With the ever-increasing trend in the number of social interactions getting intermediated by technology (the world wide web) as the backdrop, this thesis focuses on the design of mechanisms for online communities (crowds) which strive to come together, albeit in ad-hoc fashion, to achieve a social objective. Two examples of such web-based social communities which are of central concern in this thesis are crowdsourcing markets and crowdfunding platforms. For these settings which involve strategic human agents, we design mechanisms that incentivize contributions (effort, funds, or information) from the crowd and aggregate these contributions to achieve the specified objective. Our work is thus concerned with the challenge of designing mechanisms which encourage social coordination and cooperation among large groups of (of-ten) anonymous users to achieve group efficiency (social welfare). We address the following four related challenges: • Can we design mechanisms to solve the free-rider problem in public goods settings? Can large anonymous groups of individuals be incentivized to contribute to create public goods? • Can we design mechanisms that harness social networks to achieve coordination of contributions towards a public good to ensure that publicly desirable goods are successfully funded via private contributions? How do we make such mechanisms fair • Can we design mechanisms that improve the efficiency of markets by expanding the set of individuals who participate in the market? Can these individuals be incentivized to increase the group efficiency and, if so, at what cost? • Can we design mechanisms that make crowdsourcing markets more equitable by offering participation opportunities to novices and higher incentives to agents with high reliability? What is the price of reliability? Using mechanism design as the principal design tool, the thesis attempts to offer rigorous solutions to the above challenges

A practice of applying of Product Service System (PSS)—Xinmade.com is demonstrated by a business plan and this paper discusses about using Crowdsourcing in the traditional New Product Development (NPD). Finally tips of applying Crowdsourcing in PSS are summarized.

Due to the current, global challenges such as resource depletion and economic crisis, and international societal mega-trends such as multi-internationalisation, we are in transition from conventional methods of production to relatively novel methods that strives to be competitive, satisfy customer needs and have a lower environmental impact. Product-Service System (PSS) method is deemed to be a solid alternative towards this vision. To do that, we are in need of novel approaches to re-envision the current system. Therefore, Innovation methods are the backbone of PSS. Since PSS highly emphasizes the customers' needs and co-creation with them, user-innovation methods are required in order to boost PSS Innovation. Among user-innovation methods, Crowdsourcing seems to be valid option which would enable us to attract a large, undefined network of people to the innovation process. In this research, a success model for crowdsourcing practice is proposed and validated by literature and expert interviews. As a follow-up, based on the success model, a strategic guideline for innovation using open modes of collaboration is proposed. Moreover, we discuss the implication of PSS and sustainability and how these concepts can be empowered by crowdsourcing.

The recently released High Efficiency Video Coding (HEVC) standard, which halves the transmission bandwidth requirement of encoded video for almost the same quality when compared to H.264/AVC, and the availability of increased network bandwidth (e.g. from 2 Mbps for 3G networks to almost 100 Mbps for 4G/LTE) have led to the proliferation of video streaming services. Based on these major innovations, the prevalence and diversity of video application are set to increase over the coming years. However, the popularity and success of current and future video applications will depend on the perceived quality of experience (QoE) of end users. How to measure or predict the QoE of delivered services becomes an important and inevitable task for both service and network providers. Video quality can be measured either subjectively or objectively. Subjective quality measurement is the most reliable method of determining the quality of multimedia applications because of its direct link to users’ experience. However, this approach is time consuming and expensive and hence the need for an objective method that can produce results that are comparable with those of subjective testing. In general, video quality is impacted by impairments caused by the encoder and the transmission network. However, videos encoded and transmitted over an error-prone network have different quality measurements even under the same encoder setting and network quality of service (NQoS). This indicates that, in addition to encoder settings and network impairment, there may be other key parameters that impact video quality. In this project, it is hypothesised that video content type is one of the key parameters that may impact the quality of streamed videos. Based on this assertion, parameters related to video content type are extracted and used to develop a single metric that quantifies the content type of different video sequences. The proposed content type metric is then used together with encoding parameter settings and NQoS to develop content-based video quality models that estimate the quality of different video sequences delivered over IP-based network. This project led to the following main contributions: (1) A new metric for quantifying video content type based on the spatiotemporal features extracted from the encoded bitstream. (2) The development of novel subjective test approach for video streaming services. (3) New content-based video quality prediction models for predicting the QoE of video sequences delivered over IP-based networks. The models have been evaluated using subjective and objective methods.

Global Navigation Satellite Systems (GNSS) have found wide adoption in various applications, be they military, civilian or commercial. The susceptibility of GNSS to radio-frequency interference can, thus, be very disruptive, even for emergency services, therefore threatening people's lives. An early prototype of a system providing relatively cheap widescale GNSS jamming detection, called J911, is explored in this thesis. J911 is smartphone-based crowdsourcing of GNSS observations, most interesting of which are carrier-to-noise-density ratio (<img src="http://www.diva-portal.org/cgi-bin/mimetex.cgi?%5Cfrac%7BC%7D%7BN_0%7D" />) and Automatic Gain Control (AGC) voltage. To implement the prototype, an Android application to provide the measurements, a backend to parse and store the measurements, and a frontend to visualize the measurements were developed. In real-world use, the thesis argues, the J911 system would best be implemented over existing Enhanced 9-1-1 (E911) infrastructure, becoming a standardized part of the Public Switched Telephone Network (PSTN). The Android application, running on a smartphone, would periodically construct messages to be sent to the backend over an Internet connection. The messages would include: current location from all location providers available in Android OS, observed satellites from all supported constellations, the satellites' <img src="http://www.diva-portal.org/cgi-bin/mimetex.cgi?%5Cfrac%7BC%7D%7BN_0%7D" />, and a timestamp. Once a message is received on the backend, the data would be extracted and stored in a database. The frontend would query the database and produce a map with the collected datapoints overlaid on top of it, whose color indicates received signal strength at that point. When a jammer gets close enough to a few smartphones, they will all be jammed, which is easily observed on the map. On top of that, if enough samples are gathered, a Power Difference of Arrival localization algorithm can be used to localize the jammer. The smartphones that the system was planned to be tested with did not support AGC level readings, therefore in order to obtain AGC levels over time, a few SiGe GN3S Samplers, which are radio-frequency frontends, were used. In eastern Idaho, United States, over three nights in July 2017, an exercise, named 2017 DHS JamX, was performed with the help of the US Department of Homeland Security. Sadly, the approval for the publication of the test results did not come in time to be included in this thesis.

To develop and deliver an innovative and technologically superior product is not enough to succeed when it does not meet the user's daily needs. To develop such a product, you need an abstract and easy to use communication platform for target users, decision makers, and developers, that can also act as a model of the relevant part of the real world displaced by a possible innovation, auxiliary tool in creating a mind map and documentation, and a way of promoting the final product. An instance of such a platform is a sophisticated comic book, itself an instance of sequential art. Not only is it a feature rich and intuitive tool for collaboration of interested parties with different backgrounds, skills and roles, but since it essentially reflects the relevant part of the real world displaced by the innovation, it's pretty easy and quick for a new user to learn and master. Although not limited to such instances, it can be found as an especially useful tool for crowdsourced and open source based projects. This thesis will lay down the much needed theoretical basis for the Sequential Art Driven Development method and offer a practical application of such method, with an open call for contributions from members of the crowd, in the form of a CC0 licensed comic book series "Who is Secret Agent X-9?", a showcase platform for cutting edge technologies like the Bitcoin network and Nemo Mobile operating system.

Natural Language Processing (NLP) is an interdisciplinary research field of Computer Science, Linguistics, and Pattern Recognition that studies, among others, the use of human natural languages in Human-Computer Interaction (HCI). Most of NLP research tasks can be applied for solving real-world problems. This is the case of natural language recognition and natural language translation, that can be used for building automatic systems for document transcription and document translation. Regarding digitalised handwritten text documents, transcription is used to obtain an easy digital access to the contents, since simple image digitalisation only provides, in most cases, search by image and not by linguistic contents (keywords, expressions, syntactic or semantic categories). Transcription is even more important in historical manuscripts, since most of these documents are unique and the preservation of their contents is crucial for cultural and historical reasons. The transcription of historical manuscripts is usually done by paleographers, who are experts on ancient script and vocabulary. Recently, Handwritten Text Recognition (HTR) has become a common tool for assisting paleographers in their task, by providing a draft transcription that they may amend with more or less sophisticated methods. This draft transcription is useful when it presents an error rate low enough to make the amending process more comfortable than a complete transcription from scratch. Thus, obtaining a draft transcription with an acceptable low error rate is crucial to have this NLP technology incorporated into the transcription process. The work described in this thesis is focused on the improvement of the draft transcription offered by an HTR system, with the aim of reducing the effort made by paleographers for obtaining the actual transcription on digitalised historical manuscripts. This problem is faced from three different, but complementary, scenarios: · Multimodality: The use of HTR systems allow paleographers to speed up the manual transcription process, since they are able to correct on a draft transcription. Another alternative is to obtain the draft transcription by dictating the contents to an Automatic Speech Recognition (ASR) system. When both sources (image and speech) are available, a multimodal combination is possible and an iterative process can be used in order to refine the final hypothesis. · Interactivity: The use of assistive technologies in the transcription process allows one to reduce the time and human effort required for obtaining the actual transcription, given that the assistive system and the palaeographer cooperate to generate a perfect transcription. Multimodal feedback can be used to provide the assistive system with additional sources of information by using signals that represent the whole same sequence of words to transcribe (e.g. a text image, and the speech of the dictation of the contents of this text image), or that represent just a word or character to correct (e.g. an on-line handwritten word). · Crowdsourcing: Open distributed collaboration emerges as a powerful tool for massive transcription at a relatively low cost, since the paleographer supervision effort may be dramatically reduced. Multimodal combination allows one to use the speech dictation of handwritten text lines in a multimodal crowdsourcing platform, where collaborators may provide their speech by using their own mobile device instead of using desktop or laptop computers, which makes it possible to recruit more collaborators. / El Procesamiento del Lenguaje Natural (PLN) es un campo de investigación interdisciplinar de las Ciencias de la Computación, Lingüística y Reconocimiento de Patrones que estudia, entre otros, el uso del lenguaje natural humano en la interacción Hombre-Máquina. La mayoría de las tareas de investigación del PLN se pueden aplicar para resolver problemas del mundo real. Este es el caso del reconocimiento y la traducción del lenguaje natural, que se pueden utilizar para construir sistemas automáticos para la transcripción y traducción de documentos. En cuanto a los documentos manuscritos digitalizados, la transcripción se utiliza para facilitar el acceso digital a los contenidos, ya que la simple digitalización de imágenes sólo proporciona, en la mayoría de los casos, la búsqueda por imagen y no por contenidos lingüísticos. La transcripción es aún más importante en el caso de los manuscritos históricos, ya que la mayoría de estos documentos son únicos y la preservación de su contenido es crucial por razones culturales e históricas. La transcripción de manuscritos históricos suele ser realizada por paleógrafos, que son personas expertas en escritura y vocabulario antiguos. Recientemente, los sistemas de Reconocimiento de Escritura (RES) se han convertido en una herramienta común para ayudar a los paleógrafos en su tarea, la cual proporciona un borrador de la transcripción que los paleógrafos pueden corregir con métodos más o menos sofisticados. Este borrador de transcripción es útil cuando presenta una tasa de error suficientemente reducida para que el proceso de corrección sea más cómodo que una completa transcripción desde cero. Por lo tanto, la obtención de un borrador de transcripción con una baja tasa de error es crucial para que esta tecnología de PLN sea incorporada en el proceso de transcripción. El trabajo descrito en esta tesis se centra en la mejora del borrador de transcripción ofrecido por un sistema RES, con el objetivo de reducir el esfuerzo realizado por los paleógrafos para obtener la transcripción de manuscritos históricos digitalizados. Este problema se enfrenta a partir de tres escenarios diferentes, pero complementarios: · Multimodalidad: El uso de sistemas RES permite a los paleógrafos acelerar el proceso de transcripción manual, ya que son capaces de corregir en un borrador de la transcripción. Otra alternativa es obtener el borrador de la transcripción dictando el contenido a un sistema de Reconocimiento Automático de Habla. Cuando ambas fuentes están disponibles, una combinación multimodal de las mismas es posible y se puede realizar un proceso iterativo para refinar la hipótesis final. · Interactividad: El uso de tecnologías asistenciales en el proceso de transcripción permite reducir el tiempo y el esfuerzo humano requeridos para obtener la transcripción correcta, gracias a la cooperación entre el sistema asistencial y el paleógrafo para obtener la transcripción perfecta. La realimentación multimodal se puede utilizar en el sistema asistencial para proporcionar otras fuentes de información adicionales con señales que representen la misma secuencia de palabras a transcribir (por ejemplo, una imagen de texto, o la señal de habla del dictado del contenido de dicha imagen de texto), o señales que representen sólo una palabra o carácter a corregir (por ejemplo, una palabra manuscrita mediante una pantalla táctil). · Crowdsourcing: La colaboración distribuida y abierta surge como una poderosa herramienta para la transcripción masiva a un costo relativamente bajo, ya que el esfuerzo de supervisión de los paleógrafos puede ser drásticamente reducido. La combinación multimodal permite utilizar el dictado del contenido de líneas de texto manuscrito en una plataforma de crowdsourcing multimodal, donde los colaboradores pueden proporcionar las muestras de habla utilizando su propio dispositivo móvil en lugar de usar ordenadores, / El Processament del Llenguatge Natural (PLN) és un camp de recerca interdisciplinar de les Ciències de la Computació, la Lingüística i el Reconeixement de Patrons que estudia, entre d'altres, l'ús del llenguatge natural humà en la interacció Home-Màquina. La majoria de les tasques de recerca del PLN es poden aplicar per resoldre problemes del món real. Aquest és el cas del reconeixement i la traducció del llenguatge natural, que es poden utilitzar per construir sistemes automàtics per a la transcripció i traducció de documents. Quant als documents manuscrits digitalitzats, la transcripció s'utilitza per facilitar l'accés digital als continguts, ja que la simple digitalització d'imatges només proporciona, en la majoria dels casos, la cerca per imatge i no per continguts lingüístics (paraules clau, expressions, categories sintàctiques o semàntiques). La transcripció és encara més important en el cas dels manuscrits històrics, ja que la majoria d'aquests documents són únics i la preservació del seu contingut és crucial per raons culturals i històriques. La transcripció de manuscrits històrics sol ser realitzada per paleògrafs, els quals són persones expertes en escriptura i vocabulari antics. Recentment, els sistemes de Reconeixement d'Escriptura (RES) s'han convertit en una eina comuna per ajudar els paleògrafs en la seua tasca, la qual proporciona un esborrany de la transcripció que els paleògrafs poden esmenar amb mètodes més o menys sofisticats. Aquest esborrany de transcripció és útil quan presenta una taxa d'error prou reduïda perquè el procés de correcció siga més còmode que una completa transcripció des de zero. Per tant, l'obtenció d'un esborrany de transcripció amb un baixa taxa d'error és crucial perquè aquesta tecnologia del PLN siga incorporada en el procés de transcripció. El treball descrit en aquesta tesi se centra en la millora de l'esborrany de la transcripció ofert per un sistema RES, amb l'objectiu de reduir l'esforç realitzat pels paleògrafs per obtenir la transcripció de manuscrits històrics digitalitzats. Aquest problema s'enfronta a partir de tres escenaris diferents, però complementaris: · Multimodalitat: L'ús de sistemes RES permet als paleògrafs accelerar el procés de transcripció manual, ja que són capaços de corregir un esborrany de la transcripció. Una altra alternativa és obtenir l'esborrany de la transcripció dictant el contingut a un sistema de Reconeixement Automàtic de la Parla. Quan les dues fonts (imatge i parla) estan disponibles, una combinació multimodal és possible i es pot realitzar un procés iteratiu per refinar la hipòtesi final. · Interactivitat: L'ús de tecnologies assistencials en el procés de transcripció permet reduir el temps i l'esforç humà requerits per obtenir la transcripció real, gràcies a la cooperació entre el sistema assistencial i el paleògraf per obtenir la transcripció perfecta. La realimentació multimodal es pot utilitzar en el sistema assistencial per proporcionar fonts d'informació addicionals amb senyals que representen la mateixa seqüencia de paraules a transcriure (per exemple, una imatge de text, o el senyal de parla del dictat del contingut d'aquesta imatge de text), o senyals que representen només una paraula o caràcter a corregir (per exemple, una paraula manuscrita mitjançant una pantalla tàctil). · Crowdsourcing: La col·laboració distribuïda i oberta sorgeix com una poderosa eina per a la transcripció massiva a un cost relativament baix, ja que l'esforç de supervisió dels paleògrafs pot ser reduït dràsticament. La combinació multimodal permet utilitzar el dictat del contingut de línies de text manuscrit en una plataforma de crowdsourcing multimodal, on els col·laboradors poden proporcionar les mostres de parla utilitzant el seu propi dispositiu mòbil en lloc d'utilitzar ordinadors d'escriptori o portàtils, la qual cosa permet ampliar el nombr / Granell Romero, E. (2017). Advances on the Transcription of Historical Manuscripts based on Multimodality, Interactivity and Crowdsourcing [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/86137 / TESIS

Předložená dizertační práce se zabývá moderními algoritmy pro kódovaní videosekvencí, zejména algoritmem High Efficiency Video Coding, a jeho použítím v prostředí online streamování. Vzhledem k tomu, že chování koncových diváků směřuje ke sledování video obsahu kdykoli a kdekoli, způsob, jakým je obsah doručen k divákovi, se stává stejně důležitým, jakým je samotné kódování. V této práci se zaměřujeme na užití HEVC ve službách založených na HTTP adaptivním streamování, zejména ve službách využívajích DASH. Dále se zabýváme dalšími aspekty, které mají vliv na kvalitu zážitku (Quality of Experience) tak, jak jej vnímá koncový uživatel. Takovými jsou na příklad přítomnost reklamy či další systémové parametry. Abychom mohli sbírat názory uživatelů, pro naše experimenty často používáme crowdsourcing. Z tohoto důvodu je část této práce věnována samotnému crowdsourcingu a tomu, jak jej lze využít pro hodnocení kvality videa.

abstract: This dissertation seeks to understand and study the process of attention harvesting and knowledge production on typical online Q&A communities. Goals of this study include quantifying the attention harvesting and online knowledge, damping the effect of competition for attention on knowledge production, and examining the diversity of user behaviors on question answering. Project 1 starts with a simplistic discrete time model on a scale-free network and provides the method to measure the attention harvested. Further, project 1 highlights the effect of distractions on harvesting productive attention and in the end concludes which factors are influential and sensitive to the attention harvesting. The main finding is the critical condition to optimize the attention harvesting on the network by reducing network connection. Project 2 extends the scope of the study to quantify the value and quality of knowledge, focusing on the question answering dynamics. This part of research models how attention was distributed under typical answering strategies on a virtual online Q&A community. The final result provides an approach to measure the efficiency of attention transferred into value production and observes the contribution of different scenarios under various computed metrics. Project 3 is an advanced study on the foundation of the virtual question answering community from project 2. With highlights of different user behavioral preferences, algorithm stochastically simulates individual decisions and behavior. Results from sensitivity analysis on different mixtures of user groups gives insight of nonlinear dynamics for the objectives of success. Simulation finding shows reputation rewarding mechanism on Stack Overflow shapes the crowd mixture of behavior to be successful. In addition, project proposed an attention allocation scenario of question answering to improve the success metrics when coupling with a particular selection strategy. / Dissertation/Thesis / Doctoral Dissertation Applied Mathematics for the Life and Social Sciences 2019

This presented work deals with crowdsourcing tools for mapping and filtering of data that are created by the Ushahidi, Inc. and ways of their use. Ushahidi and SwiftRiver platforms and hosted version of Ushahidi called Crowdmap are counted among the tools for crisis mapping; however, more and more they are also used for other topics or issues. The aim of this work is to subject to a critical point of view not only the Ushahidi platform as a tool, but also a number of significant or interesting projects in which it was used. Presented is also the recommendation, how to use Ushahidi to create a successful project and the other way round what to avoid, when you work with Ushahidi. The basic building elements of Ushahidi are crowdsourcing, citizen journalism, geospatial information, and in particular the work of volunteers. This work describes the role of these building elements in Ushahidi, and subjects to critical reflection also the problematic sides, which Ushahidi is struggling with. Following is the analysis of selected sample of Ushahidi and Crowdmap deployments, which deals with the thematic, geographical and time stratification of the maps in the sample. Some significant uses of Ushahidi with humanitarian and non-humanitarian purpose of the deployment are examined in the end.