Forecasting success on large projects : developing reliable scales to predict multiple perspectives by multiple stakeholders over multiple time frames

Our aim is to develop a set of leading performance indicators to enable managers of large projects to forecast during project execution how various stakeholders will perceive success months or even years into the operation of the output. Large projects have many stakeholders who have different objectives for the project, its output, and the business objectives they will deliver. The output of a large project may have a lifetime that lasts for years, or even decades, and ultimate impacts that go beyond its immediate operation. How different stakeholders perceive success can change with time, and so the project manager needs leading performance indicators that go beyond the traditional triple constraint to forecast how key stakeholders will perceive success months or even years later. In this article, we develop a model for project success that identifies how project stakeholders might perceive success in the months and years following a project. We identify success or failure factors that will facilitate or mitigate against achievement of those success criteria, and a set of potential leading performance indicators that forecast how stakeholders will perceive success during the life of the project's output. We conducted a scale development study with 152 managers of large projects and identified two project success factor scales and seven stakeholder satisfaction scales that can be used by project managers to predict stakeholder satisfaction on projects and so may be used by the managers of large projects for the basis of project control.

A penalty-based grouping genetic algorithm for multiple composite SaaS components clustering in Cloud

Software as a Service (SaaS) in Cloud is getting more and more significant among software users and providers recently. A SaaS that is delivered as composite application has many benefits including reduced delivery costs, flexible offers of the SaaS functions and decreased subscription cost for users. However, this approach has introduced a new problem in managing the resources allocated to the composite SaaS. The resource allocation that has been done at the initial stage may be overloaded or wasted due to the dynamic environment of a Cloud. A typical data center resource management usually triggers a placement reconfiguration for the SaaS in order to maintain its performance as well as to minimize the resource used. Existing approaches for this problem often ignore the underlying dependencies between SaaS components. In addition, the reconfiguration also has to comply with SaaS constraints in terms of its resource requirements, placement requirement as well as its SLA. To tackle the problem, this paper proposes a penalty-based Grouping Genetic Algorithm for multiple composite SaaS components clustering in Cloud. The main objective is to minimize the resource used by the SaaS by clustering its component without violating any constraint. Experimental results demonstrate the feasibility and the scalability of the proposed algorithm.

Online multiple profile manager for eHealth information sharing

Online social networks connect millions of people around the globe. These electronic bonds make individuals comfortable with their behaviours. Such positive signs of sharing information is useful phenomena requires consideration to establish a socio-scientific effect. Recently, many web users have more than one social networking account. This means a user may hold multiple profiles which are stored in different Social Network Sites (SNNs). Maintaining these multiple online social network profiles is cumbersome and time-consuming [1]. In this paper we will propose a framework for the management of a user's multiple profiles. A demonstrator, called Multiple Profile Manager (MPM), will be showcased to illustrate how effective the framework will be.

Short answer versus multiple choice examination questions for first year chemistry

Multiple choice (MC) examinations are frequently used for the summative assessment of large classes because of their ease of marking and their perceived objectivity. However, traditional MC formats usually lead to a surface approach to learning, and do not allow students to demonstrate the depth of their knowledge or understanding. For these reasons, we have trialled the incorporation of short answer (SA) questions into the final examination of two first year chemistry units, alongside MC questions. Students’ overall marks were expected to improve, because they were able to obtain partial marks for the SA questions. Although large differences in some individual students’ performance in the two sections of their examinations were observed, most students received a similar percentage mark for their MC as for their SA sections and the overall mean scores were unchanged. In-depth analysis of all responses to a specific question, which was used previously as a MC question and in a subsequent semester in SA format, indicates that the SA format can have weaknesses due to marking inconsistencies that are absent for MC questions. However, inclusion of SA questions improved student scores on the MC section in one examination, indicating that their inclusion may lead to different study habits and deeper learning. We conclude that questions asked in SA format must be carefully chosen in order to optimise the use of marking resources, both financial and human, and questions asked in MC format should be very carefully checked by people trained in writing MC questions. These results, in conjunction with an analysis of the different examination formats used in first year chemistry units, have shaped a recommendation on how to reliably and cost-effectively assess first year chemistry, while encouraging higher order learning outcomes.

Preliminary insights from a multiple case study on process modelling impact

Process modelling – the design and use of graphical documentations of an organisation’s business processes – is a key method to document and use information about business processes in organisational projects. Still, despite current interest in process modelling, this area of study still faces essential challenges. One of the key unanswered questions concerns the impact of process modelling in organisational practice. Process modelling initiatives call for tangible results in the form of returns on the substantial investments that organisations undertake to achieve improved processes. This study explores the impact of process model use on end-users and its contribution to organisational success. We posit that the use of conceptual models creates impact in organisational process teams. We also report on a set of case studies in which we explore tentative evidence for the development of impact of process model use. The results of this work provide a better understanding of process modelling impact from information practices and also lead to insights into how organisations should conduct process modelling initiatives in order to achieve an optimum return on their investment.

A practical signal processing approach for condition monitoring of low speed machinery using Peak-Hold-Down-Sample algorithm

A simple and effective down-sample algorithm, Peak-Hold-Down-Sample (PHDS) algorithm is developed in this paper to enable a rapid and efficient data transfer in remote condition monitoring applications. The algorithm is particularly useful for high frequency Condition Monitoring (CM) techniques, and for low speed machine applications since the combination of the high sampling frequency and low rotating speed will generally lead to large unwieldy data size. The effectiveness of the algorithm was evaluated and tested on four sets of data in the study. One set of the data was extracted from the condition monitoring signal of a practical industry application. Another set of data was acquired from a low speed machine test rig in the laboratory. The other two sets of data were computer simulated bearing defect signals having either a single or multiple bearing defects. The results disclose that the PHDS algorithm can substantially reduce the size of data while preserving the critical bearing defect information for all the data sets used in this work even when a large down-sample ratio was used (i.e., 500 times down-sampled). In contrast, the down-sample process using existing normal down-sample technique in signal processing eliminates the useful and critical information such as bearing defect frequencies in a signal when the same down-sample ratio was employed. Noise and artificial frequency components were also induced by the normal down-sample technique, thus limits its usefulness for machine condition monitoring applications.

Measurement of structural changes to a food material during dehydration

Rates of dehydration/rehydration are important quality parameters for dried products. Theoretically, if there are no adverse effects on the integrity of the tissue structure, it should absorb water to the same moisture content of the initial product before drying.The purpose of this work is to semi-automate the process of detection of cell structure boundaries as a food is dehydrated and rehydrated. This will enable food materials researchers to quantify changes to material’s structure as these processes take place. Images of potato cells as they were dehydrated and rehydrated were taken using an electron microscope. Cell boundaries were detected using an image processing algorithm. Average cell area and perimeter at each stage of dehydration were calculated and plotted versus time. The results show that the algorithm can successfully identify cell boundaries.

The relationship between fundamental movement skills and self-reported physical activity during Finnish junior high school

Background: Previous studies have shown that fundamental movement skills (FMS) and physical activity are related. Specifically, earlier studies have demonstrated that the ability to perform a variety of FMS increases the likelihood of children participating in a range of physical activities throughout their lives. To date, however, there have not been studies focused on the development of, or the relationship between, these variables through junior high school (that is, between the ages of 13 and 15). Such studies might provide important insights into the relationships between FMS and physical activity during adolescence, and suggest ways to design more effective physical education programmes for adolescents. Purpose: The main purposes of the study are: (1) to investigate the development of the students' self-reported physical activity and FMS from Grade 7 to Grade 9, (2) to analyse the associations among the students' FMS and self-reported physical activity through junior high school, (3) to analyse whether there are gender differences in research tasks one and/or two. Participants and setting: The participants in the study were 152 Finnish students, aged 13 and enrolled in Grade 7 at the commencement of the study. The sample included 66 girls and 86 boys who were drawn from three junior high schools in Middle Finland. Research design and data collection: Both the FMS tests and questionnaires pertaining to self-reported physical activity were completed annually during a 3 year period: in August (when the participants were in Grade 7), January (Grade 8), and in May (Grade 9). Data analysis: Repeated measures multivariate analysis of variances (MANOVAs) were used to analyse the interaction between gender and time (three measurement points) in FMS test sumscores and self-reported physical activity scores. The relationships between self-reported physical activity scores and fundamental movement skill sumscores through junior high school were analysed using Structural Equation Modelling (SEM) with LISREL 8.80 software. Findings: The MANOVA for self-reported physical activity demonstrated that both genders' physical activity decreased through junior high school. The MANOVA for the FMS revealed that the boys' FMS sumscore increased whereas the girls' skills decreased through junior high school. The SEM and squared multiple correlations revealed FMS in Grades 7 and 8 as well as physical activity in Grade 9 explained FMS in Grade 9. The portion of prediction was 69% for the girls and 55% for the boys. Additionally, physical activity measured in Grade 7 and FMS measured in Grade 9 explained physical activity in Grade 9. The portion of prediction was 12% for the girls and 29% for the boys. In the boys' group, three additional paths were found; FMS in Grade 7 explained physical activity in Grade 9, physical activity in Grade 7 explained FMS in Grade 8, and physical activity in Grade 7 explained physical activity in Grade 8. Conclusions: The study suggests that supporting and encouraging FMS and physical activity are co-related and when considering combined scores there is a greater likelihood of healthy lifelong outcomes. Therefore, the conclusion can be drawn that FMS curriculum in school-based PE is a plausible way to ensure good lifelong outcomes. Earlier studies support that school physical education plays an important role in developing students FMS and is in a position to thwart the typical decline of physical activity in adolescence. These concepts are particularly important for adolescent girls as this group reflects the greatest decline in physical activity during the adolescent period.

Reliability of partial ambiguity fixing with multiple GNSS constellations

Reliable ambiguity resolution (AR) is essential to Real-Time Kinematic (RTK) positioning and its applications, since incorrect ambiguity fixing can lead to largely biased positioning solutions. A partial ambiguity fixing technique is developed to improve the reliability of AR, involving partial ambiguity decorrelation (PAD) and partial ambiguity resolution (PAR). Decorrelation transformation could substantially amplify the biases in the phase measurements. The purpose of PAD is to find the optimum trade-off between decorrelation and worst-case bias amplification. The concept of PAR refers to the case where only a subset of the ambiguities can be fixed correctly to their integers in the integer least-squares (ILS) estimation system at high success rates. As a result, RTK solutions can be derived from these integer-fixed phase measurements. This is meaningful provided that the number of reliably resolved phase measurements is sufficiently large for least-square estimation of RTK solutions as well. Considering the GPS constellation alone, partially fixed measurements are often insufficient for positioning. The AR reliability is usually characterised by the AR success rate. In this contribution an AR validation decision matrix is firstly introduced to understand the impact of success rate. Moreover the AR risk probability is included into a more complete evaluation of the AR reliability. We use 16 ambiguity variance-covariance matrices with different levels of success rate to analyse the relation between success rate and AR risk probability. Next, the paper examines during the PAD process, how a bias in one measurement is propagated and amplified onto many others, leading to more than one wrong integer and to affect the success probability. Furthermore, the paper proposes a partial ambiguity fixing procedure with a predefined success rate criterion and ratio-test in the ambiguity validation process. In this paper, the Galileo constellation data is tested with simulated observations. Numerical results from our experiment clearly demonstrate that only when the computed success rate is very high, the AR validation can provide decisions about the correctness of AR which are close to real world, with both low AR risk and false alarm probabilities. The results also indicate that the PAR procedure can automatically chose adequate number of ambiguities to fix at given high-success rate from the multiple constellations instead of fixing all the ambiguities. This is a benefit that multiple GNSS constellations can offer.

A particle-based micromechanics approach to simulate structural changes of plant cells during drying

This paper is concerned with applying a particle-based approach to simulate the micro-level cellular structural changes of plant cells during drying. The objective of the investigation was to relate the micro-level structural properties such as cell area, diameter and perimeter to the change of moisture content of the cell. Model assumes a simplified cell which consists of two basic components, cell wall and cell fluid. The cell fluid is assumed to be a Newtonian fluid with higher viscosity compared to water and cell wall is assumed to be a visco-elastic solid boundary located around the cell fluid. Cell fluid is modelled with Smoothed Particle Hydrodynamics (SPH) technique and for the cell wall; a Discrete Element Method (DEM) is used. The developed model is two-dimensional, but accounts for three-dimensional physical properties of real plant cells. Drying phenomena is simulated as fluid mass reductions and the model is used to predict the above mentioned structural properties as a function of cell fluid mass. Model predictions are found to be in fairly good agreement with experimental data in literature and the particle-based approach is demonstrated to be suitable for numerical studies of drying related structural deformations. Also a sensitivity analysis is included to demonstrate the influence of key model parameters to model predictions.

Structural characterisation of kaolinite : NaCl intercalate and its derivatives

Kaolinite:NaCl intercalates with basal layer dimensions of 0.95 and 1.25 nm have been prepared by direct reaction of saturated aqueous NaCl solution with well-crystallized source clay KGa-1. The intercalates and their thermal decomposition products have been studied by XRD, solid-state 23Na, 27Al, and 29Si MAS NMR, and FTIR. Intercalate yield is enhanced by dry grinding of kaolinite with NaCl prior to intercalation. The layered structure survives dehydroxylation of the kaolinite at 500°–600°C and persists to above 800°C with a resultant tetrahedral aluminosilicate framework. Excess NaCl can be readily removed by rinsing with water, producing an XRD ‘amorphous’ material. Upon heating at 900°C this material converts to a well-crystallized framework aluminosilicate closely related to low-camegieite, NaAlSiO4, some 350°C below its stability field. Reaction mechanisms are discussed and structural models proposed for each of these novel materials.

Protein monoubiquitination and polyubiquitination generate structural diversity to control distinct biological processes

Ubiquitination involves the attachment of ubiquitin (Ub) to lysine residues on substrate proteins or itself, which can result in protein monoubiquitination or polyubiquitination. Polyubiquitination through different lysines (seven) or the N-terminus of Ub can generate different protein-Ub structures. These include monoubiquitinated proteins, polyubiqutinated proteins with homotypic chains through a particular lysine on Ub or mixed polyubiquitin chains generated by polymerization through different Ub lysines. The ability of the ubiquitination pathway to generate different protein-Ub structures provides versatility of this pathway to target proteins to different fates. Protein ubiquitination is catalyzed by Ub-conjugating and Ub-ligase enzymes, with different combinations of these enzymes specifying the type of Ub modification on protein substrates. How Ub-conjugating and Ub-ligase enzymes generate this structural diversity is not clearly understood. In the current review, we discuss mechanisms utilized by the Ub-conjugating and Ub-ligase enzymes to generate structural diversity during protein ubiquitination, with a focus on recent mechanistic insights into protein monoubiquitination and polyubiquitination.

Contribution of DEAF1 structural domains to the interaction with the breast cancer oncogene LMO4

The proteins LMO4 and DEAF1 contribute to the proliferation of mammary epithelial cells. During breast cancer LMO4 is upregulated, affecting its interaction with other protein partners. This may set cells on a path to tumour formation. LMO4 and DEAF1 interact, but it is unknown how they cooperate to regulate cell proliferation. In this study, we identify a specific LMO4-binding domain in DEAF1. This domain contains an unstructured region that directly contacts LMO4, and a coiled coil that contains the DEAF1 nuclear export signal (NES). The coiled coil region can form tetramers and has the typical properties of a coiled coil domain. Using a simple cell-based assay, we show that LMO4 modulates the activity of the DEAF NES, causing nuclear accumulation of a construct containing the LMO4-interaction region of DEAF1.

Damage detection in slab-on-girder bridges using vibration characteristics

This paper develops and applies a multi-criteria procedure, incorporating changes in natural frequencies, modal flexibility and the modal strain energy, for damage detection in slab-on-girder bridges. The proposed procedure is first validated through experimental testing of a model bridge. Numerically simulated modal data obtained through finite element analyses are then used to evaluate the vibration parameters before and after damage and used as the indices for assessment of the state of structural health. The procedure is illustrated by its application to full scale slab-on-girder bridges under different damage scenarios involving single and multiple damages on the deck and girders.

Towards Bayesian experimental design for nonlinear models that require a large number of sampling times

The use of Bayesian methodologies for solving optimal experimental design problems has increased. Many of these methods have been found to be computationally intensive for design problems that require a large number of design points. A simulation-based approach that can be used to solve optimal design problems in which one is interested in finding a large number of (near) optimal design points for a small number of design variables is presented. The approach involves the use of lower dimensional parameterisations that consist of a few design variables, which generate multiple design points. Using this approach, one simply has to search over a few design variables, rather than searching over a large number of optimal design points, thus providing substantial computational savings. The methodologies are demonstrated on four applications, including the selection of sampling times for pharmacokinetic and heat transfer studies, and involve nonlinear models. Several Bayesian design criteria are also compared and contrasted, as well as several different lower dimensional parameterisation schemes for generating the many design points.