The Digital Transformation of the News Media Business – Paid Content and Entrepreneurship in Digital Journalism

The digital transformation of the news business continues to agitate publishers. Concerned about declining sales in the print segment, legacy outlets, local news companies and freelance journalists alike search for ways to monetize digital journalism properly. At first glance, digital journalism and its monetisation as paid content seem a promising effort. The digitisation of the news business enabled distribution at a marginal cost of almost zero while giving journalists access to new research technologies and lowering the cost of entry for smaller companies. However, while digital journalism enjoys broad popularity and use, online news are gaining few paying customers. Furthermore, online news compete within a larger digital media complex, comprising movies, games, and social media. After 25 years of experimentation, the digital future of journalism is still heavily debated in media management. Concerning the reconstitution as a digital medium, this research examines conditions of success and obstacles for the digital news media business to be successful as a business venture. Therefore, the research question reads What factors enable the viability and entrepreneurial success of the news media business in light of the consequences of digital transformation? The overarching research question is considered from two angles: The first angle concerns the demand side by looking at the antecedents of the audience's willingness to pay for paid content. The second angle focuses on the supply side and therefore examines antecedents of success in the context of digital journalistic start-ups and founders. In four studies, this thesis develops an analysis of the online news business with a local focus on the German news market. For this purpose, a variety of methods ranging from qualitative work and literature review to empirical research employing path analysis and predictive analytics are applied. Theoretically, digital transformation, free mentality and other peculiarities of information goods inform the frame of this work. Thus, this research aims at contributing to a financially sustainable news media business

3D scanning with a Kinect depth sensor

Real-life objects can be transferred to the virtual 3D world with 3D scanning techniques. Scanning can be performed either with a stationary camera while rotating the object or by moving the camera around the scanned object. This work investigates how a two-dimensional depth image of a depth sensor can be transformed into a three-dimensional point cloud and what filtering methods can be used to separate an object from its background. Point clouds taken from different directions are combined, and the quality of the obtained point clouds is studied. Microsoft Kinect V2 depth sensor was used to take depth images. The device calculates the distance to the destination by measuring the flight time of the infrared pulse it emits. Color information for the image was available, but this work focused only on using distance information. The device was used to scan objects from several different viewpoints. Background points were gradually filtered out of each image until only the scanned object point cloud remained. Each image taken from a different angle is initially in its own coordinate system. Point clouds are aligned and connected to the same global coordinate system. Alignment is performed using an iterative closest point (ICP) algorithm. The quality of the resulting point clouds for small objects is not good. The overall shapes of the resulting point cloud is correct, but the more accurate surface shapes disappear in the error noise. With a larger object, the error noise did not have as much effect on the result as the surface area was larger. This results a decent quality point cloud. A good scan result requires special features of the object and the environment. For example, reflective surfaces cause incorrect locations for points. These types of surfaces should be avoided or considered when handling data. Important point information may be lost in filtering, and errors may accumulate when points are combined using the ICP algorithm. The methods used are well suited for use if the goal is to obtain only a rough model of the described object.Tosielämän esineitä voidaan siirtää virtuaaliseen 3D-maailmaan 3D-skannaustekniikoilla. Skannaus voidaan suorittaa joko paikallaan olevalla kameralla kohdetta pyörittämällä tai liikuttamalla kameraa skannattavan kohteen ympärillä. Tässä työssä tutkitaan, kuinka syvyyssensorin kaksiulotteinen syvyyskuva voidaan muuntaa kolmiulotteiseksi pistepilveksi ja millä suodatusmenetelmillä kohde voidaan erottaa taustastaan. Eri suunnista otettuja pistepilviä yhdistetään ja saatujen pistepilvien laatua tutkitaan. Microsoft Kinect V2 -syvyysanturia käytettiin syvyyskuvien ottamiseen. Laite laskee etäisyyden kohteeseen mittaamalla lähettämänsä infrapunapulssin lentoajan keston. Kuvan väritiedot olivat saatavilla, mutta tässä työssä keskityttiin vain etäisyystietojen käyttöön. Laitteen avulla esineitä skannattiin useista eri näkökulmista. Taustapisteitä suodatettiin vähitellen pois jokaisesta kuvasta, kunnes jäljelle jäi vain skannatun esineen pistepilvi. Jokainen eri kulmasta otettu kuva on aluksi omassa koordinaatistossaan. Pistepilvet kohdistetaan ja yhdistetään samaan globaaliin koordinaattijärjestelmään. Kohdistus suoritetaan käyttämällä iteratiivista lähimmän pisteen algoritmia, ICP:tä (engl. iterative closest point). Tuloksena saatujen pistepilvien laatu pienille kohteille ei ole hyvä. Pistepilvien ulkomuodot ovat oikeat, mutta tarkemmat pinnanmuodot katoavat virhekohinassa. Suuremmalla kuvattavalla kohteella virhekohinalla ei ollut kovin suurta vaikutusta tulokseen, kun kohteen pinta-ala oli suurempi. Tämä tuottaa melko hyvänlaatuisen pistepilven. Hyvä skannaustulos vaatii kohteen ja ympäristön erityispiirteitä. Esimerkiksi heijastavat pinnat aiheuttavat virheellisiä sijainteja pisteille. Tämäntyyppisiä pintoja tulee välttää tai ottaa huomioon datan käsittelyssä. Tärkeät pistetiedot voivat kadota suodatuksessa ja virheitä voi kertyä, kun pisteitä yhdistetään ICP-algoritmilla. Käytetyt menetelmät sopivat hyvin käyttötarkoitukseen, jos tavoitteena on saada vain karkea malli kuvatusta kohteesta

Interpolation and extrapolation methods for WLAN-based positioning

WLAN-based positioning is obtaining more and more attention in the research field no-wadays. In order to create better Location Based Services (LBSs), the demand to achieve higher user location accuracy is increasing. This thesis aims at studying the ef-fect of different interpolation and extrapolation methods in the WLAN-based indoor positioning, based on collected WLAN data. Depending on the embraced positioning method, there are various errors in WLAN-based positioning, such as calibration error, measurement errors, shadowing, etc. The motivation of this work came from trying to decrease the positioning error in the ab-sence of complete information about the indoor environment. This can be done by using interpolation and extrapolation methods, which are widely used in image processing nowadays. However, they are also an available and efficient way to deal with WLAN-based positioning studies. Among interpolation methods, Delaunay triangulation can partly avoid introducing dis-tortions in the measurement databases. Therefore, it makes sense to investigate triangula-tion based methods and to study their usefulness in the WLAN context. Practically, it is very hard to extrapolate appropriately and the implementation of the extrapolation is much more complex than the one of the interpolation. Thus in this thesis, simple extrapo-lation methods have been performed. The results here are based on measurement data. The performance of each method is analyzed in terms of the error between the received signal strengths (RSS) coming from the measurements and the RSS obtained through interpolation and extrapolation. WLAN data was collected from several buildings of Tampere University of Technology. Results show that extrapolation methods may increase the RSS estimation error some-times because it is very hard to predict the outside range. However, with more accurate extrapolation, the error would decrease. The performances of natural neighbor, linear and cubic interpolation are similar. The highest impact on RSS estimation comes from the extrapolation

Impact of Industrial Internet related tecnologies to the business and business models

Industrial Internet is one of the most talking topics in the recent years in both practical implications and literature reviews being a new paradigm for almost all industry sectors. It has been defined as the next industrial revolution since it opens a new and wide range of possibilities to the actual industry. This is possi-ble through the latest advancements and trends of some key technologies such as sensors, actuators, RFID, communication technologies, cloud computing and big data analytics. Industrial Internet is supposed to revolutionize the business and the business models through new valuable information that was not availa-ble before due to the new huge amounts of accurate data that can be collected out of the machines, devices, processes and products. This thesis aims to develop a better understanding of the impact of the major Industrial Internet technologies to the business and business models of mid-sized production line manufacturers. The current study started with a literature review, investigating the Industrial Internet concept and background as well as some other basic related concepts such as IoT, Industry 4.0, CPS and Smart Manufacturing. The differences between them were established and the oppor-tunities and risks related to Industrial Internet among the literature were identi-fied. The key Industrial Internet technologies were reviewed and categorized, and the basic functionalities, capabilities and optimization levels were defined. Finally, the BM literature was also reviewed and the Business Model Canvas framework was selected in order to carry out the last part of the interviews re-lated to the impact of data and information to the business model components. Data was collected through semi-structured interviews with three mid-sized pro-duction line manufacturers’ representatives. The interview structure was divided into three parts: risks and opportunities perception, perceived impact to the business model components and role of the data and information in the busi-ness and industry. The results showed that Industrial Internet is perceived to have a big impact in the business and business model components and also that the opportunities of it, seem to be clearer that the risks which can be translated into the willingness of the companies to adopt Industrial Internet and to start offering innovative business models

Utilizing the Environmental Advantages in the Sales Process

Global warming and environmental changes are compelling private sector businesses to transition towards more environmentally friendly processes. The drive for this shift comes from global agreements, governmental regulations, and evolving customer preferences. Companies striving for improved environmental practices are discovering a novel source of competitive advantage. Although the relationship between a company's environmental performance and financial success has been explored from various angles in academic literature, research combining environmental performance with sales success remains scarce. This research seeks to bridge the gap in academic understanding by examining how companies can leverage the environmental benefits of their offerings within their sales processes. To guide this investigation, the following research questions have been formulated: 1) What environmental benefits do customers desire from their suppliers? 2) How can sales teams leverage the environmental benefits of products to their advantage 3) During which stages of the sales funnel can environmental offerings be effectively utilized? The study commences with a literature analysis of modern B2B sales processes, the dimensions of environmental sustainability, and the environmentally friendly practices adopted within companies' supply chain management. A framework for integrating environmental sustainability into sales processes is developed. The empirical segment of the study involves qualitative interviews with seven sales professionals. The findings underscore how environmental concerns have gained prominence in companies' purchasing decisions, yet these considerations are seldom the foremost determining factor for manufacturing firms. While companies have long focused on factors with a positive environmental impact, such as energy and water usage reduction, these efforts have been primarily driven by potential cost savings. However, there is a growing emphasis on highlighting the favourable environmental impacts of these initiatives. Environmental projects and processes are now employed in stakeholder communications and marketing materials, presenting new avenues for sales teams to differentiate their offerings. For manufacturing companies, the three most critical environmental dimensions are energy usage, water usage, and circular economy practices. The priority of these dimensions varies across industries and company levels. Sectors with the highest environmental focus are often related to renewable energy sources, such as biofuel manufacturers. The most promising markets for capitalizing on a product's environmental benefits are typically found in developed countries, particularly within the EU, due to the stringent environmental targets and regulations in these regions. Leveraging a product's environmental benefits enables companies to establish a competitive edge over rivals. This advantage is particularly manifested through enhanced brand image and company reputation, driving additional sales. The study also identifies increased customer loyalty and a more adept response to customer needs as positive outcomes contributing to sales success. The integration of environmental benefits into sales processes divides the sales journey into three phases: pre-sales, sales, and after-sales processes. The pre-sales phase involves collecting information about customers' environmental objectives, levels of commitment, and focus areas, thereby initiating the process of identifying customer-specific benefits. During the sales process, customer-specific benefits are pinpointed, and communication efforts to convey these benefits are launched. In the after-sales process, customer communication is concluded, and supplementary offerings can be proposed

A New Approach to Automatic Saliency Identification in Images Based on Irregularity of Regions

This research introduces an image retrieval system which is, in different ways, inspired by the human vision system. The main problems with existing machine vision systems and image understanding are studied and identified, in order to design a system that relies on human image understanding. The main improvement of the developed system is that it uses the human attention principles in the process of image contents identification. Human attention shall be represented by saliency extraction algorithms, which extract the salient regions or in other words, the regions of interest. This work presents a new approach for the saliency identification which relies on the irregularity of the region. Irregularity is clearly defined and measuring tools developed. These measures are derived from the formality and variation of the region with respect to the surrounding regions. Both local and global saliency have been studied and appropriate algorithms were developed based on the local and global irregularity defined in this work. The need for suitable automatic clustering techniques motivate us to study the available clustering techniques and to development of a technique that is suitable for salient points clustering. Based on the fact that humans usually look at the surrounding region of the gaze point, an agglomerative clustering technique is developed utilising the principles of blobs extraction and intersection. Automatic thresholding was needed in different stages of the system development. Therefore, a Fuzzy thresholding technique was developed. Evaluation methods of saliency region extraction have been studied and analysed; subsequently we have developed evaluation techniques based on the extracted regions (or points) and compared them with the ground truth data. The proposed algorithms were tested against standard datasets and compared with the existing state-of-the-art algorithms. Both quantitative and qualitative benchmarking are presented in this thesis and a detailed discussion for the results has been included. The benchmarking showed promising results in different algorithms. The developed algorithms have been utilised in designing an integrated saliency-based image retrieval system which uses the salient regions to give a description for the scene. The system auto-labels the objects in the image by identifying the salient objects and gives labels based on the knowledge database contents. In addition, the system identifies the unimportant part of the image (background) to give a full description for the scene

The Inter-cloud meta-scheduling

Inter-cloud is a recently emerging approach that expands cloud elasticity. By facilitating an adaptable setting, it purposes at the realization of a scalable resource provisioning that enables a diversity of cloud user requirements to be handled efficiently. This study’s contribution is in the inter-cloud performance optimization of job executions using metascheduling concepts. This includes the development of the inter-cloud meta-scheduling (ICMS) framework, the ICMS optimal schemes and the SimIC toolkit. The ICMS model is an architectural strategy for managing and scheduling user services in virtualized dynamically inter-linked clouds. This is achieved by the development of a model that includes a set of algorithms, namely the Service-Request, Service-Distribution, Service-Availability and Service-Allocation algorithms. These along with resource management optimal schemes offer the novel functionalities of the ICMS where the message exchanging implements the job distributions method, the VM deployment offers the VM management features and the local resource management system details the management of the local cloud schedulers. The generated system offers great flexibility by facilitating a lightweight resource management methodology while at the same time handling the heterogeneity of different clouds through advanced service level agreement coordination. Experimental results are productive as the proposed ICMS model achieves enhancement of the performance of service distribution for a variety of criteria such as service execution times, makespan, turnaround times, utilization levels and energy consumption rates for various inter-cloud entities, e.g. users, hosts and VMs. For example, ICMS optimizes the performance of a non-meta-brokering inter-cloud by 3%, while ICMS with full optimal schemes achieves 9% optimization for the same configurations. The whole experimental platform is implemented into the inter-cloud Simulation toolkit (SimIC) developed by the author, which is a discrete event simulation framework

Electronic Smart Canes for Visually Impaired People

Στα πλαίσια αυτής της εργασίας, έγινε μια εκτενής ανασκόπηση με τις σημαντικότερες και πιο πρόσφατες τεχνολογίες «έξυπνων» μπαστουνιών για τυφλούς και άτομα με απώλεια όρασης. Σε αυτή την ανασκόπηση περιλαμβάνονται τα πιο πρόσφατα ερευνητικά αποτελέσματα της διεθνούς επιστημονικής βιβλιογραφίας, σχετικές πατέντες αλλά και τα εμπορικά διαθέσιμα προϊόντα. Για κάθε μία από αυτές τις συσκευές περιγράφεται περιληπτικά η αρχή λειτουργίας της που συνοδεύεται από το πρωτότυπο του συστήματος. Στη συνέχεια, οι συσκευές ταξινομούνται σύμφωνα με τις τεχνολογίες που χρησιμοποιούν και τα βασικά χαρακτηριστικά τους, ενώ παρουσιάζονται επιπλέον πληροφορίες σχετικά με τις ερευνητικές δοκιμασίες με χρήστες που διεξήχθησαν και τα αποτελέσματά τους. Το συμπέρασμα που προκύπτει είναι ότι πολλά από τα συστήματα υποβοήθησης των τυφλών προσφέρουν περιορισμένες δυνατότητες και άλλα μπορούν να επιτύχουν εν μέρει την απαιτούμενη ακρίβεια. Κανένα, όμως, από αυτά δεν πληροί όλα τα απαραίτητα και θεμελιώδη χαρακτηριστικά που θα καθιστούσαν κάποια συσκευή ιδανική ως προς τη χρήση της. Αυτή η εργασία, λοιπόν, φανερώνει την πρόοδο της τεχνολογίας σε αυτό το επιστημονικό πεδίο, το πού βρίσκεται σήμερα και πού οδεύει με την εξέλιξή της και τονίζει, εμμέσως, την ανάγκη σχεδίασης συσκευών που εξασφαλίζουν πλήρως την ασφάλεια και την ανεξαρτησία των τυφλών και των ατόμων με απώλεια όρασης.In the context of this work, an extensive review was carried out with the most important and latest technologies of smart sticks for blind and visually impaired people. This review includes the most recent research results of international scientific literature, relevant patents and commercially available products. For each of these devices, the operating principle is briefly described and it is accompanied by the prototype of the system. The devices are then sorted according to the technologies they use and their basic features, while additional information is provided on the user research trials and their results. The resulting conclusion is that many of the blind aid systems offer limited capabilities, and others can achieve the required precision in part. None of these, however, fulfills all the essential and fundamental features that would make a device ideal for its use. This work, therefore, reveals the advancement of technology in this scientific field, where it is today and where it is progressing with its development, and indirectly emphasizes the need for designing devices that fully guarantee the safety and independence of the blind and visually impaired people

Mobile Health Technologies

Mobile Health Technologies, also known as mHealth technologies, have emerged, amongst healthcare providers, as the ultimate Technologies-of-Choice for the 21st century in delivering not only transformative change in healthcare delivery, but also critical health information to different communities of practice in integrated healthcare information systems. mHealth technologies nurture seamless platforms and pragmatic tools for managing pertinent health information across the continuum of different healthcare providers. mHealth technologies commonly utilize mobile medical devices, monitoring and wireless devices, and/or telemedicine in healthcare delivery and health research. Today, mHealth technologies provide opportunities to record and monitor conditions of patients with chronic diseases such as asthma, Chronic Obstructive Pulmonary Diseases (COPD) and diabetes mellitus. The intent of this book is to enlighten readers about the theories and applications of mHealth technologies in the healthcare domain