Image Heritage - The Temporal Dimension in Consumers' Corporate Image Constructions

Images and brands have been topics of great interest in both academia and practice for a long time. The company’s image, which in this study is considered equivalent to the actual corporate brand, has become a strategic issue and one of the company’s most valuable assets. In contrast to mainstream corporate branding research focusing on consumerimages as steered and managed by the company, in the present study a genuine consumer-focus is taken. The question is asked: how do consumers perceive the company, and especially, how are their experiences of the company over time reflected in the corporate image? The findings indicate that consumers’ corporate images can be seen as being constructed through dynamic relational processes based on a multifaceted network of earlier images from multiple sources over time. The essential finding is that corporate images have a heritage. In the thesis, the concept of image heritage is introduced, which stands for the consumer’s earlier company-related experiences from multiple sources over time. In other words, consumers construct their images of the company based on earlier recalled images, perhaps dating back many years in time. Therefore, corporate images have roots - an image heritage – on which the images are constructed in the present. For companies, image heritage is a key for understanding consumers, and thereby also a key for consumer-focused branding strategies and activities. As image heritage is the consumer’s interpretation base and context for image constructions here and now, branding strategies and activities that meet this consumer-reality has a potential to become more effective. This thesis is positioned in the tradition of The Nordic School of Marketing Thought and introduces a relational dynamic perspective into branding through consumers’ image heritage. Anne Rindell is associated to CERS, the Center for Relationship Marketing and Service Management at the Swedish School of Economics and Business Administration.

Value of Image in Service

Purpose This paper takes a customer view on corporate image and value, and discusses the value of image in service. We propose a model depicting how the customer’s corporate brand image affects the customer’s value-in-use. Methodology/approach The paper represents conceptual development on customers’ value and image construction processes. By integrating ideas and elements from the current service and branding literature a model is proposed that extends current views on how value-in-use emerges. Findings From a current service perspective it is the customer who makes value assessments when experiencing service. Similarly, if branding is a concept used to denote the service provider’s intentions and attempts to create a corporate brand, image construction is the corresponding process where the customer constructs the corporate image. This image construction process is always present both in service interactions and in communication and has an effect on the customer’s value-in-use. We argue that two interrelated concepts are needed to capture corporate image construction and dynamics and value-in-use – the image-in-use and image heritage. Research implications The model integrates two different streams of research pointing to the need to consider traditional marketing communication and service interactions as inherently related to each other from the customer’s point of view. Additionally the model gives a platform for understanding how value-in-use emerges over time. New methodological approaches and techniques to capture image-in-use and image heritage and their interplay with value-in-use are needed. Practical implications The company may not be able to control the emergence of value-in-use but may influence it, not only in interactions with the customer but also with pure communication. Branding activities should therefore be considered related to service operations and service development. Additionally, practitioners would need to apply qualitative methods to understand the customer’s view on image and value-in-use. Originality/value The paper presents a novel approach for understanding and studying that the customer’s image of a company influences emergence of value-in-use. The model implies that the customer’s corporate image has a crucial role for experienced value-in-use.

Narratives of Travel and the Travelling Concept of Narrative: Genre Blending and the Art of Transformation

In this article I shall argue that understandings of what constitutes narrative, how it functions, and the contexts in which it applies have broadened in line with cultural, social and intellectual trends which have seen a blurring, if not the dissolution, of boundaries between ‘fact’ and ‘fiction’; ‘literary’ and ‘non-literary’ narrative spaces; history and story; concepts of time and space, text and image, teller and tale, representation and reality.To illustrate some of the ways in which the concept of narrative has travelled across disciplinary and generic boundaries, I shall look at The Art of Travel (de Botton 2003), with a view to demonstrating how the blending of genres works to produce a narrative that is at once personal and philosophical; visual and verbal; didactic and poetic. I shall show that such a text constitutes a site of interrogation of concepts of narrative, even as it depends on the reader’s ability to narrativize experience.

Puunoston kehittäminen Stora Enso Metsän Helsingin palvelupisteessä

The operation environment in the roundwood trade in Finland in the 1990’s include several changes. They are changes in the structure of non-industrial private forest (NIPF) ownership, forest taxation, in forest legislation, in price recommendation agreement, diminishing resources of forestry extension services, etc. At the same time, the roundwood demand has been rising. All these developments cause uncertainty in wood procurement organisations, and call for research to find out how to adapt into the changing environment. The objective of this study is to produce information for roundwood purchasing planning and cus-tomer satisfaction management to be used by Stora Enso Metsä Customer Service, Helsinki. For this pur-pose, data needs to be gathered about the urban NIPFs and their forest estates, behaviour related to forestry and timber-selling, customer satisfaction in their latest timber selling transaction, and their opinions about Enso’s new customer service office and its service concept. To fulfil the objective of the study, a NIPF -owner -survey (N=1064, response rate 39,7%) was con-ducted in October 1998-January 1999. The sample was made on the basis of the marketing database of Stora Enso Oyj Forest Customer Service in Helsinki. In planning the frame of reference of the empirical study, the model of service quality by Grönroos was applied. The following aspects were included in the 7-page questionnaire: demographic, sosio-economic and forest estate background, relation to the forest service supply, behaviour related to forestry, timber-selling motives and behaviour, last contact organisation and its image in forestry business, expectations and percep-tions in the latest timber-selling transactions, and behavioural intentions. The results revealed that the share of women, pensioners and academically educated people among forest owners was quite high. The majority of the forest estates of the metropolitan forest owners were situ-ated in the provinces of South Finland and East Finland. The average forest estate area was considerably smaller than in a previous study. Economic and recreational objectives were most important in the use of forests. Forest Associations were involved in half of the roundwood sales transactions of the respondents in the metropolitan area. The wood quantity of transactions was considerably higher than the average in the whole country. Bank-organised forest-related activities, taxation infos and trips to the forest were the most popular activities. Among the services, silvicultural advices were needed mostly and stub treatment least. Brochure material related to stumpage timber sales and taxation were considered most important compared to material related to delivery sales. The service expectations were at highest for women and they were less satisfied with the service than men. 2nd and 3rd generation residents of the metropolitan area thought about the new customer service concept more positively than the 1st generation residents. Internet users under 60 years thought more positively about new satellite picture-based woodlot search concept. Cross-tabulation of factor scores against background variables indicated that women with relatively low education level a greater need to sell roundwood than entrepreneurs, white-collar workers and directors, and Internet users. Suspiciousness towards timber procurement organisations was relatively strong among women and those whose forest income share of the total income was either null or over 20 %. The average customer satisfaction score was negative in all nine questions. Statistical differences be-tween different companies did not exist in the average satisfaction scores. Stora Enso’s Helsinki forest cus-tomer service could choose the ability to purchase all timber grades as its competitive advantage. Out of nine service dimension included in the questionnaire, in this particular service dimension, Enso’s Helsinki forest customer service’s score exceeded most all organisations’ average customer satisfaction score. On the basis of importance – performance matrix, advice and quidance could have been provided more to the forest owners in their latest timber–selling transaction.

An Analysis of the Concept of Citizenship: Legal, Political and Social Dimensions

The thesis aims at analyzing concept of citizenship in political philosophy. The concept of citizenship is a complex one: it does not have a definitive explication, but it nevertheless is a very important category in contemporary world. Citizenship is a powerful ideal, and often the way a person is treated depends on whether he or she has the status of a citizen. Citizenship includes protection of a person’s rights both at home and abroad. It entails legal, political and social dimension: the legal status as a full member of society, the recognition of that status by fellow citizens and acting as a member of society. The thesis discusses these three dimensions. Its objective is to show how all of them, despite being insufficient in some aspects, reach something important about the concept. The main sources of the thesis are Civic Republicanism by Iseult Honohan (Routledge 2002), Republicanism by Philip Pettit (Clarendon Press 1997), and Taking Rights Seriously by Ronald Dworkin (1997). In addition, the historical part of the thesis relies mainly on the works of Aristotle, Immanuel Kant, Adam Smith, Quentin Skinner, James Pocock and James Tully. The writings of Will Kymlicka, John Rawls, Chantal Mouffe, and Shane Phelan are referred to in the presentation and critique of the liberal tradition of thought. Hannah Arendt and Seyla Benhabib’s analysis of Arendt’s philosophy both address the problematic relations between human rights and nation-states as the main guarantors of rights. The chapter on group rights relies on Peter Jones’ account of corporate and collective rights, after which I continue to Seumas Miller’s essay on the (liberal) account of group rights and their relation to the concept of citizenship. Republicanism and Political Theory (2002) edited by Cécile Laborde and John Maynor is also references. David Miller and Maurizio Viroli represent the more “rooted” version of republicanism. The thesis argues that the full concept of citizenship should be seen as containing legal, political and social dimensions. The concept can be viewed from all of these three angles. The first means that citizenship is connected with certain rights, like the right to vote or stand for election, the right to property and so on. In most societies, the law guarantees these rights to every citizen. Then there is also the social dimension, which can be said to be as important as the legal one: the recognition of equality and identities of others. Finally, there is the political dimension, meaning the importance of citizens’ participation in the society, which is discussed in connection with the contemporary account of republicanism. All these issues are discussed from the point of view of groups demanding for group-specific rights and equal recognition. The challenge with these three aspects of citizenship is, however, that they are difficult to discuss under one heading. Different theories or discourses of citizenship each approach the subject from different starting points, which make reconciling them sometimes hard. The fundamental questions theories try to answer may differ radically depending on the theory. Nevertheless, in order to get the whole image of what the citizenship discourses are about all the aspects deserve to be taken into account.

WebGeSTer DB-a transcription terminator database

We present WebGeSTer DB, the largest database of intrinsic transcription terminators (http://pallab.serc.iisc.ernet.in/gester). The database comprises of a million terminators identified in 1060 bacterial genome sequences and 798 plasmids. Users can obtain both graphic and tabular results on putative terminators based on default or user-defined parameters. The results are arranged in different tiers to facilitate retrieval, as per the specific requirements. An interactive map has been incorporated to visualize the distribution of terminators across the whole genome. Analysis of the results, both at the whole-genome level and with respect to terminators downstream of specific genes, offers insight into the prevalence of canonical and non-canonical terminators across different phyla. The data in the database reinforce the paradigm that intrinsic termination is a conserved and efficient regulatory mechanism in bacteria. Our database is freely accessible.

Wavelet Transform Codec for Fast Retrieval of Slices of 3D Objects

We propose a method to encode a 3D magnetic resonance image data and a decoder in such way that fast access to any 2D image is possible by decoding only the corresponding information from each subband image and thus provides minimum decoding time. This will be of immense use for medical community, because most of the PET and MRI data are volumetric data. Preprocessing is carried out at every level before wavelet transformation, to enable easier identification of coefficients from each subband image. Inclusion of special characters in the bit stream facilitates access to corresponding information from the encoded data. Results are taken by performing Daub4 along x (row), y (column) direction and Haar along z (slice) direction. Comparable results are achieved with the existing technique. In addition to that decoding time is reduced by 1.98 times. Arithmetic coding is used to encode corresponding information independently

Multi-spectral satellite image classification using Glowworm Swarm Optimization

This paper investigates a new Glowworm Swarm Optimization (GSO) clustering algorithm for hierarchical splitting and merging of automatic multi-spectral satellite image classification (land cover mapping problem). Amongst the multiple benefits and uses of remote sensing, one of the most important has been its use in solving the problem of land cover mapping. Image classification forms the core of the solution to the land cover mapping problem. No single classifier can prove to classify all the basic land cover classes of an urban region in a satisfactory manner. In unsupervised classification methods, the automatic generation of clusters to classify a huge database is not exploited to their full potential. The proposed methodology searches for the best possible number of clusters and its center using Glowworm Swarm Optimization (GSO). Using these clusters, we classify by merging based on parametric method (k-means technique). The performance of the proposed unsupervised classification technique is evaluated for Landsat 7 thematic mapper image. Results are evaluated in terms of the classification efficiency - individual, average and overall.

Kannada WordNet - a lexical database

This paper presents the preliminary analysis of Kannada WordNet and the set of relevant computational tools. Although the design has been inspired by the famous English WordNet, and to certain extent, by the Hindi WordNet, the unique features of Kannada WordNet are graded antonyms and meronymy relationships, nominal as well as verbal compoundings, complex verb constructions and efficient underlying database design (designed to handle storage and display of Kannada unicode characters). Kannada WordNet would not only add to the sparse collection of machine-readable Kannada dictionaries, but also will give new insights into the Kannada vocabulary. It provides sufficient interface for applications involved in Kannada machine translation, spell checker and semantic analyser.

DSA image registration using non-uniform MRF model and pivotal control points

In order to reduce the motion artifacts in DSA, non-rigid image registration is commonly used before subtracting the mask from the contrast image. Since DSA registration requires a set of spatially non-uniform control points, a conventional MRF model is not very efficient. In this paper, we introduce the concept of pivotal and non-pivotal control points to address this, and propose a non-uniform MRF for DSA registration. We use quad-trees in a novel way to generate the non-uniform grid of control points. Our MRF formulation produces a smooth displacement field and therefore results in better artifact reduction than that of registering the control points independently. We achieve improved computational performance using pivotal control points without compromising on the artifact reduction. We have tested our approach using several clinical data sets, and have presented the results of quantitative analysis, clinical assessment and performance improvement on a GPU. (C) 2013 Elsevier Ltd. All rights reserved.

Database Independent Human Emotion Recognition with Meta-Cognitive Neuro-Fuzzy Inference System

Facial emotions are the most expressive way to display emotions. Many algorithms have been proposed which employ a particular set of people (usually a database) to both train and test their model. This paper focuses on the challenging task of database independent emotion recognition, which is a generalized case of subject-independent emotion recognition. The emotion recognition system employed in this work is a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). McFIS has two components, a neuro-fuzzy inference system, which is the cognitive component and a self-regulatory learning mechanism, which is the meta-cognitive component. The meta-cognitive component, monitors the knowledge in the neuro-fuzzy inference system and decides on what-to-learn, when-to-learn and how-to-learn the training samples, efficiently. For each sample, the McFIS decides whether to delete the sample without being learnt, use it to add/prune or update the network parameter or reserve it for future use. This helps the network avoid over-training and as a result improve its generalization performance over untrained databases. In this study, we extract pixel based emotion features from well-known (Japanese Female Facial Expression) JAFFE and (Taiwanese Female Expression Image) TFEID database. Two sets of experiment are conducted. First, we study the individual performance of both databases on McFIS based on 5-fold cross validation study. Next, in order to study the generalization performance, McFIS trained on JAFFE database is tested on TFEID and vice-versa. The performance The performance comparison in both experiments against SVNI classifier gives promising results.

A Split-and-Merge Dictionary Learning Algorithm for Sparse Representation: Application to Image Denoising

In big data image/video analytics, we encounter the problem of learning an over-complete dictionary for sparse representation from a large training dataset, which cannot be processed at once because of storage and computational constraints. To tackle the problem of dictionary learning in such scenarios, we propose an algorithm that exploits the inherent clustered structure of the training data and make use of a divide-and-conquer approach. The fundamental idea behind the algorithm is to partition the training dataset into smaller clusters, and learn local dictionaries for each cluster. Subsequently, the local dictionaries are merged to form a global dictionary. Merging is done by solving another dictionary learning problem on the atoms of the locally trained dictionaries. This algorithm is referred to as the split-and-merge algorithm. We show that the proposed algorithm is efficient in its usage of memory and computational complexity, and performs on par with the standard learning strategy, which operates on the entire data at a time. As an application, we consider the problem of image denoising. We present a comparative analysis of our algorithm with the standard learning techniques that use the entire database at a time, in terms of training and denoising performance. We observe that the split-and-merge algorithm results in a remarkable reduction of training time, without significantly affecting the denoising performance.

FIVDL: Fingerprint Image Verification using Dictionary Learning

Fingerprints are used for identification in forensics and are classified into Manual and Automatic. Automatic fingerprint identification system is classified into Latent and Exemplar. A novel Exemplar technique of Fingerprint Image Verification using Dictionary Learning (FIVDL) is proposed to improve the performance of low quality fingerprints, where Dictionary learning method reduces the time complexity by using block processing instead of pixel processing. The dynamic range of an image is adjusted by using Successive Mean Quantization Transform (SMQT) technique and the frequency domain noise is reduced using spectral frequency Histogram Equalization. Then, an adaptive nonlinear dynamic range adjustment technique is utilized to determine the local spectral features on corresponding fingerprint ridge frequency and orientation. The dictionary is constructed using spatial fundamental frequency that is determined from the spectral features. These dictionaries help in removing the spurious noise present in fingerprints and reduce the time complexity by using block processing instead of pixel processing. Further, dictionaries are used to reconstruct the image for matching. The proposed FIVDL is verified on FVC database sets and Experimental result shows an improvement over the state-of-the-art techniques. (C) 2015 The Authors. Published by Elsevier B.V.

Image-based localization and pose recovery using scale invariant features

In this paper, we propose a vision based mobile robot localization strategy. Local scale-invariant features are used as natural landmarks in unstructured and unmodified environment. The local characteristics of the features we use prove to be robust to occlusion and outliers. In addition, the invariance of the features to viewpoint change makes them suitable landmarks for mobile robot localization. Scale-invariant features detected in the first exploration are indexed into a location database. Indexing and voting allow efficient recognition of global localization. The localization result is verified by epipolar geometry between the representative view in database and the view to be localized, thus the probability of false localization will be decreased. The localization system can recover the pose of the camera mounted on the robot by essential matrix decomposition. Then the position of the robot can be computed easily. Both calibrated and un-calibrated cases are discussed and relative position estimation based on calibrated camera turns out to be the better choice. Experimental results show that our approach is effective and reliable in the case of illumination changes, similarity transformations and extraneous features. © 2004 IEEE.

Exploring Semantic Textual Similarity

[EN]Measuring semantic similarity and relatedness between textual items (words, sentences, paragraphs or even documents) is a very important research area in Natural Language Processing (NLP). In fact, it has many practical applications in other NLP tasks. For instance, Word Sense Disambiguation, Textual Entailment, Paraphrase detection, Machine Translation, Summarization and other related tasks such as Information Retrieval or Question Answering. In this masther thesis we study di erent approaches to compute the semantic similarity between textual items. In the framework of the european PATHS project1, we also evaluate a knowledge-base method on a dataset of cultural item descriptions. Additionaly, we describe the work carried out for the Semantic Textual Similarity (STS) shared task of SemEval-2012. This work has involved supporting the creation of datasets for similarity tasks, as well as the organization of the task itself.