Yhteisö-tv palvelukonseptina, case: Finnish Satellite Television Oy

Menestyäkseen nykymaailmassa ihmiset ovat turvautuneet toisiinsa muodostaen samallaerilaisia yhteisöjä ja verkostoja. Näille yhteisöille on tunnusomaista, että niissä vaikuttavien jäsenien ajatustavat yhtyvät keskenään. Yhteisöissä syntyy uusia ideoita ja keksintöjä. Niiden välittäminen maailmalle on usein kuitenkin ongelmallista. Digitaalisuus, Internet ja monet muut uudet teknologiat tuovat yhden ratkaisun ongelmaan. Eräs uuden teknologian mahdollistama kanava on yhteisötelevisio, jonka kautta yhteisön viestintää voidaan tehokkaasti välittää. Yhteisöilläei kuitenkaan ole teknistä taitoa toteuttaa tällaista palvelua. Yhteisöille, kuten pk-yrityksille, kouluille, seuroille, yhdistyksille ja jopa yksittäisille ihmisille, tuleekin pystyä tarjoamaan valmis konsepti, joka on helposti heidän käytettävissään. Tämä diplomityö toimii teknisenä pohjana Finnish Satellite Television Oy:n yhteisö-tv -palvelukonseptille, joka tullaan ottamaan laajamittaiseen käyttöön vuoden 2007 aikana. Työssä käydään läpi yhteisön ja yhteisöllisyyden tunnusmerkit ja peruspiirteet, luodaan katsaus yhteisötelevision alkutaipaleisiin, nykytilaan ja sen eri ratkaisuihin. Lisäksi tutustutaan yhteisö-tv:n kansainvälisiin ja kotimaisiin kokeiluihin ja pilottiprojekteihin. Työn teknisessä osassa tutkitaan yhteisötelevision mahdollistaviin teknologioihin, siirtoteihin sekä digitaalisiin tuotantojärjestelmiin. Lopuksi työssä kootaan yhteen käytettävyydeltään, liikutettavuudeltaan ja kustannustehokkuudeltaan sopivimmat tekniset toteutusvaihtoehdot konseptin käyttöönottoa varten.

Estimation of forest canopy cover : a comparison of field measurement techniques

Abstract

Embedding, Extraction and Detection of Digital Watermark in Spectral Images

Tässä diplomityössä tutkitaan tekniikoita, joillavesileima lisätään spektrikuvaan, ja menetelmiä, joilla vesileimat tunnistetaanja havaitaan spektrikuvista. PCA (Principal Component Analysis) -algoritmia käyttäen alkuperäisten kuvien spektriulottuvuutta vähennettiin. Vesileiman lisääminen spektrikuvaan suoritettiin muunnosavaruudessa. Ehdotetun mallin mukaisesti muunnosavaruuden komponentti korvattiin vesileiman ja toisen muunnosavaruuden komponentin lineaarikombinaatiolla. Lisäyksessä käytettävää parametrijoukkoa tutkittiin. Vesileimattujen kuvien laatu mitattiin ja analysoitiin. Suositukset vesileiman lisäykseen esitettiin. Useita menetelmiä käytettiin vesileimojen tunnistamiseen ja tunnistamisen tulokset analysoitiin. Vesileimojen kyky sietää erilaisia hyökkäyksiä tarkistettiin. Diplomityössä suoritettiin joukko havaitsemis-kokeita ottamalla huomioon vesileiman lisäyksessä käytetyt parametrit. ICA (Independent Component Analysis) -menetelmää pidetään yhtenä mahdollisena vaihtoehtona vesileiman havaitsemisessa.

Color ad spectral image assessment using novel quality and fidelity techniques

The ongoing development of the digital media has brought a new set of challenges with it. As images containing more than three wavelength bands, often called spectral images, are becoming a more integral part of everyday life, problems in the quality of the RGB reproduction from the spectral images have turned into an important area of research. The notion of image quality is often thought to comprise two distinctive areas – image quality itself and image fidelity, both dealing with similar questions, image quality being the degree of excellence of the image, and image fidelity the measure of the match of the image under study to the original. In this thesis, both image fidelity and image quality are considered, with an emphasis on the influence of color and spectral image features on both. There are very few works dedicated to the quality and fidelity of spectral images. Several novel image fidelity measures were developed in this study, which include kernel similarity measures and 3D-SSIM (structural similarity index). The kernel measures incorporate the polynomial, Gaussian radial basis function (RBF) and sigmoid kernels. The 3D-SSIM is an extension of a traditional gray-scale SSIM measure developed to incorporate spectral data. The novel image quality model presented in this study is based on the assumption that the statistical parameters of the spectra of an image influence the overall appearance. The spectral image quality model comprises three parameters of quality: colorfulness, vividness and naturalness. The quality prediction is done by modeling the preference function expressed in JNDs (just noticeable difference). Both image fidelity measures and the image quality model have proven to be effective in the respective experiments.

A Technique for Digital Color Image Watermarking Using ICA

With the increase of use of digital media the need for the methods of multimedia protection becomes extremely important. The number of the solutions to the problem from encryption to watermarking is large and is growing every year. In this work digital image watermarking is considered, specifically a novel method of digital watermarking of color and spectral images. An overview of existing methods watermarking of color and grayscale images is given in the paper. Methods using independent component analysis (ICA) for detection and the ones using discrete wavelet transform (DWT) and discrete cosine transform (DCT) are considered in more detail. A novel method of watermarking proposed in this paper allows embedding of a color or spectral watermark image into color or spectral image consequently and successful extraction of the watermark out of the resultant watermarked image. A number of experiments have been performed on the quality of extraction depending on the parameters of the embedding procedure. Another set of experiments included the test of the robustness of the algorithm proposed. Three techniques have been chosen for that purpose: median filter, low-pass filter (LPF) and discrete cosine transform (DCT), which are a part of a widely known StirMark - Image Watermarking Robustness Test. The study shows that the proposed watermarking technique is fragile, i.e. watermark is altered by simple image processing operations. Moreover, we have found that the contents of the image to be watermarked do not affect the quality of the extraction. Mixing coefficients, that determine the amount of the key and watermark image in the result, should not exceed 1% of the original. The algorithm proposed has proven to be successful in the task of watermark embedding and extraction.

Open Preservation: Community Approaches to Ensuring Long-Term Access to Digital Collections

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

Spatial modeling techniques for mapping and characterization of acid sulfate soils

Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.

Digital Content Marketing in the Business-to-Business Context. A Case Study on Marketing Communications Agencies.

Marketing has changed because of digitalization. Marketing is moving towards digital channels and more companies are transitioning from “pushing” advertising messages to “pull” marketing, that attracts audience with the content that interests and benefits the audience. This kind of marketing is called content marketing or “inbound” marketing. This study focuses on how marketing communications agencies utilize digital content marketing and what are the best practices with the selected digital content marketing channels. In this study, those channels include blogs, Facebook, Twitter, and LinkedIn. The qualitative research method was utilized in order to examine the phenomenon of digital content marketing in-depth. The chosen data collecting method was semi-structured interviewing. A total of seven marketing communications agencies, who currently utilize digital content marketing, were selected as case companies and interviewed. All the case companies are from the marketing communications industry because that industry can be assumed to be well adapted to digital content marketing techniques. There is a research gap about digital content marketing in the B2B context, which increases the novelty value of this research. The study examines what is digital content marketing, why B2B companies use digital content marketing, and how should digital content marketing be conducted through blogs and social media. The informants perceived digital marketing to be a fundamental part of their all marketing. They conduct digital content marketing for the following reasons: to increase sales, to improve their brand image and to demonstrate their own skills. Concrete results of digital content marketing for the case companies include sales leads, new clients, better brand image, and that recruiting is easier. The most important success factors with blogs and social media are the following: 1) Audience-centric thinking. All content planning should start from figuring out which themes interests the target audience. Social media channel choices should be based on where the target audience can be reached. 2) Companies should not talk only about themselves. Instead, content is made about themes that interests the target audience. On social media channels, only a fragment of all shared content is about the company. Rather, most of the shared content is industry-specific content that helps the potential client.