Differential radio map-based robust indoor localization While wireless local area network-based indoor localization is attractive, the problems concerning how to capture the signal-propagating character in the complex dynamic environment and how to accommodate the receiver gain difference of different mobile devices are challenging. In this article, we solve these problems by modeling them as common mode noise and develop a localization algorithm based on a novel differential radio map approach. We propose a differential operation to improve the performance of the radio map module, where the location is estimated according to the difference of received signal strength (RSS) instead of RSS itself. The particle filter algorithm is adopted to realize the target localization and tracking task. Furthermore, to calculate the particle weight at arbitrary locations, we propose a local linearization technique to realize continuous interpolation of the radio map. The indoor experiment results demonstrate the effectiveness and robustness of our approach. Ubiquitous computing and communication have become popular with the development of wireless communication technology over the last decade. The need for location information to capture contexts and configure them into the computing and communication processes, coupled with the unavailability of global positioning system (GPS) in indoor environment, has triggered increased research interest in indoor localization. Recently, numerous localization systems have been developed based on the received signal strength (RSS) of the wireless local area networks (WLANs). The advantage of these systems is that the cost of deploying a specialized infrastructure is avoided. However, building an indoor localization system based on WLAN is a challenging problem due to the complex indoor signal propagation character and different hardware solutions of different mobile devices.. Radio map-based approach is the most widely adopted method to realize indoor localization [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] . The essential idea is to construct the radio map by dividing the whole deployment area into cells and then collecting the RSS measurements from various access points (APs) at each cell, and thus a mobile device can be localized by matching the observed RSS vector with the radio map. In the indoor environment, the RF signal propagation is unpredictable and affected by several factors, such as the presence and movement of human beings, relocation of furniture, multi-path fading, humidity and temperature variations, and closing or opening doors. In such a dynamic environment, the radio map obtained in one time period may not be applicable to other time periods. To solve this problem, Chen et al. [9] built multiple radio maps under various environmental conditions and used sensors to identify the current environment so as to select the most approximate map. Yin et al. [10] offset the variational environmental factors by adding some reference points as sniffers to capture the dynamic characters of the environment and rebuilt the radio map with regression method. Although these methods partially overcome the negative effect of dynamic environment, the need for specific infrastructures, such as the environmental sensors and sniffers, makes these methods impractical. More recently, Fang and Lin [11] adopted a temporal sequence of RSS samples as the character vector of the radio map so as to overcome the multipath problem. While this approach demonstrates the effectiveness for the multipath effect, it is of little use for other problems. The question of how to adapt to the dynamic complex environment without any additional infrastructure is a promising and challenging problem. Because with the changing of environment, it is most likely that the RSS measurements in one location from different APs are prone to shift in the same direction, we can model the dynamic of the indoor environment as the common mode noise. Inspired by the fact that differential signals are widely used in the circuit design to restrain the common mode noise, we adopt the difference of RSS from different APs as the characteristic signal of the radio map. Suppose the RSS measurement vector from three APs are (RSS 1 , RSS 2 , RSS 3 ). Instead of treating it as the fingerprint to realize localization, we adopt the differential vectors (RSS 1 -RSS 2 , RSS 1 -RSS 3 , RSS 2 -RSS 3 ) as fingerprint. Compared with the traditional RSS vector, the differential vector can be effectively adapted to the dynamic indoor environment. Furthermore, it can accommodate the receiver gain difference of different mobile devices. We are aware that the receiver gains of even the same type of devices are different, let alone different types of devices. If the device used in the localization phase is different from that used in the radio map building phase, then the estimation error will be increased dramatically. Because the difference of receiver gain offsets the RSS measurements in the same direction, we can also model it as common mode noise.. In this article, we propose a novel robust indoor localization algorithm under the framework of Bayesian filter. The particle filter (PF) [12, 13] is adopted to achieve the localization and tracking task, which makes full use of the history observation to improve the estimation accuracy. The differential radio map is used for building the observation likelihood for the PF algorithm so as to solve the dynamic environment and different receiver gain problem. For the sake of predicting signal strength measurements at arbitrary locations so as to calculate particle weight and improve localization accuracy, we also adopt a local linearization technique to realize continuous interpolation of the radio map.. This article is organized as follows. Section II provides a brief overview of the indoor localization problem. In Section III, the definition of the differential radio map is given, and the localization architecture is described from the view of system. The detailed implementation of our differential radio map-based PF algorithm is presented in Section IV. Section V validates our algorithm by evaluations. Finally, the conclusion is drawn in Section VI. To address the problem of realizing accurate localization in complex dynamic environment in the WLAN which A B Figure 7 Impact of the radio map spacing. is made up of different types of devices, we proposed a novel DRMBL algorithm under the Bayesian framework. We proposed a differential strategy to overcome the common mode noise and a continuous interpolation technique to accurately realize the particle weight calculation. The experiments validated our proposed schemes, and revealed that DRMBL algorithm could achieve reasonable localization results under challenging background conditions. The schemes proposed in this article are generic and could be adopted by other localization systems.. Abbreviations CDF: cumulative distribution function; DRMBL: differential radio map-based Bayesian localization; GPS: global positioning system; PDF: probability distribution function; RSS: received signal strength; SDM: signal-distance map; WLAN: wireless local area network. Figure 10 Impact of the radio map spacing with interpolation. We highlight some of the experience on the DRMBL algorithm, including the differential strategy, the density of training points, and the characteristic of the PF algorithm.. It should be mentioned that the differential strategy is generic. It can be adopted by any localization system as long as they use the RSS as measurement, such as WLAN, Zigbee, Bluetooth, and GSM-based systems. If N APs are detected, ideally there are C 2 N pairs of differential RSS measurements. For simplicity, we select the AP with the strongest RSS as the reference AP and select N -1 differential RSS measurements relative to it according to Equation 2. Computational resources permitting, one can utilize all the differential measurements to improve the performance. The performance of the differential strategy is greatly affected by the reference AP. Therefore, the selection of the most appropriate reference AP is vital for the DRMBL algorithm. We have verified four criteria: AP with the strongest RSS, AP with the weakest RSS, AP with the minimum standard deviation, and AP with the maximum standard deviation. Table 3 illustrates that the criterion of selecting the AP with the strongest RSS is superior to others.. As has been seen from Figure 7a , one shortcoming of the differential strategy is that it requires dense training points. Our DRMBL algorithm solves this problem with continuous interpolation technique. When the differential strategy is adopted, we suggest that the interpolation technique could be used for generating some virtual training points. Figure 10 demonstrates the results of DRMKNN and DRMPL with interpolation technique used in the radio maps of 4.8 and 9.6 m spacings. Moreover, with the essential similarity to PF algorithm, DRMBL deals with the location estimation problem by means of prediction and observation update process. In this article, we suppose that the algorithm knows nothing about the prior knowledge; if we have some prior information about the velocity or direction, the tracking accuracy will be improved significantly. Figure 11 demonstrates the localization error for tracking the same trace as that of Figure 9a while having prior velocity information. The estimation error is remarkably reduced, and the average localization error is only 1.17 m. Indoor localization with WLAN has been an active research area in the last decade. Honkavirta et al. [14] presented a survey of location fingerprinting methods, and Seco et al. [15] reviewed the indoor localization algorithms from the aspect of mathematic. In this section, we give a brief overview of some key research findings in this area. Considering the needs of building the radio map, we divide the methods into map-based and non-map based algorithms.. The principle of the radio map based method is to fingerprint each cell of the deployment area with a RSS measurement vector from various APs. A mobile device is then localized by matching the observed RSS against the radio map. To the best of our knowledge, radio map-based indoor localization was first introduced by Bahl and Padmanabhan [1] ; they proposed the wellknown RADAR system and realized the localization using the deterministic fingerprint. Since then some schemes have been proposed to reduce the manual calibration effort and make the radio map more robust so as to improve the localization accuracy. To reduce manual effort, Deasy and Scanlon [2] proposed a technique to estimate the radio map using a signal propagation model. They used an instrument to measure the signal propagation model parameters and built the simulated radio map automatically. Compared with the traditional measured radio map, although the building of the simulated radio map is time efficient, the localization accuracy degenerates significantly. Tsai et al. [3] also adopted the signal propagation model and the interpolation technique to build the map. Chai and Yang [4] proposed a scheme to reduce the sample location in the radio map building phase so as to reduce the manual effort and developed an interpolation technique to effectively patch a radio map. Philipp [5] introduced a collaborative way to build the radio map with the collaboration of users, each user could create and manage the map, and the whole map can be built gradually with the participation of more and more users. Recently, Chintalapudi et al. [6] also developed a collaborative localization system named EZ which did not require any knowledge about the RF environment. EZ adopted an improved genetic algorithm to solve the constraint equations defined by signal propagation models so as to calculate the parameters of the APs and training points. However, it requires the mobile device equipped with GPS, and it can work well only if there are enough APs to provide excellent coverage. In order to make the radio map more informative, Wu et al. [7] adopted the probability distribution function (PDF) as the fingerprint of the map. Youssef and Agrawala [8] also employed a stochastic description of the radio map. As has been discussed above, with the purpose of adapting the radio map to the dynamic environment, Chen et al. [9] , Yin et al. [10] , and Fang and Lin [11] have made some pioneering research contributions. As a continuation of these schemes, our proposed approach adopts the differential radio map to make the algorithm more robust and a local linearization technique to realize continuous interpolation of the radio map.. Besides the above research studies, some schemes based on the deterministic and proba-bilistic framework have also been developed. Lim et al. [16] used the truncated singular value decomposition to calculate the signal-distance map (SDM) based on the online measurements between the APs. Although the dynamic SDM makes it possible to capture the challenging dynamic indoor environment, the requirements of the high AP density and the modification of commercial AP's software make the scheme impractical. Hossain et al. [17] proposed a robust localization algorithm that could make use of multiple wireless techniques. Schwaighofer et al. [18] first adopted the Gaussian process (GP) as a non-parametric tool to realize the approximation of the radio map of cellular network. Ferris et al. [19] introduced the GP into the WLAN-based indoor localization. Compared with other regression models, the GP takes into account the noise of the observation and provides the ability to approximate nonlinear signal propagation model. Madigan et al. [20] adopted a Bayesian hierarchical approach to realize indoor localization, which eliminated the need of knowing the locations of the training points. Huang et al. [21] proposed a similar Bayesian algorithm and introduced the stochastic properties of measurement errors and the reliability of the measurement data into the factor graph framework so as to improve the accuracy. Wymeersch et al. [22] also proposed a Bayesian localization algorithm and took the cooperation of the nodes into consideration to improve the accuracy. Feng et al. [23] employed the compressive sensing theory to analyze the localization problem. The localization problem is modeled as a sparse question and can be solved by the L1 minimization. While these methods cut down the measurement effort and partially adapt to the dynamic environment, they still require effort in terms of placing sniffers, modifying commercial AP's software, obtaining the knowledge of AP placement, and of complex computation.

O O O O B I O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O B O O B O O B O O O O O O O O O O O O O O O O O B O B O O B O B O O B O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Digital Media Information Base This paper surveys recent research activities on three major areas of digital media information base, namely, video database systems as a typical example of temporal application, database systems for mixed reality as an instance of spatial application, and kansei management for digital media retrieval as a case of humanistic feelings application. Current research results by the project Advanced Database Systems for Integration of Media and User Environments are reported. Digital media information base is an extended notion over multimedia database systems [1] , [2] . It replaces the term multimedia by digital media, to make clear that one of the essential characteristics of so called multimedia information is digitization. It also extends the term database to information base, to claim that database systems should incorporate such new capabilities as to handle temporal and spatial information, and to manipulate human feelings (kansei).. This paper surveys recent research trends on digital media information base. It focuses on three major areas, namely, video database systems as a typical example of temporal application, database systems for mixed reality as an instance of spatial application and kansei or feeling management for digital media retrieval as a case of human senses application. Some research results by the Grant-in-Aid for Scientific Research on Priority Areas, "Advanced Database Systems for Integration of Media and User Environments" or simply Advanced Database Systems are reported.. The rest of this paper is organized as follows. Section 2 reviews research trends on video database systems. Section 3 summarizes research activities on mixed reality, or databases augmented and mixed with virtual reality. Section 4 discusses how we should in-corporate kansei or humanistic aspects into database architecture. Brief concluding remarks are given in Sect. 5. This paper surveyed recent research activities on three major areas of digital media information base. We have reviewed several database systems that can handle temporal information (video data), spatial information (mixed reality), and kansei information (humanistic feelings). Current research results by the Advanced Database Systems are summarized. All the researches indicate that database systems incorporating those capabilities are now growing up to be what we call information base here, however researches on integrated or unified modeling of information base for digital media is still underway. Due to current advance of computer technology, realtime three dimensional computer graphics (3D CG) virtual spaces can be affordable for ordinary users. Real- time 3D CG allows us to simulate phenomena in the real world. 3D experiences can be realized in the virtual spaces as same as in the real world. In order to build a virtual space corresponding to a part of the real world, a large amount of spatial data must be treated on computer. Thus, database technology is necessary to manage large scale virtual spaces. Real-time 3D CG is also considered advanced multimedia user interfaces. The cost of processing 3D CG is no longer high. Real-time 3D CG is used even for most of the recent TV games. We should create new and more efficient style visual interfaces using real-time 3D CG [23] . Our brain has a function of prominent 3D spatial perception evolved in the real world. 3D visual interfaces are natural and desirable for human's perception. Current 3D CG interface is new and naive but more sophisticated visual interfaces will appear in the near future. Consequently, it is possible that most visual interfaces on the computer become virtual spaces. From this viewpoint, 3D virtual spaces are important as advanced visual user interfaces of databases.. Computer network systems provide the function of sharing real-time data among distributed computers. On the other hand, conventional database systems have dealt with batch processing for past data or a large number of delay permissible simple transactions for small data. One of the characteristics of virtual space applications is real-time interactivity for broad band shared data. Database systems for 3D virtual spaces need to support real-time interaction with broad band shared data. Realizing the capability of managing real-time broad band data in databases is equivalent to embedding the capability of real-time broad band data communication into database systems.. We, humans, live on our mother Earth. Much information related to us can be related to locations of the earth. Also, many 3D virtual spaces must be related to the earth, even if there are many imaginary virtual spaces. There are many aspects of virtual space data and applications related to the earth, such as variety of uses, wide range of scales from 1:1 to 1:100,000,000, live sensing data, and historical/temporal data. The Earthrelated virtual space applications must be considered as promising ones on Internet [24] . Since the applications have not yet been studied well, it is important to construct fundamental models and reveal unsolved issues on the applications. Because of a large scale and a wide variety of spatial data related to the earth, there are many difficult problems to integrate the data using current technologies of databases and virtual reality. Furthermore, this application must reveal weak points of the technologies. In the remainder of this chapter, we discuss primal features of virtual space applications or mixed reality [25] related to the earth.

B I O O O O O O O O O O O O O B I O O O O B I O O O O O O O B I O B I O O O O O O O B O O B I O O O O O O O O O O O O O O O B I O O O O O O O O O B I O O O O O O O O B I O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O B O O O O O O O B I O O O O O O O O O O B I O O O O O O O B I O B I O O O O O O O B O O O O B I O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O B I O O O O O O B I O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O B I O O O O O O O O O B I O B O O O O O O O O O B I O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O


An imaginary friend that connects with the user's emotions In this paper we present a metaphor of an Imaginary Friend that walks along with the user. Due to a special bond with the user, the Imaginary Friend can see the emotions that the human companion is feeling glowing around her. As the user moves around she leaves behind emotion cookies that the Imaginary Friend will collect and treasure. In order to enable rich and playful interactions in the virtual-real continuum the implementation of the Imaginary Friend responds to motion, to the electrodermal activity and resorts to GPS coordinates. The Imaginary Friend was tested with several users to evaluate the connection between humans and this creature that lives in the border that separates imagination and reality. Sometimes, one wants a friendly shoulder to lean on or someone with whom to share the good and the bad times. Here, we propose a metaphor of an imaginary friend who accompanies the user and to whom the user can confide her emotions.. Imaginary friends, though nonexistent, provide many advantages to their human companions. According to Eva Hoff, imaginary friends can help one get through difficult or stressful times [1] and children with imaginary friends are significantly more creative [2] . Imaginary friends are common among children. Approximately 50% of children aged between 5 and 12 years old have experiences with imaginary friends [3] . Perhaps many adults also have imaginary friends but lack the courage to assume it because they feel it is too childish a thing for their age. That is not the case of adult fiction writers, as 92% of them experience the illusion that their characters have independent thoughts, words or actions, as if they were real persons [4] .. Countless people write to an imaginary friend that exists only in the pages of a diary. One of the most famous of these imaginary friends is Kitty, who accompanied Anne Frank through the difficult times in the attic during the Second World War. Another well know imaginary friend is Hobbes from the Calvin and Hobbes cartoon books by Bill Watterson. Hobbes is a tiger that accompanies Calvin and discusses everyday matters with him. Hobbes is really just a stuffed tiger but, for Calvin, Hobbes is much more than a mere toy. He is alive and has feelings, just like a real person.. The Imaginary Friend proposed here walks by the side of the user. The user can confide the emotions she is feeling to the Imaginary Friend. This concept is further detailed in Section 2 and the user tests can be found in Section 3. In Section 4 a proposal to expand the Imaginary Friend to a multiplayer game is presented. In this paper a metaphor of an Imaginary Friend and the implementation of that metaphor were presented. The Imaginary Friend walks along the user and collects the emotion cookies that user leaves behind. The user can later visualize those cookies inside a jar where the Imaginary Friend stored them ( Figure 10) . It is also possible to consult a list with the past emotions ( Figure 11 ) or the places where the emotion cookies were collected ( Figure 12 ). The Imaginary Friend resorts to variations in the electrodermal activity to know when to ask the user how she is feeling. The data obtained with the electrodermal activity sensor is transmitted via Bluetooth to the mobile phone where the Imaginary Friend's application is running. The mobile phone is connected to a pico projector that is attached to the user's backpack should strap ( Figure 2 and Figure 4 ) and projects the Imaginary Friend on the floor. The Imaginary Friend mimics the user, walking when she is walking and standing still when the user is standing still. This behavior was implemented resorting to the accelerometer of the mobile phone.. Assuming that devices capable of monitoring electrodermal activity may, one day, become as common as mobile phones equipped with GPS and accelerometer functionality, a proposal for a multiplayer game, where users resort to their emotions to compete for the rule of emotion castles, is presented.. The interaction of the Imaginary Friend with users was tested. Results indicate that 82% felt an emotional connection with the Imaginary Friend. 63% thought it was fun to register their emotions. Fun was, furthermore, the most frequent expression, chosen by the users, to describe the Imaginary Friend. 90% of the users also considered that the Imaginary Friend could help them reflect about their emotions and take import conclusions about their life.. The electrodermal activity was an adequate indicator to know when to question the users as 55% of them thought the Imaginary Friend questioned them the appropriate number of times. 45% thought the Imaginary Friend questioned them many times, but no user responded that the Imaginary Friend questioned her too many times.. However, 64% of the users felt that certain emotion tags were missing among the ones presented by the Imaginary Friend. We could simply add extra emotions to the ones presented in Figure 9 , but if there are too many emotion tags it will be more difficult for the user to find the one she wants. As emotion tags are differentiated by color, it will also be more difficult to find a unique color for every emotion tag. Future work will still have to be done in what concerns the emotion tags. One possibility to better organize the emotion tags is to take into consideration the arousal and valence of each emotion. According to Rosalind Picard a device who knows the emotions of the person who is using it will open possibilities for new and imaginative interactions in games [12] . Some even foresee that, someday, we shall use devices that interpret our emotions and inform us of everything we need to do to be happy [13] .. The Imaginary Friend is an application that is in touch with the user's emotions. Several other forms to interact with the user's emotions have already been proposed. In [14] a robot recognizes the user's affective state and displays empathic behaviors. The authors of [15] propose a computer based model that recognizes the students' affective state and reacts in such a way that learning proceeds at optimal pace. In [16] a robot mirrors the emotions happiness, fear and neutral of a human being. The How Was Your Day Companion establishes a conversation with the user about work related topics [17] . In [18] the player's facial expression of emotion controls the growth of a plant. The objective of the game is to grow the plant as fast as possible resorting to positive emotions like happiness or surprise.. One of the functionalities of the Imaginary Friend is to record and display past emotions. The Mappiness application asks users if they feel happy, relaxed or awake to discover how people's happiness is affected by their local environment [19] . The Glow mobile app shows where people are feeling good [20] . MobiMood is another mobile application that enables groups of friends to share their moods with each other [21] . In the Twitter mood project [22] the happiness of users was inferred from the analysis of their tweets. However, neither the Twitter mood project nor any of the mobile applications mentioned relate the user's emotions to the electrodermal activity.. The Imaginary Friend is projected on the floor via a pico projector connected to a mobile phone. Projectors have already been used for interacting with smart objects [23] , to overcome the limitations of the small displays of mobile phones [24] , to share the feelings of the user [25] or even to provide a sixth sense [26] .. In what concerns the detection of emotions, the authors of [27] present a multimodal affect detector that combines conversational cues, body language, and facial features. In [28] the authors propose a method for the recognition of happiness, disgust and fear using input signals such as facial electromyograms, electrocardiogram, the respiration and the electrodermal skin response. The authors of [29] propose yet another emotion recognition system that resorts to electrocardiogram, skin temperature variation and electrodermal activity as input signals. Finally, the iCalm is a wristband that measures electrodermal activity which does not need sticky gel [30] .

O B I O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O B I O O O O O O O B O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O B I O O O O O B I O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O B I O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O B I O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O B I O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B I O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O B I O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O B I O O O O O O O O O O B I O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O B I O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O B I O O O O O O O O


Robust Estimation of Dimension Reduction Space Most dimension reduction methods based on nonparametric smoothing are highly sensitive to outliers and to data coming from heavy-tailed distributions. We show that the recently proposed methods by Xia et al. (2002) can be made robust in such a way that preserves all advantages of the original approach. Their extension based on the local one-step M-estimators is sufficiently robust to outliers and data from heavy tailed distributions, it is relatively easy to implement, and surprisingly, it performs as well as the original methods when applied to normally distributed data. In regression, we aim to estimate the regression function, which describes the relationship between a dependent variable y ∈ R and explanatory variables X ∈ R p . This relationship can be, without prior knowledge and with full generality, modelled nonparametrically, but an increasing number of explanatory variables makes nonparametric estimation suffer from the curse of dimensionality. There are two main approaches to deal with a large number of explanatory variables: to assume a simpler form of the regression function (e.g., its additivity) or to reduce the dimension of the space of explanatory variables. The latter, more general approach received a lot of attention recently; see Li (1991) and Xia et al. (2002) , for instance. Our first aim is to study the latter approach and examine its sensitivity to heavy-tailed and contaminated data, which can adversely influence both parametric and nonparametric estimation methods (seeČížek, 2004 , and Sakata and White, 1998, for evidence in financial data). Further, we propose robust and computationally feasible modifications of Xia et al. (2002) 's methods and study their behavior by means of Monte Carlo experiments.. A dimension-reduction (DR) regression model can be written as. where g is an unknown smooth link function, B 0 represents a p × D orthogonal matrix, D ≤ p, and E(ε|X) = 0 almost surely. Hence, to explain the dependent variable y, the space of p explanatory variables X can be reduced to a D-dimensional space given by B 0 (for D = p, the standard nonparametric regression model results). The vectors of B 0 are called directions in this context. The dimension reduction methods aim to find the dimension D of the DR space and the matrix B 0 defining this space.. Recently, Xia et al. (2002) proposed the minimum average variance estimator (MAVE), which improves in several aspects over other existing estimators, such as sliced inverse regression (SIR) by Li (1991) . First, MAVE does not need undersmoothing when estimating the link function g to achieve a faster rate of convergence. Second, MAVE can be applied to many models including time series data and readily extended to other related problems such as classification (Antoniadis et al., 2003) and functional data analysis (Amato et al., 2005) . Finally, the MAVE approach renders generalizations of some other nonparametric methods; for example, Xia's outer product of gradients (OPG) estimator extends the average derivative estimator (ADE) of Härdle and Stoker (1989) to multi-index models.. Despite many features, MAVE does not seem to be robust to outliers in the dependent variable y since it is based on local least-squares estimation (for evidence, see Leroy, 2003, in parametric andČížek, 2004 , in nonparametric regression). Similar sensitivity to outliers in the space of explanatory variables X (so-called leverage points), was observed and remedied in the case of the sliced inverse regression (SIR) by Gather et al. (2001) . At the same time, the robustness of DR methods is crucial since analyzed data are typically highly dimensional, and as such, are difficult to check and clean. Therefore, because of many advantages that MAVE possess, we address its low robustness to outlying observations and propose ways to improve it without affecting main strengths of MAVE. Additionally, we also employ and generalize OPG because, despite being inferior to MAVE, it provides an easyto-implement and fast-to-compute method that could prove preferable in some applications (especially if dimension D is expected to be very small).. The rest of the paper is organised as follows. In Section 2, we describe both the MAVE and OPG methods and discuss their sensitivity to outliers. Robust enhancements of these methods are proposed in Section 3. Finally, we compare all methods by means of simulations in Section 4. We proposed robust enhacements of MAVE and OPG that can perform equally well as the original methods under 'normal' data, are robust to outliers and heavy-tailed distributions, and are easy to implement. Should we pick up one method for a general use, MAVE-HUBER seems to be the most suitable candidate as (i) MAVE-LS is not robust, (ii) MAVE-L1 is slow to compute, see Section 3.1, and (iii) MAVE-HAMPEL does not perform so well for normal data.

O O O B I O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Visual Tracking in Occlusion Environments by Autonomous Switching of Targets Visual tracking is required by many vision applications such as human-computer interfaces and human-robot interactions. However, in daily living spaces where such applications are assumed to be used, stable tracking is often difficult because there are many objects which can cause the visual occlusion. While conventional tracking techniques can handle, to some extent, partial and short-term occlusion, they fail when presented with complete occlusion over long periods. They also cannot handle the case that an occluder such as a box and a bag contains and carries the tracking target inside itself, that is, the case that the target invisibly moves while being contained by the occluder. In this paper, to handle this occlusion problem, we propose a method for visual tracking by a particle filter, which switches tracking targets autonomously. In our method, if occlusion occurs during tracking, a model of the occluder is dynamically created and the tracking target is switched to this model. Thus, our method enables the tracker to indirectly track the “invisible target” by switching its target to the occluder effectively. Experimental results show the effectiveness of our method. We carried out two experiments to show the effectiveness of the proposed method.

B I O B O O B I I I B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B I O O B I O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Adaptive Optimization of Join Trees for Multi-join Queries over Sensor Streams Abstract-Data processing applications for sensor streams have to deal with multiple continuous data streams with inputs arriving at highly variable and unpredictable rates from various sources. These applications perform various operations (e.g. filter, aggregate, join etc) on incoming data streams in real-time according to predefined queries or rules. Since the data rate and data distribution fluctuate over time, an appropriate join tree for processing join queries must be adaptively maintained in response to dynamic changes to prevent rapid degradation of the system performance. In this paper, we address the problem of finding an optimal join tree that maximizes throughput for sliding window based multi-join queries over continuous data streams and prove its NP-Hardness. We present a dynamic programming algorithm, OptDP, which produces the optimal tree but runs in an exponential time in the number of input streams. We then present a polynomial time greedy algorithm, XGreedyJoin. We tested these algorithms in ARES, an adaptively re-optimizing engine for stream queries, which we developed by extending Jess 1 .For almost all instances, trees from XGreedyJoin perform 1 Jess is a popular RETE-based, forward chaining rule engine written in java close to the optimal trees from OptDP, and significantly better than common heuristics-based XJoin algorithms.

B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


On the deterministic code capacity region of an arbitrarily varying multiple-access channel under list decoding We study the capacity region CL of an arbitrarily varying multiple-access channel (AVMAC) for deterministic codes with decoding into a list of a fixed size L and for the average error probability criterion. Motivated by known results in the study of fixed size list decoding for a point-to-point arbitrarily varying channel, we define for every AVMAC whose capacity region for random codes is nonempty, a nonnegative integer U called its symmetrizability. It is shown that for every L ≤ U , CL has an empty interior, and for every L ≥ (U +1) 2 , CL equals the capacity region of the AVMAC for random codes with a known single-letter characterization. We study the deterministic code capacity region of an arbitrarily varying multiple-access channel (AVMAC) under fixed size-L list decoding. For every received sequence, a list decoder outputs a list of message pairs of size at most L. The error occurs when the transmitted message pair is not in the output list. We restrict ourselves to a discrete memoryless AVMAC with finite inputs, output and state alphabets and the average error probability criterion.. For point-to-point transmission over an arbitrarily varying channel (AVC), it is known [1] that the (list-of-1 size) deterministic code capacity equals either 0 or the random code capacity. The latter capacity is defined for a "random code" in which the encoder and the decoder are assumed to have shared access to a random experiment whose result can be used in selecting a deterministic code from a pool of such codes. Later, it was shown in [6] , [5] that a necessary and sufficient condition for the deterministic code capacity to be zero is when the AVC is "symmetrizable." When list decoding of a fixed size L is considered, it also holds that the list-of-L size capacity for deterministic codes equals either 0 or the random code capacity; a necessary and sufficient condition for the listof-L size capacity for deterministic codes to be zero was given in [3] , [8] in terms of a quantity termed the "symmetrizability" of the AVC defined in [8] . This latter concept can be regarded as a generalization of the symmetrizable condition of the AVC considered in [6] , [5] . Precisely, an AVC is symmetrizable if its symmetrizability is at least 1.. Next, turning to transmission over an AVMAC with the usual decoding (L = 1), Jahn [9] has shown that the capacity region C 1 for deterministic codes either has an empty interior or equals the random code capacity region defined and characterized therein. Gubner [7] introduced the symmetrizable condition for an AVMAC and showed that it implies that the interior of C 1 is empty. Later, Ahlswede and Cai [2] proved that this condition is also necessary for C 1 to have an empty interior.. In the present paper, we introduce a concept of symmetrizability of an AVMAC and study its relationship with its listof-L size capacity region for deterministic codes At present, there is a gap between Theorem 2 and Theorem 3, i.e., there exists a range of list sizes for which we cannot determine C L . This is caused by the fact that our present definition of symmetrizability only captures the "shapes" of A-diagonal (3) and A-rectangle (4), while the output of a list decoder (for a fixed received sequence) can have any shape. It remains to capture the other shapes in a "single-letter" form similart to in Definition 1.. The generalization to the case of an AVMAC with mtransmitters is fairly straightforward. In particular, Definition 1 can be modified to take care of A-diagnals and A-rectangles in the m-product space of indices. In addition, g m (A) (as in (8)) can also be defined as the smallest cardinality of a subset of the m-product space of indices which always contains either an Adiagonal or an A-rectangle. In general, g m (A) ≤ (A−1) m +1. By suitably generalizing the list decoding scheme and Lemma 4 in the proof of Theorem 3, the latter can be generalized for an AVMAC with m-transmitters which will give a lower bound = (U + 1) m for the list size above which C L = C R .

O O B I B I O O O O B I O B I O O O B I O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O B I O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O B I B I O O O O B I O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I O O O O O O O O B I O O O O O O B I O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O B I B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Using standard image compression algorithms to store data from computational fluid dynamics Three-dimensional numerical modeling of fluid flows is an important research tool to understand many fluid dynamical effects observed in nature. With the strong growth of available computational resources the use of such models has greatly increased over the last years. Because the available mass storage has not increased in the same order as the CPU speed many researchers nowadays face the problem of how to store and transfer the large data sets produced by the model calculations for post-processing. The use of lossy wavelet-based compression techniques on this data has been investigated in several publications. These techniques are often specialized to one problem and are not easy to implement. In the area of digital media, however, advances have been made for still image (JPEG, JPEG-2000) and motion image (MPEG) compression. In this paper we investigate the usefulness of these image compression algorithms for the storage of data from computational fluid dynamics on regular cartesian grids. We analyze both the compression ratios achieved and the error introduced by these lossy compression schemes. We found that, for our purposes, the JPEG compression scheme allows an easy-to-use, portable, robust, and computationally efficient lossy compression. For the easy use of these compression algorithms we present a simple wrapper library. r Due to the rapid increase of available computer power over the last years, the use of fully three-dimensional (3D) numerical simulations of nonstationary fluid flows has greatly increased. Many examples come from geophysical research: flows in porous media, creeping convection in the Earth's mantle and magneto-convection in the outer core. Other prominent examples are local and global atmospheric models and ocean circulation models. Only a decade ago the use of such models was worldwide limited to a few meteorological services who had the computational resources whereas today such calculations are feasible on a cluster of workstations or a large computer. The increased efficiency of the numerical models is due not only to the availability of faster computers, but also to the development of sophisticated numerical methods such as multi-grid methods or adaptive grid refinement.. This together has led to a revival of the classical field of fluid dynamics where fundamental questions could not be addressed analytically due to the nonlinear nature of the governing equations and laboratory experiments were difficult to quantify.. Numerical models work in a way that they solve a number of coupled partial differential equations (PDEs) on a computational grid using a numerical method such as Finite Differences, Finite Volumes, Finite Elements or Spectral Methods. The amount of output data ranges from three variables per computational node when solving a Navier-Stokes equation for an incompressible media to eight variables when looking at magnetoconvection in a compressible flow. Often there is also interest in monitoring the transport of a varying number of chemical components, such as trace gases in atmospheric models, which adds another advection-diffusion equation to the numerical model.. The spatial resolution of such models is today typically in the range from 32 Â 32 Â 32 grid-nodes up to 256 Â 256 Â 64 grid-nodes. Because of the complex nature of the evolving flows, one often has to integrate the equations in time for several thousand timesteps in order to observe generic behavior and to analyze the different timescales involved.. Although computers have become faster such a simulation cannot be done interactively but will still require computer time in the order of weeks or even months. Visualization and analysis of the results is typically done by post-processing the data saved at different stages of the numerical simulation. Because it is not always obvious which fraction of the computed data is needed for post-processing, the researcher tries to save as much data as possible.. Moreover due to specialized graphics hardware the machine used to post-process the data is often different from the one used to carry out the simulation. Especially when using a mainframe computer this often means that the binary format and/or the byte order of the machines differ. This is not a principal problem, but it poses constraints on the way the data are stored.. Storing the result of one time-step with a resolution of 128 Â 128 Â 64 nodes and four variables per node leads to a filesize of 17 Mega Bytes (MB) when using a 32-bit binary floating point value and about 50 MB when using a portable ASCII representation. For calculating trajectories in the flow during post-processing or generating an animated image sequence of the data, one typically needs to save every 10th Lewy-Courant constrained timestep. Given that the calculation often consists of several thousand timesteps, the resulting data filesize is often in the order several Gigabytes (GB). This makes storage and handling of the data not only inconvenient, but also makes it impossible to keep several result files on a disk when carrying out a systematic parameter study.. Therefore it is highly desirable to store the data in a more compact manner. Standard lossless compression algorithms such as Huffman encoding or the LempelZiv encoding (e.g. Salomon, 2000) which are implemented for example in the gzip utility do lead to a size reduction of only 10-20% for the binary data and are computationally intensive.. For post-processing the data calculated in the fluiddynamical simulation it is often acceptable that the data are not available in full precision but with a lower accuracy. The required accuracy depends on the kind of post-processing carried out on the data. For visualization purposes, for example, a relatively low precision is sufficient.. Another important aspect when thinking about data compression is the existence of characteristics in the data set which could aid the compression process. Examples of these are temporal and/or spatial coherent structures or the fact that fields do change smoothly in space due to diffusive terms in the governing equations. When the compression scheme chosen is able to utilize these characteristics a high compression ratio can be achieved.. The field of data compression is still evolving at a high rate. Because of its key relevance for different fields there are many publications available. The probably most complete reference is the book by Salomon (2000) which treats all of the compression algorithms applied in the present paper. Application of data compression to Earth science can be found for seismic data (Vassiliou and Wickerhauser, 1997; Villasenor et al., 1996; Lervik et al., 1996) and for ocean-model data (Tao and Moorhead, 1994a, b; Bradley and Brislawn, 1993) . All these publications apply wavelet-based methods. Their aim is mostly to speed up visualization and exploration of data. In the field of turbulence simulation Zubair et al. (1992) and Wilson (2002) also discuss the use of waveletbased methods.. These publications present the leading edge in data compression. Their main aim is to achieve the highest compression ratios while minimizing the introduced artifacts. The approach of the present paper is a different, more technical one. For many researchers involved in CFD, particularly in small and medium sized research groups, the size of the data generated is becoming a real problem. In this case the priorities are different. The key issues are: The robustness of the method, the availability of the source code, the portability of the source code over different machine architectures, the computational resources required, and the programming effort required for using this method. In addition it is important to have a wide range of compression ratios easily available in order to account for different post-processing needs. All these issues are for most researchers more important than the optimal compression ratio.. In this paper we address most of the issues mentioned before by using standard video and image compression software which has mostly been available for years. Lossy encoding schemes are widely used in still and motion image compression. The compression algorithms used in these fields are complex and have undergone extensive testing. This poses the question we address in the paper of whether they could also be used to store the data from fluid-dynamical simulation in an effective manner. Codes like the JPEG implementation has been available for over a decade and have been ported to a wide variety of different architectures. With the help of a small wrapper library we have made the different standard compression algorithms easily available to both Fortran77/90 and C/C+ + programs. We have investigated the properties of different lossy compression schemes for compressing data from computational fluid dynamics. Since the investigated JPEG, JPEG-2000 and MPEG compression methods are designed for image compression they may not be optimal for compressing data from numerical simulation of fluid flow. They do however provide an easily available, easily adopted and well debugged tool to compress CFD data.. Together with a simple compression scheme which stores a data-point as two ASCII characters, the investigated compression schemes compress the data in a range from 50% up to 99.7% compared to the size of the binary written data set. The compressed data are portable across different machine architectures. We have investigated the maximum and average errors connected with the compression schemes, which does correlate to the achieved compression. The processor time spent for compressing the data sets was found to be moderate for the JPEG and high for the MPEG scheme and even higher for JPEG-2000. Decompression times however proved to be much smaller for the MPEG scheme, while still being high for the JPEG-2000 scheme.. Because of the different properties of the methods we conclude that it is useful to have three methods easily available and present a simple wrapper library to access the different compression algorithms from within a CFD program.. With the market for digital image compression growing rapidly over the last years there are also new algorithms appearing. Implementations of the new MPEG-4 standards allow higher compression while maintaining a higher image quality. With the growing size of the data sets in CFD it is important to monitor these developments and to use the technology for our purposes.

O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Power assignment for k-connectivity in wireless ad hoc networks prohlem Min-Power k-Connectivity seeks a power assignment to the nodes in a given wireless ad hoc network such that the produced network topology is k-connected and the total power is the lowest, In this paper, we present several approximation algorithms for this problem. Specifically, we propose a Yk-approximatiun algorithm for any k 2 3, a (k -t E H (k))-approximation algorithm for k (2k -1) 5 TI where n is the network A (di)graph is k-connected if it contains at least k independent paths between any pair of distinct vertices.By the well-known Menger's theorem, a (di)graph I;-connected if and only if the deletion of any set of less than k nodes leaves a connected (di)graph. The connectivity of (di)graph is defined to be the maximum k for which it is k-connected. In this paper, we study the following Min-Power k-Connectivity problem: Find a power assignment with minimal total power to a given set of network nodes which produces a I;-connected

B I O B O O O O O O O B O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B I O O O O O O O O O O O O O O O


On hash functions using checksums We analyse the security of iterated hash functions that compute an input dependent checksum which is processed as part of the hash computation. We show that a large class of such schemes, including those using non-linear or even one-way checksum functions, is not secure against the second preimage attack of Kelsey and Schneier, the herding attack of Kelsey and Kohno and the multicollision attack of Joux. Our attacks also apply to a large class of cascaded hash functions. Our second preimage attacks on the cascaded hash functions improve the results of Joux presented at Crypto'04. We also apply our attacks to the MD2 and GOST hash functions. Our second preimage attacks on the MD2 and GOST hash functions improve the previous best known short-cut second preimage attacks on these hash functions by factors of at least 2 26 and 2 54 , respectively. Our herding and multicollision attacks on the hash functions based on generic checksum functions (e.g., one-way) are a special case of the attacks on the cascaded iterated hash functions previously analysed by Dunkelman and Preneel and are not better than their attacks. On hash functions with easily invertible checksums, our multicollision and herding attacks (if the hash value is short as Coppersmith [2] presented a short-cut collision attack on a 128-bit hash function based on the DES algorithm proposed by Quisquater and Girault [28] which processes two supplementary checksum blocks each computed independently using XOR and modular addition of message blocks. Joux [11] provided a technique to find 2 k -collisions for a MD hash function for only about k times as much work as is required for a collision, and uses this technique to attack cascade hashes. Gauravaram and Kelsey [7] analysed the security of the variants of MD hash functions that compute linear-XOR or additive checksums over message blocks, intermediate hash values, or both, and process these checksums in computing the final hash value. Dunkelman and Preneel [5] analysed the security of general iterated hash functions called "concatenated schemes" (also called cascaded constructions). Nandi and Stinson [23] have shown the applicability of multicollision attacks to a variant of MD in which each message block is processed multiple times; Hoch and Shamir [10] extended the results of [23] showing that generalised sequential hash functions with any fixed repetition of message blocks do not resist multicollision attacks.. The MD2 hash function [12] uses a non-linear checksum function. Vulnerabilities in MD2 have been exposed through collision attacks on its compression function [15, 30] and (second) preimage attacks on the full hash function [15, 16, 22] by exploiting weaknesses in its compression function. Mendel, Pramstaller and Rechberger [20] presented a short-cut (second) preimage attack on the 256-bit GOST hash function for a target message of at least 257 message blocks in 2 192 evaluations of the compression function. . Herding attack of [13] Cryptographic hash functions are important tools of cryptology used in many applications for secure and efficient information processing. Hash functions are expected to resist collision and (second) preimage attacks to provide security in such applications. Furthermore, they are often assumed to behave "randomly". In practice, the requirement of these security properties depends entirely on the application.. For efficiency reasons, iterated hash functions are used in many real-life applications. The Merkle-Damgård construction [3, 21] (MD construction in the rest of this article) is the most commonly used iterated hash function framework to design hash functions; almost all widely used hash functions follow this framework. Given a fixed input length collision-resistant compression function, a variable input length collision-resistant hash function can be designed using this framework.. A number of so-called generic attacks on the MD construction have shown that this construction does not satisfy some expected security properties. This structure is not as resistant to second preimage attacks as an ideal hash function as shown by Dean [4] and Kelsey and Schneier [14] , and it also has other undesired weaknesses in the form of multicollisions [11] and herding attacks [13] .

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A New Data Processing Inequality and Its Applications in Distributed Source and Channel Coding In the distributed coding of correlated sources, the problem of characterizing the joint probability distribution of a pair of random variables satisfying an n-letter Markov chain arises. The exact solution of this problem is intractable. In this paper, we seek a singleletter necessary condition for this n-letter Markov chain. To this end, we propose a new data processing inequality on a new measure of correlation by means of spectrum analysis. Based on this new data processing inequality, we provide a single-letter necessary condition for the required joint probability distribution. We apply our results to two specific examples involving the distributed coding of correlated sources: multi-terminal rate-distortion region and multiple access channel with correlated sources, and propose new necessary conditions for these two problems. In the distributed coding on correlated sources, the problem of describing a joint distribution involving an n-letter Markov chain arises. By means of spectrum analysis, we provided a new data processing inequality based on a new measure of correlation, which gave us a single-letter necessary condition for the n-letter Markov chain. We applied our results to two specific examples involving distributed coding of correlated sources: the multi-terminal rate-distortion region and the multiple access channel with correlated sources, and proposed two new outer bounds for these two problems.

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A note on permutations and rank aggregation In this brief note we consider rank aggregation, a popular method in voting theory, social choice, business decisions etc. Mathematically the problem is to find a permutation -viewed as a vector -that minimizes the sum of the 1-distances to a given family of permutations. The problem may be solved as an assignment problem and we establish several properties of optimal solutions in this problem. There is a significant interest in the area of rank aggregation. The problem is to aggregate several given rankings (preferences) into a single ranking in a best possible way. This problem is central in social choice and voting theory, it is of interest in sports ranking, business decisions and, recently, in web based rankings. A recent presentation of rank aggregation procedures may be found in [16] where a comparison of different methods is given and computational aspects are discussed. A related study of aggregation methods is [8] . In [6] one considers rank aggregation for partial rankings (where only subsets of alternatives are ranked, under different criteria) using the so-called Spearman footrule distance (see below). We refer to [2] , [12] , [15] for presentations of voting theory, ranking and its history. In particular, the recent paper [15] contains an interesting presentation of the challenges (and paradoxes) in voting theory, and invites mathematicians to look at problems in this area. For permutations, permutation matrices and related matrix classes, we recommend the book [4] .. The purpose of the present note is to study rank aggregation based on the 1 -distance (which corresponds to Spearman footrule) and properties of this approach. Our approach is combinatorial, although the basic problem is formulated as an optimization problem of geometrical nature. As kindly pointed out by a referee some of our results are similar to results in [5] (using a different terminology) where one considered rank aggregation using 1 -distances and allowed, more generally, partial rankings. Several properties of the aggregation method were shown in [5] . However, in contrast to [5] , we discuss an efficient computational method for finding an optimal rank aggregation, and etablish some other properties of such optimal solutions. In [7] rank aggregation (based on 1 -distance) is discussed and used as the basis for a rank distance categorization method.. In [3] techniques from combinatorial optimization (integer programming, the knapsack problem) are used study certain minimal fractions of votes that could have elected the US President in the Electoral College (in the period . The geometry of voting theory, where voting rules are investigated using geometrical notions (like simplices and partitions of these), has been subject to intensive research in recent years, see the work by Saari, e.g., [12] , [13] , [14] and [15] , and by Zwicker [17] . In [17] the notion of a mean proximity rule is central: loosely speaking, voters choose score vectors, their mean (vector)x is calculated and the problem is to find a nearest "aggregated score vector" tox. We prove a related result for the rank aggregation procedure treated here (using Spearman footrule distance), but here the main role is played by the medians of certain numbers (scores), not the mean.. The main goal in this paper is to investigate properties of 1 -minimal permutations. Section 2 contains basic notions and definitions and some examples. In Section 3 we discuss how to compute an 1 -minimal permutation, while Section 4 focuses on different properties of rank aggregation based on 1 -minimal permutations. Let · 1 denote the 1 -norm of vectors in IR n , i.e., the sum of the absolute values of the components, and define the corresponding distance function. is obtained by finding the distance between the ranking of each alternative a j according to < π and < σ , and summing these distances over all alternatives a 1 , a 2 , . . . , a n . The distance d coincides with the Spearman footrule distance [9] . We shall refer to d as the 1 -distance. It represents a measure of the difference between two total orders of an n-set A. For instance, if π = (4, 3, 1, 2) and σ = (2, 3, 1, 4), then d(π, σ) = |4 − 2| + |3 − 3| + |1 − 1| + |2 − 4| = 4. The 1 -distance is a metric on the set S n of permutations (i.e., it satisfies for π, σ, µ ∈ S n : (i) d ≥ 0, and d(π, σ) = 0 if and. S n be a family of permutations π i (i ≤ m). We extend the 1 -distance to measure the distance between a permutation σ and the family P and define. Note that the order of the permutations π i in P does not affect the value of this function d. A permutation σ * satisfying d(σ * , P) = min{d(σ, P) : σ ∈ S n } is called 1 -minimal for P. Let M(P) denote the set of all 1 -minimal permutations for P. M(P) is clearly nonempty (as we optimize over a finite set).

O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O


Statistical transliteration for english-arabic cross language information retrieval Out of vocabulary (OOV) words are problematic for cross language information retrieval. One way to deal with OOV words when the two languages have different alphabets, is to transliterate the unknown words, that is, to render them in the orthography of the second language. In the present study, we present a simple statistical technique to train an English to Arabic transliteration model from pairs of names. We call this a selected n-gram model because a two-stage training procedure first learns which n-gram segments should be added to the unigram inventory for the source language, and then a second stage learns the translation model over this inventory. This technique requires no heuristics or linguistic knowledge of either language. We evaluate the statistically-trained model and a simpler hand-crafted model on a test set of named entities from the Arabic AFP corpus and demonstrate that they perform better than two online translation sources. We also explore the effectiveness of these systems on the TREC 2002 cross language IR task. We find that transliteration either of OOV named entities or of all OOV words is an effective approach for cross language IR. Out of vocabulary (OOV) words are a common source of errors in cross language information retrieval (CLIR). Bilingual dictionaries are often limited in their coverage of named-entities, numbers, technical terms and acronyms. There is a need to generate translations for these "on-the-fly" or at query time.. A significant proportion of OOV words are named entities and technical terms. Typical analyses find around 50% of OOV words to be named entities [6] [8] . Yet these can be the most important words in the queries. Larkey et al [16] showed that cross language retrieval performance (average precision) reduced more than 50% when named entities in the queries were not translated.. Variability in the English spelling of words of foreign origin may contribute to OOV errors. Whitaker [21] , for example, identifies 32 different English spellings for the name of the Libyan leader Muammar Gaddafi.. When the query language and the document language share the same alphabet it may be sufficient to use the OOV word as its own translation. However, when the two languages have different alphabets, the query term must somehow be rendered in the orthography of the other language. The process of converting a word from one orthography into another is called transliteration.. Foreign words often occur in Arabic text as transliterations. This is the case for many categories of foreign words, not just proper names but also technical terms such as disease names like Bilharzia and common words such as caviar, telephone, television, computer and internet. Words of foreign origin are often transliterated into English as well. Examples of these are Arabic proper names and words like hummus and hookah.. There is great variability in the Arabic rendering of foreign words, especially named entities. Although there are spelling conventions, there isn't one "correct" spelling. We have observed multiple spellings for a word even within the same document. Listed below are 6 different spellings for the name Milosevic found in one collection of news articles. We have demonstrated a simple technique for statistical transliteration that works well for cross-language IR, in terms of accuracy and retrieval effectiveness. The results of our experiments support the following generalizations:. • Good quality transliteration models can be generated automatically from reasonably small data sets.. • A hand-crafted model performs slightly better than the automatically-trained model The automatically trained models sometimes generated transliterations with common spelling errors like missing letters. These actually occur in the corpus but would not be found in a dictionary and would not be generated by the hand-crafted model. A few examples are shown below, with the missing letters in parenthesis:. These translations would occasionally allow the retrieval of documents that would be missed by more "accurate" methods. One source of retrieval errors is false hits, when transliterations match the wrong word. False hits were more common for short words than for long words, thus in the future one might want to generate more alternatives for long words, or avoid transliterations for very short (e.g. 3 letter) words.. Another possible direction for the future would be to train separate models for words of Arabic origin and words of other origin.. One could also train a back-transliteration model based on an approach similar to the selected n-gram model.. For Arabic, the hand-crafted model performed better than the automatically-trained model, and could be further improved via some error analysis and automatic tuning of weights. However, the automatic selected n-gram approach would be useful when dealing with a new, unfamiliar language. Although organizations that provide online translation from English to Arabic appear to include English/Arabic transliteration systems, little is published about them. [1] [2] . No information is available about how they generate transliterations, or how well they work. Darwish et al. [9] described a transliterator used for TREC-2001, but provided no evaluation of it effectiveness.. Most prior work in Arabic-related transliteration has been for the purpose of machine translation, and for Arabic/English transliteration. Arbabi et al. [5] developed a hybrid neural network and knowledge-based system to generate multiple English spellings for Arabic person names. Knight and Graehl [13] developed a five stage statistical model to do back transliteration, that is, recover the original English name from its transliteration into Japanese Katakana. Stalls and Knight [20] adapted this approach for back transliteration from Arabic to English of English names. These systems are very complex, involving a great deal of human design, probably because they were dealing with a more difficult problem than that of forward transliteration. However, as the Milosevic example reveals, forward transliteration for information retrieval is not as simple as the problem of forward transliteration for machine translation, in which one reasonable transliteration is good enough. Al-Onaizan and Knight [3] have produced a simpler Arabic/English transliterator and evaluates how well their system can match a source spelling. Their work includes an evaluation of the transliterations in terms of their reasonableness according to human judges. None of these studies measures their performance on a retrieval task or on other NLP tasks.. Fujii and Ishikawa [10] describe a transliteration system for English-Japanese cross language IR that requires some linguistic knowledge. They evaluate the effectiveness of their system on an English-Japanese cross language IR task. The problem they look at is somewhat different from the one we address, as they only attempted to produce one acceptable translation per word. In Japanese, foreign words are written in a special orthography so it is easy to select which words to transliterate. Our research differs in that our system requires no linguistic knowledge or heuristics. We perform a similar evaluation of our system on the retrieval task and also compare our system with other bilingual resources. The output of the transliteration models were evaluated in two different ways. The first evaluation uses a measure of translation accuracy described below, which measures the correctness of transliterations generated by the models, using the spellings found in the AFP corpus as the standard for correct spelling. The second kind of evaluation uses a cross language information retrieval task and looks at how retrieval performance changes as a result of including transliterations in query translations.

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