bed agglomeration will also be investigated.

Materials & Design, 2007

The effect of tyre pressure, wheel configuration and axle load variations of a transportation tru... more The effect of tyre pressure, wheel configuration and axle load variations of a transportation truck, on structural performance of a flexible road pavement with thin asphalt surfacing layer and soft peat soil subgrade was evaluated using the finite element method. The ...

Frontiers in sustainability, Aug 3, 2022

Frontiers in Education, 2022

International Journal of Forest Engineering

Journal of Learning Analytics

Journal of Learning Analytics, 2016

Non-cognitive Skills and Factors in Educational Attainment, 2016

Encyclopedia of Forest Sciences, 2004

2009 Reno, Nevada, June 21 - June 24, 2009, 2009

Materials & Design, 2007