Nokia

About: Nokia is a company organization based out in Espoo, Finland. It is known for research contribution in the topics: Signal & Mobile station. The organization has 16625 authors who have published 28347 publications receiving 695725 citations. The organization is also known as: Nokia Oyj & Oy Nokia Ab.

Method and apparatus for controlling and securing mobile phones that are lost, stolen or misused

Abstract: A method and apparatus is provided for controlling a mobile phone when it has been lost or stolen in order to prevent its use except to help the owner find it. Controlling the phone remotely may be implemented via a known Short Messaging System, for example. The security features provided are as follows: (1) Displaying contact information (phone number) of the owner on screen when the mobile phone can not start up normally, for example, due to an incorrect security code entry; (2) Setting the mobile phone in a secure state where it can only be used to call one number (Emergency calls are of course always possible.); and (3) Commanding the mobile phone to send information about its location and usage via SMS to a given number.

Emerging MPEG Standards for Point Cloud Compression

Abstract: Due to the increased popularity of augmented and virtual reality experiences, the interest in capturing the real world in multiple dimensions and in presenting it to users in an immersible fashion has never been higher. Distributing such representations enables users to freely navigate in multi-sensory 3D media experiences. Unfortunately, such representations require a large amount of data, not feasible for transmission on today’s networks. Efficient compression technologies well adopted in the content chain are in high demand and are key components to democratize augmented and virtual reality applications. Moving Picture Experts Group, as one of the main standardization groups dealing with multimedia, identified the trend and started recently the process of building an open standard for compactly representing 3D point clouds, which are the 3D equivalent of the very well-known 2D pixels. This paper introduces the main developments and technical aspects of this ongoing standardization effort.

Mobile communications matching system

Abstract: A wireless communications network comprises a server in a central location storing matching profiles for a plurality of users of the network. The matching profile for each user is stored in the server through the user's mobile unit or a secure page on the Internet. Each matching profile is corresponded with a respective mobile unit using the same identification information (ID) of the respective mobile unit utilized for carrying out phone calls. The server has a customizable variable matching algorithm and probes the matching profiles corresponding to the respective mobile units in a cell or group of cells for a match every time a new mobile unit subscribes into the cell or group of cells. When there is a match of matching profiles, the two persons are put in contact or advised of each other through a phone call or other communications method.

Conference call method and apparatus therefor

Abstract: A conference call facility is described in which one (2a) of a group of communication devices (2a,2b,2c,2d) connected to a low power radio frequency network (9) is able to set up a call to a party external of the network (9) and then selectively add further devices (2a,2b,2c) to the call under the control of the user of the one device (2a) The users of the other devices (2b,2c) are able to enable or disable the selection of their device in a conference call One or more of the communication devices may be a mobile radio telephone equipped with the necessary network interface (1)

Efficient aggregation for graph summarization

Abstract: Graphs are widely used to model real world objects and their relationships, and large graph datasets are common in many application domains. To understand the underlying characteristics of large graphs, graph summarization techniques are critical. However, existing graph summarization methods are mostly statistical (studying statistics such as degree distributions, hop-plots and clustering coefficients). These statistical methods are very useful, but the resolutions of the summaries are hard to control.In this paper, we introduce two database-style operations to summarize graphs. Like the OLAP-style aggregation methods that allow users to drill-down or roll-up to control the resolution of summarization, our methods provide an analogous functionality for large graph datasets. The first operation, called SNAP, produces a summary graph by grouping nodes based on user-selected node attributes and relationships. The second operation, called k-SNAP, further allows users to control the resolutions of summaries and provides the "drill-down" and "roll-up" abilities to navigate through summaries with different resolutions. We propose an efficient algorithm to evaluate the SNAP operation. In addition, we prove that the k-SNAP computation is NP-complete. We propose two heuristic methods to approximate the k-SNAP results. Through extensive experiments on a variety of real and synthetic datasets, we demonstrate the effectiveness and efficiency of the proposed methods.