Corporate green image communication through public disclosures and social media

Today, companies need to mind the environment in all their actions. Policies, regulations and growing pressure from environmentally conscious public are driving corporations to invest increasingly in their green images. Communication plays a key role in forming and maintaining that image. This thesis explores how six selected companies communicate about their environmental efforts and activities, and its linkage to their green images, in annual and sustainability reports and in Facebook. The companies come from the U.S. and Europe and operate in three different industries: ICT, oil and gas, and aerospace & defense. Qualitative and quantitative content analyses are conducted to examine 36 reports and 121 Facebook messages, collected from the period of 2010-2014, and from 2005 for comparison. The results show that although the quality and quantity of environmental disclosure is increasing, there is still room for improvement. Overall, disclosure in the ICT sector is on the highest level. The European companies disclose more and on average have stronger green images than the American ones. Emissions and ways to reduce them is by far the most covered topic in both continents and in all three industry sectors. The messages in Facebook are closer to advertising, and overall the platform is utilized surprisingly little.

Side information creation for efficient Wyner-Ziv video coding: Classifying and reviewing

Video coding technologies have played a major role in the explosion of large market digital video applications and services. In this context, the very popular MPEG-x and H-26x video coding standards adopted a predictive coding paradigm, where complex encoders exploit the data redundancy and irrelevancy to 'control' much simpler decoders. This codec paradigm fits well applications and services such as digital television and video storage where the decoder complexity is critical, but does not match well the requirements of emerging applications such as visual sensor networks where the encoder complexity is more critical. The Slepian Wolf and Wyner-Ziv theorems brought the possibility to develop the so-called Wyner-Ziv video codecs, following a different coding paradigm where it is the task of the decoder, and not anymore of the encoder, to (fully or partly) exploit the video redundancy. Theoretically, Wyner-Ziv video coding does not incur in any compression performance penalty regarding the more traditional predictive coding paradigm (at least for certain conditions). In the context of Wyner-Ziv video codecs, the so-called side information, which is a decoder estimate of the original frame to code, plays a critical role in the overall compression performance. For this reason, much research effort has been invested in the past decade to develop increasingly more efficient side information creation methods. This paper has the main objective to review and evaluate the available side information methods after proposing a classification taxonomy to guide this review, allowing to achieve more solid conclusions and better identify the next relevant research challenges. After classifying the side information creation methods into four classes, notably guess, try, hint and learn, the review of the most important techniques in each class and the evaluation of some of them leads to the important conclusion that the side information creation methods provide better rate-distortion (RD) performance depending on the amount of temporal correlation in each video sequence. It became also clear that the best available Wyner-Ziv video coding solutions are almost systematically based on the learn approach. The best solutions are already able to systematically outperform the H.264/AVC Intra, and also the H.264/AVC zero-motion standard solutions for specific types of content. (C) 2013 Elsevier B.V. All rights reserved.

Perceptually driven video error protection using a distributed source coding approach

In video communication systems, the video signals are typically compressed and sent to the decoder through an error-prone transmission channel that may corrupt the compressed signal, causing the degradation of the final decoded video quality. In this context, it is possible to enhance the error resilience of typical predictive video coding schemes using as inspiration principles and tools from an alternative video coding approach, the so-called Distributed Video Coding (DVC), based on the Distributed Source Coding (DSC) theory. Further improvements in the decoded video quality after error-prone transmission may also be obtained by considering the perceptual relevance of the video content, as distortions occurring in different regions of a picture have a different impact on the user's final experience. In this context, this paper proposes a Perceptually Driven Error Protection (PDEP) video coding solution that enhances the error resilience of a state-of-the-art H.264/AVC predictive video codec using DSC principles and perceptual considerations. To increase the H.264/AVC error resilience performance, the main technical novelties brought by the proposed video coding solution are: (i) design of an improved compressed domain perceptual classification mechanism; (ii) design of an improved transcoding tool for the DSC-based protection mechanism; and (iii) integration of a perceptual classification mechanism in an H.264/AVC compliant codec with a DSC-based error protection mechanism. The performance results obtained show that the proposed PDEP video codec provides a better performing alternative to traditional error protection video coding schemes, notably Forward Error Correction (FEC)-based schemes. (C) 2013 Elsevier B.V. All rights reserved.

Semi-automatic knowledge extraction, representation and context-sensitive intelligent retrieval of video content using collateral context modelling with scalable ontological networks

Automatic indexing and retrieval of digital data poses major challenges. The main problem arises from the ever increasing mass of digital media and the lack of efficient methods for indexing and retrieval of such data based on the semantic content rather than keywords. To enable intelligent web interactions, or even web filtering, we need to be capable of interpreting the information base in an intelligent manner. For a number of years research has been ongoing in the field of ontological engineering with the aim of using ontologies to add such (meta) knowledge to information. In this paper, we describe the architecture of a system (Dynamic REtrieval Analysis and semantic metadata Management (DREAM)) designed to automatically and intelligently index huge repositories of special effects video clips, based on their semantic content, using a network of scalable ontologies to enable intelligent retrieval. The DREAM Demonstrator has been evaluated as deployed in the film post-production phase to support the process of storage, indexing and retrieval of large data sets of special effects video clips as an exemplar application domain. This paper provides its performance and usability results and highlights the scope for future enhancements of the DREAM architecture which has proven successful in its first and possibly most challenging proving ground, namely film production, where it is already in routine use within our test bed Partners' creative processes. (C) 2009 Published by Elsevier B.V.

Semantic-associative visual content labelling and retrieval: A multimodal approach

A novel framework referred to as collaterally confirmed labelling (CCL) is proposed, aiming at localising the visual semantics to regions of interest in images with textual keywords. Both the primary image and collateral textual modalities are exploited in a mutually co-referencing and complementary fashion. The collateral content and context-based knowledge is used to bias the mapping from the low-level region-based visual primitives to the high-level visual concepts defined in a visual vocabulary. We introduce the notion of collateral context, which is represented as a co-occurrence matrix of the visual keywords. A collaborative mapping scheme is devised using statistical methods like Gaussian distribution or Euclidean distance together with collateral content and context-driven inference mechanism. We introduce a novel high-level visual content descriptor that is devised for performing semantic-based image classification and retrieval. The proposed image feature vector model is fundamentally underpinned by the CCL framework. Two different high-level image feature vector models are developed based on the CCL labelling of results for the purposes of image data clustering and retrieval, respectively. A subset of the Corel image collection has been used for evaluating our proposed method. The experimental results to-date already indicate that the proposed semantic-based visual content descriptors outperform both traditional visual and textual image feature models. (C) 2007 Elsevier B.V. All rights reserved.

MPEG-M: A Digital Media Ecosystem for Interoperable Applications

MPEG-M is a suite of ISO/IEC standards (ISO/IEC 23006) that has been developed under the auspices of Moving Picture Experts Group (MPEG). MPEG-M, also known as Multimedia Service Platform Technologies (MSPT), facilitates a collection of multimedia middleware APIs and elementary services as well as service aggregation so that service providers can offer users a plethora of innovative services by extending current IPTV technology toward the seamless integration of personal content creation and distribution, e-commerce, social networks and Internet distribution of digital media.

Quality of experience of adaptive video streaming: investigation in service parameters and subjective quality assessment methodology

The usage of HTTP adaptive streaming (HAS) has become widely spread in multimedia services. Because it allows the service providers to improve the network resource utilization and user׳s Quality of Experience (QoE). Using this technology, the video playback interruption is reduced since the network and server status in addition to capability of user device, all are taken into account by HAS client to adapt the quality to the current condition. Adaptation can be done using different strategies. In order to provide optimal QoE, the perceptual impact of adaptation strategies from point of view of the user should be studied. However, the time-varying video quality due to the adaptation which usually takes place in a long interval introduces a new type of impairment making the subjective evaluation of adaptive streaming system challenging. The contribution of this paper is two-fold: first, it investigates the testing methodology to evaluate HAS QoE by comparing the subjective experimental outcomes obtained from ACR standardized method and a semi-continuous method developed to evaluate the long sequences. In addition, influence of using audiovisual stimuli to evaluate the video-related impairment is inquired. Second, impact of some of the adaptation technical factors including the quality switching amplitude and chunk size in combination with high range of commercial content type is investigated. The results of this study provide a good insight toward achieving appropriate testing method to evaluate HAS QoE, in addition to designing switching strategies with optimal visual quality.

Adjustable compression method for still JPEG images

There are a large number of image processing applications that work with different performance requirements and available resources. Recent advances in image compression focus on reducing image size and processing time, but offer no real-time solutions for providing time/quality flexibility of the resulting image, such as using them to transmit the image contents of web pages. In this paper we propose a method for encoding still images based on the JPEG standard that allows the compression/decompression time cost and image quality to be adjusted to the needs of each application and to the bandwidth conditions of the network. The real-time control is based on a collection of adjustable parameters relating both to aspects of implementation and to the hardware with which the algorithm is processed. The proposed encoding system is evaluated in terms of compression ratio, processing delay and quality of the compressed image when compared with the standard method.

Aldeias de crianças SOS

Dissertação de Mestrado para obtenção do grau de Mestre em Design de Comunicação, apresentada na Universidade de Lisboa - Faculdade de Arquitectura.

A CSR communication strategy for Continente: Improving brand image and reinforcing local community bonds

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Commercial blog communication and brand image

The aim of this thesis was to examine whether company initiated commercial communication in personal blogs has an effect on consumers’ brand image. A detailed picture of the main topics was built based on the previous academic literature. The study explores how sponsored and company-initiated blog postings influence consumers’ brand image with a qualitative research. A framework defines the link between the main concepts of commercial blog communication and how this can be used in order to reach positive results in relation to consumers’ brand image. The findings of this study demonstrate that if the tech-savvy consumers consider that the commercial blog communication is genuine and the blogger stands behind the recommendation of the blog posting, it will result on a more positive brand image. However, if the consumers consider the content of the blog posting to be too controlled by the company, it is automatically seen as an advertisement instead of a recommendation by someone trustworthy. The company-controlled commercial blog communication without presenting the personality of the blogger has negative effects on brand image.

Crisis communication in politics: forgiveness as image restoration tool

Crisis communication is a widely treated field. There are lot of works and guides which provide helpful information in order to face crisis situations successfully (Alcat, 2005, Benoit, 1997) and articles about case studies (Nespereira, 2014, Blaney y Benoit 2001). Nonetheless, most of times, these guides are focused on business or corporations (Abeler, 2010) and there are not such information about crisis communications in politics (Gaspar e Ibeas, 2015). The field is smaller if we speak about forgiveness as restoration image tool in politics (Harris 2006). Despite all, we live in “forgiveness era” as Krauze said (1998) where people demand to politicians to apologize when they have mistakes (Harris et al. 2006:716). So, we will try to make an approach to forgiveness in politics as a image restoration tool and analyze its capabilities in order to face crisis management.