Crowdsourcing interactions : using crowdsourcing for evaluating interactive information retrieval systems

In the field of information retrieval (IR), researchers and practitioners are often faced with a demand for valid approaches to evaluate the performance of retrieval systems. The Cranfield experiment paradigm has been dominant for the in-vitro evaluation of IR systems. Alternative to this paradigm, laboratory-based user studies have been widely used to evaluate interactive information retrieval (IIR) systems, and at the same time investigate users’ information searching behaviours. Major drawbacks of laboratory-based user studies for evaluating IIR systems include the high monetary and temporal costs involved in setting up and running those experiments, the lack of heterogeneity amongst the user population and the limited scale of the experiments, which usually involve a relatively restricted set of users. In this paper, we propose an alternative experimental methodology to laboratory-based user studies. Our novel experimental methodology uses a crowdsourcing platform as a means of engaging study participants. Through crowdsourcing, our experimental methodology can capture user interactions and searching behaviours at a lower cost, with more data, and within a shorter period than traditional laboratory-based user studies, and therefore can be used to assess the performances of IIR systems. In this article, we show the characteristic differences of our approach with respect to traditional IIR experimental and evaluation procedures. We also perform a use case study comparing crowdsourcing-based evaluation with laboratory-based evaluation of IIR systems, which can serve as a tutorial for setting up crowdsourcing-based IIR evaluations.

On managing information technology capabilities

Information technology (IT) plays a critical role of enabler of activities that improve the performance of business processes. This enabling role of IT resources means continuous investment in IT is a strategic necessity. It is established that organizations’ IT-related capabilities leverage the enabling potential of IT resources. Today’s turbulent and challenging business environment requires organizations to do more from their existing and newly acquired IT resources. To achieve this, organizations need to discover ways or establish environments to nourish their existing IT-related capabilities, and develop new IT-related capabilities. We suggest one such environment, a dynamic IT-learning environment that could contribute to nourishing existing IT-related capabilities, and developing new IT-related capabilities. This environment is a product of coordination of four organizational factors that relate to the ways in which IT-related knowledge is applied to business processes, the accompanying reward structures, and ways in which the IT-related learning and knowledge is shared within the organization. Using 216 field survey responses, this paper shows that two IT-related capabilities of top management commitment to IT initiatives, and shared organizational knowledge between the IT and business unit managers has a stronger positive influence on business process performance in the presence of this dynamic IT-learning environment. The study also shows that a marginal IT-related capability, technical IT skills, has a positive and significant influence on business process performance in the presence of this environment. These outcomes imply that organizations’ internal environments could contribute to the management of their IT-related capabilities.

Factors affecting the extraction of absorbed dose information in a 3D polymer gel dosimeter by X ray computed tomography (IAEA-CN-96/122P)

Two sources of uncertainty in the X ray computed tomography imaging of polymer gel dosimeters are investigated in the paper.The first cause is a change in postirradiation density, which is proportional to the computed tomography signal and is associated with a volume change. The second cause of uncertainty is reconstruction noise.A simple technique that increases the residual signal to noise ratio by almost two orders of magnitude is examined.

New criterion for the stability of a human body in floodwaters

The authors must be congratulated for their original and important study. The flooding of urbanised areas constitutes a hazard to the population and infrastructure. Floods through inundated urban environments have been studied only recently and few considered the potential impact of flowing waters on pedestrians...

How much information can be obtained from tracking the position of the leading edge in a scratch assay?

Moving cell fronts are an essential feature of wound healing, development and disease. The rate at which a cell front moves is driven, in part, by the cell motility, quantified in terms of the cell diffusivity $D$, and the cell proliferation rate �$\lambda$. Scratch assays are a commonly-reported procedure used to investigate the motion of cell fronts where an initial cell monolayer is scratched and the motion of the front is monitored over a short period of time, often less than 24 hours. The simplest way of quantifying a scratch assay is to monitor the progression of the leading edge. Leading edge data is very convenient since, unlike other methods, it is nondestructive and does not require labeling, tracking or counting individual cells amongst the population. In this work we study short time leading edge data in a scratch assay using a discrete mathematical model and automated image analysis with the aim of investigating whether such data allows us to reliably identify $D$ and $\lambda$�. Using a naıve calibration approach where we simply scan the relevant region of the ($D$;$\lambda$�) parameter space, we show that there are many choices of $D$ and $\lambda$� for which our model produces indistinguishable short time leading edge data. Therefore, without due care, it is impossible to estimate $D$ and $\lambda$� from this kind of data. To address this, we present a modified approach accounting for the fact that cell motility occurs over a much shorter time scale than proliferation. Using this information we divide the duration of the experiment into two periods, and we estimate $D$ using data from the first period, while we estimate �$\lambda$ using data from the second period. We confirm the accuracy of our approach using in silico data and a new set of in vitro data, which shows that our method recovers estimates of $D$ and $\lamdba$� that are consistent with previously-reported values except that that our approach is fast, inexpensive, nondestructive and avoids the need for cell labeling and cell counting.

Process model abstraction : a slider approach

Process models provide companies efficient means for managing their business processes. Tasks where process models are employed are different by nature and require models of various abstraction levels. However, maintaining several models of one business process involves a lot of synchronization effort and is erroneous. Business process model abstraction assumes a detailed model of a process to be available and derives coarse grained models from it. The task of abstraction is to tell significant model elements from insignificant ones and to reduce the latter. In this paper we argue that process model abstraction can be driven by different abstraction criteria. Criterion choice depends on a task which abstraction facilitates. We propose an abstraction slider - a mechanism that allows user control of the model abstraction level. We discuss examples of combining the slider with different abstraction criteria and sets of process model transformation rules.

Connectivity of workflow nets : the foundations of stepwise verification

Behavioral models capture operational principles of real-world or designed systems. Formally, each behavioral model defines the state space of a system, i.e., its states and the principles of state transitions. Such a model is the basis for analysis of the system’s properties. In practice, state spaces of systems are immense, which results in huge computational complexity for their analysis. Behavioral models are typically described as executable graphs, whose execution semantics encodes a state space. The structure theory of behavioral models studies the relations between the structure of a model and the properties of its state space. In this article, we use the connectivity property of graphs to achieve an efficient and extensive discovery of the compositional structure of behavioral models; behavioral models get stepwise decomposed into components with clear structural characteristics and inter-component relations. At each decomposition step, the discovered compositional structure of a model is used for reasoning on properties of the whole state space of the system. The approach is exemplified by means of a concrete behavioral model and verification criterion. That is, we analyze workflow nets, a well-established tool for modeling behavior of distributed systems, with respect to the soundness property, a basic correctness property of workflow nets. Stepwise verification allows the detection of violations of the soundness property by inspecting small portions of a model, thereby considerably reducing the amount of work to be done to perform soundness checks. Besides formal results, we also report on findings from applying our approach to an industry model collection.

Process compliance analysis based on behavioural profiles

Process compliance measurement is getting increasing attention in companies due to stricter legal requirements and market pressure for operational excellence. In order to judge on compliance of the business processing, the degree of behavioural deviation of a case, i.e., an observed execution sequence, is quantified with respect to a process model (referred to as fitness, or recall). Recently, different compliance measures have been proposed. Still, nearly all of them are grounded on state-based techniques and the trace equivalence criterion, in particular. As a consequence, these approaches have to deal with the state explosion problem. In this paper, we argue that a behavioural abstraction may be leveraged to measure the compliance of a process log – a collection of cases. To this end, we utilise causal behavioural profiles that capture the behavioural characteristics of process models and cases, and can be computed efficiently. We propose different compliance measures based on these profiles, discuss the impact of noise in process logs on our measures, and show how diagnostic information on non-compliance is derived. As a validation, we report on findings of applying our approach in a case study with an international service provider.

On optimal control of constrained linear systems with imperfect state information and stochastic disturbances

We address the problem of finite horizon optimal control of discrete-time linear systems with input constraints and uncertainty. The uncertainty for the problem analysed is related to incomplete state information (output feedback) and stochastic disturbances. We analyse the complexities associated with finding optimal solutions. We also consider two suboptimal strategies that could be employed for larger optimization horizons.

Overview of building information modelling in healthcare projects

In this paper, we explore how BIM functionalities together with novel management concepts and methods have been utilized in thirteen hospital projects in the United States and the United Kingdom. Secondary data collection and analysis were used as the method. Initial findings indicate that the utilization of BIM enables a holistic view of project delivery and helps to integrate project parties into a collaborative process. The initiative to implement BIM must come from the top down to enable early involvement of all key stakeholders. It seems that it is rather resistance from people to adapt to the new way of working and thinking than immaturity of technology that hinders the utilization of BIM.

The Interaction of lean and building information modeling in construction

Lean construction and building information modeling (BIM) are quite different initiatives, but both are having profound impacts on the construction industry. A rigorous analysis of the myriad specific interactions between them indicates that a synergy exists which, if properly understood in theoretical terms, can be exploited to improve construction processes beyond the degree to which it might be improved by application of either of these paradigms independently. Using a matrix that juxtaposes BIM functionalities with prescriptive lean construction principles, 56 interactions have been identified, all but four of which represent constructive interaction. Although evidence for the majority of these has been found, the matrix is not considered complete but rather a framework for research to explore the degree of validity of the interactions. Construction executives, managers, designers, and developers of information technology systems for construction can also benefit from the framework as an aid to recognizing the potential synergies when planning their lean and BIM adoption strategies.

Lean construction, building information modelling and sustainability

This paper investigates the mutual relations of three current drivers of construction: lean construction, building information modelling and sustainability. These drivers are based on infrequently occurring changes, only incidentally simultaneous, in their respective domains. It is contended that the drivers are mutually supportive and thus synergistic. They are aligned in the sense that all require, promote or enable collaboration. It is argued that these three drivers should be implemented in a unified manner for rapid and robust improvements in construction industry performance and the quality of the constructed facilities and their benefits for stakeholders and wider society.

Analysis framework for the interaction between lean construction and building information modelling

Building with Building Information Modelling (BIM) changes design and production processes. But can BIM be used to support process changes designed according to lean production and lean construction principles? To begin to answer this question we provide a conceptual analysis of the interaction of lean construction and BIM for improving construction. This was investigated by compiling a detailed listing of lean construction principles and BIM functionalities which are relevant from this perspective. These were drawn from a detailed literature survey. A research framework for analysis of the interaction between lean and BIM was then compiled. The goal of the framework is to both guide and stimulate research; as such, the approach adopted up to this point is constructive. Ongoing research has identified 55 such interactions, the majority of which show positive synergy between the two.

Understanding the information literacy experiences of EFL (English as a Foreign Language) students

This thesis investigated the information literacy experiences of EFL (English as a Foreign Language) students in a higher education institution in the United Arab Emirates (UAE). Phenomenography was used to investigate how EFL students' 'used information to learn' (ie. information literacy). The study revealed that EFL students' experienced information literacy across four categories and had varying experiences of information and learning. The research also showed that EFL students' faced a number of challenges and barriers due to language that impacted on their experiences of reading, understanding, accessing and translating information.