MPC controlled multirotor with suspended slung load: System architecture and visual load detection

There is an increased interest in the use of Unmanned Aerial Vehicles for load transportation from environmental remote sensing to construction and parcel delivery. One of the main challenges is accurate control of the load position and trajectory. This paper presents an assessment of real flight trials for the control of an autonomous multi-rotor with a suspended slung load using only visual feedback to determine the load position. This method uses an onboard camera to take advantage of a common visual marker detection algorithm to robustly detect the load location. The load position is calculated using an onboard processor, and transmitted over a wireless network to a ground station integrating MATLAB/SIMULINK and Robotic Operating System (ROS) and a Model Predictive Controller (MPC) to control both the load and the UAV. To evaluate the system performance, the position of the load determined by the visual detection system in real flight is compared with data received by a motion tracking system. The multi-rotor position tracking performance is also analyzed by conducting flight trials using perfect load position data and data obtained only from the visual system. Results show very accurate estimation of the load position (~5% Offset) using only the visual system and demonstrate that the need for an external motion tracking system is not needed for this task.

Monitoring healing progression and characterizing the mechanical environment in preclinical models for bone tissue engineering

The treatment of large segmental bone defects remains a significant clinical challenge. Due to limitations surrounding the use of bone grafts, tissue-engineered constructs for the repair of large bone defects could offer an alternative. Before translation of any newly developed tissue engineering (TE) approach to the clinic, efficacy of the treatment must be shown in a validated preclinical large animal model. Currently, biomechanical testing, histology, and microcomputed tomography are performed to assess the quality and quantity of the regenerated bone. However, in vivo monitoring of the progression of healing is seldom performed, which could reveal important information regarding time to restoration of mechanical function and acceleration of regeneration. Furthermore, since the mechanical environment is known to influence bone regeneration, and limb loading of the animals can poorly be controlled, characterizing activity and load history could provide the ability to explain variability in the acquired data sets and potentially outliers based on abnormal loading. Many approaches have been devised to monitor the progression of healing and characterize the mechanical environment in fracture healing studies. In this article, we review previous methods and share results of recent work of our group toward developing and implementing a comprehensive biomechanical monitoring system to study bone regeneration in preclinical TE studies.

An economical, adaptable and user-friendly drip-perfusion bioreactor system designed for in vitro three dimensional cell culturing

This research project investigated a bioreactor system capable of high density cell growth intended for use in regenerative medicine and protein production. The bioreactor was based on a drip-perfusion concept and constructed with minimal costs, readily available components, and straightforward processes for usage. This study involved the design, construction, and testing of the bioreactor where the results showed promising three dimensional cell growth within a polymer structure. The accessibility of this equipment and the capability of high density, three dimensional cell growth would be suitable for future research in pharmaceutical drug manufacturing, and human organ and tissue regeneration.

Exploiting the beta distribution-based reputation model in recommender system

Reputation systems are employed to measure the quality of items on the Web. Incorporating accurate reputation scores in recommender systems is useful to provide more accurate recommendations as recommenders are agnostic to reputation. The ratings aggregation process is a vital component of a reputation system. Reputation models available do not consider statistical data in the rating aggregation process. This limitation can reduce the accuracy of generated reputation scores. In this paper, we propose a new reputation model that considers previously ignored statistical data. We compare our proposed model against state-of the-art models using top-N recommender system experiment.

Organisational culture and quality management system implementation in Indonesian construction companies

The study of the organisational culture in the construction industry is still in the stage of debate (Oney-Yazıcı et al., 2007). Despite the complexities involved in measuring the culture of the construction industry (Tijhuis and Fellows, 2012), this culture is regarded as being worthy of research, especially in relation to the organisational culture needed to support quality management systems (Koh and Low, 2008; Watson and Howarth, 2011) and to improve organisational effectiveness, and therefore, organisational performance (Coffey, 2010; Cheung et al., 2011). A number of recent studies have examined the construction companies’ organisational culture within the context of the use of Cameron and Quinn’s Competing Value Framework (CVF), as well as the use of their Organizational Culture Assessment Instrument (OCAI) as the conceptual paradigm for the analyses (Thomas et al., 2002; Nummelin, 2006; Oney- Yazıcı et al., 2007; Koh and Low, 2008). However, there has been little research based on the use of Cameron and Quinn’s CVF-OCAI tool for identifying types of construction companies’ organisational culture and their influences on the implementation of QMS-ISO 9001. Research output and information is also very limited relating to the strength of the companies’ organisational culture driving an effective QMS-ISO 9001 implementation, affecting the companies’ effectiveness. To rectify these research gaps, the research has been aimed to study organisational culture types (based on CVF) and their influences on the implementation of QMS-ISO 9001:2008 principles and elements, which eventually lead to improved companies’ quality performance. In order to fully examine the status of the QMS being implemented, the research has studied the relationships of the barriers of QMS implementation with the implementation of QMS-ISO 9001:2008 principles and elements and with the business performance of the companies, as well as the examination of the relationships of the implementation of QMS-ISO 9001:2008 principles and elements with the companies’ business performance. The research output has been the development of fundamental and original studies on the study topics, to provide the knowledge for improvements in Indonesian construction companies’ quality performance and quality outcomes.

Electronic Building Passport - Final Report: Project 2 National Energy Efficient Building Project Phase 2

The National Energy Efficient Building Project (NEEBP) Phase One report, published in December 2014, investigated “process issues and systemic failures” in the administration of the energy performance requirements in the National Construction Code. It found that most stakeholders believed that under-compliance with these requirements is widespread across Australia, with similar issues being reported in all states and territories. The report found that many different factors were contributing to this outcome and, as a result, many recommendations were offered that together would be expected to remedy the systemic issues reported. To follow up on this Phase 1 report, three additional projects were commissioned as part of Phase 2 of the overall NEEBP project. This Report deals with the development and piloting of an Electronic Building Passport (EBP) tool – a project undertaken jointly by pitt&sherry and a team at the Queensland University of Technology (QUT) led by Dr Wendy Miller. The other Phase 2 projects cover audits of Class 1 buildings and issues relating to building alterations and additions. The passport concept aims to provide all stakeholders with (controlled) access to the key documentation and information that they need to verify the energy performance of buildings. This trial project deals with residential buildings but in principle could apply to any building type. Nine councils were recruited to help develop and test a pilot electronic building passport tool. The participation of these councils – across all states – enabled an assessment of the extent to which these councils are currently utilising documentation; to track the compliance of residential buildings with the energy performance requirements in the National Construction Code (NCC). Overall we found that none of the participating councils are currently compiling all of the energy performance-related documentation that would demonstrate code compliance. The key reasons for this include: a major lack of clarity on precisely what documentation should be collected; cost and budget pressures; low public/stakeholder demand for the documentation; and a pragmatic judgement that non-compliance with any regulated documentation requirements represents a relatively low risk for them. Some councils reported producing documentation, such as certificates of final completion, only on demand, for example. Only three of the nine council participants reported regularly conducting compliance assessments or audits utilising this documentation and/or inspections. Overall we formed the view that documentation and information tracking processes operating within the building standards and compliance system are not working to assure compliance with the Code’s energy performance requirements. In other words the Code, and its implementation under state and territory regulatory processes, is falling short as a ‘quality assurance’ system for consumers. As a result it is likely that the new housing stock is under-performing relative to policy expectations, consuming unnecessary amounts of energy, imposing unnecessarily high energy bills on occupants, and generating unnecessary greenhouse gas emissions. At the same time, Councils noted that the demand for documentation relating to building energy performance was low. All the participant councils in the EBP pilot agreed that documentation and information processes need to work more effectively if the potential regulatory and market drivers towards energy efficient homes are to be harnessed. These findings are fully consistent with the Phase 1 NEEBP report. It was also agreed that an EBP system could potentially play an important role in improving documentation and information processes. However, only one of the participant councils indicated that they might adopt such a system on a voluntary basis. The majority felt that such a system would only be taken up if it were: - A nationally agreed system, imposed as a mandatory requirement under state or national regulation; - Capable of being used by multiple parties including councils, private certifiers, building regulators, builders and energy assessors in particular; and - Fully integrated into their existing document management systems, or at least seamlessly compatible rather than a separate, unlinked tool. Further, we note that the value of an EBP in capturing statistical information relating to the energy performance of buildings would be much greater if an EBP were adopted on a nationally consistent basis. Councils were clear that a key impediment to the take up of an EBP system is that they are facing very considerable budget and staffing challenges. They report that they are often unable to meet all community demands from the resources available to them. Therefore they are unlikely to provide resources to support the roll out of an EBP system on a voluntary basis. Overall, we conclude from this pilot that the public good would be well served if the Australian, state and territory governments continued to develop and implement an Electronic Building Passport system in a cost-efficient and effective manner. This development should occur with detailed input from building regulators, the Australian Building Codes Board (ABCB), councils and private certifiers in the first instance. This report provides a suite of recommendations (Section 7.2) designed to advance the development and guide the implementation of a national EBP system.

Assessing the integrated sustainability of a public rental housing project from the perspective of complex eco-system

Public rental housing (PRH) projects are the mainstream of China's new affordable housing policies, and their integrated sustainability has a far-reaching effect on medium-low income families' well-being and social stability. However, there are few quantitative researches on the integrated sustainability of PRH projects. Our study tries to fill this gap through proposing an assessment model of the integrated sustainability for PRH projects. First, this paper defines what the sustainability of a PRH project is. Second, after constructing the sustainable system of a PRH project from the perspective of complex eco-system, the paper explores the internal operation mechanism and the coupling mechanism among the ecological, economic and social subsystems. Third, it identifies fourteen indices to represent the sustainability system of a PRH project, including six indices of ecological subsystem, five of economic subsystem and three of social subsystem. Fourth, it qualifies the weights of three subsystems and their internal representative indices. In addition, an assessment model is established through expert surveys and analytic network process (ANP). Finally, the paper carries out an empirical research on a PRH project in Nanjing city of China, followed by suggestions to enhance the integrated sustainability. The sustainability system and its evaluation model proposed in this paper are concise and easy to understand and can provide a theoretical foundation and a scientific basis for the evaluation and optimization of PRH projects.

Statistical analysis of spectral data: A methodology for designing an intelligent monitoring system for the diabetic foot

Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

Open source computer-vision based guidance system for UAVs on-board decision making

The use of UAVs for remote sensing tasks; e.g. agriculture, search and rescue is increasing. The ability for UAVs to autonomously find a target and perform on-board decision making, such as descending to a new altitude or landing next to a target is a desired capability. Computer-vision functionality allows the Unmanned Aerial Vehicle (UAV) to follow a designated flight plan, detect an object of interest, and change its planned path. In this paper we describe a low cost and an open source system where all image processing is achieved on-board the UAV using a Raspberry Pi 2 microprocessor interfaced with a camera. The Raspberry Pi and the autopilot are physically connected through serial and communicate via MAVProxy. The Raspberry Pi continuously monitors the flight path in real time through USB camera module. The algorithm checks whether the target is captured or not. If the target is detected, the position of the object in frame is represented in Cartesian coordinates and converted into estimate GPS coordinates. In parallel, the autopilot receives the target location approximate GPS and makes a decision to guide the UAV to a new location. This system also has potential uses in the field of Precision Agriculture, plant pest detection and disease outbreaks which cause detrimental financial damage to crop yields if not detected early on. Results show the algorithm is accurate to detect 99% of object of interest and the UAV is capable of navigation and doing on-board decision making.

A review on exploring the behavior of multi-layer composite structures under dynamic loading

This paper reviews the recent research progress on multi-layer composite structures composed of variety of materials. The utilization of multi-layer composite system is found to be common in metal structures and pavement systems. The layer of composite structure designed to encounter heavy dynamic energy should have sufficient ductility to counteract the intensity of energy. Therefore, the selection of materials and enhancement of interface bonding become crucial and both are discussed in this paper. The failure modes have also been explored in conjunction with stresses at failures and inferred solutions are also revealed. The paper attempts to reveal all technical facts on multi-layer composite structure in a broad field.

Risk assessment for airborne infectious diseases between natural ventilation and split-system air conditioner in a university classroom

Indoor air quality is a critical factor in the classroom due to high people concentration in a unique space. Indoor air pollutant might increase the chance of both long and short-term health problems among students and staff, reduce the productivity of teachers and degrade the student’s learning environment and comfort. Adequate air distribution strategies may reduce risk of infection in classroom. So, the purpose of air distribution systems in a classroom is not only to maximize conditions for thermal comfort, but also to remove indoor contaminants. Natural ventilation has the potential to play a significant role in achieving improvements in IAQ. The present study compares the risk of airborne infection between Natural Ventilation (opening windows and doors) and a Split-System Air Conditioner in a university classroom. The Wells-Riley model was used to predict the risk of indoor airborne transmission of infectious diseases such as influenza, measles and tuberculosis. For each case, the air exchange rate was measured using a CO2 tracer gas technique. It was found that opening windows and doors provided an air exchange rate of 2.3 air changes/hour (ACH), while with the Split System it was 0.6 ACH. The risk of airborne infection ranged between 4.24 to 30.86 % when using the Natural Ventilation and between 8.99 to 43.19% when using the Split System. The difference of airborne infection risk between the Split System and the Natural Ventilation ranged from 47 to 56%. Opening windows and doors maximize Natural Ventilation so that the risk of airborne contagion is much lower than with Split System.

Time-driven life cycle cost estimation system for product family design

This research develops a design support system, which is able to estimate the life cycle cost of different product families at the early stage of product development. By implementing the system, a designer is able to develop various cost effective product families in a shorter lead-time and minimise the destructive impact of the product family on the environment.

Automated feature engineering for HTTP tunnel detection

Generating discriminative input features is a key requirement for achieving highly accurate classifiers. The process of generating features from raw data is known as feature engineering and it can take significant manual effort. In this paper we propose automated feature engineering to derive a suite of additional features from a given set of basic features with the aim of both improving classifier accuracy through discriminative features, and to assist data scientists through automation. Our implementation is specific to HTTP computer network traffic. To measure the effectiveness of our proposal, we compare the performance of a supervised machine learning classifier built with automated feature engineering versus one using human-guided features. The classifier addresses a problem in computer network security, namely the detection of HTTP tunnels. We use Bro to process network traffic into base features and then apply automated feature engineering to calculate a larger set of derived features. The derived features are calculated without favour to any base feature and include entropy, length and N-grams for all string features, and counts and averages over time for all numeric features. Feature selection is then used to find the most relevant subset of these features. Testing showed that both classifiers achieved a detection rate above 99.93% at a false positive rate below 0.01%. For our datasets, we conclude that automated feature engineering can provide the advantages of increasing classifier development speed and reducing development technical difficulties through the removal of manual feature engineering. These are achieved while also maintaining classification accuracy.

A cloud-based intelligent computing system for contextual exploration on personal sleep-tracking data using association rule mining

With the development of wearable and mobile computing technology, more and more people start using sleep-tracking tools to collect personal sleep data on a daily basis aiming at understanding and improving their sleep. While sleep quality is influenced by many factors in a person’s lifestyle context, such as exercise, diet and steps walked, existing tools simply visualize sleep data per se on a dashboard rather than analyse those data in combination with contextual factors. Hence many people find it difficult to make sense of their sleep data. In this paper, we present a cloud-based intelligent computing system named SleepExplorer that incorporates sleep domain knowledge and association rule mining for automated analysis on personal sleep data in light of contextual factors. Experiments show that the same contextual factors can play a distinct role in sleep of different people, and SleepExplorer could help users discover factors that are most relevant to their personal sleep.

Reasoning about discontinuance of information system use

While many studies have explored conditions and consequences of information systems adoption and use, few have focused on the final stages of the information system lifecycle. In this paper, I develop a theoretical and an initial empirical contribution to understanding individuals’ intentions to discontinue the use of an information system. This understanding is important because it yields implications about maintenance, retirement, and users’ switching decisions, which ultimately can affect work performance, system effectiveness, and return on technology investments. In this paper, I offer a new conceptualization of factors determining users’ intentions to discontinue the use of information systems. I then report on a preliminary empirical test of the model using data from a field study of information system users in a promotional planning routine in a large retail organization. Results from the empirical analysis provide first empirical support for the theoretical model. I discuss the work’s implications for theory on information systems continuance and dual-factor logic in information system use. I also provide suggestions for managers dealing with cessation of information systems and broader work routine change in organizations due to information system end-of-life decisions.