Abstract Although a lot of research work has been done concerning schema changes that deal with basic components of XML Schemas, like element and attribute declarations, simple types, and complex type definitions, the current literature of the XML database field does not include any paper that studies changes of advanced concepts of XML Schemas, like XML namespaces, local (or global) qualified (or unqualified) declarations, and schema definition styles (e.g.,... Although a lot of research work has been done concerning schema changes that deal with basic components of XML Schemas, like element and attribute declarations, simple types, and complex type definitions, the current literature of the XML database field does not include any paper that studies changes of advanced concepts of XML Schemas, like XML namespaces, local (or global) qualified (or unqualified) declarations, and schema definition styles (e.g., Russian Doll, Garden of Eden). In this paper, we study how XML namespace evolution is handled in an XML environment that supports both schema and document versioning. To the best of our knowledge, this is the first work on such a topic. Indeed, we propose a systematic approach that allows specifying changes on XML namespaces defined in XML Schemas, and propagating their effects to underlying XML documents, while maintaining all XML schema and XML instance versions. Read More Read Less

Abstract As social media becomes an important platform for organizations to use to interact with users, the ability to understand user opinions in social media communications has gained increased attention. One of the most popular approaches for exploring user opinions is sentiment analysis, which employs natural language processing, statistics, or machine learning to extract the sentiment of a text unit in terms of positive or negative attitudes. However, the... As social media becomes an important platform for organizations to use to interact with users, the ability to understand user opinions in social media communications has gained increased attention. One of the most popular approaches for exploring user opinions is sentiment analysis, which employs natural language processing, statistics, or machine learning to extract the sentiment of a text unit in terms of positive or negative attitudes. However, the effectiveness, interpretation, and accuracy of sentiment analysis rely heavily on the context in which it is conducted. In this paper, we investigate three sentiment analysis techniques for Twitter use by governments with their citizens, including a lexicon-based approach, a machine learning-based approach, and a hybrid approach. Our results reveal that, while each technique is developed based upon different rationales, the results are statistically robust and comparable. The study provides new insights into sentiment analysis in the context of government uses of social med Read More Read Less

Abstract Digital image inpainting pertains to the reconstruction of missing or damaged portions of images in a manner that is not detectable to the observer. This study evaluates the Criminisi algorithm for digital image inpainting and proposes four improvements. First, a new priority function was introduced using piecewise function to adjust the sequence of inpainting process and change the operation used from multiplication to addition under certain conditions. This... Digital image inpainting pertains to the reconstruction of missing or damaged portions of images in a manner that is not detectable to the observer. This study evaluates the Criminisi algorithm for digital image inpainting and proposes four improvements. First, a new priority function was introduced using piecewise function to adjust the sequence of inpainting process and change the operation used from multiplication to addition under certain conditions. This adjustment improved the flexibility of the algorithm thereby avoiding incorrect filling sequence caused by rapid decay of data term. Second, Sobel operator instead of the traditional gradient direction was used to improve the computation of isophote. This approach first restored points on the isophote, which is beneficial to information fusion. Third, a new matching function was proposed and a new matching search method was employed to identify samples in the neighborhood of the damaged region based on similarity. This improvement created the nearest optimal matching block used for inpainting. Finally, a new formula of smoothing error propagation for updating confidence value was defined. This method ensured the correct sequence of synthesis from the periphery to the center. Experimental results show that this improved algorithm yields satisfactory inpainting results and improves repair efficiency. Read More Read Less

Abstract E-commerce cloud warehouse is a logistic service model developed to meet e-commerce demands. The model is characterized by multi-site warehousing, big data prediction, accurate stock, and nearby distribution. A set of unified management standards must be established to effectively address the difficulty in ecommerce cloud warehouse management. For the convenience of quantitative grading management of branch warehouses, the method for confirming ecommerce cloud warehouse grading based on mass simulation data... E-commerce cloud warehouse is a logistic service model developed to meet e-commerce demands. The model is characterized by multi-site warehousing, big data prediction, accurate stock, and nearby distribution. A set of unified management standards must be established to effectively address the difficulty in ecommerce cloud warehouse management. For the convenience of quantitative grading management of branch warehouses, the method for confirming ecommerce cloud warehouse grading based on mass simulation data analysis was proposed in this paper. The discrete event simulation model was built, the simulation experiment was designed, and the mass experimental data were analyzed and integrated to finally obtain the model of e-commerce cloud warehouse grading. The effectiveness of the grading model was also verified. Analysis results suggest that historical data cannot guarantee adequate big data size and sufficiently high data accuracy for the issues of e-commerce cloud warehouse grading. Thus, experimental data must be obtained by building a discrete event simulation model. The validity and universality of the simulation model are necessary to ensure the rationality of experimental data. Through simulation modeling, simulation experiment design, and experimental data mining, the quantitative standards for e-commerce cloud warehouse grading can be obtained. Verification results show that the quantitative grading results are consistent with the experience-based grading results. This research proves the feasibility of obtaining the quantitative standards for e-commerce cloud warehouse grading based on mass simulation experimental data. The proposed grading model is suitable for e-commerce cloud warehouses of different industries. Read More Read Less

Abstract To develop the methodological recommendations based on the concept of intellectual capital for the subjective evaluation of the importance of its components for a particular business and their vulnerability to risks leading to a decrease in the value of intellectual capital with the information technology is proposed. Using the morphological analysis technique, the authors highlight the key components of intellectual capital that are valued in terms of utility... To develop the methodological recommendations based on the concept of intellectual capital for the subjective evaluation of the importance of its components for a particular business and their vulnerability to risks leading to a decrease in the value of intellectual capital with the information technology is proposed. Using the morphological analysis technique, the authors highlight the key components of intellectual capital that are valued in terms of utility and rarity. Using questionnaire, a survey carried out in the form of interviews with 72 representatives of small, medium-sized and large business; the importance of structural components of intellectual capital has been identified for different size businesses and influence of information technology, as well as the distribution of risks of utilityand rarity loss has been obtained depending on types of intellectual capital. The differences in the structure of the intellectual capital of small, medium-sized and large organizations of the Rostov region, associated with the increase of the importance of organizational capital with the consolidation of the organization, are identified. It is established that the greatest concerns among respondents is associated with the risk of utility loss of existing intangible assets, while risks, leading to the loss of rarity, are not perceived as serious danger. The results of the study allow defining strategic pathways to invest funds in maintaining and increasing the value of intellectual capital using the risk-based approach. Intangible assets,which are identified as most important, as well as loss of their value to the specific organization, vulnerable to the risks, should become priorities in the intellectual capital cost management. Read More Read Less

Abstract We present a new method for simulating swarms and herds of animals using a modified version of particle swarm optimization algorithm [1], a robust collision detection and resolution system and a mechanism for restricting velocity and angular acceleration to make the movement natural as possible. Our model is designed to simulate the search for food butitcan be used for locating safe spots and predatorprey interaction by changing the... We present a new method for simulating swarms and herds of animals using a modified version of particle swarm optimization algorithm [1], a robust collision detection and resolution system and a mechanism for restricting velocity and angular acceleration to make the movement natural as possible. Our model is designed to simulate the search for food butitcan be used for locating safe spots and predatorprey interaction by changing the fitness function, in which each swarm member interacts with the environment and the other swarm members to produce a movement that leads the member and the swarm change their position to a more fitting one. Read More Read Less