Use of Document Management Systems - a Case Study of the Finnish Construction Industry

Triggered by the very quick proliferation of Internet connectivity, electronic document management (EDM) systems are now rapidly being adopted for managing the documentation that is produced and exchanged in construction projects. Nevertheless there are still substantial barriers to the efficient use of such systems, mainly of a psychological nature and related to insufficient training. This paper presents the results of empirical studies carried out during 2002 concerning the current usage of EDM systems in the Finnish construction industry. The studies employed three different methods in order to provide a multifaceted view of the problem area, both on the industry and individual project level. In order to provide an accurate measurement of overall usage volume in the industry as a whole telephone interviews with key personnel from 100 randomly chosen construction projects were conducted. The interviews showed that while around 1/3 of big projects already have adopted the use of EDM, very few small projects have adopted this technology. The barriers to introduction were investigated through interviews with representatives for half a dozen of providers of systems and ASP-services. These interviews shed a lot of light on the dynamics of the market for this type of services and illustrated the diversity of business strategies adopted by vendors. In the final study log files from a project which had used an EDM system were analysed in order to determine usage patterns. The results illustrated that use is yet incomplete in coverage and that only a part of the individuals involved in the project used the system efficiently, either as information producers or consumers. The study also provided feedback on the usefulness of the log files.

Voting Paths

We consider a variant of the popular matching problem here. The input instance is a bipartite graph $G=(\mathcal{A}\cup\mathcal{P},E)$, where vertices in $\mathcal{A}$ are called applicants and vertices in $\mathcal{P}$ are called posts. Each applicant ranks a subset of posts in an order of preference, possibly involving ties. A matching $M$ is popular if there is no other matching $M'$ such that the number of applicants who prefer their partners in $M'$ to $M$ exceeds the number of applicants who prefer their partners in $M$ to $M'$. However, the “more popular than” relation is not transitive; hence this relation is not a partial order, and thus there need not be a maximal element here. Indeed, there are simple instances that do not admit popular matchings. The questions of whether an input instance $G$ admits a popular matching and how to compute one if it exists were studied earlier by Abraham et al. Here we study reachability questions among matchings in $G$, assuming that $G=(\mathcal{A}\cup\mathcal{P},E)$ admits a popular matching. A matching $M_k$ is reachable from $M_0$ if there is a sequence of matchings $\langle M_0,M_1,\dots,M_k\rangle$ such that each matching is more popular than its predecessor. Such a sequence is called a length-$k$ voting path from $M_0$ to $M_k$. We show an interesting property of reachability among matchings in $G$: there is always a voting path of length at most 2 from any matching to some popular matching. Given a bipartite graph $G=(\mathcal{A}\cup\mathcal{P},E)$ with $n$ vertices and $m$ edges and any matching $M_0$ in $G$, we give an $O(m\sqrt{n})$ algorithm to compute a shortest-length voting path from $M_0$ to a popular matching; when preference lists are strictly ordered, we have an $O(m+n)$ algorithm. This problem has applications in dynamic matching markets, where applicants and posts can enter and leave the market, and applicants can also change their preferences arbitrarily. After any change, the current matching may no longer be popular, in which case we are required to update it. However, our model demands that we switch from one matching to another only if there is consensus among the applicants to agree to the switch. Hence we need to update via a voting path that ends in a popular matching. Thus our algorithm has applications here.

Cluster based core vector machine

Core Vector Machine(CVM) is suitable for efficient large-scale pattern classification. In this paper, a method for improving the performance of CVM with Gaussian kernel function irrespective of the orderings of patterns belonging to different classes within the data set is proposed. This method employs a selective sampling based training of CVM using a novel kernel based scalable hierarchical clustering algorithm. Empirical studies made on synthetic and real world data sets show that the proposed strategy performs well on large data sets.

Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network

In this paper. we propose a novel method using wavelets as input to neural network self-organizing maps and support vector machine for classification of magnetic resonance (MR) images of the human brain. The proposed method classifies MR brain images as either normal or abnormal. We have tested the proposed approach using a dataset of 52 MR brain images. Good classification percentage of more than 94% was achieved using the neural network self-organizing maps (SOM) and 98% front support vector machine. We observed that the classification rate is high for a Support vector machine classifier compared to self-organizing map-based approach.

The Context and Diffusion of Knowledge in the Finnish Jewellery Industry - The role of the House of Fabergé

Researchers within the fields of economic geography and organizational management have extensively studied learning and the prerequisites and impediments for knowledge transfer. This paper combines two discourses within the two subjects: the-communities-of-practice and the learning region approaches, merging them through the so-called ecology of knowledge-approach, which is used to examine the knowledge transfer from the House of Fabergé to the Finnish jewellery industry. We examine the pre-revolution St Petersburg jewellery cluster and the post-revolution Helsinki, and the transfer of knowledge between these two locations through the components of communities of people, institutions and industry. The paper shows that the industrial dynamics of the Finnish modern-day goldsmith industry was inherently shaped both through the transfer and the non-transfer of knowledge. It also contends that the “knowledge-economy” is not anchored in and exclusive for the high technology sector of the late 20th century.

Scalable non-linear Support Vector Machine using hierarchical clustering

This paper discusses a method for scaling SVM with Gaussian kernel function to handle large data sets by using a selective sampling strategy for the training set. It employs a scalable hierarchical clustering algorithm to construct cluster indexing structures of the training data in the kernel induced feature space. These are then used for selective sampling of the training data for SVM to impart scalability to the training process. Empirical studies made on real world data sets show that the proposed strategy performs well on large data sets.

Dimensionality of quality from a customer perspective in the wood industry

The research analyzes product quality from a customer perspective in the case of the wood products industry. Of specific interest is to understand better how environmental quality is perceived from a customer perspective. The empirical material used comprises four data-sets from Finland, Germany and the UK, collected during 1992 2004. The methods consist of a set of quantitative statistical analyses. The results indicate that perceived quality from a customer perspective can be presented using a multidimensional and hierarchical construct with tangible and intangible dimensions, that is common to different markets and products. This applies in the case of wood products but also more generally at least for some other construction materials. For wood products, tangible product quality has two main sub-dimensions: technical quality and appearance. For product intangibles, a few main quality dimensions seem be detectable: Quality of intangibles related to the physical product, such as environmental issues and product-related information, supplier-related characteristics, and service and sales personnel behavior. Environmental quality and information are often perceived as being inter-related. Technical performance and appearance are the most important considerations for customers in the case of wood products. Organizational customers in particular also clearly consider certain intangible quality dimensions to be important, such as service and supplier reliability. The high technical quality may be considered as a license to operate , but product appearance and intangible quality provide potential for differentiation for attracting certain market segments. Intangible quality issues are those where Nordic suppliers underperform in comparison to their Central-European competitors on the important German markets. Environmental quality may not have been used to its full extent to attract customers. One possibility is to increase the availability of the environment-related information, or to develop environment-related product characteristics to also provide some individual benefits. Information technology provides clear potential to facilitate information-based quality improvements, which was clearly recognized by Finnish forest industry already in the early 1990s. The results indeed indicate that wood products markets are segmented with regard to quality demands

An SIMD machine for low-level vision

This paper presents an SIMD machine which has been tuned to execute low-level vision algorithms employing the relaxation labeling paradigm. Novel features of the design include: 1. (1) a communication scheme capable of window accessing under a single instruction. 2. (2) flexible I/O instructions to load overlapped data segments; and 3. (3) data-conditional instructions which can be nested to an arbitrary degree. A time analysis of the stereo correspondence problem, as implemented on a simulated version of the machine using the probabilistic relaxation technique, shows a speed up of almost N2 for an N × N array of PEs.