Exploring the nexus between tourism and output in Cook Islands: An ARDL bounds approach

Tourism plays an important role in the development of Cook Islands. In this paper we examine the nexus between tourism and growth using quarterly data over the period 2009Q1–2014Q2 using the recently upgraded ARDL bounds test to cointegration tool, Microfit 5.01, which provides sample adjusted bounds and hence is more reliable for small sample size studies. We perform the cointegration using the ARDL bounds test and examine the direction of causality. Using visitor arrival and output in per capita terms as respective proxy for tourism development and growth, we examine the long-run association and report the elasticity coefficient of tourism and causality nexus, accordingly. Using unit root break tests, we note that 2011Q1 and 2011Q2 are two structural break periods in the output series. However, we note that this period is not statistically significant in the ARDL model and hence excluded from the estimation. Subsequently, the regression results show the two series are cointegrated. The long-run elasticity coefficient of tourism is estimated to be 0.83 and the short-run is 0.73. A bidirectional causality between tourism and income is noted for Cook Islands which indicates that tourism development and income mutually reinforce each other. In light of this, socio-economic policies need to focus on broad-based, inclusive and income-generating tourism development projects which are expected to have feedback effect.

Structure matters: Adoption of structured classification Approach in the context of cognitive presence classification

Within online learning communities, receiving timely and meaningful insights into the quality of learning activities is an important part of an effective educational experience. Commonly adopted methods – such as the Community of Inquiry framework – rely on manual coding of online discussion transcripts, which is a costly and time consuming process. There are several efforts underway to enable the automated classification of online discussion messages using supervised machine learning, which would enable the real-time analysis of interactions occurring within online learning communities. This paper investigates the importance of incorporating features that utilise the structure of on-line discussions for the classification of "cognitive presence" – the central dimension of the Community of Inquiry framework focusing on the quality of students' critical thinking within online learning communities. We implemented a Conditional Random Field classification solution, which incorporates structural features that may be useful in increasing classification performance over other implementations. Our approach leads to an improvement in classification accuracy of 5.8% over current existing techniques when tested on the same dataset, with a precision and recall of 0.630 and 0.504 respectively.

Ink-jet printing of graphene for flexible electronics: An environmentally-friendly approach

Mechanical flexibility is considered an asset in consumer electronics and next-generation electronic systems. Printed and flexible electronic devices could be embedded into clothing or other surfaces at home or office or in many products such as low-cost sensors integrated in transparent and flexible surfaces. In this context inks based on graphene and related two-dimensional materials (2DMs) are gaining increasing attention owing to their exceptional (opto)electronic, electrochemical and mechanical properties. The current limitation relies on the use of solvents, providing stable dispersions of graphene and 2DMs and fitting the proper fluidic requirements for printing, which are in general not environmentally benign, and with high boiling point. Non-toxic and low boiling point solvents do not possess the required rheological properties (i.e., surface tension, viscosity and density) for the solution processing of graphene and 2DMs. Such solvents (e.g., water, alcohols) require the addition of stabilizing agents such as polymers or surfactants for the dispersion of graphene and 2DMs, which however unavoidably corrupt their properties, thus preventing their use for the target application. Here, we demonstrate a viable strategy to tune the fluidic properties of water/ethanol mixtures (low-boiling point solvents) to first effectively exfoliate graphite and then disperse graphene flakes to formulate graphene-based inks. We demonstrate that such inks can be used to print conductive stripes (sheet resistance of ~13 kΩ/□) on flexible substrates (polyethylene terephthalate), moving a step forward towards the realization of graphene-based printed electronic devices.

“It’s in the syllabus”: Identifying information literacy and data information literacy opportunities using a grounded theory approach

Developing innovative library services requires a real world understanding of faculty members' desired curricular goals. This study aimed to develop a comprehensive and deeper understanding of Purdue's nutrition science and political science faculties' expectations for student learning related to information and data information literacies. Course syllabi were examined using grounded theory techniques that allowed us to identify how faculty were addressing information and data information literacies in their courses, but it also enabled us to understand the interconnectedness of these literacies to other departmental intentions for student learning, such as developing a professional identity or learning to conduct original research. The holistic understanding developed through this research provides the necessary information for designing and suggesting information literacy and data information literacy services to departmental faculty in ways supportive of curricular learning outcomes.

Studying change in popular culture: A "middle-range" approach

"This chapter reviews the capacity of the discipline field to account for the velocity and quality of digitally-driven transformations, while making a case for a "middle range" approach that steers between unbridled optimism ("all-change") and determined scepticism ("Continuity") about the potential of such change. The chapter focuses on online screen distribution as a case study, considering the evidence for, and significance of, change in industry structure and the main payers, how content is produced and by whom, the nature of content, and the degree to which online screen distribution has reached thresholds of mainstream popularity."

A biomechanical approach to iris normalization

The richness of the iris texture and its variability across individuals make it a useful biometric trait for personal authentication. One of the key stages in classical iris recognition is the normalization process, where the annular iris region is mapped to a dimensionless pseudo-polar coordinate system. This process results in a rectangular structure that can be used to compensate for differences in scale and variations in pupil size. Most iris recognition methods in the literature adopt linear sampling in the radial and angular directions when performing iris normalization. In this paper, a biomechanical model of the iris is used to define a novel nonlinear normalization scheme that improves iris recognition accuracy under different degrees of pupil dilation. The proposed biomechanical model is used to predict the radial displacement of any point in the iris at a given dilation level, and this information is incorporated in the normalization process. Experimental results on the WVU pupil light reflex database (WVU-PLR) indicate the efficacy of the proposed technique, especially when matching iris images with large differences in pupil size.

Automating marine mammal detection in aerial images captured during wildlife surveys: A deep learning approach

Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.

Adolescent sexual behavioral intentions measurement: A gender approach in the Colombian Caribbean region [Medición de la Intención en la Actividad Sexual en Adolescentes: una Aproximación de Acuerdo al Género del Caribe Colombiano]

The study of 1777 male and female adolescent students of 11-19 years in the Colombian Caribbean had two objectives: development and validation of two reproductive health intention scales and analyze gender differences. The pilot of the scale consisted of 8 items and was reduced to 6, to check the reliability and validity using factor analysis and principal components with VARIMAX rotation yielded two factors: Intention and Intention Risk Protection, explained between 69.4% and 70% respectively. In the male Protection Intent (M = 3.87 and SD = 1.29) and risk (M = 2.56 and SD = 1.18) obtained an alpha between 0.74 and 0.86, and in Protection of Intent to female (M = 3.49 and SD = 1.35) and risk (M = 1.50 and SD = 0.89) ranged between 0.78 and 086. In conclusion, the reliability and structural stability are adequate and there are gender differences in the scales.

A queuing approach for inventory planning with batch ordering in multi-echelon supply chains

This paper presents stylized models for conducting performance analysis of the manufacturing supply chain network (SCN) in a stochastic setting for batch ordering. We use queueing models to capture the behavior of SCN. The analysis is clubbed with an inventory optimization model, which can be used for designing inventory policies . In the first case, we model one manufacturer with one warehouse, which supplies to various retailers. We determine the optimal inventory level at the warehouse that minimizes total expected cost of carrying inventory, back order cost associated with serving orders in the backlog queue, and ordering cost. In the second model we impose service level constraint in terms of fill rate (probability an order is filled from stock at warehouse), assuming that customers do not balk from the system. We present several numerical examples to illustrate the model and to illustrate its various features. In the third case, we extend the model to a three-echelon inventory model which explicitly considers the logistics process.

Design and a deep customer insight approach to innovation

This paper proposes and explores the Deep Customer Insight Innovation Framework in order to develop an understanding as to how design can be integrated within existing innovation processes. The Deep Customer Insight Innovation Framework synthesises the work of Beckman and Barry (2007) as a theoretical foundation, with the framework explored within a case study of Australian Airport Corporation seeking to drive airport innovations in operations and retail performance. The integration of a deep customer insight approach develops customer-centric and highly integrated solutions as a function of concentrated problem exploration and design-led idea generation. Businesses’ facing complex innovation challenges or seeking to making sense of future opportunities will be able to integrate design into existing innovation processes, anchoring the new approach between existing market research and business development activities. This paper contributes a framework and novel understanding as to how design methods are integrated into existing innovation processes for operationalization within industry.

Spin populations in one-dimensional alternant spin systems: A theoretical approach

Spin-density maps, deduced from polarized neutron diffraction experiments, for both the pair and chain compounds of the system Mn2+Cu2+ have been reported recently. These results have motivated us to investigate theoretically the spin populations in such alternant mixed-spin systems. In this paper, we report our studies on the one-dimensional ferrimagnetic systems (S-A,S-B)(N) where hi is the number of AB pairs. We have considered all cases in which the spin Sri takes on allowed values in the range I to 7/2 while the spin S-B is held fixed at 1/2. The theoretical studies have been carried out on the isotropic Heisenberg model, using the density matrix renormalization group method. The effect of the magnitude of the larger spin SA On the quantum fluctuations in both A and B sublattices has been studied as a function of the system size N. We have investigated systems with both periodic and open boundary conditions, the latter with a view to understanding end-of-chain effects. The spin populations have been followed as a function of temperature as well as an applied magnetic field. High-magnetic fields are found to lead to interesting re-entrant behavior. The ratio of spin populations P-A-P-B is not sensitive to temperature at low temperatures.

Affective learning design: A principled approach to emotion in learning

This PhD project set out to explore the role of emotion during learning in sport, focusing on how actions, emotions and cognitions interact under the influence of constraints. Key outcomes include the development of the theoretical concept - Affective Learning Design, and a new tool for assessing the intensity of emotions during learning - the Sport Learning and Emotions Questionnaire. The findings presented in this thesis provide both theoretical and practical implications discussing why emotion should be considered in the design of learning environments in sport.

Normalizing Foucault? A rhizomatic approach to plateaus in anglophone educational research

This paper offers a rhizomatic reading of Foucault scholarship in anglophone educational research. It delineates unique parameters of an educational field, the conditions of receptivity for Foucault's work, and identifies three temporary plateau-formations that have erupted in educational research. Indebted to (non-formulaic) principles of connectivity and heterogeneity, multiplicity, and asignifying ruptures the analysis brings to notice the recombinatorial attributes of the discipline of education through attention to what is encamped and what seeps in debates over his work.

Synthesis of novel poly[(2,5-dimethoxy-p-phenylene)vinylene] precursors having two eliminatable groups: An approach for the control of conjugation length

Poly[(2,5-dimethoxy-p-phenylene)vinylene] (DMPPV) of varying conjugation length was synthesized by selective elimination of organic soluble precursor polymers that contained two eliminatable groups, namely, methoxy and acetate groups. These precursor copolymers were in turn synthesized by competitive nucleophilic substitution of the sulfonium polyelectrolyte precursor (generated by the standard Wessling route) using methanol and sodium acetate in acetic acid. The composition of the precursor copolymer, in terms of the relative amounts of methoxy and acetate groups, was controlled by varying the composition of the reaction mixture during nucleophilic substitution. Thermal elimination of these precursor copolymers at 250 degrees C, yielded partially conjugated polymers, whose color varied from light yellow to deep red. FT-IR studies confirmed that, while essentially all the acetate groups were eliminated, the methoxy groups were intact and caused the interruption in conjugation. Preliminary photoluminescence studies of the partially eliminated DMPPV samples showed a gradual shift in the emission maximum from 498 to 598 nm with increasing conjugation lengths, suggesting that the color of LED devices fabricated from such polymers can, in principle, be fine-tuned.

Reservoir Operation for Hydropower Optimization: A Chance-Constrained Approach

This paper presents a chance-constrained linear programming formulation for reservoir operation of a multipurpose reservoir. The release policy is defined by a chance constraint that the probability of irrigation release in any period equalling or exceeding the irrigation demand is at least equal to a specified value P (called reliability level). The model determines the maximum annual hydropower produced while meeting the irrigation demand at a specified reliability level. The model considers variation in reservoir water level elevation and also the operating range within which the turbine operates. A linear approximation for nonlinear power production function is assumed and the solution obtained within a specified tolerance limit. The inflow into the reservoir is considered random. The chance constraint is converted into its deterministic equivalent using a linear decision rule and inflow probability distribution. The model application is demonstrated through a case study.