The worst emperor? Assessing the effects of contested storytelling of iconic figures by the heritage destination: evidence from deep learning

Title of the dissertationConcept for sustainable development of tourist destination (on the example of Varna municipality)SupervisorProf. Svetla Rakadjiiska, University of Economics - Varna, BulgariaInstitution awarding the Ph. D. DegreeInstitute of Economics, Bulgarian Academy of Sciences, SofiaDate of defence17th April 2008Goal and objectives of the dissertationGoalThe main goal is to develop a concept for sustainable development of tourist destinations, and the specific mechanism for its implementation. The author's thesis is that achieving the necessary sustainable development of tourist destination requires clear concepts and specific mechanisms. These are elaborated on the basis of analysed sustainable development of the destination, taking into account specific environment and pre-conditions, in order to achieve a balance between the destination development and preservation of its natural and social environment.Objectives1. Presenting a concept for solving negative impacts of tourism development at the tourist destination.2. Defining a solution for preventing and eliminating the negative consequences of tourism development in the destination, while keeping or increasing its competitiveness and attractiveness.3. Defining a specific methodology and mechanism for the implementation of the solution for a balance between tourism development and long term development of the destination.Methodology1. Theoretical and comparative analysis.2. Methods of deduction and induction.3. Survey of 50 respondents, including representatives of tourist organisations, the local government, public institutions and NGOs. The survey was conducted in Varna municipality.4. Analysis of sustainable development of the tourist destination implementing a specially elaborated methodology.Results1. Elaborated concept for development of tourist destinations based on the theory of sustainable development.2. Elaborated specific mechanism for sustainable development of the tourist destination identified as a key determinant for sustainable development of the tourist destination.3. Created appropriate methodology for the analysis and assessment of sustainable development of the tourist destination.4. The methodology for analysis and assessment of sustainable development of the tourist destination as implemented and tested for Varna Municipality.5. The directions for sustainable development of Varna tourist destination are determined.Theoretical conclusionsThe idea of sustainable development is fundamental for tourism transformation, because the negative impacts on the natural and social environment are minimised fostering positive short and long-term economical and social benefits. Sustainable development of tourism can be better achieved when the specific characteristics and problems are raised and addressed, meaning they should be considered at the local level, namely the tourist destination.To achieve balance between the development of the tourist destination and preservation of the environment, key resources and values, that are critical for having a sustainable destination, should be identified and protected. This includes the elaboration of specific mechanism for sustainable development of the tourist destination, for example the preservation of the irreversible natural and social capital.Practical application of the dissertationThe concept of sustainable development of the tourist destination can be used for:- solving the problem of de-coupling the tourism development from its destructive exploitation of natural and social capital without decreasing the well-being of local population;- creating a strategy for the development of the tourist destination based on the principles of sustainable development.Content of the dissertationAbstract of chapter oneIn the first chapter, the concept of sustainable development of tourist destinations is elaborated. …

Kazakhstan, with its significant natural and cultural potential, faces difficulties in the field of sustainable development of tourist destinations, including due to mass tourism, which has a negative impact on the ecosystem and traditional way of life of local communities. This problem hinders the sustainable development of tourist destinations and reduces the attractiveness of tourist resources within the boundaries of the tourist area. In accordance with global trends, soft tourism is one of the important tools that can ensure the sustainable development of domestic tourist destinations. The article examines the concept of soft tourism as a tool that allows for the sustainable development of destinations in the regions of Kazakhstan. The authors analyzed the basic principles of soft tourism in modern conditions and considered ways of their application in the development of domestic tourist territories. The study examined, using statistical analysis methods, the hypotheses that soft tourism today is the main means of sustainable development of destinations, and modern tourists are interested in the transition from mass tourism to soft tourism, and try to take responsibility for the environment. As a result of the study, the authors identified the importance of soft tourism in ensuring sustainable development of the destination and noted its economic and social significance.

This paper aims to reveal the factors which are crucial for the sustainable development of rural-based tourist destination. This paper is possibly one of the few studies which apply rough sets theory (RST) analysis in destination image identification. Using Nanzhuang as a case study, this paper shows that RST analysis can identify the defining image attributes or attractors of a destination. RST analysis confirms the attractors that “pull” tourists to Nanzhuang are rural-tourism-related. RST decision rules reveal how an attribute single-handedly or a handful of attributes influence overall satisfaction. It also provides useful ideas on sustainable development of the destination.

The development of the economy’s tourism sector is one of the priority tasks set by the leadership of the Krasnodar Territory and Russian Federation. Thus, the construction of a model of the impact of tourist flows on the sustainability of the destination is very relevant. The authors developed a simulation model of the impact of tourist flows on the sustainable development of destination. The weighted net savings indicator was used as a measure of sustainability. This model can be further used in predicting the development of the studied sector of the economy. Using the developed tool for medium- and long-term planning will provide additional data to decision makers, reducing uncertainty, and thus improving the quality of management. The accuracy of the model is based entirely on publicly available statistics and expert assessments.

Huge amounts of useful data are easily generated and gathered currently at a rapid rate from a broad range of rich data sources in numerous applications and services in the real world. Data science applies database techniques, scientific and engineering methods, mathematical and statistical models, data mining algorithms, and/or machine learning tools to manage data, extract the useful information and discover the new knowledge from these big data. This explains why data science for big data applications and services has become a fundamental technology in providing novel solutions in various areas in business, engineering, health, humanities, natural sciences, social sciences, etc. (e.g., healthcare, manufacturing, social life). Usually, data science focuses on big data management, analytics and visualization. Once big data are managed (i.e., captured, curated, managed and processed), big data are analyzed with an aim to discover interesting knowledge and information, which is usually presented in text or table form. Consistent with a proverb that “a picture is worth a thousand words”, big data visualization as well as visual analytics helps to reveal and explain the discovered interesting knowledge and information. In this paper, we present (a) big data management with focus on information fusion and the data lake; (b) big data analytics and mining, with focus on frequent patterns; as well as (c) big data visualization with focus on a few visual analytic systems for visualizing big data and mined frequent patterns. For illustration, we discuss these three aspects of data science on coronavirus disease 2019 (COVID-19) data. This highlights some important aspects of data science for big data analyses, services, and smart data.

Objectives: Data visualization, the use of images to represent information, is now becoming properly appreciated due to the benefits it can bring to business. This paper focuses on the general background of data visualization and visualization techniques. Methods: Data visualization has the prospective to assist humans in analysing and comprehending large volumes of data, and to detect patterns, clusters and outliers that are not obvious using non-graphical forms of presentation. For this reason, data visualizations have an important role to play in a diverse range of applied problems, including data exploration and mining, Information retrieval and intelligence analysis. In real time various techniques have been used of which Geometric projection techniques, Iconographic display techniques, Pixel-oriented, Hierarchical techniques, Graph-based techniques are discussed. Findings: The major difficultly in big data visualization is to preserve any of the original dimensional information. The taxonomy detailed here show that the local and global structure of the data can be visualized in an interactive manner and has a massive advantage.

Subject area This case facilitates students of tourism and marketing to use Kapferer’s brand prism model to analyse the case. Study level/applicability This case can be used for tourism undergraduate and marketing students to make them understand the processes for revitalising and developing a destination brand to increase the number of visitors and become more attractive to tourists and visitors. The case highlights the major strategies used by the Sharjah Investment and Development Authority team to develop Sharjah as a family, entertainment, eco-tourism and heritage destination among the seven emirates of the United Arab Emirates. Case overview Sharjah is one of the emirates which form the United Arab Emirates. The case describes how a young leader of Sharjah developed destination Al Qasba as a tourist attraction, which was earlier not frequented by family and investors. After that, he was vested with the responsibility of developing Sharjah into an investment and heritage destination in United Arab Emirates. The case details how the team used different strategies to attract investors to the destination to make it more attractive to tourists as well the dwellers of the emirates. Expected learning outcomes To understand the process of sustainable destination development or place development practices. To analyse the case using using existing models or frameworks such as Kapferer’s brand identity prism or Aaker’s theory and any other. To recommend suggestions in improving the destination development strategies. Supplementary materials Teaching Notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes. Subject code CSS 12: Tourism and Hospitality.

Thousands of network cameras stream real-time visual data for different environments, such as streets, shopping malls, and natural scenes. The big visual data from these cameras can be useful for many applications, but analyzing the large quantities of data requires significant amounts of resources. These resources can be obtained from cloud vendors offering cloud instances (referred to as instances in this paper) with different capabilities and hourly costs. It is a challenging problem to manage cloud resources to reduce the cost for analyzing the big real-time visual data from network cameras while meeting the performance requirements. That is because the problem is affected by many factors related to the analysis programs, the cameras, and the instances. This paper proposes a cloud resource manager (referred to as manager in this paper) that aims at solving this problem. The manager estimates the resource requirements of analyzing the data stream from each camera, formulates the resource allocation problem as a 2D vector bin packing problem, and solves it using a heuristic algorithm. The resource manager monitors the allocated instances; it allocates more instances if needed and deallocates existing instances to reduce the cost if possible. The experiments show that the resource manager is able to reduce up to 60 percent of the overall cost. The experiments use multiple analysis programs, such as moving objects detection, feature tracking, and human detection. One experiment analyzes more than 97 million images (3.3 TB of data) from 5,310 cameras simultaneously over 24 hours using 15 Amazon EC2 instances costing $188.

This study, based on the stakeholder theory, explores the sustainable development of sport event tourism destinations from the perspective of conflicts and demands of the core stakeholders. The core stakeholders of sport event tourism destinations include the government, sport enterprises, tourists, and residents. Through detailed analysis of the performance and causes of the core stakeholders’ interest conflicts and demands, we can draw the enlightenment of the sustainable development of sport event destinations in China as follows: introducing a monitoring mechanism to ease conflicts, establishing a communication mechanism to reduce conflicts, integrating development to guide demands, and recognizing the equal status to stimulate demands.

The authors on the basis of a representative analysis of expert opinion assessed the major problems arising in the development of sustainable tourism management system, and especially rural tourism. The key areas of work for the forming effective investment policy in sustainable tourism are identified, as well as challenges in the formation of consumer interest and demand for sustainable tourism products and their solutions are revealed. The scientific staff of the department UNWTO-RIAT and research laboratory for sustainable development of tourist destinations of Moscow branch of RIAT during the expert survey, conducted with the support of the Federal Agency for Tourism within the framework of scientific cooperation with the Organization United Nations Environment Programme (UNEP) and World Tourism Organization (UNWTO) in 2015 surveyed 92 experts in the field of tourism from 19 regions of Russian Federation. The study identified the main problems limiting and inhibitory management processes, as well as the main directions of work for the sustainable development of tourist destinations, which should be in focus of legal regulation of tourism development in the country and in the regions. The research results can be used by tourism authorities at the federal, regional and municipal levels for the formation of effective management stratgy, investment policy and the territorial system of marketing tourist destinations. The results of the expert survey can become a base for research and be used in the educational process. For the successful implementation of sustainable tourism development principles at all levels (federal, regional, municipal) the management and investment models should be clearly elaborated and business process algorithms for project management of sustainable development of tourist destinations and their promotion on the market should be created. All parties need to clearly understand and respect the interests of the subjects of relations, and in this case they need to have a common goal – an effective sustainable development.

Big Data, structured and unstructured data, contains millions attributes in multiple dimensions. This has arisen threeissues: 1) how to measure the structured and unstructured multidimensional data patterns for Big Data analysis; 2) how to display multidimensional data patterns in normal size of screen; 3) how to optimize the data attributes in Big Data visualization. In this work, we have visual analyzed Big Datavariety based on the complexity of multidimensional data. Firstly, we introduce2D dimension which divided the multidimensional dataset into 2D data pattern subsets, and then establish 2D-Ratio algorithm to measure 2D dimension in multiple data patterns. Second, we createtwo additional parallel axes by using 2D-Ratio to compare 2D dimensional patterns for visualization. Third, the dimension clustering and shrunk attribute have been introduced in 2D-Ratio parallel coordinates to reduce the data over-crowed. The experiment shows that our model can be efficiently and accurately used for Big Data analysis and visualization.

Predicting Atrial Fibrillation from Automated Measurements of Left Atrial Volume Using Routine Chest CT Examination: Overlooked and Underrecognized Risk Factors.

Visitor management and sustainable destination management nexus in Zegie Peninsula, Northern Ethiopia

Cultural landscape changes in the built environment at World Heritage Sites: Lessons from Bukovina, Romania

The digital transformations and use of healthcare information system, electronic medical records, wearable technology, and smart devices are increasing with the passage of time. A variety of sources of big data in healthcare are available, such as biometric data, registration data, electronic health record, medical imaging, patient reported data, biomarker data, clinical data, and administrative data. Visualization of data is a key tool for producing images, diagrams, or animations to convey messages from the viewed insight. The role of cardiology in healthcare is obvious for living and life. The function of heart is the control of blood supply to the entire parts of the body. Recent speedy growth in healthcare and the development of computation in the field of cardiology enable researchers and practitioners to mine and visualize new insights from patient data. The role of visualization is to capture the important information from the data and to visualize it for the easiness of doctors and practitioners. To help the doctors and practitioners, the proposed study presents a detailed report of the existing literature on visualization of data in the field of cardiology. This report will support the doctors and practitioners in decision-making process and to make it easier. This detailed study will eventually summarize the results of the existing literature published related to visualization of data in the cardiology. This research uses the systematic literature protocol and the data was collected from the studies published during the year 2009 to 2018 (10 years). The proposed study selected 53 primary studies from different repositories according to the defined exclusion, inclusion, and quality criteria. The proposed study focused mainly on the research work been done on visualization of big data in the field of cardiology, presented a summary of the techniques used for visualization of data in cardiology, and highlight the benefits of visualizations in cardiology. The current research summarizes and organizes the available literature in the form of published materials related to big data visualization in cardiology. The proposed research will help the researchers to view the available research studies on the subject of medical big data in cardiology and then can ultimately be used as evidence in future research. The results of the proposed research show that there is an increase in articles published yearly wise and several studies exist related to medical big data in cardiology. The derivations from the studies are presented in the paper.