Software business expansion through distribution channel : Case M-Files - Denmark

The purpose of this study was to find out how a software company can successfully expand business to the Danish software market through distribution channel. The study was commissioned by a Finnish software company and it was conducted using a qualitative research method by analyzing external and internal business environment, and interviewing Danish ICT organizations and M-Files personnel. Interviews were semi-structured interviews, which were designed to collect comprehensive information on the existing ICT and software market in Denmark. The research used three external and internal analyzing frameworks; PEST analysis (market level), Porter´s Five Force analysis (industry level competition) and SWOT analysis (company level). Distribution channels theory was a base to understand why and what kind of distribution channels the case company uses, and what kind of channels target markets companies’ uses. Channel strategy and design were integrated to the industry level analysis. The empirical findings revealed that Denmark has very business friendly ICT environment. Several organizations have ranked Denmark´s information and communication technology as the best in the world. Denmark’s ICT and software market are relatively small, compared to many other countries in Europe. Danish software market is centralized. Largest software clusters are in the largest cities; Copenhagen, Aarhus, Odense and Aalborg. From these clusters, software companies can most likely find suitable resellers. The following growing trends are clearly seen in the software market: mobile and wireless applications, outsourcing, security solutions, cloud computing, social business solutions and e-business solutions. When expanding software business to the Danish market, it is important to take into account these trends. In Denmark distribution channels varies depending on the product or service. For many, a natural distribution channel is a local partner or internet. In the public sector solutions are purchased through a public procurement process. In the private sector the buying process is more straight forwarded. Danish companies are buying software from reliable suppliers. This means that they usually buy software direct from big software vendors or local partners. Some customers prefer to use professional consulting companies. These consulting companies can strongly influence on the selection of the supplier and products, and in this light, consulting companies can be important partners for software companies. Even though the competition is fierce in ECM and DMS solutions, Danish market offers opportunities for foreign companies. Penetration to the Danish market through reseller channel requires advanced solutions and objective selection criteria for channel partners. Based on the findings, Danish companies are interested in advanced and efficient software solutions. Interest towards M-Files solutions was clearly seen and the company has excellent opportunity to expand business to the Danish market through reseller channel. Since the research explored the Danish ICT and software market, the results of the study may offer valuable information also to the other software companies which are expanding their business to the Danish market.

CloudSimDisk: Energy-Aware Storage Simulation in CloudSim

Cloud Computing paradigm is continually evolving, and with it, the size and the complexity of its infrastructure. Assessing the performance of a Cloud environment is an essential but strenuous task. Modeling and simulation tools have proved their usefulness and powerfulness to deal with this issue. This master thesis work contributes to the development of the widely used cloud simulator CloudSim and proposes CloudSimDisk, a module for modeling and simulation of energy-aware storage in CloudSim. As a starting point, a review of Cloud simulators has been conducted and hard disk drive technology has been studied in detail. Furthermore, CloudSim has been identified as the most popular and sophisticated discrete event Cloud simulator. Thus, CloudSimDisk module has been developed as an extension of CloudSim v3.0.3. The source code has been published for the research community. The simulation results proved to be in accordance with the analytic models, and the scalability of the module has been presented for further development.

Healthcare Services In CloudComputing

The Thesis title” Healthcare services in cloud computing” discusses the healthcare services available in the new converging technology called cloud computing. This computing technology had craved its path in the desirable market field healthcare. Healthcare is an extensive and a massive mission of maintenance and providing a complete treatment to the person suffering from ailments. In the olden days well equipped healthcare surveillance is not accessible to all communities of people due to several reasons like, geographical locations, equipment cost, and infrastructure, and skilled medical practitioners, now due to the advancement of the medicine in cloud technology has reached some of its barriers making it more viable to all the people (communities) with all the robust technologies and techniques. This study will give an overview of the healthcare transformation of different approaches of cloud computing over information technology and its strategic usage. Further enhancing better healthcare to ensure scalable, compatible functions supporting the well-being, this study also considers the techniques of cloud computing and its application, advancement in healthcare.

Big Data Processing in the Cloud: a Hydra/Sufia Experience

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Use of scenario analysis in studying emerging technology – Case Grid computing

Tutkimuksen selvitettiin miten skenaarioanalyysia voidaan käyttää uuden teknologian tutkimisessa. Työssä havaittiin, että skenaarioanalyysin soveltuvuuteen vaikuttaa eniten teknologisen muutoksen taso ja saatavilla olevan tiedon luonne. Skenaariomenetelmä soveltuu hyvin uusien teknologioiden tutkimukseen erityisesti radikaalien innovaatioiden kohdalla. Syynä tähän on niihin liittyvä suuri epävarmuus, kompleksisuus ja vallitsevan paradigman muuttuminen, joiden takia useat muut tulevaisuuden tutkimuksen menetelmät eivät ole tilanteessa käyttökelpoisia. Työn empiirisessä osiossa tutkittiin hilaverkkoteknologian tulevaisuutta skenaarioanalyysin avulla. Hilaverkot nähtiin mahdollisena disruptiivisena teknologiana, joka radikaalina innovaationa saattaa muuttaa tietokonelaskennan nykyisestä tuotepohjaisesta laskentakapasiteetin ostamisesta palvelupohjaiseksi. Tällä olisi suuri vaikutus koko nykyiseen ICT-toimialaan erityisesti tarvelaskennan hyödyntämisen ansiosta. Tutkimus tarkasteli kehitystä vuoteen 2010 asti. Teorian ja olemassa olevan tiedon perusteella muodostettiin vahvaan asiantuntijatietouteen nojautuen neljä mahdollista ympäristöskenaariota hilaverkoille. Skenaarioista huomattiin, että teknologian kaupallinen menestys on vielä monen haasteen takana. Erityisesti luottamus ja lisäarvon synnyttäminen nousivat tärkeimmiksi hilaverkkojen tulevaisuutta ohjaaviksi tekijöiksi.

Computing the persistent homology of range images with alpha shapes

Laser scanning is becoming an increasingly popular method for measuring 3D objects in industrial design. Laser scanners produce a cloud of 3D points. For CAD software to be able to use such data, however, this point cloud needs to be turned into a vector format. A popular way to do this is to triangulate the assumed surface of the point cloud using alpha shapes. Alpha shapes start from the convex hull of the point cloud and gradually refine it towards the true surface of the object. Often it is nontrivial to decide when to stop this refinement. One criterion for this is to do so when the homology of the object stops changing. This is known as the persistent homology of the object. The goal of this thesis is to develop a way to compute the homology of a given point cloud when processed with alpha shapes, and to infer from it when the persistent homology has been achieved. Practically, the computation of such a characteristic of the target might be applied to power line tower span analysis.

Trigger and data link system for CMS Resistive Plate Chambers at the LHC accelerator

The purpose of the work was to realize a high-speed digital data transfer system for RPC muon chambers in the CMS experiment on CERN’s new LHC accelerator. This large scale system took many years and many stages of prototyping to develop, and required the participation of tens of people. The system interfaces to Frontend Boards (FEB) at the 200,000-channel detector and to the trigger and readout electronics in the control room of the experiment. The distance between these two is about 80 metres and the speed required for the optic links was pushing the limits of available technology when the project was started. Here, as in many other aspects of the design, it was assumed that the features of readily available commercial components would develop in the course of the design work, just as they did. By choosing a high speed it was possible to multiplex the data from some the chambers into the same fibres to reduce the number of links needed. Further reduction was achieved by employing zero suppression and data compression, and a total of only 660 optical links were needed. Another requirement, which conflicted somewhat with choosing the components a late as possible was that the design needed to be radiation tolerant to an ionizing dose of 100 Gy and to a have a moderate tolerance to Single Event Effects (SEEs). This required some radiation test campaigns, and eventually led to ASICs being chosen for some of the critical parts. The system was made to be as reconfigurable as possible. The reconfiguration needs to be done from a distance as the electronics is not accessible except for some short and rare service breaks once the accelerator starts running. Therefore reconfigurable logic is extensively used, and the firmware development for the FPGAs constituted a sizable part of the work. Some special techniques needed to be used there too, to achieve the required radiation tolerance. The system has been demonstrated to work in several laboratory and beam tests, and now we are waiting to see it in action when the LHC will start running in the autumn 2008.

Variational ensemble Kalman filtering applied to data assimilation problems in computational fluid dynamics

One challenge on data assimilation (DA) methods is how the error covariance for the model state is computed. Ensemble methods have been proposed for producing error covariance estimates, as error is propagated in time using the non-linear model. Variational methods, on the other hand, use the concepts of control theory, whereby the state estimate is optimized from both the background and the measurements. Numerical optimization schemes are applied which solve the problem of memory storage and huge matrix inversion needed by classical Kalman filter methods. Variational Ensemble Kalman filter (VEnKF), as a method inspired the Variational Kalman Filter (VKF), enjoys the benefits from both ensemble methods and variational methods. It avoids filter inbreeding problems which emerge when the ensemble spread underestimates the true error covariance. In VEnKF this is tackled by resampling the ensemble every time measurements are available. One advantage of VEnKF over VKF is that it needs neither tangent linear code nor adjoint code. In this thesis, VEnKF has been applied to a two-dimensional shallow water model simulating a dam-break experiment. The model is a public code with water height measurements recorded in seven stations along the 21:2 m long 1:4 m wide flume’s mid-line. Because the data were too sparse to assimilate the 30 171 model state vector, we chose to interpolate the data both in time and in space. The results of the assimilation were compared with that of a pure simulation. We have found that the results revealed by the VEnKF were more realistic, without numerical artifacts present in the pure simulation. Creating a wrapper code for a model and DA scheme might be challenging, especially when the two were designed independently or are poorly documented. In this thesis we have presented a non-intrusive approach of coupling the model and a DA scheme. An external program is used to send and receive information between the model and DA procedure using files. The advantage of this method is that the model code changes needed are minimal, only a few lines which facilitate input and output. Apart from being simple to coupling, the approach can be employed even if the two were written in different programming languages, because the communication is not through code. The non-intrusive approach is made to accommodate parallel computing by just telling the control program to wait until all the processes have ended before the DA procedure is invoked. It is worth mentioning the overhead increase caused by the approach, as at every assimilation cycle both the model and the DA procedure have to be initialized. Nonetheless, the method can be an ideal approach for a benchmark platform in testing DA methods. The non-intrusive VEnKF has been applied to a multi-purpose hydrodynamic model COHERENS to assimilate Total Suspended Matter (TSM) in lake Säkylän Pyhäjärvi. The lake has an area of 154 km2 with an average depth of 5:4 m. Turbidity and chlorophyll-a concentrations from MERIS satellite images for 7 days between May 16 and July 6 2009 were available. The effect of the organic matter has been computationally eliminated to obtain TSM data. Because of computational demands from both COHERENS and VEnKF, we have chosen to use 1 km grid resolution. The results of the VEnKF have been compared with the measurements recorded at an automatic station located at the North-Western part of the lake. However, due to TSM data sparsity in both time and space, it could not be well matched. The use of multiple automatic stations with real time data is important to elude the time sparsity problem. With DA, this will help in better understanding the environmental hazard variables for instance. We have found that using a very high ensemble size does not necessarily improve the results, because there is a limit whereby additional ensemble members add very little to the performance. Successful implementation of the non-intrusive VEnKF and the ensemble size limit for performance leads to an emerging area of Reduced Order Modeling (ROM). To save computational resources, running full-blown model in ROM is avoided. When the ROM is applied with the non-intrusive DA approach, it might result in a cheaper algorithm that will relax computation challenges existing in the field of modelling and DA.