Science and Technology Studies Commons^™

La Investigación En La Era Digital, Ana Milena Bejarano Torres

Galeria de Libros

La aparición y difusión de nuevas tecnologías con redes públicas de internet han permitido un amplio acceso de las poblaciones a la información y al conocimiento. Sin embargo, hay que preguntarse si esto se da en condiciones de igualdad y universalidad. Desde la UNESCO es claro que debe caminarse en la senda de desarrollo humano y sostenible. Así, las sociedades del conocimiento se deben apoyar en “la libertad de expresión, el acceso universal a la información y al conocimiento, el respeto a la diversidad cultural y lingüística, y una educación de calidad para todos”.

El Tercer Simposio de Ciencia Tecnología …

Towards A More Effective Bidirectional Lstm-Based Learning Model For Human-Bacterium Protein-Protein Interactions, Huaming Chen, Jun Shen, Lei Wang, Yaochu Jin

Faculty of Engineering and Information Sciences - Papers: Part B

The identification of protein-protein interaction (PPI) is one of the most important tasks to understand the biological functions and disease mechanisms. Although numerous databases of biological interactions have been published in debt to advanced high-throughput technology, the study of inter-species protein-protein interactions, especially between human and bacterium pathogens, remains an active yet challenging topic to harness computational models tackling the complex analysis and prediction tasks. In this paper, we comprehensively revisit the prediction task of human-bacterium protein-protein interactions (HB-PPI), which is a first ever endeavour to report an empirical evaluation in learning and predicting HB-PPI based on machine learning models. …

Hybrid Translation And Language Model For Micro Learning Material Recommendation, Jiayin Lin

Faculty of Engineering and Information Sciences - Papers: Part A

As an emerging pedagogy, micro learning aims to make use of people’s fragmented spare time and provide personalized online learning service, for example, by pushing fragmented knowledge to specific learners. In the context of big data, the recommender system is the key factor for realizing the online personalization service, which significantly determines what information will be fmally accessed by the target learners. In the education discipline, due to the pedagogical requirements and the domain characteristics, ranking recommended learning materials is essential for maintaining the outcome of the massive learning scenario. However, many widely used recommendation strategies in other domains showed …

A Novel Monte Carlo-Based Neural Network Model For Electricity Load Forecasting, Binbin Yong, Zijian Xu, Jun Shen, Huaming Chen, Jianqing Wu, Fucun Li, Qingguo Zhou

Faculty of Engineering and Information Sciences - Papers: Part B

The ongoing rapid growth of electricity over the past few decades greatly promotes the necessity of accurate electricity load forecasting. However, despite a great number of studies, electricity load forecasting is still an enormous challenge for its complexity. Recently, the developments of machine learning technologies in different research areas have demonstrated its great advantages. General Vector Machine (GVM) is a new machine learning model, which has been proven very effective in time series prediction. In this article, we firstly review the basic concepts and implementation of GVM. Then we apply it in electricity load forecasting, which is based on the …

Apex2s: A Two-Layer Machine Learning Model For Discovery Of Host-Pathogen Protein-Protein Interactions On Cloud-Based Multiomics Data, Huaming Chen, Jun Shen, Lei Wang, Chi-Hung Chi

Faculty of Engineering and Information Sciences - Papers: Part B

No abstract provided.

Deep Sequence Labelling Model For Information Extraction In Micro Learning Service, Jiayin Lin, Zhexuan Zhou, Geng Sun, Jun Shen, David Pritchard, Tingru Cui, Dongming Xu, Li Li, Ghassan Beydoun

Faculty of Engineering and Information Sciences - Papers: Part B

Micro learning aims to assist users in making good use of smaller chunks of spare time and provides an effective online learning service. However, to provide such personalized online services on the Web, a number of information overload challenges persist. Effectively and precisely mining and extracting valuable information from massive and redundant information is a significant preprocessing procedure for personalizing online services. In this study, we propose a deep sequence labelling model for locating, extracting, and classifying key information for micro learning services. The proposed model is general and combines the advantages of different types of classical neural network. Early …

A New Data Driven Long-Term Solar Yield Analysis Model Of Photovoltaic Power Plants, Biplob Ray, Rakibuzzaman Shah, Md Rabiul Islam, Syed Islam

Faculty of Engineering and Information Sciences - Papers: Part B

Historical data offers a wealth of knowledge to the users. However, often restrictively mammoth that the information cannot be fully extracted, synthesized, and analyzed efficiently for an application such as the forecasting of variable generator outputs. Moreover, the accuracy of the prediction method is vital. Therefore, a trade-off between accuracy and efficacy is required for the data-driven energy forecasting method. It has been identified that the hybrid approach may outperform the individual technique in minimizing the error while challenging to synthesize. A hybrid deep learning-based method is proposed for the output prediction of the solar photovoltaic systems (i.e. proposed PV …

Model Predictive Control For A New Magnetic Linked Multilevel Inverter To Integrate Solar Photovoltaic Systems With The Power Grids, A M. Mahfuz-Ur-Rahman, Md Rabiul Islam, Kashem M. Muttaqi, Danny Sutanto

Faculty of Engineering and Information Sciences - Papers: Part B

The multilevel inverters are becoming increasingly popular for use in the grid integration of wind and photovoltaic (PV) power plants due to their higher voltage handling capability and the better output power quality. There are several types of multilevel inverters that have been proposed in the literature; among them the active neutral point clamp (ANPC) multilevel inverters have been drawing significant attention specially for solving the problems with other multilevel inverters. However, with the increase of number of levels, the ANPC requires more electronic switches and flying capacitors, by which the complexity and the cost increases. In this paper, an …

A Novel Empirical Heat Transfer Model For A Solar Thermal Storage Process Using Phase Change Materials, Yu Bie, Ming Li, Fei Chen, Grzegorz Krolczyk, Lin Yang, Zhixiong Li, Weihua Li

Faculty of Engineering and Information Sciences - Papers: Part B

Numerical and experimental analyses are often used to evaluate the solar thermal system with latent heat thermal energy storage (LHTES). However, the relationship between the numerical simulation and actual heat transfer process is still unclear. This work compares the simulated average temperature of two different phase change materials (PCMs) with experimental result at different operation conditions for the purpose of developing a temperature correction model. A novel empirical heat transfer model is then established to improve the simulation accuracy of PCM-based solar thermal systems. The contributions of this work include that (1) the system performance could be evaluated by the …

Leveraging Smote In A Two-Layer Model For Prediction Of Protein-Protein Interactions, Huaming Chen, Lei Wang, Chi-Hung Chi, Jun Shen

Faculty of Engineering and Information Sciences - Papers: Part B

The research of the mechanisms of infectious diseases between host and pathogens remains a hot topic. It takes stock of the interactions data between host and pathogens, including proteins and genomes, to facilitate the discoveries and prediction of underlying mechanisms. However, the incomplete protein-protein interactions data impediment the advances in this exploration and solicit the wet-lab experiments to examine and verify the latent interactions. Although there have been numerous studies trying to leverage the computational models, especially machine learning models, the performances of these models were not good enough to produce high-fidelity candidates of interactions data due to the nature …

A Theoretical Model For Total Suction Effects By Tree Roots, Udeshini Pathirage, Buddhima Indraratna, Muditha Pallewattha, Ana Heitor

Faculty of Engineering and Information Sciences - Papers: Part B

Strengthening soft and weak soil by way of root reinforcement is a well-known strategy that is adopted worldwide. In Australia, native gum trees remain evergreen throughout the year and have been utilised to stabilise transportation corridors by way of reinforcement provided by the roots and the suction generated within the root domain as a function of evapotranspiration through the canopy. A mature gum tree can induce a missive total suction pressure exceeding 30MPa through its root water and solute uptake in terms of matric plus osmotic suction. This cumulative effect of matric and osmotic suctions contributes to the overall shear …

Formulation Of A Model Predictive Control Algorithm To Enhance The Performance Of A Latent Heat Solar Thermal System, Gianluca Serale, Massimo Fiorentini, Alfonso Capozzoli, Paul Cooper, Marco Perino

Faculty of Engineering and Information Sciences - Papers: Part B

Model predictive control has proved to be a promising control strategy for improving the operational performance of multi-source thermal energy generation systems with the aim of maximising the exploitation of on-site renewable resources. This paper presents the formulation and implementation of a model predictive control strategy for the management of a latent heat thermal energy storage unit coupled with a solar thermal collector and a backup electric heater. The system uses an innovative Phase Change Material slurry for both the heat transfer fluid and storage media. The formulation of a model predictive controller of such a closed-loop solar system is …

Developing A Theoretical Model And Questionnaire Survey Instrument To Measure The Success Of Electronic Health Records In Residential Aged Care, Ping Yu, Siyu Qian

Faculty of Engineering and Information Sciences - Papers: Part B

Electronic health records (EHR) are introduced into healthcare organizations worldwide to improve patient safety, healthcare quality and efficiency. A rigorous evaluation of this technology is important to reduce potential negative effects on patient and staff, to provide decision makers with accurate information for system improvement and to ensure return on investment. Therefore, this study develops a theoretical model and questionnaire survey instrument to assess the success of organizational EHR in routine use from the viewpoint of nursing staff in residential aged care homes. The proposed research model incorporates six variables in the reformulated DeLone and McLean information systems success model: …

Model Predictive Control (Mpc) For Enhancing Building And Hvac System Energy Efficiency: Problem Formulation, Applications And Opportunities, Gianluca Serale, Massimo Fiorentini, Alfonso Capozzoli, Daniele Bernardini, Alberto Bemporad

Faculty of Engineering and Information Sciences - Papers: Part B

In the last few years, the application of Model Predictive Control (MPC) for energy management in buildings has received significant attention from the research community. MPC is becoming more and more viable because of the increase in computational power of building automation systems and the availability of a significant amount of monitored building data. MPC has found successful implementation in building thermal regulation, fully exploiting the potential of building thermal mass. Moreover, MPC has been positively applied to active energy storage systems, as well as to the optimal management of on-site renewable energy sources. MPC also opens up several opportunities …

A System Model For Personalized Medication Management (Mymediman)-The Consumers' Point Of View, Elena Vlahu-Gjorgievska, Khin Than Win, Willy Susilo

Faculty of Engineering and Information Sciences - Papers: Part B

In this paper, we propose a design for a personalized medication management system model MyMediMan that provides medication information for different stakeholders. The focus of the paper is on the system's features and personalized information provided for the consumers as primary users of the proposed solution. The presented design introduces the consumers to different aspects of the medications they take and their overall health condition. The personalized information should increase the consumers' awareness about the positive benefits of taking the medications as well as the consequences that particular medication can have on their health condition. By obtaining this information, the …

Optimal Control Based Stiffness Identification Of An Ankle-Foot Orthosis Using A Predictive Walking Model, Manish Sreenivasa, Matthew Millard, Martin Felis, Katja Mombaur, Sebastian I. Wolf

Faculty of Engineering and Information Sciences - Papers: Part B

Predicting the movements, ground reaction forces and neuromuscular activity during gait can be a valuable asset to the clinical rehabilitation community, both to understand pathology, as well as to plan effective intervention. In this work we use an optimal control method to generate predictive simulations of pathological gait in the sagittal plane. We construct a patient-specific model corresponding to a 7-year old child with gait abnormalities and identify the optimal spring characteristics of an ankle-foot orthosis that minimizes muscle effort. Our simulations include the computation of foot-ground reaction forces, as well as the neuromuscular dynamics using computationally efficient muscle torque …

Development Of A Dynamic Model For A Hybrid Photovoltaic Thermal Collector - Solar Air Heater With Fins, Wenke Fan, Georgios Kokogiannakis, Zhenjun Ma, Paul Cooper

Faculty of Engineering and Information Sciences - Papers: Part A

A dynamic model for a hybrid Photovoltaic Thermal Collector-Solar Air Heater (PVT-SAH) with longitudinal fins was developed to enable assessment of the potential of the system to provide high temperature outlet air (60-90 °C) under dynamic boundary conditions. The model description includes the method for discretising the system into a number of control volumes, the energy balance equations for each control volume and the implementation of the numerical solution. Model validation has been successfully undertaken by using empirical verification of model predictions with an experimental facility and by comparing the model outputs with the reference data from the literature. The …

Statistical Shape Model Generation Using Diffeomorphic Surface Registration, Jiaqi Wu, Guangxu Li, Huimin Lu, Hyoung Kim, Philip O. Ogunbona

Faculty of Engineering and Information Sciences - Papers: Part B

Statistical shape modelling is an efficient and robust method for medical image segmentation in computer-aided diagnosis. The key step in building a statistical shape model is to find corresponding landmarks in each instance of a training set. In this paper, a novel landmark correspondence estimation method that uses edge collapse surface simplification and the sphere registration is proposed. All the landmarks are selected and transformed by spherical conformal mapping from the instances of the training set and the associated correspondence are automatically found on the spheres. We applied our method on 21 cases of 3-D right lung shapes. The results …

Hybrid Model Predictive Control Of A Residential Hvac System With On-Site Thermal Energy Generation And Storage, Massimo Fiorentini, Josh Wall, Zhenjun Ma, Julio H. Braslavsky, Paul Cooper

Faculty of Engineering and Information Sciences - Papers: Part A

This paper describes the development, implementation and experimental investigation of a Hybrid Model Predictive Control (HMPC) strategy to control solar-assisted heating, ventilation and air-conditioning (HVAC) systems with on-site thermal energy generation and storage. A comprehensive approach to the thermal energy management of a residential building is presented to optimise the scheduling of the available thermal energy resources to meet a comfort objective. The system has a hybrid nature with both continuous variables and discrete, logic-driven operating modes. The proposed control strategy is organized in two hierarchical levels. At the high-level, an HMPC controller with a 24-h prediction horizon and a …

Model-Based Optimization Of Ground Source Heat Pump Systems, Zhenjun Ma, Lei Xia

Faculty of Engineering and Information Sciences - Papers: Part A

This paper presents the development of an optimization strategy for ground source heat pump (GSHP) systems equipped with variable speed pumps in the ground loop system. The optimization problem is formulated using a model-based approach, in which the component models are used to estimate the system performance under various trial settings and an exhaustive search method is used to identify the optimal settings under the search ranges defined. The variable optimized is the outlet water temperature from the ground heat exchangers, which can be used as a set-point to control the operation of the variable speed pumps in the ground …

Aligning Business Strategy With It Strategy From Business Model To Enterprise In Saudi Arabia Public Sector, Abdulaziz Alghazi, Mengxiang Li, Jun Shen, Samuel Fosso Wamba

Faculty of Engineering and Information Sciences - Papers: Part B

Over the last decades researchers seem to have big concerns on the complexity of business-IT alignment with the government organizational strategy goals. The Saudi Arabian (SA) government is one of the world’s governments that has launched the national government strategy for 2030 to all public sectors to enhance performance. This research proposal is aimed at investigating the adoption performance of alignment strategy incorporated by the SA government in order to benefit of IT infrastructure and achieve high performance, quality of service (QoS) and return of investment (ROI). This study will use mixed method design combines both qualitative and quantitative methods …

The Effect Of Imputing Missing Clinical Attribute Values On Training Lung Cancer Survival Prediction Model Performance, Mohamed S. Barakat, Matthew Field, Aditya K. Ghose, David Stirling, Lois C. Holloway, Shalini K. Vinod, Andre Dekker, David Thwaites

Faculty of Engineering and Information Sciences - Papers: Part B

According to the estimations of the World Health Organization and the International Agency for Research in Cancer, lung cancer is the most common cause of death from cancer worldwide. The last few years have witnessed a rise in the attention given to the use of clinical decision support systems in medicine generally and in cancer in particular. These can predict patients' likelihood of survival based on analysis of and learning from previously treated patients. The datasets that are mined for developing clinical decision support functionality are often incomplete, which adversely impacts the quality of the models developed and the decision …

Motion Optimization And Parameter Identification For A Human And Lower Back Exoskeleton Model, Paul Manns, Manish Sreenivasa, Matthew Millard, Katja Mombaur

Faculty of Engineering and Information Sciences - Papers: Part B

Designing an exoskeleton to reduce the risk of low-back injury during lifting is challenging. Computational models of the human-robot system coupled with predictive movement simulations can help to simplify this design process. Here, we present a study that models the interaction between a human model actuated by muscles and a lower back exoskeleton. We provide a computational framework for identifying the spring parameters of the exoskeleton using an optimal control approach and forward-dynamics simulations. This is applied to generate dynamically consistent bending and lifting movements in the sagittal plane. Our computations are able to predict motions and forces of the …

Patients' Acceptance Of Smartphone Health Technology For Chronic Disease Management: A Theoretical Model And Empirical Test, Kaili Dou, Ping Yu, Ning Deng, Fang Liu, Yingping Guan, Zhenye Li, Yumeng Ji, Ningkai Du, Xudong Lu, Huilong Duan

Faculty of Engineering and Information Sciences - Papers: Part B

No abstract provided.

Bayesian Learning And Predictability In A Stochastic Nonlinear Dynamical Model, John Parslow, Noel Cressie, Edward P. Campbell, Emlyn Jones, Lawrence Murray

Professor Noel Cressie

Bayesian inference methods are applied within a Bayesian hierarchical modelling framework to the problems of joint state and parameter estimation, and of state forecasting. We explore and demonstrate the ideas in the context of a simple nonlinear marine biogeochemical model. A novel approach is proposed to the formulation of the stochastic process model, in which ecophysiological properties of plankton communities are represented by autoregressive stochastic processes. This approach captures the effects of changes in plankton communities over time, and it allows the incorporation of literature metadata on individual species into prior distributions for process model parameters. The approach is applied …

Analytic Performance Model For State-Based Mac Layer Cooperative Retransmission Protocols, Brett Hagelstein, Mehran Abolhasan, Daniel R. Franklin, Farzad Safaei, Wei Ni

Faculty of Engineering and Information Sciences - Papers: Part A

Cooperative retransmission can significantly improve link reliability over lossy and time-varying wireless links. However, comparing retransmission protocols is challenging, and generally requires simplistic assumptions specific to each protocol. In this paper, we develop a general model to evaluate cooperative retransmission protocols with distributed, slot-based contention algorithms. Specifically, we propose to calculate the relay time-out probabilities at a MAC time-slot scale, formulate retransmission outcomes as functions of the time-out probabilities, and derive the probability of a retransmission process for every data frame. We also propose a Markov extension of our model to characterise the dependency between retransmissions of multiple frames. This …

Microstructure And Micro-Texture Evolution During The Dynamic Recrystallisation Of A Ni-30fe-Nb-C Model Alloy, Parvez Mannan, Ahmed A. Saleh, Azdiar A. Gazder, Gilberto Casillas, Elena V. Pereloma

Faculty of Engineering and Information Sciences - Papers: Part A

The evolution of microstructure and micro-texture during discontinuous dynamic recrystallisation of an austenitic Ni-30Fe-Nb-C model alloy subjected to interrupted plane strain compression at strains (ε) of 0.23, 0.35, 0.68, 0.85 and 1.2 was investigated using electron backscattering diffraction and transmission electron microscopy. Throughout the strain range, the majority of dynamic recrystallisation events comprised nucleation in necklace-like arrangements located at and along grain boundaries via bulging. At ε ≥ 0.68, discrete nucleation events were also observed within grain interiors. Grain growth during dynamic recrystallisation is characteristic of strain induced boundary migration. The initial texture comprised Cube-RD ({013}〈100〉), Cube-ND ({001}〈310〉) and Cube …

A Data-Driven Predictive Model For Residential Mobility In Australia - A Generalised Linear Mixed Model For Repeated Measured Binary Data, Mohammad-Reza Namazi-Rad, Payam Mokhtarian, Nagesh Shukla, Albert Munoz

Faculty of Engineering and Information Sciences - Papers: Part A

Household relocation modelling is an integral part of the Government planning process as residential movements influence the demand for community facilities and services. This study will address the problem of modelling residential relocation choice by estimating a logit-link class model. The proposed model estimates the probability of an event which triggers household relocation. The attributes considered in this study are: requirement for bedrooms, employment status, income status, household characteristics, and tenure (i.e. duration living at the current location). Accurate prediction of household relocations for population units should rely on real world observations. In this study, a longitudinal survey data gathered …

Design-Oriented Stress–Strain Model For Concrete Under Combined Frp-Steel Confinement, G Lin, Tao Yu, Jin Guang Teng

Faculty of Engineering and Information Sciences - Papers: Part A

Extensive research has been conducted on fiber-reinforced polymer (FRP)-confined plain and RC columns, leading to a large number of stress–strain models. Most of these models have been developed for FRP-confined plain concrete and are thus applicable only to concrete in FRP-confined RC columns with a negligible amount of transverse steel reinforcement. The few models that have been developed for concrete under the combined confinement of FRP and transverse steel reinforcement are either inaccurate or too complex for direct use in design. This paper presents an accurate design-oriented stress–strain model for concrete under combined FRP-steel confinement in FRP-confined circular RC columns. …

A New Micro Scale Fe Model Of Crystalline Materials In Micro Forming Process, Liang Luo, Haibo Xie, Dongbin Wei, Xiaogang Wang, Cunlong Zhou, Zhengyi Jiang

Faculty of Engineering and Information Sciences - Papers: Part A

Micro forming of metals has drawn global attention due to the increasing requirement of micro metal products. However, the size effects become significant in micro forming processes and affect the application of finite element (FE) simulation of micro forming processes. Dividing samples into small areas according to their microstructures and assigning individual properties to each small area are a possible access to micro forming simulation considering material size effects. In this study, a new model that includes both grains and their boundaries was developed based on the observed microstructures of samples. The divided subareas in the model have exact shapes …