158 resultados para Smart Vending Machine, Automation, Programmable Logic Controllers, Creativity, Innovation
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The main strengths of professional knowledge-intensive business services (P-KIBS) are knowledge and creativity which needs to be fostered, maintained and supported. The process of managing P-KIBS companies deals with financial, operational and strategic risks. That is why it is reasonable to apply risk management techniques and frameworks in this context. A significant challenge hides in choosing reasonable ways of implementing risk management, which will not limit creative ability in organization, and furthermore will contribute to the process. This choice is related to a risk intelligent approach which becomes a justified way of finding the required balance. On a theoretical level the field of managing both creativity and risk intelligence as a balanced process remains understudied in particular within KIBS industry. For instance, there appears to be a wide range of separate models for innovation and risk management, but very little discussion in terms of trying to find the right balance between them. This study aims to shed light on the importance of well-managed combination of these concepts. The research purpose of the present study is to find out how the balance between creativity and risk intelligence can be managed in P-KIBS. The methodological approach utilized in the study is strictly conceptual without empirical aspects. The research purpose can be achieved through answering the following research supporting questions: 1. What are the characteristics and role of creativity as a component of innovation process in a P-KIBS company? 2. What are the characteristics and role of risk intelligence as an approach towards risk management process implementation in a P-KIBS company? 3. How can risk intelligence and creativity be balanced in P-KIBS? The main theoretical contribution of the study conceals in a proposed creativity and risk intelligence stage process framework. It is designed as an algorithm that can be applied on organizational canvas. It consists of several distinct stages specified by actors involved, their roles and implications. Additional stage-wise description provides detailed tasks for each of the enterprise levels, while combining strategies into one. The insights driven from the framework can be utilized by a vast range of specialists from strategists to risk managers, and from innovation managers to entrepreneurs. Any business that is designing and delivering knowledge service can potentially gain valuable thoughts and expand conceptual understanding from the present report. Risk intelligence in the current study is a unique way of emphasizing the role of creativity in professional knowledge-intensive industry and a worthy technique for making profound decisions towards risks.
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The aim of this research was to develop a framework to analyze how physical environment influences scientific creativity. Due to the relative novelty of this topic, there is still a gap in the unified method to study connection between physical environment and creativity. Therefore, in order to study this issue deeply, the qualitative method was used (interviews and qualitative questionnaire). Scientists (PhD students and senior researchers) of Graduate School of Management were interviewed to build the model and one expert interview was conducted to assess its validity. The model highlights several dimensions via which physical environment can influence scientific creativity: Comfort, Instruments and Diversity. Comfort and Instruments are considered to be related mostly to productivity, an initial requirement for creativity, while Diversity is the factor responsible for supporting all the stages of scientific creative process. Thus, creative physical environment is not one place by its nature, but an aggregative phenomenon. Due to two levels of analysis, the model is named the two-level model of creative physical environment.
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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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Biomedical natural language processing (BioNLP) is a subfield of natural language processing, an area of computational linguistics concerned with developing programs that work with natural language: written texts and speech. Biomedical relation extraction concerns the detection of semantic relations such as protein-protein interactions (PPI) from scientific texts. The aim is to enhance information retrieval by detecting relations between concepts, not just individual concepts as with a keyword search. In recent years, events have been proposed as a more detailed alternative for simple pairwise PPI relations. Events provide a systematic, structural representation for annotating the content of natural language texts. Events are characterized by annotated trigger words, directed and typed arguments and the ability to nest other events. For example, the sentence “Protein A causes protein B to bind protein C” can be annotated with the nested event structure CAUSE(A, BIND(B, C)). Converted to such formal representations, the information of natural language texts can be used by computational applications. Biomedical event annotations were introduced by the BioInfer and GENIA corpora, and event extraction was popularized by the BioNLP'09 Shared Task on Event Extraction. In this thesis we present a method for automated event extraction, implemented as the Turku Event Extraction System (TEES). A unified graph format is defined for representing event annotations and the problem of extracting complex event structures is decomposed into a number of independent classification tasks. These classification tasks are solved using SVM and RLS classifiers, utilizing rich feature representations built from full dependency parsing. Building on earlier work on pairwise relation extraction and using a generalized graph representation, the resulting TEES system is capable of detecting binary relations as well as complex event structures. We show that this event extraction system has good performance, reaching the first place in the BioNLP'09 Shared Task on Event Extraction. Subsequently, TEES has achieved several first ranks in the BioNLP'11 and BioNLP'13 Shared Tasks, as well as shown competitive performance in the binary relation Drug-Drug Interaction Extraction 2011 and 2013 shared tasks. The Turku Event Extraction System is published as a freely available open-source project, documenting the research in detail as well as making the method available for practical applications. In particular, in this thesis we describe the application of the event extraction method to PubMed-scale text mining, showing how the developed approach not only shows good performance, but is generalizable and applicable to large-scale real-world text mining projects. Finally, we discuss related literature, summarize the contributions of the work and present some thoughts on future directions for biomedical event extraction. This thesis includes and builds on six original research publications. The first of these introduces the analysis of dependency parses that leads to development of TEES. The entries in the three BioNLP Shared Tasks, as well as in the DDIExtraction 2011 task are covered in four publications, and the sixth one demonstrates the application of the system to PubMed-scale text mining.
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One of the main challenges in Software Engineering is to cope with the transition from an industry based on software as a product to software as a service. The field of Software Engineering should provide the necessary methods and tools to develop and deploy new cost-efficient and scalable digital services. In this thesis, we focus on deployment platforms to ensure cost-efficient scalability of multi-tier web applications and on-demand video transcoding service for different types of load conditions. Infrastructure as a Service (IaaS) clouds provide Virtual Machines (VMs) under the pay-per-use business model. Dynamically provisioning VMs on demand allows service providers to cope with fluctuations on the number of service users. However, VM provisioning must be done carefully, because over-provisioning results in an increased operational cost, while underprovisioning leads to a subpar service. Therefore, our main focus in this thesis is on cost-efficient VM provisioning for multi-tier web applications and on-demand video transcoding. Moreover, to prevent provisioned VMs from becoming overloaded, we augment VM provisioning with an admission control mechanism. Similarly, to ensure efficient use of provisioned VMs, web applications on the under-utilized VMs are consolidated periodically. Thus, the main problem that we address is cost-efficient VM provisioning augmented with server consolidation and admission control on the provisioned VMs. We seek solutions for two types of applications: multi-tier web applications that follow the request-response paradigm and on-demand video transcoding that is based on video streams with soft realtime constraints. Our first contribution is a cost-efficient VM provisioning approach for multi-tier web applications. The proposed approach comprises two subapproaches: a reactive VM provisioning approach called ARVUE and a hybrid reactive-proactive VM provisioning approach called Cost-efficient Resource Allocation for Multiple web applications with Proactive scaling. Our second contribution is a prediction-based VM provisioning approach for on-demand video transcoding in the cloud. Moreover, to prevent virtualized servers from becoming overloaded, the proposed VM provisioning approaches are augmented with admission control approaches. Therefore, our third contribution is a session-based admission control approach for multi-tier web applications called adaptive Admission Control for Virtualized Application Servers. Similarly, the fourth contribution in this thesis is a stream-based admission control and scheduling approach for on-demand video transcoding called Stream-Based Admission Control and Scheduling. Our fifth contribution is a computation and storage trade-o strategy for cost-efficient video transcoding in cloud computing. Finally, the sixth and the last contribution is a web application consolidation approach, which uses Ant Colony System to minimize the under-utilization of the virtualized application servers.
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This study examines information security as a process (information securing) in terms of what it does, especially beyond its obvious role of protector. It investigates concepts related to ‘ontology of becoming’, and examines what it is that information securing produces. The research is theory driven and draws upon three fields: sociology (especially actor-network theory), philosophy (especially Gilles Deleuze and Félix Guattari’s concept of ‘machine’, ‘territory’ and ‘becoming’, and Michel Serres’s concept of ‘parasite’), and information systems science (the subject of information security). Social engineering (used here in the sense of breaking into systems through non-technical means) and software cracker groups (groups which remove copy protection systems from software) are analysed as examples of breaches of information security. Firstly, the study finds that information securing is always interruptive: every entity (regardless of whether or not it is malicious) that becomes connected to information security is interrupted. Furthermore, every entity changes, becomes different, as it makes a connection with information security (ontology of becoming). Moreover, information security organizes entities into different territories. However, the territories – the insides and outsides of information systems – are ontologically similar; the only difference is in the order of the territories, not in the ontological status of entities that inhabit the territories. In other words, malicious software is ontologically similar to benign software; they both are users in terms of a system. The difference is based on the order of the system and users: who uses the system and what the system is used for. Secondly, the research shows that information security is always external (in the terms of this study it is a ‘parasite’) to the information system that it protects. Information securing creates and maintains order while simultaneously disrupting the existing order of the system that it protects. For example, in terms of software itself, the implementation of a copy protection system is an entirely external addition. In fact, this parasitic addition makes software different. Thus, information security disrupts that which it is supposed to defend from disruption. Finally, it is asserted that, in its interruption, information security is a connector that creates passages; it connects users to systems while also creating its own threats. For example, copy protection systems invite crackers and information security policies entice social engineers to use and exploit information security techniques in a novel manner.
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This master’s thesis was done for a small company, Vipetec Oy, which offers specialized technological services for companies mainly in forest industry. The study was initiated partly because the company wants to expand its customer base to a new industry. There were two goals connected to each other. First was to find out how much and what kind of value current customers have realized from ATA Process Event Library, one of the products that the company offers. Second was to determine the best way to present this value and its implications for future value potential to both current and potential customers. ATA helps to make grade and product changes, starting after machine downtime, and recovery from production break faster for customers. All three events sometimes occur in production line. The faster operation results to savings in time and material. In addition to ATA Vipetec also offers other services related to development of automation and optimization of controls. Theoretical part concentrates on the concept of value, how it can be delivered to customers, and what kind of risk customer faces in industrial purchasing. Also the function of reference marketing towards customers is discussed. In the empirical part the realized value for existing customers is evaluated based on both numerical data and interviews. There’s also a brief case study about one customer. After that the value-based reference marketing for a target industry is examined through interviews of these potential customers. Finally answers to the research questions are stated and compared also to the theoretical knowledge about the subject. Results show that those customers’ machines which use the full service concept of ATA usually are able to save more time and material than the machines which use only some features of the product. Interviews indicated that sales arguments which focus on improved competitive status are not as effective as current arguments which focus on numerical improvements. In the case of potential customers in the new industry, current sales arguments likely work best for those whose irregular production situations are caused mainly by fault situations. When the actions of Vipetec were compared to ten key elements of creating customer references, it was seen that many of them the company has either already included in its strategy or has good chances to include them with the help of the results of this study.
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This study applied qualitative case study method for solving what kind of benefits salespeople and their customers perceived to gain when sales reps used a specific sales force automation tool, that defined the values and identified segment that best fit to each customer. The data consisting of four interviews was collected using semi-structured individual method and analyzed with thematic analysis technique. The analysis revealed five salespeople perceived benefits and four customer perceived benefits. Salespeople perceived benefits were improvements in customer knowledge, guidance of sales operations, salesperson-customer relationship building, time management and growing performance. Customer perceived benefits were information transmission, improved customer service, customer-salesperson relationship building and development of operations, which of the last was found as a new previously unrecognized customer benefit.
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Työssä tarkasteltiin älykkäiden sähköverkkojen näkökulmasta, millaisia toiminnallisuuksia kiinteistöautomaatiojärjestelmiltä odotetaan ja miten markkinoilla olevat järjestelmät vastaavat näihin odotuksiin. Lisäksi arvioitiin, kuinka taloudellisesti kannattavia valittuihin automaatiojärjestelmiin kuuluvat energian käytön hallintaan liittyvät toiminnallisuudet ovat sähkönkäyttäjien näkökulmasta. Lopuksi tehtiin lyhyt katsaus kiinteistöautomaatiojärjestelmien tulevaisuuden näkymiin. Kiinteistöautomaatiolla voidaan vaikuttaa energian käytön tehokkuuteen ohjaamalla esimerkiksi valaistusta, ilmanvaihtoa, ilmastointia, lämmitystä ja sähkölaitteita. Eräs vaihtoehto on toteuttaa ohjauksen avulla markkinapohjaista kysyntäjoustoa, jossa kiinteistön sähköjärjestelmän toimintaa säädetään sähkön hinnan perusteella. Kiinteistössä tulee myös voida tehdä laitekohtaisia energiankulutuksen mittauksia, jotka antavat tietoa sähkönkäyttäjille eri laitteiden sähkönkulutuksesta. Kiinteistöautomaation ja sähkön pientuotannon yleistymisen myötä on myös etähallittavien virtuaalivoimaloiden toteuttaminen tulossa mahdolliseksi. Lisäksi laskettiin sähkönkäyttäjän kannalta lämmityksen, valaistuksen ja ilmanvaihdon ohjauksen kannattavuutta ja selvitettiin, että tutkituissa esimerkkijärjestelmissä suurin säästöpotentiaali on lämmityksen ohjauksessa.
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The aim of this master’s thesis is to research and analyze how purchase invoice processing can be automated and streamlined in a system renewal project. The impacts of workflow automation on invoice handling are studied by means of time, cost and quality aspects. Purchase invoice processing has a lot of potential for automation because of its labor-intensive and repetitive nature. As a case study combining both qualitative and quantitative methods, the topic is approached from a business process management point of view. The current process was first explored through interviews and workshop meetings to create a holistic understanding of the process at hand. Requirements for process streamlining were then researched focusing on specified vendors and their purchase invoices, which helped to identify the critical factors for successful invoice automation. To optimize the flow from invoice receipt to approval for payment, the invoice receiving process was outsourced and the automation functionalities of the new system utilized in invoice handling. The quality of invoice data and the need of simple structured purchase order (PO) invoices were emphasized in the system testing phase. Hence, consolidated invoices containing references to multiple PO or blanket release numbers should be simplified in order to use automated PO matching. With non-PO invoices, it is important to receive the buyer reference details in an applicable invoice data field so that automation rules could be created to route invoices to a review and approval flow. In the beginning of the project, invoice processing was seen ineffective both time- and cost-wise, and it required a lot of manual labor to carry out all tasks. In accordance with testing results, it was estimated that over half of the invoices could be automated within a year after system implementation. Processing times could be reduced remarkably, which would then result savings up to 40 % in annual processing costs. Due to several advancements in the purchase invoice process, business process quality could also be perceived as improved.
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Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.
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Electrical machines have significant improvement potential. Nevertheless, the field is characterized by incremental innovations. Admittedly, steady improvement has been achieved, but no breakthrough development. Radical development in the field would require the introduction of new elements, such that may change the whole electrical machine industry system. Recent technological advancements in nanomaterials have opened up new horizons for the macroscopic application of carbon nanotube (CNT) fibres. With values of 100 MS/m measured on individual CNTs, CNT fibre materials hold promise for conductivities far beyond those of metals. Highly conductive, lightweight and strong CNT yarn is finally within reach; it could replace copper as a potentially better winding material. Although not yet providing low resistivity, the newest CNT yarn offers attractive perspectives for accelerated efficiency improvement of electrical machines. In this article, the potential for using new CNT materials to replace copper in machine windings is introduced. It does so, firstly, by describing the environment for a change that could revolutionize the industry and, secondly, by presenting the breakthrough results of a prototype construction. In the test motor, which is to our knowledge the first in its kind, the presently most electrically conductive carbon nanotube yarn replaces usual copper in the windings.
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A direct-driven permanent magnet synchronous machine for a small urban use electric vehicle is presented. The measured performance of the machine at the test bench as well as the performance over the modified New European Drive Cycle will be given. The effect of optimal current components, maximizing the efficiency and taking into account the iron loss, is compared with the simple id=0 – control. The machine currents and losses during the drive cycle are calculated and compared with each other.
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Efficient production and consumption of energy has become the top priority of national and international policies around the world. Manufacturing industries have to address the requirements of the government in relation to energy saving and ecologically sustainable products. These industries are also concerned with energy and material usage due to their rising costs. Therefore industries have to find solutions that can support environmental preservation yet maintain competitiveness in the market. Welding, a major manufacturing process, consumes a great deal of material and energy. It is a crucial process in improving a product’s life-cycle cost, strength, quality and reliability. Factors which lead to weld related inefficiencies have to be effectively managed, if industries are to meet their quality requirements and fulfil a high-volume production demand. Therefore it is important to consider some practical strategies in welding process for optimization of energy and material consumption. The main objective of this thesis is to explore the methods of minimizing the ecological footprint of the welding process and methods to effectively manage its material and energy usage in the welding process. The author has performed a critical review of the factors including improved weld power source efficiency, efficient weld techniques, newly developed weld materials, intelligent welding systems, weld safety measures and personnel training. The study lends strong support to the fact that the use of eco-friendly welding units and the quality weld joints obtained with minimum possible consumption of energy and materials should be the main directions of improvement in welding systems. The study concludes that, gradually implementing the practical strategies mentioned in this thesis would help the manufacturing industries to achieve on the following - reduced power consumption, enhanced power control and manipulation, increased deposition rate, reduced cycle time, reduced joint preparation time, reduced heat affected zones, reduced repair rates, improved joint properties, reduced post-weld operations, improved automation, improved sensing and control, avoiding hazardous conditions and reduced exposure of welder to potential hazards. These improvement can help in promotion of welding as a green manufacturing process.
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The problem of automatic recognition of the fish from the video sequences is discussed in this Master’s Thesis. This is a very urgent issue for many organizations engaged in fish farming in Finland and Russia because the process of automation control and counting of individual species is turning point in the industry. The difficulties and the specific features of the problem have been identified in order to find a solution and propose some recommendations for the components of the automated fish recognition system. Methods such as background subtraction, Kalman filtering and Viola-Jones method were implemented during this work for detection, tracking and estimation of fish parameters. Both the results of the experiments and the choice of the appropriate methods strongly depend on the quality and the type of a video which is used as an input data. Practical experiments have demonstrated that not all methods can produce good results for real data, whereas on synthetic data they operate satisfactorily.