A Data-Driven Approach for Tag Refinement and Localization in Web Videos

Tagging of visual content is becoming more and more widespread as web-based services and social networks have popularized tagging functionalities among their users. These user-generated tags are used to ease browsing and exploration of media collections, e.g. using tag clouds, or to retrieve multimedia content. However, not all media are equally tagged by users. Using the current systems is easy to tag a single photo, and even tagging a part of a photo, like a face, has become common in sites like Flickr and Facebook. On the other hand, tagging a video sequence is more complicated and time consuming, so that users just tag the overall content of a video. In this paper we present a method for automatic video annotation that increases the number of tags originally provided by users, and localizes them temporally, associating tags to keyframes. Our approach exploits collective knowledge embedded in user-generated tags and web sources, and visual similarity of keyframes and images uploaded to social sites like YouTube and Flickr, as well as web sources like Google and Bing. Given a keyframe, our method is able to select on the fly from these visual sources the training exemplars that should be the most relevant for this test sample, and proceeds to transfer labels across similar images. Compared to existing video tagging approaches that require training classifiers for each tag, our system has few parameters, is easy to implement and can deal with an open vocabulary scenario. We demonstrate the approach on tag refinement and localization on DUT-WEBV, a large dataset of web videos, and show state-of-the-art results.Comment: Preprint submitted to Computer Vision and Image Understanding (CVIU

Development of a Web Based Monitoring System for a Distributed and Modern Production

AbstractWeb technologies have experienced a rapid development in recent years. In particular web browsers enhanced their abilities because of the improvement of JavaScript, CSS3 and HTML5. Hence, richer web-based software solutions with an increasing range of functions are available. By using responsive web design (RWD), a technology to display content without resizing on different screens, developers are able to support a diverse range of devices with small effort.In order to enable a monitoring of the current status of a production system, signals of many different sensors, machine and production data are required. Combining microcontrollers with sensors to embedded sensors enables an efficient way to communicate with web services. Due to the strong decline of prices for semiconductor technologies, companies are able to set up production machines with these technologies at low costs.This paper presents a way to set up a distributed manufacturing control system by using common web technologies like RWD and embedded systems. We discuss advantages and drawbacks of web-based software solutions and show a methodical approach for the use in a modern production system. Finally, the functionality of the method is proven within an application example

Sistem Informasi Pelayanan Jasa pada Lucky Photo

The development of services has developed into the internet media, to make it easier for customers and employees in managing a job. In the problem of Lucky Photo, which covers services including printing, sales, stock of goods, purchases, and reports are not effective properly. The researcher aims to develop a service system entitled Service Information Systems at Lucky Photo. By building a web-based application, a waterfall method is needed to become a benchmark for the creation of a service information system, so the results will be obtained on a web-based application system to demand progress in a company, including services that become easier, easier customer service in conduct transactions, generate reports, and process customer data. So it can be concluded that with the construction of a new Service Information System it will be easier to make transactions, make it easier for customers, create reports, and process customer data that is embedded in the Mysql database which will become a well-systemized report

Extending sensor networks into the cloud using Amazon web services

Sensor networks provide a method of collecting environmental data for use in a variety of distributed applications. However, to date, limited support has been provided for the development of integrated environmental monitoring and modeling applications. Specifically, environmental dynamism makes it difficult to provide computational resources that are sufficient to deal with changing environmental conditions. This paper argues that the Cloud Computing model is a good fit with the dynamic computational requirements of environmental monitoring and modeling. We demonstrate that Amazon EC2 can meet the dynamic computational needs of environmental applications. We also demonstrate that EC2 can be integrated with existing sensor network technologies to offer an end-to-end environmental monitoring and modeling solution

3PAC: Enforcing Access Policies for Web Services

Web services fail to deliver on the promise of ubiquitous deployment and seamless interoperability due to the lack of a uniform, standards-based approach to all aspects of security. In particular, the enforcement of access policies in a service oriented architecture is not addressed adequately. We present a novel approach to the distribution and enforcement of credentials-based access policies for Web services (3PAC) which scales well and can be implemented in existing deployments

Developing a distributed electronic health-record store for India

The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

Workload characterization and customer interaction at e-commerce web servers

Electronic commerce servers have a significant presence in today's Internet. Corporations want to maintain high availability, sufficient capacity, and satisfactory performance for their E-commerce Web systems, and want to provide satisfactory services to customers. Workload characterization and the analysis of customers' interactions with Web sites are the bases upon which to analyze server performance, plan system capacity, manage system resources, and personalize services at the Web site. To date, little empirical evidence has been discovered that identifies the characteristics for Web workloads of E-commerce systems and the behaviours of customers. This thesis analyzes the Web access logs at public Web sites for three organizations: a car rental company, an IT company, and the Computer Science department of the University of Saskatchewan. In these case studies, the characteristics of Web workloads are explored at the request level, functionlevel, resource level, and session level; customers' interactions with Web sites are analyzed by identifying and characterizing session groups. The main E-commerce Web workload characteristics and performance implications are: i) The requests for dynamic Web objects are an important part of the workload. These requests should be characterized separately since the system processes them differently; ii) Some popular image files, which are embedded in the same Web page, are always requested together. If these files are requested and sent in a bundle, a system will greatly reduce the overheads in processing requests for these files; iii) The percentage of requests for each Web page category tends to be stable in the workload when the time scale is large enough. This observation is helpful in forecasting workload composition; iv) the Secure Socket Layer protocol (SSL) is heavily used and most Web objects are either requested primarily through SSL or primarily not through SSL; and v) Session groups of different characteristics are identified for all logs. The analysis of session groups may be helpful in improving system performance, maximizing revenue throughput of the system, providing better services to customers, and managing and planning system resources. A hybrid clustering algorithm, which is a combination of the minimum spanning tree method and k-means clustering algorithm, is proposed to identify session clusters. Session clusters obtained using the three session representations Pages Requested, Navigation Pattern, and Resource Usage are similar enough so that it is possible to use different session representations interchangeably to produce similar groupings. The grouping based on one session representation is believed to be sufficient to answer questions in server performance, resource management, capacity planning and Web site personalization, which previously would have required multiple different groupings. Grouping by Pages Requested is recommended since it is the simplest and data on Web pages requested is relatively easy to obtain in HTTP logs