From Counterculture to Intangible Heritage and Tourism Supply: Artistic Expressions in Ibiza, Spain

Until the beginning of the 20th century, Ibiza was rural, developmentally lagging, and separate from the modern world. These characteristics made it attractive as a refuge for European intellectuals and artists as soon as communications with the outside world began to develop. The first significant presence of artists occurred in the 1930s, just before the Spanish Civil War. After years of war and isolation, artists returned in a larger volume and variety than before. Other regions also had artistic and countercultural communities, but Ibiza decided to use them as an element of its tourist promotions, making the hippie movement a part of its culture and history and the most internationally known element. The objective of this paper is to expose the importance of art and artists, a direct inheritance of that time, in Ibizan promotion and tourism. The authorities and entrepreneurs of the island realized the media interest they received and the importance of this media impact on developing the tourism sector. The result was that they supported artistic avant-garde and various activities derived from the hippie movement to differentiate Ibiza and make it known in Spain and abroad, creating the myth of Ibiza as an island of freedom, harmony, and nightlife (the current image of the island).

FROM INDUSTRY TO TOURISM: THE CASE OF LX FACTORY IN THE ALCÂNTARA DISTRICT (LISBON)

In the past few years Lisbon has been through many changes, most of them related to the tourism growth. Alcântara is one of the neighbourhoods that became popular, once an industrial area that is presently experiencing a process of urban regeneration. Alcântara is probably the best district of Lisbon to recall the industrial era. At the same time, it has all the services that it needs to welcome visitors: diversity of tourist supplies; a vibrant image, trendy, but also authentic; a barycentric position between two well-known quarters (Baixa and Belém); a good accessibility, still being strengthened; a fast growth in accommodation supply. Arguably, an important role in the tourist development of Alcântara is played by the LX Factory, a former industrial area of around 23.000 m2, where important companies were located. LX Factory is considered a successful experiment of reconversion of an industrial space into a multifunctional complex, which still preserves the former factory atmosphere, although according to a contemporary formula. The LX Factory was inaugurated in 2008. It hosts design offices, art ateliers, start-ups, shops, restaurants, cafés, night clubs, co-working spaces, and even a hostel. It also hosts cultural activities, concerts, workshops, and a Sunday market of vintage and biological products. A previous research (Zarrilli et al., 2019) showed that LX Factory is by far the main tourist attractor of Alcântara. In this contribution, we will try to deeper investigate what we may call the LX Factory phenomenon, in terms of tourist image, flows, motivations and assessments. At this aim, a questionnaire was administered to a sample of shop owners located in its facilities. Conclusions allow us to understand LX Factory main issues from the shop owners’ perspective, regarding the commercial activity, the current image, the people who visit it, and their opinion about the neighbourhood.

Visual Servoing of Unknown Objects for Family Service Robots

Aiming at satisfying the increasing demand of family service robots for housework, this paper proposes a robot visual servoing scheme based on the randomized trees to complete the visual servoing task of unknown objects in natural scenes. Here, “unknown” means that there is no prior information on object models, such as template or database of the object. Firstly, an object to be manipulated is randomly selected by user prior to the visual servoing task execution. Then, the raw image information about the object can be obtained and used to train a randomized tree classifier online. Secondly, the current image features can be computed using the well-trained classifier. Finally, the visual controller can be designed according to the error of image feature, which is defined as the difference between the desired image features and current image features. Five visual positioning of unknown objects experiments, including 2D rigid object and 3D non-rigid object, are conducted on a MOTOMAN-SV3X six degree-of-freedom (DOF) manipulator robot. Experimental results show that the proposed scheme can effectively position an unknown object in complex natural scenes, such as occlusion and illumination changes. Furthermore, the developed robot visual servoing scheme has an excellent positioning accuracy within 0.05 mm positioning error.

Bestselling ‘beeldekens’. Hendrik Consciences “Hoe men schilder wordt” (1843) en de negentiende-eeuwse populaire beeldcultuur

Around the mid-nineteenth century, European literature abounded with book illustrations and the use of a pictorial style. Depending on the context and perspective, this literary fashion was associated with a threatening democratization of literature or perceived as a chance to reach new audiences. This article investigates whether the striking interactions between text and image in the internationally popular novella Hoe men schilder wordt (1843) by the Flemish author Hendrik Conscience can be regarded as a factor in its nineteenth-century popularity, and as a starting point for Conscience’s current image as an author of ‘popular’ literature, aiming at broad upcoming audiences.

Semantic Segmentation of Remote Sensing Image Based on GAN and FCN Network Model

Accurate remote sensing image segmentation can guide human activities well, but current image semantic segmentation methods cannot meet the high-precision semantic recognition requirements of complex images. In order to further improve the accuracy of remote sensing image semantic segmentation, this paper proposes a new image semantic segmentation method based on Generative Adversarial Network (GAN) and Fully Convolutional Neural Network (FCN). This method constructs a deep semantic segmentation network based on FCN, which can enhance the receptive field of the model. GAN is integrated into FCN semantic segmentation network to synthesize the global image feature information and then accurately segment the complex remote sensing image. Through experiments on a variety of datasets, it can be seen that the proposed method can meet the high-efficiency requirements of complex image semantic segmentation and has good semantic segmentation capabilities.

Colourlab Image Database: Geometric Distortions

Over the years, a high number of different objective image quality metrics have been proposed. While some image quality metrics show a high correlation with subjective scores provided in different datasets, there still exists room for improvement. Different studies have pointed to evaluating the quality of images affected by geometrical distortions as a challenge for current image quality metrics. In this work, we introduce the Colourlab Image Database: Geometric Distortions (CID:GD) with 49 different reference images made specifically to evaluate image quality metrics. CID:GD is one of the first datasets which include three different types of geometrical distortions; seam carving, lens distortion, and image rotation. 35 state-ofthe-art image quality metrics are tested on this dataset, showing that apart from a handful of these objective metrics, most are not able to show a high performance. The dataset is available at <ext-link ext-link-type="url" xlink:href="http://www.colourlab.no/cid">www.colourlab.no/cid</ext-link>.

How Good is Too Good? A Subjective Study on Over Enhancement of Images

For a long time different studies have focused on introducing new image enhancement techniques. While these techniques show a good performance and are able to increase the quality of images, little attention has been paid to how and when overenhancement occurs in the image. This could possibly be linked to the fact that current image quality metrics are not able to accurately evaluate the quality of enhanced images. In this study we introduce the Subjective Enhanced Image Dataset (SEID) in which 15 observers are asked to enhance the quality of 30 reference images which are shown to them once at a low and another time at a high contrast. Observers were instructed to enhance the quality of the images to the point that any more enhancement will result in a drop in the image quality. Results show that there is an agreement between observers on when over-enhancement occurs and this point is closely similar no matter if the high contrast or the low contrast image is enhanced.

RNIC-A Retrospect Network for image captioning

As cross-domain research combining computer vision and natural language processing, the current image captioning research mainly considers how to improve the visual features, less attention has been paid to utilizing the inherent properties of language to boost captioning performance. Facing this challenge, we proposed a textual attention mechanism, which can obtain semantic relevance between words by scanning all generated words. The Retrospect Network for image captioning(RNIC) proposed in this paper aims to improve input and prediction process by using textual attention. Concretely, the textual attention mechanism is applied to the model simultaneously with the visual attention mechanism to provide the input of the model with the maximum information required for generating captions. In this way, our model can learn to collaboratively attend on both visual and textual features. Moreover, the semantic relevance between words obtained by retrospect is used as the basis for prediction, so that the decoder can simulate the human language system and better make predictions based on the already generated contents. We evaluate the effectiveness of our model on the COCO image captioning datasets and achieve superior performance overthe previous methods.extraction function to extract the hidden unit information of multiple time steps for prediction, to solve the problem of insufficient LSTM prediction information. Experiments have shown that both model significantly improved the various evaluation indicators in the AI CHALLENGER test set.

Key Characteristics of the Current Image of a Law Enforcement Officer: Problems of Formation and Perception

Defined are the critical competence characteristics of the current image of a police officer, the main trends in its change and to determine the problems of forming a whole positive image of a law enforcement officer in the conditions of modern Russia. The article shows the relevance and necessity of a positive image of a police officer in the mass consciousness. The author has carried out an empirical study that made it possible to determine the main parameters of the image of a modern police officer. The scientific novelty of the work lies in the fact that in the course of a comparative analysis of the perceptions of a police officer by the internal and external segments of the target image audience, it was possible to establish not only the key image parameters of the police officer that are relevant at the moment, but also to determine the main contradictions in the image of a law enforcement officer and determine their main the reasons. As a result, it is shown that the current image of a police officer, on the one hand, is influenced by the stereotypes that were formed during the perestroika period, on the other, the images and ideas broadcast by the mass media, and on the third, the activities of the police themselves, perceived directly through personal contact. In addition, it was found that the main problem on the way of forming an integral favorable image of a law enforcement officer is the lack of a unified information policy in this area of activity, as well as the unregulated nature of multiple information flows by state structures, one way or another, affecting the perception of the activities of the internal affairs bodies of the mass audience, which ultimately gives rise to a contradictory and largely eclectic image.