Adaptive Merging on Phase Change Memory

Indexing is a well-known database technique used to facilitate data access and speed up query processing. Nevertheless, the construction and modification of indexes are very expensive. In traditional approaches, all records in the database table are equally covered by the index. It is not effective, since some records may be queried very often and some never. To avoid this problem, adaptive merging has been introduced. The key idea is to create index adaptively and incrementally as a side-product of query processing. As a result, the database table is indexed partially depending on the query workload. This paper faces a problem of adaptive merging for phase change memory (PCM). The most important features of this memory type are: limited write endurance and high write latency. As a consequence, adaptive merging should be investigated from the scratch. We solve this problem in two steps. First, we apply several PCM optimization techniques to the traditional adaptive merging approach. We prove that the proposed method (eAM) outperforms a traditional approach by 60%. After that, we invent the framework for adaptive merging (PAM) and a new PCM-optimized index. It further improves the system performance by 20% for databases where search queries interleave with data modifications

The 45th Australasian Universities Building Education Association Conference: Global Challenges in a Disrupted World: Smart, Sustainable and Resilient Approaches in the Built Environment, Conference Proceedings, 23 - 25 November 2022, Western Sydney University, Kingswood Campus, Sydney, Australia

This is the proceedings of the 45th Australasian Universities Building Education Association (AUBEA) conference which will be hosted by Western Sydney University in November 2022. The conference is organised by the School of Engineering, Design, and Built Environment in collaboration with the Centre for Smart Modern Construction, Western Sydney University. This year’s conference theme is “Global Challenges in a Disrupted World: Smart, Sustainable and Resilient Approaches in the Built Environment”, and expects to publish over a hundred double-blind peer review papers under the proceedings

Measuring knowledge sharing processes through social network analysis within construction organisations

The construction industry is a knowledge intensive and information dependent industry. Organisations risk losing valuable knowledge, when the employees leave them. Therefore, construction organisations need to nurture opportunities to disseminate knowledge through strengthening knowledge-sharing networks. This study aimed at evaluating the formal and informal knowledge sharing methods in social networks within Australian construction organisations and identifying how knowledge sharing could be improved. Data were collected from two estimating teams in two case studies. The collected data through semi-structured interviews were analysed using UCINET, a Social Network Analysis (SNA) tool, and SNA measures. The findings revealed that one case study consisted of influencers, while the other demonstrated an optimal knowledge sharing structure in both formal and informal knowledge sharing methods. Social networks could vary based on the organisation as well as the individuals’ behaviour. Identifying networks with specific issues and taking steps to strengthen networks will enable to achieve optimum knowledge sharing processes. This research offers knowledge sharing good practices for construction organisations to optimise their knowledge sharing processes

Student Expectations: The effect of student background and experience

CONTEXT The perspectives and previous experiences that students bring to their programs of study can affect their approaches to study and the depth of learning that they achieve Prosser & Trigwell, 1999; Ramsden, 2003). Graduate outcomes assume the attainment of welldeveloped independent learning skills which can be transferred to the work-place. PURPOSE This 5-year longitudinal study investigates factors influencing students’ approaches to learning in the fields of Engineering, Software Engineering, and Computer Science, at two higher education institutes delivering programs of various levels in Australia and New Zealand. The study aims to track the development of student approaches to learning as they progress through their program. Through increased understanding of students’ approaches, faculty will be better able to design teaching and learning strategies to meet the needs of an increasingly diverse student body. This paper reports on the first stage of the project. APPROACH In August 2017, we ran a pilot of our survey using the Revised Study Process Questionnaire(Biggs, Kember, & Leung, 2001) and including some additional questions related to student demographics and motivation for undertaking their current program of study. Data were analysed to evaluate the usefulness of data collected and to understand the demographics of the student cohort. Over the period of the research, data will be collected using the questionnaire and through focus groups and interviews. RESULTS Participants provided a representative sample, and the data collected was reasonable, allowing the questionnaire design to be confirmed. CONCLUSIONS At this preliminary stage, the study has provided insight into the student demographics at both institutes and identified aspects of students’ modes of engagement with learning. Some areas for improvement of the questionnaire have been identified, which will be implemented for the main body of the study

Dynamic Characteristics and Wind-induced Response of a Tall Building

The design of tall buildings requires an accurate understanding of the expected wind loads and the resulting responses. The techniques used to estimate the wind-induced response are subject to uncertainty, which can result in unsatisfactory building performance or an over-designed structure. Altering the structure to rectify unsatisfactory performance can be extremely difficult and prohibitively expensive, while an over-designed structure represents unnecessary cost to the owner. This implies that accurate estimates of wind loads and responses are crucial to tall building design. Two aspects of tall building wind-induced response estimation are investigated: the estimation of natural frequencies and damping ratios; and the understanding of mechanisms causing wind-induced responses. This was primarily conducted via full-scale testing of a tall building. The building used for full-scale measurements is Latitude tower, an office tower located in the Sydney central business district, with a height of 187m above ground and 28m of underground levels. The building has a composite design including a reinforced concrete core, and reinforced concrete floor slabs supported by steel beams spanning between the core and perimeter columns. Outriggers linking the core and perimeter columns, as well as offset outriggers at the facade, are located at mid-height. The full-scale testing was conducted in two parts: vibration testing during construction; and a two year monitoring programme commenced after construction completion. Vibration testing during construction was conducted to determine the natural frequencies and damping ratios as the structure changed. Forced vibration testing and ambient vibration testing techniques were used. The Frequency Domain Decomposition and Stochastic Subspace Identification techniques were used to estimate the natural frequencies and damping ratios from the ambient vibration test outputs. The natural frequencies and damping ratios from the forced and ambient vibration tests differed by less than 5% and 30% respectively. Changes in the fundamental natural frequencies during construction were discussed in conjunction with the structural changes to further the understanding of how changes in the stiffness and mass of a tall building influence the natural frequencies. The measured natural frequencies during the early stages of construction were used to update a finite element model representing the structure at the time of testing. The material properties and floor beams were the primary focus of the model updating. The knowledge gained from partial structure updating was applied to a model of the completed structure, and the natural frequency estimate errors improved from 17% to 7%. The fundamental mode damping ratios measured during construction changed by less than 15% between the first test, conducted when 38% of the tower height was reached, and the final test at construction completion. The wind-induced monitoring programme included the measurement of wind velocities, accelerations, and displacements at the top of the building. The peak events for southerly and westerly wind directions were discussed. It was found that the acceleration response was dominated by the fundamental vibration mode. For southerly winds this corresponded to an along-wind response, but for westerly winds this corresponds to a cross-wind response. The probability distributions of upcrossings for along-wind and cross-wind responses where not significantly different to a Gaussian distribution for both southerly and westerly winds. The slope of the linear least squares fit was greater than two in all cases, which suggested intermittent characteristics were present in the responses. The standard deviation resonant acceleration responses from a high frequency base balance wind tunnel test were within 29% of the measured values

Chair a session/Integration of theory and practice in the learning and teaching process

The theme for AAEE-2017 is “Integrated Engineering”, which covers a range of sub-themes, such as: Integration of theory and practice in the learning and teaching process Interdisciplinary and cross-disciplinary engineering programs and learning environments Integration of teaching and research in the engineering training process The role and impact of engineering students and educators in the wider community Systems perspectives on engineering education. Integration is also about connections, e.g. between students and teachers, between students in learning together, and between educational institutions and industry and wider society in the engineering education process

A new strategy for active learning to maximise performance in intensive courses

This paper describes an innovation in the delivery of an introductory thermodynamics course offered to students studying towards an engineering qualification. The course was delivered in intensive format, across three weeks of study. Students find it challenging to engage with complex engineering topics in a short period of time, and there is no sizeable study break for pre-exam study. This means that students cannot afford to delay in learning and applying content. Every class must be an opportunity to interact with the content immediately. The innovation described here involved implementing a new daily structure for the course that attempted to mimic the standard process by which students learn material, apply it, study it and practice it in across a traditional-length semester. The new structure involved integrating the lecture and recitation components to the course to increasing the active learning during material delivery, then allowing students to engage in guided study and open-book formative assessment. This paper describes the implementation of this innovation. A brief review of the literature on intensive courses is provided, followed by a description of the approach used in this particular class. The results are then presented, and evaluated in the context of the research and the instructor’s own critical reflection

Data-driven conceptual modeling: how some knowledge drivers for the enterprise might be mined from enterprise data

As organizations perform their business, they analyze, design and manage a variety of processes represented in models with different scopes and scale of complexity. Specifying these processes requires a certain level of modeling competence. However, this condition does not seem to be balanced with adequate capability of the person(s) who are responsible for the task of defining and modeling an organization or enterprise operation. On the other hand, an enterprise typically collects various records of all events occur during the operation of their processes. Records, such as the start and end of the tasks in a process instance, state transitions of objects impacted by the process execution, the message exchange during the process execution, etc., are maintained in enterprise repositories as various logs, such as event logs, process logs, effect logs, message logs, etc. Furthermore, the growth rate in the volume of these data generated by enterprise process execution has increased manyfold in just a few years. On top of these, models often considered as the dashboard view of an enterprise. Models represents an abstraction of the underlying reality of an enterprise. Models also served as the knowledge driver through which an enterprise can be managed. Data-driven extraction offers the capability to mine these knowledge drivers from enterprise data and leverage the mined models to establish the set of enterprise data that conforms with the desired behaviour. This thesis aimed to generate models or knowledge drivers from enterprise data to enable some type of dashboard view of enterprise to provide support for analysts. The rationale for this has been started as the requirement to improve an existing process or to create a new process. It was also mentioned models can also serve as a collection of effectors through which an organization or an enterprise can be managed. The enterprise data refer to above has been identified as process logs, effect logs, message logs, and invocation logs. The approach in this thesis is to mine these logs to generate process, requirement, and enterprise architecture models, and how goals get fulfilled based on collected operational data. The above a research question has been formulated as whether it is possible to derive the knowledge drivers from the enterprise data, which represent the running operation of the enterprise, or in other words, is it possible to use the available data in the enterprise repository to generate the knowledge drivers? . In Chapter 2, review of literature that can provide the necessary background knowledge to explore the above research question has been presented. Chapter 3 presents how process semantics can be mined. Chapter 4 suggest a way to extract a requirements model. The Chapter 5 presents a way to discover the underlying enterprise architecture and Chapter 6 presents a way to mine how goals get orchestrated. Overall finding have been discussed in Chapter 7 to derive some conclusions