Generation of crossmedia dynamic learning contexts from iTV Tendencies in convergence, integration and co-existence of several media technologies are creating new opportunities for the globalization of learning practices. Simultaneously, the lifelong learning phenomena, which will take place in a wide variety of contexts and locations, call for flexible environments. iTV holds a great potential in this scenario, but there is still limited research in terms of cognitive and interaction aspects. This paper presents a new paradigm to generate crossmedia dynamic learning contexts from iTV with the aim to link the mentioned opportunities in flexible, adequate and effective learning contexts. In order to better illustrate this paradigm an iTV system, (e-iTV), was designed. The system generates, via iTV, Crossmedia Online Personalized Learning Environments, also designated as COPLE or web lessons, accessible from several types of devices. The system is prepared to respond to communication needs of the viewers since and allows them to share their web lesson. In practical terms, the e-iTV system uses the TV set, not as the final medium, but as a starting point to new crossmedia dynamic learning and communications contexts. The motivations and goals of this work are presented, followed by a review of related work and concepts and the presentation of the conceptual framework. A description of the analysis, planning, development and evaluation of the e-iTV system is presented based on a specific HCI based model. The paper concludes by opening perspectives for future research and developments. The history of iTV, is full of pitfalls which have dictated a journey of advancements and recoils [2] . Nevertheless, iTV technology combines the appeal and mass audience of full motion TV with the interactivity of the web and the internet, providing new services, giving viewers more control over what they see and creating a new and very rich environment. It is, in the opinion of many researchers and producers, a technology that is increasingly being used and will conquer its market space [2; 32] . This conviction is clearly supported by the number of research studies that were conducted on these last few years. Some studies have identified a potential for the use of iTV for increasing learning opportunities in the home, in particular through personalized options [5] and the need to find ways of utilizing the powerful combination of broadcast TV and interactive services to provide hooks to draw viewers into active learning environments [5] .. The success of iTV requires technological solutions, sustainable models and pedagogical solutions issues, and there is still limited research in this particular area, especially on cognitive and interaction aspects [5; 21] . This is an important field in the emerging era of lifelong learning, as learning will take place in a wide variety of contexts and locations and informal and nonformal learning will become as important as formal learning [5] , calling for flexible environments. Simultaneously, global access to information and technology is changing the relationship between people and knowledge, and the trends in convergence, integration and co-existence of various media technologies is creating new opportunities for the globalization of learning and communicational practices.. In spite being a traditionally passive device, the TV set may conduct viewers into different cognitive states (more or less reflective) in seconds. These cognition states may appear inside or outside typical learning environments: daily activities, like watching a TV program may, at some point in time, create the need to learn more about a specific issue that caught our attention, and thus create a reflective cognition state.. The main goal of our research is to study a new paradigm to generate crossmedia dynamic learning contexts from iTV in order to link the mentioned opportunities with effective learning situations. The e-iTV system designed to illustrate and explore this paradigm generates Cross-media Online Personalized Learning Environments (COPLE), also designated as web lessons, in response to learning opportunities specifically created by TV.. From a conceptual point of view, we expect to understand the advantages and added value of connecting these media, exploring effective ways of designing crossmedia dynamic learning contexts based on cognitive, affective and interaction aspects. Technically, we expect to propose a new and personalized type of service, which is the next direction to follow [6; 12; 32] .. Concluding, some of the main research questions are: (a) is there an advantage in connecting these media? (b) are the interfaces adequate (easy to use and understand)? (c) is the preferred interface the less intrusive? (d) are the web lessons appropriate to give sequence to the learning opportunities created by the visualization of the iTV program (are they capable to contextualize viewers in relation to what they first saw and give a sequence to that)? (e) what other functionalities would the viewer like to see implemented? (f) in general, is the system considered interesting?. The paper is organized as follows: section 2 presents related work, section 3 presents the conceptual framework followed, section 4 presents the e-iTV system and, finally, section 5 presents the conclusions and perspectives for future work. As a result of the analysis stage we decided to implement the e-iTV system which will work integrated with the traditional iTV in order to accommodate viewer's changes in cognition modes. While watching a TV program, when in a reflective cognitive mode, the viewer will be able to select (tag) the specific issues in which s/he is interested in learning more about. A website with a personalized web lesson addressing the selected issues and related web links will be generated by the system, in a server, and made available to the viewer, via the Internet, in a format to be viewed on four different media/devices: PC, iTV, PDAs and mobile phones. If the viewer choice is to see the web lesson through in the PC, mobile phone or PDA he will receive an e-mail, a SMS, or both, with the web link address to the web lesson. If the viewer choice is to see the web lesson through the iTV, the link will be immediately available via the iTV application. These web lessons are designed to satisfy the viewer's information needs, by containing more information in breadth, depth, and points of view than the original broadcast content, on the aspects selected while watching the TV program. Thus, it provides an answer to the learning opportunities created by an entertainment environment like TV involving different media and, instead of being seen as the end product, the broadcast program can be the starting point to a crossmedia dynamically built learning space, a new crossmedia learning context, to be further explored. It will also allow the viewer to share its web lesson with his contacts which is a way to fulfil his communication needs while watching TV, a concept that was referred, by Geerts [13] , as "social TV" and that is growing due to the proliferation of different technological communication devices. In fact, since TV works as a promoter of interpersonal communication [2] and T-learning has social features [1] , this communication functionality turns out to be important. Due to the convergence between TV and the Internet, several research projects aimed at finding ways of combining TV and web content (with informational and/or communicational purposes) appeared. We present some of the more relevant.. The 2BEON [2] is an iTV application, which supports and facilitates the communication between viewers, allowing them to communicate textually, in real time, while watching a specific program.. Geerts et al. [13] , studied a system for sending and receiving enriched video fragments to and from a range of devices. The goal was to understand which program genres were preferred for talking while watching, talking about after watching and for sending to users with different devices.. WebTV [36] is a system which enabled users to access the Internet via a TV set while watching it.. HyperSoap [9] explored interaction designs for the iTV paradigm, expecting a more passive audience, allow showing interest in topics to be later explored in a more reflective mode.. The TAMALLE project [29] developed a dual device system for informal language learning, based on iTV and mobile phones, supporting learners of English as a second language in their TV viewing, selecting what to access later on the phone.. MyInfo [10] extracts specific web content listed in the user profile and displays personalized TV news programs -weather, traffic, sports, financial news, headlines, and local events -on the TV based on the web content.. InfoSip [10] is a movie information retrieval application which analyzes the movie content and gives audiences information (overlaid onscreen) on such as who's the actor? What's the song? Nadamoto et al. [26] have developed a 'TV-style presentation' system capable of searching the web, extracting related and relevant web pages, automatically transforming the text and image based web content found into audio-visual TV -program type content -through the use of character animated agents and text read-out; and fusing it with normal broadcasted TV program contents. Miyamori et al. [24] have developed the opposite idea, i. e., a 'Web-browser-style presentation' system named Webified Video capable to automatically transform traditional TV content into web content and fusing it with other web content.. Ma et al. [22] have developed a 'Parallel presentation' system named Webtelop. The system is capable of simultaneously presenting TV program contents and web contents on the TV and thus enables viewers to browse web content while watching the TV program content. The system proposed by Miyamori et al. [25] generates views of TV programs based on viewer's perspectives expressed in live web chats.. CoTV™ [8] or coactive TV automatically presents, on a PC, web content related to the on-air program. It acts like a special web search engine that is continuously and automatically driven by the TV-viewing context (not driven by the viewers' actions). It also includes a portal with traditional iTV services as for instance program guides, video on demand, etc. Cronkite [20] provides extra information to viewers of broadcast news. While the viewer is watching a news story, he may feel the need to know more about it. Thus, he presses the "interest" button on his remote control and, the system provides him with extra information on a computer display. The extra information comprises information related to the story that he is watching (not specific issues of that story) and also pointers to other related stories.

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 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 B 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 B 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 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 B 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 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 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 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 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 O O O O O O O O O O O O O O O O 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 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 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 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 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 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 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 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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


Tracking Nonrigid Motion and Structure from 2D Satellite Cloud Images without Correspondences AbstractÐTracking both structure and motion of nonrigid objects from monocular images is an important problem in vision. In this paper, a hierarchical method which integrates local analysis (that recovers small details) and global analysis (that appropriately limits possible nonrigid behaviors) is developed to recover dense depth values and nonrigid motion from a sequence of 2D satellite cloud images without any prior knowledge of point correspondences. This problem is challenging not only due to the absence of correspondence information but also due to the lack of depth cues in the 2D cloud images (scaled orthographic projection). In our method, the cloud images are segmented into several small regions and local analysis is performed for each region. A recursive algorithm is proposed to integrate local analysis with appropriate global fluid model constraints, based on which a structure and motion analysis system, SMAS, is developed. We believe that this is the first reported system in estimating dense structure and nonrigid motion under scaled orthographic views using fluid model constraints. Experiments on cloud image sequences captured by meteorological satellites (GOES-8 and GOES-9) have been performed using our system, along with their validation and analyses. Both structure and 3D motion correspondences are estimated to subpixel accuracy. Our results are very encouraging and have many potential applications in earth and space sciences, especially in cloud models for weather prediction. CLOUD motion analysis is a very important application area in computer vision, especially in nonrigid motion analysis. Accurate cloud heights and winds are significant for a number of meteorological and climate applications [7] , such as cloud model verification, physically-based numerical weather prediction and data assimilation, cloud-wind height assignment [6] , [8] , [18] , [7] , convective intensity estimation [24] , [25] , naval aviation, and radiation balance estimation for Mission to Planet Earth type climate baseline studies.. During the past decades, many studies have been conducted on the structure recovery from rigid motion [30] , [2] and the motion recovery from stereo images [32] . In particular, different vision algorithms were proposed and employed to address the problem of automatic cloud motion analysis. Fujita et al. pioneered the use of ATS-1, the first geosynchronous meteorological satellites, launched in 1966, for measuring large scale cloud motion [5] . Leese et al. [16] , Smith and Phillips [26] , and Phillips et al. [23] implemented local area cross-correlation-based automatic cloud tracking using ATS imagery. Cross-correlation methods implicitly assume a local rigid motion model. However, this assumption fails in tracking mesoscale atmospheric phenomena such as hurricanes and severe convective storms [9] . Aggarwal and Duda [1] studied the motion of polygonal objects and used vertices as matching features to estimate cloud motions from satellite images. Kambhamettu et al. [14] used a continuous motion model, where individual cloud elements are assumed to undergo locally continuous deformation (i.e., the cloud surface patch can be smoothly stretched with local elements maintaining their neighborhood relationships), while Palaniappan et al. [20] , [19] used a semifluid model which allows cloud surface patches to merge, split, or cross over. However, their methods relied on 3D cloud data and utilized the changes in differential geometric properties of 3D cloud surfaces in motion in order to perform cloud tracking. The 3D cloud data were obtained from stereo analysis and/or by approximating 2D intensity images for depth information. Kambhamettu et al. [12] applied coupled stereo and motion analysis of clouds using a simple-to-complex multiresolution approach. Recently, multispectral satellite information, such as moisture data and infrared data, was incorporated into the automatic cloud motion vector estimation algorithms by Velden [27] and Velden et al. [28] , [29] . They discussed the impact of multispectral satellite information on both tropical cyclone tracking and cloud intensification analysis.. The previous approaches focused on dense nonrigid motion estimation of clouds using multiview or multispectral satellite cloud image sequences. However, they did not recover dense structure and nonrigid motion from a single 2D image sequence. In this paper, we generalize our previous work in [34] , [35] and propose a novel algorithm to estimate both dense structure and nonrigid motion from a sequence of 2D cloud images using global fluid model constraints. The task is challenging due to the complex dynamics of the imaging instruments and the underlying nonlinear phenomena of cloud formation and weather, as well as the scaled orthographic projection of cloud imagery, which makes the structure estimation problem even more difficult. In our algorithm, the cloud images are first segmented into small regions and local analysis is performed for each region, assuming that similar nonrigid motion is present within each region for a short time period. Then, a recursive algorithm is proposed to integrate local analysis with appropriate global constraints. A system called SMAS has been implemented based on our algorithm. Experiments using Hurricane Luis image sequences were performed to estimate the complete hurricane structure and 3D motion correspondences, along with extensive error analysis. The remainder of this paper is organized as follows: Section 2 explains the data acquisition of cloud image sequences. Section 3 briefly presents the local analysis of 2D cloud image sequences. Section 4 discusses the global analysis. Section 5 presents the experimental results on satellite images of Hurricane Luis. Section 6 validates and evaluates our results. Finally, conclusions and future work are presented in Section 7. This paper presents the tracking of dense structure and nonrigid motion from a sequence of 2D cloud images. The main contribution of this research is that it not only deals with the problem of recovering structure from the scaled orthographic projection views but also performs nonrigid motion estimation to obtain 3D correspondences by integrating local and global analysis. The results are very encouraging and have tremendous applications in meteorology for cloud modeling and weather prediction. A similar 2. For more results and animations, please refer to [33] . approach can be applied for perspective projection imagery such as lip motion, human facial expressions, biomedical applications, etc.. Our future directions include the following:. 1. use of complex fluid models to capture the variation of fluid density in clouds, 2. cloud motion segmentation, and 3. use of multispectral satellite images in cloud structure and nonrigid motion tracking. Our ultimate goal is to have a set of techniques that can perform cloud motion classification and apply appropriate motion models in cloud tracking and nonrigid motion and structure analysis for long term climate studies and for short term numerical weather prediction.

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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 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


The Dial-A-Ride Problem with Transfers The Dial-A-Ride Problem with Transfers (DARPT) consists in defining a set of routes that satisfy transportation requests of users between a set of pickup points and a set of delivery points, in the presence of ride time constraints. Users may change vehicles during their trip. This change of vehicle, called a transfer, is made at specific locations called transfer points. Solving the DARPT involves modeling and algorithmic difficulties. In this paper we provide a solution method based on an Adaptive Large Neighborhood Search (ALNS) metaheuristic and explain how to check the feasibility of a request insertion. The method is evaluated on real-life and generated instances. Experiments show that savings due to transfers can be up to 8% on real-life instances. The Dial-A-Ride Problem (DARP) consists in defining a set of minimum cost routes in order to satisfy a set of transportation requests. Each request involves transporting a set of users from a set of origins, called pickup points to a set of destinations, called delivery points. Users associated with distinct requests can share the same vehicle as long as its capacity is not exceeded. In addition, a maximum ride time is associated with each request. It corresponds to the maximum duration of the trip between the pickup point and the delivery point. This paper addresses a generalization of the DARP in which users can be transferred from one vehicle to another at intermediate points, called transfer points [1] . This problem is called the Dial-A-Ride Problem with Transfers (DARPT). As the DARP is a special case of the DARPT for which the set of transfer points is empty, the DARPT is NP-hard.. The DARP is a generalization of the Vehicle Routing Problem (VRP). It can be either static [2] , when each request is known in advance, or dynamic, when requests can be integrated at any time [3] . Since the DARP deals with people transportation, specific requirements concerning the quality of service have to be taken into account. The objective function to be optimized is application-dependent: the number of vehicles used, total ride time, total distance, cost or service-related criteria [4] . In the remainder of this article, we consider a static case problem in which the objective function is to minimize the total distance traveled. Quality of service is enforced by defining appropriate maximum ride times for each user.. This study is motivated by a demand-responsive transport application for people with mental disabilities traveling to and from their home to social centers, vocational rehabilitation centers or schools. These persons are able to get onto or off vehicles without physical assistance, but due to their lack of autonomy, they cannot use public transportation systems. They travel in dedicated vehicles whose use is very costly. Some organizations, responsible for the transportation of people with disabilities, wish to pool their transportation system in order to decrease costs. The objective is thus to design routes in order to service the users of several centers at a reduced cost. In order to improve the use of the vehicles, one method consists in concentrating several vehicles in predetermined locations, called transfer points, where users are transferred from one vehicle to another.. In this article, we show that the introduction of transfer points may generate significant savings for both real-life and generated instances of the DARP. We extend an Adaptive Large Neighborhood Search (ALNS) previously designed for the Pickup and Delivery Problem with Transfers (PDPT) [5] . We also integrate a preliminary study on feasibility algorithms for the DARPT [6] . Besides, when the operators that introduce transfers are not used, the proposed ALNS competes with the state of the art algorithms for the DARP.. The remainder of this article is organized as follows. First, we present a review of related works. Then, we formally describe the DARPT and the reasons for studying this problem. Section 4 is devoted to the description of the solution method. Section 5 focuses on the problem of checking whether a given set of routes is feasible or not. More specifically, we discuss how the feasibility can be verified within the solution method framework. Section 6 presents computational experiments, while the conclusion appears in the last section. In this article, we developed an Adaptive Large Neighborhood Search (ALNS) to solve the Dial-A-Ride Problem with Transfers. The algorithm strongly relies on previous work carried out on the Pickup and Delivery Problem with Transfers [5] and competes with state-of-the art methods for the DARP. We show that the feasibility of the insertion of a request into a feasible solution can be efficiently checked. We provide lower bounds for the savings due to transfers and apply the ALNS to real-life instances for which we evaluate the practical savings due to transfers. The introduction of transfer points can lead to nonnegligible savings (up to 8.25%). However, it does not seem straightforward to characterize instances that may benefit most from the introduction of transfers.. This work opens up some new perspectives. In this study, the quality of service provided to the users has been modeled only by maximum ride time constraints. However, users generally consider transfers as a deterioration in their quality of service. As a matter of fact, one could consider to restricting the number of passengers transferred, the maximum waiting time of an user at a transfer point or the overall waiting time of the users at transfer points. As far as we know, the only known definition of the DARPT as it is considered in this article is given in works [1, 6] . This section presents relevant studies concerning the DARP and the Pickup and Delivery Problem with Transfers (PDPT), since these problems are related to the DARPT. The PDPT, which is a special case of the DARPT without the maximum ride time constraints has been the subject of little research. Some of these works concerning the PDPT come from dial-a-ride applications, where no quality of service constraints or objective are considered.. Cordeau and Laporte [2] provide a litterature review about the DARP. The main heuristic methods proposed for solving the DARP are the following: Cordeau and Laporte [7] develop a Tabu Search . Parragh et al. [8] propose a Variable Neighborhood Search (VNS), whose results are competitive with the Tabu Search of Cordeau and Laporte [7] . Jain and Van Hentenryck [9] develop a constraint-based Large Neighborhood Search (LNS) to solve the DARP in limited time. Parragh and Schmid [10] integrate column generation in a Large Neighborhood Search.. As for the VRPTW, feasibility checking in local search methods has to be efficiently enforced for the DARP. The maximum ride time constraint complicates this task significantly and several algorithms have been proposed on this subject [11, 12] .. To the best of our knowledge, the first work considering the opportunity of transferring users in a dial-aride application is that of Stein [13] . In this study, neither the capacity of vehicles nor the time windows are taken into account. The objective is to minimize the completion time of all routes. The author propose two heuristics for this problem. Shang and Cuff [14] present a heuristic for a PDPT in which every vertex can be used to perform a transfer. In this work, the transfer operation can be viewed as a recourse policy, as transfers are used only if the insertion of a request into the solution requires the use of an additional vehicle. Tangiah et al. [15] adapt the heuristic of Shang and Cuff to a dynamic version of the problem. Cortés and Jayakrishnan [16] develop a simulation for a demand-responsive transit system that allows a single transfer per passenger, in order to evaluate the feasibility of such a system. Mues and Pickl [17] present a heuristic column generation for a problem with a single transfer point. The algorithm is evaluated on instances with up to 70 requests. Mitrović-Minić and Laporte [18] present a local search for a PDPT with uncapacitated vehicles. Experiments are performed on instances using the Manhattan distance. These instances consider up to 100 requests. Gørtz et al. [19] propose heuristics for a PDPT with capacitated and uncapacitated vehicles. Their objective is to minimize the makespan. Petersen and Ropke [20] present an ALNS for a pickup and delivery problem with a single transfer point, concerning the transportation of flowers in Denmark. The algorithm is evaluated on real-life instances containing up to 982 requests. Qu and Bard [21] propose a GRASP coupled with an ALNS. The algorithm is evaluated on instances with up to 25 requests. Masson et al. [5] develop an ALNS for the PDPT. They present competitive results on the instances of Mitrović-Minić and Laporte and on real-life instances with up to 193 requests.. Very few exact approaches have been proposed for the PDPT. Cortés et al. [22] introduce the first mathematical formulation of it, which they use to solve instances with up to six requests using a Branchand-Cut algorithm. Kerivin et al. [23] present a mathematical formulation for a version of the problem without time windows. In their formulation, the time is discretized and every vertex can be used to perform a transfer. Instances with up to 15 requests are solved using a Branch-and-Cut algorithm in less than five hours. Fugenschuh [24] works on a school bus problem where the routes are already designed and need to be assigned to a minimum number of vehicles. Some passengers can be transferred from one bus to another. Nakao and Nagamochi [25] present a lower bound for the cost of the solution of the PDPT with no time window and a single transfer point. This lower bound depends on the value z(P DP ) of the optimal solution without transfers. If z(P DP T ) denotes the optimal solution of the problem with transfers and |R| the number of requests, then z(P DP T ) > z(P DP ). . Masson et al. [26] develop a Branch-and-Cut-and-Price for a special case of the PDPT, called the Pickup and Delivery Problem with Shuttles routes, where the set of distinct delivery locations is limited. In this problem, a vehicle is not allowed to visit more than two distinct delivery locations within its route. Real-life instances are used for experimentations. Instances with up to 87 customers are solved to optimality in less than 1 hour.

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


STARPU: A Unified Platform for Task Scheduling on Heterogeneous Multicore Architectures Abstract. In the field of HPC, the current hardware trend is to design multiprocessor architectures that feature heterogeneous technologies such as specialized coprocessors (e.g., Cell/BE SPUs) or data-parallel accelerators (e.g., GPGPUs). Approaching the theoretical performance of these architectures is a complex issue. Indeed, substantial efforts have already been devoted to efficiently offload parts of the computations. However, designing an execution model that unifies all computing units and associated embedded memory remains a main challenge. We have thus designed STARPU, an original runtime system providing a highlevel, unified execution model tightly coupled with an expressive data management library. The main goal of STARPU is to provide numerical kernel designers with a convenient way to generate parallel tasks over heterogeneous hardware on the one hand, and easily develop and tune powerful scheduling algorithms on the other hand. We have developed several strategies that can be selected seamlessly at run time, and we have demonstrated their efficiency by analyzing the impact of those scheduling policies on several classical linear algebra algorithms that take advantage of multiple cores and GPUs at the same time. In addition to substantial improvements regarding execution times, we obtained consistent superlinear parallelism by actually exploiting the heterogeneous nature of the machine. Multicore processors are now mainstream. To face the ever-increasing demand for more computational power, HPC architectures are not only going to be massively multicore, they are going to feature heterogeneous technologies such as specialized coprocessors (e.g., Cell/BE SPUs) or data-parallel accelerators (e.g., GPGPUs). As illustrated by the currently TOP500-leading IBM RoadRunner machine, which is composed of a mix of CELLs and OPTERONs, accelerators have indeed gained a significant audience. In fact, heterogeneity not only affects the design of computing units itself (CPU vs CELL's SPU), but also memory design (cache and memory banks hierarchy) and even programming paradigms (MIMD vs SIMD).. But is HPC, and its usual momentum, ready to face such a revolution? At the moment, this is clearly not the case, and progress will only come from our ability to harness such architectures while requiring minimal changes to programmers' habits. As none of the main programming standards (i.e., MPI and OPENMP) currently address all the requirements of heterogeneous machines, important standardization efforts are needed. Unless such efforts are made, accelerators will remain a niche. In this respect, the OpenCL initiative is clearly a valuable attempt in providing a common programming interface for CPUs, GPGPUs, and possibly other accelerators. However, the OpenCL API is a very low-level one which basically offers primitives for explicitely offloading tasks or moving data between coprocessors. It provides no support for task scheduling or global data consistency, and thus can not be considered as a true "runtime system", but rather as a virtual device driver.. To bridge the gap between such APIs and HPC applications, one crucial step is to provide optimized versions of computation kernels (BLAS routines, FFT, and other numerical libraries) capable of running seemlessly over heterogenenous architectures. However, since no performance model that would allow to use a static hardware resource assignment is likely to emerge in the near future, these kernels must be designed to dynamically adapt themselves to the available resources and the application load.. As an attempt to provide a runtime system allowing the implementation of such numerical kernels, we have recently developed a data-management library that seamlessly enforces a coherent view of all hardware memory banks (e.g., main memory, SPU local store, GPU on-board memory, etc.) [1] . This library was successfully used to implement some simple numerical kernels quite easily (using a straightforward scheduling scheme), the next step is now to abstract the concept of task on heterogeneous hardware and to provide expert programmers with scheduling facilities. Integrated within high-level programming environments such as OPENMP, this would indeed help application developers to concentrate on high-level algorithmic issues, regardless of the underlying scheduling issues.. We here propose STARPU, a simple tasking API that provides numerical kernel designers with a convenient way to execute parallel tasks over heterogeneous hardware on the one hand, and easily develop and tune powerful scheduling algorithms on the other hand. STARPU is based on the integration of the data-management facility with a task execution engine. We demonstrate the relevance of our approach by showing how heterogeneous parallel versions of some numerical kernels were developed together with advanced scheduling policies. Section 2.2 presents the unified model we propose to design in STARPU. In section 3, we enrich our model with support for scheduling policies. We study how scheduling improves the performance of our model in section 4. We compare our results with similar works in section 5, and section 6 draws a conclusion and plans for future work. We presented STARPU, a new runtime system that efficiently exploits heterogeneous multicore architectures. It provides a uniform execution model, a high-level framework to design scheduling policies and a library that automates data transfers. We have written several scheduling strategies and observed how they perform on some classical numerical algebra problems.. In addition to improving programmability by the means of a high level uniform approach, we have shown that applying simple scheduling strategies can significantly reduce load balancing issues and improve data locality. Since there exists no ultimate scheduling strategy that addresses all algorithms, programmers who need to hard-code task scheduling within their hand-tuned code may experiment important difficulties to select the most appropriate strategy. Many parameters may indeed influence which policy is best suited for a given input. Empirically selecting at runtime the most efficient one makes it possible to benefit from scheduling without putting restrictions or making excessive assumptions. We also demonstrated that given a proper scheduling, it is possible to exploit the specificity of the various computation units of a heterogeneous platform and to obtain a consistent superlinear efficiency.. It is crucial to offer a uniform abstraction of the numerous programming interfaces that result from the advent of accelerator technologies. Unless such a common approach is adopted, it is very unlikely that accelerators will evolve from a niche with dispersed efforts to an actual mainstream technique. While the OPENCL standard also does provide task queues and an API to offload tasks, our work shows that such a programming model needs to offer an interface that is simple but also expressive.. We plan to implement our model on additional accelerator architectures, such as the CELL by the means of a driver for the CELL RUNTIME LIBRARY [12] , or on top of generic accelerators with an OPENCL driver. In the future, we expect STARPU to offer If accelerators have received a lot of attention in the last years, most people program them directly on top of constructors' API at a low level, with little attention to code portability. While GPGPUs were historically programmed using standard graphical APIs [14] , AMD's FIRESTREAM and especially NVIDIA's CUDA are by far the most common way to program GPUs nowadays. Likewise, CELL is usually programmed directly on top of the low level LIBSPE interface even if IBM ALF targets both CELL and multicore processors. FPGA, CLEARSPEED and all other accelerating boards still need specific vendor interfaces. Most efforts however tend to be around writing fast computation kernels rather than designing a generic programming model.. In contrast, multicore (and SMP) programming is getting more mature and standards such as OPENMP, which has gained substantial audience in spite of MPI which still remains the most commonly used standard in HPC. Besides the OPENCL standardization effort which not only attempts to unify programming paradigms, but also proposes a low-level device interface, a lot of projects thus try to implement the MPI standard on the CELL [13] while it does not seem to be adapted for GPUs even if it becomes common to use hybrid models (e.g., CUDA with MPI processes). DURAN et al. propose to enrich OPENMP with directives to declare data dependencies [8] , which is particularly useful for all accelerator technologies. OPENMP therefore seems to be a promising programming interface for both CELL [4] and GPUs provided compiling environments are offered sufficient support. STARPU could thus be used as a back-end for CELLSS or for the HMPP [7] which generate codelets resp. for the CELL and for GPUs.. A lot of efforts have also been devoted to design or to extend languages with a proper support for data and task parallelism, but most of them actually re-implement a streaming paradigm [11] which does not necessarily capture all applications that may exploit accelerators. Various projects intend to implement libraries with computation kernels that are actually offloaded [5] , but STARPU avoids for instance the limitation of the size of problems solved by BARRACHINA et al. [3] while preserving the benefits of their work at the algorithmic level.. Some runtime systems were designed to address multicore and accelerators architectures [6, 12, 16] . Most approaches adopt an interface similar to CHARM++'s asynchronous OFFLOAD API. The well established CHARM++ runtime system actually offers support for both CELL [10] and GPUs [16] (even though there are no performance evaluation available yet for GPUs to the best of our knowledge). But its rather low level interface only has limited support for data management: offloaded tasks only access blocks of data instead of our high level arbitrary data structures, and they do not benefit from our caching techniques. JIMENEZ et al. use performance prediction to schedule tasks between a CPU and a GPU [9] , but their approach is not applicable to scheduling inter-dependent tasks since data transfers are explicit.

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


An application of Darbo's fixed point theorem in the investigation of periodicity of solutions of difference equations Using the technique of Darbo's fixed point theorem we investigate a nonlinear second order difference equation of the form @D(r"n@Dx"n)=a"nf(x"n"+"1) where x:N"0->R, a,r:N"0->R and f:R->R is a continuous function. Additionally, the Sturm-Liouville difference equation is considered as a special case of the above equation. Sufficient conditions for the existence of an asymptotically periodic solution of this equation are obtained. An example illustrates the result. Next, the conditions under which this equation has no asymptotically periodic solutions are presented.

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Towards Integration of Biological, Psychological and Social Aspects in Agent-Based Simulation of Violent Offenders In the analysis of criminal behavior, a combination of biological, psychological and social aspects may be taken into account. Dynamical modeling methods developed in recent years often address biological, psychological or social dynamical systems separately. This paper makes the first step in the development of an agent-based modeling approach for criminal behavior in which these aspects are integrated in one dynamical system. It is shown how within a certain (multi-agent) social context, biological factors, such as certain brain deviations, testosterone levels and serotonin levels, affect cognitive and emotional functioning in such a way that a crime is committed when the perceived opportunity is there. This paper presents one generic model for the behavior of violent offenders with parameters that can be set to obtain simulation traces for three known types of offenders. Within criminology, the analysis of criminal behavior is a central issue. Such an analysis involves different aspects, such as biological, psychological, and social, and their mutual interactions [e.g. [1] [2] [3] [4] [5] [6] . Usually such analyses are made by criminologist researchers or practitioners in a non-exact manner, without using any formalization or computer support. The interplay between the various aspects involved may be complex and dynamic. Therefore such a task requires a rare combination of expertise in different knowledge domains. But even if such a combination of expertise is available, often it is not straightforward and in certain cases may be quite difficult indeed. Therefore computer support is more than welcome, both concerning the expertise in the different knowledge domains and the complexity of the dynamical aspects of the integrated process. Due to the difficulty to address this area within criminology, the few contributions made to the literature often address only one or some of these types of aspects, for example, social and environmental aspects, as in [7] .. In recent years much progress has been made in biological, cognitive and social complex dynamical systems modeling within areas such as artificial intelligence, computational biology/artificial life, cognitive science, and computational social science/organization theory. The methods developed in these areas usually address one of the disciplines separately. For example, in social simulation the agents usually are assumed to show simple behav-iors, and their internal cognitive systems are not taken into account. Similarly, in cognitive modeling often biological factors are not addressed [8] .. However, when an integrated modeling approach is applied, this opens the perspective to address the analysis of criminal behavior in more exact, formalized and computer-supported manners. Thus, the way is paved to a more solid basis and computer support for simulation and analysis in the area of criminology. The research discussed here explores this potential. It identifies on the one hand useful knowledge from the literature in criminology and the different disciplines underlying it [e.g. 1, 4, 5, 9, 10] , and on the other hand it exploits dedicated agentbased modeling techniques [10] . The aim is, by combining these, to develop an integrated computer-supported method to criminal behavior analysis and management. The work reported here has been performed in close collaboration with a team of scientists from different disciplines including outstanding criminologists and psychologists. They consider the approach explored here as having a high potential to develop support for policy makers and practitioners in management of crime in society.. As part of this enterprise, agent-based dynamical models for different types of criminal behavior are being developed. These models may incorporate behavioral agent models from an external perspective, as well as models for internal dynamics. Behavior models from an external perspective may involve rather complex temporal relationships between (1) external factors in the criminal's social context that occur as stimuli and (2) their actions, mediated by their characteristics. Models of internal dynamics usually can be expressed by direct temporal/causal relationships between stimuli and internal states, between different internal states, and between internal states and actions. The internal states may involve, for example, cognitive, decision, reasoning, normative/ethical, attentional, emotional and personality aspects. In addition, they may involve underlying biological aspects, such as specific types of brain deviations, levels of hormones or neurotransmitters. Examples of aspects related to the wider social context are the observed level of social or organized security control, expectations about acceptance of certain actions within society or within a peer group, and social dynamics within groups. Such dynamical models are being collected in a model library. Moreover, relationships between such models are to be established, for example the fact that one model M 2 refines another model M 1 , or that a model M 1 from an internal perspective generates the behavior of a model M 2 from an external perspective.. As a first step in that direction, this paper presents one generic simulation model for the behavior of violent criminals. As input, certain parameters can be set with respect to biological and cognitive characteristics of a type of criminal, and social and environmental aspects of its environment. As output, simulation traces are generated that show the behavior over time of such a type of criminal under these circumstances.. In comparison to existing work in the analysis of criminal behavior, an important distinction is that the agentbased modeling approach presented here focuses on the dynamical aspect of criminal behavior. Most approaches to the analysis of criminal behavior that have been proposed are basically static and usually based on profiling, i.e. they assume a number of fixed criminal profiles, whose behavior depends in a deterministic way on certain personality characteristics, thereby ignoring the fact that these characteristics often are quite context-sensitive and may change over time [11] . In contrast, the proposed approach (1) takes the dynamical systems perspective on behavior as a point of departure, which considers behavior as emerging from a dynamic interplay of various components and aspects, and (2) provides an integrated approach to model such complex dynamical systems incorporating biological, psychological and social aspects.. In this paper, Section 2 discusses three specific types of criminals used as a case study: the violent psychopath, someone with an antisocial personality disorder (APD) and someone diagnosed with an intermittent explosive disorder (IED). In Section 3 the proposed methodology is discussed. In Section 4 the simulation model is presented and in Section 5 the settings for the model are discussed. Section 6 discusses some of the simulation results. Section 7 presents the validation of the simulation model and, finally, Section 8 is a discussion about the approach and its possible applications. In this article, a method to analyze criminal behavior based on integrated dynamic modeling is proposed. A generic model has been presented for the behavior of violent criminals. As input certain parameters with respect to biological, cognitive and social aspects can be set. As output simulation traces are generated that show the behavior of a violent offender over time under certain circumstances. As a case study, this method has been applied to analyze the behavior of three types of violent criminals. It has been found that the model indeed shows the behavior as known for these criminals. It takes into account a cognitive modeling approach to the preparation of actions based on BDI in a more or less standard manner [27] . However, for this standard BDI-model, desires and beliefs about opportunities are required as input. Concerning the former, additional biological, cognitive and emotional aspects have been used as a basis to generate desires. For the latter, additional social aspects have been used to generate beliefs on opportunities based on two specific criteria (suitable target, presence of guardian) s indicated by the Routine Activity Theory in [6] . For the generation of desires various other aspects as found in the literature are taken into account, varying from specific types of brain deviations, and serotonin and testosterone levels, to the extent to which me-other differentiation and a theory of mind were developed.. Thus the model integrates biological, cognitive and socially related aspects in the process of desire generation, as extracted from literature, in particular [4, 5, 9] . These involve both qualitative aspects (such as the anatomy of brain deviations, and presence or absence of agents at a specific location in the world) and quantitative aspects (such as distances and time durations in the world and hormone and neurotransmitter levels).. To achieve the integration of different aspects, the proposed modeling approach (based on the LEADSTO language) integrates qualitative, logical aspects and quantitative, numerical aspects. This integration allows exploitation of techniques from both areas. As the latter type of aspects are fully integrated in the former, this results in a declarative specification for which automated methods for logical analysis can be exploited. Conversely, as the former type of aspects is fully integrated in the latter, a simulation environment is offered that extends the usual possibilities to simulate dynamical systems using numerical methods, by incorporating qualitative elements.. Only a few papers on simulation of criminal behavior can be found in the literature, and they usually address a more limited number of aspects than the modeling approach presented in this paper. For example, [29] discuss the possible use of agent modeling approaches to criminal behavior in general, but do not report a specific model or case study. Moreover, in [7] a model is presented with emphasis on the social network and the perceived sanctions. However, this model leaves the psychological and biological aspects largely unaddressed. The same applies to the work reported in [30] , where an emphasis is on the environment, and police organization.. Within the literature of agent-based and cognitive modeling, a number of approaches have similarities with the approach presented in this paper. To start, the presented approach, and in particular the BDI-submodel, obviously has some similarities with the literature on which it was based, such as [24] [25] [26] . However, traditionally, within BDI-models no general model for generation of desires (or goals) is included. In many cases desires are simply assumed to be there, or even communicated to the agent as goals it should adopt. This holds for the traditional BDI-based approaches mentioned above as well as for application-oriented frameworks based on BDI concepts, such as PRS [31] . Nevertheless extensions of BDI models are being developed in which this is the case, e.g. in Jadex [32] . One addressed aspect is the revision of desires as a result of undertaken actions that fulfill them. Another aspect relevant for desire generation is the biological substrate of the agent. Sometimes desires are just inherent to a certain biological makeup or state. The current paper takes a similar approach, namely to incorporate biological and psychological factors into a submodel for generation of desires. Within the paper, a number of biological aspects as found in the literature have been taken into account in the dynamic generation of desires, varying from specific types of brain deviations, and serotonin and testosterone levels, to the extent to which a substrate for theory of mind was developed. Moreover, the generation of beliefs in opportunities has been based on environmental and social aspects involving two specific criteria (suitable target, presence of guardian) as indicated by the Routine Activity Theory in [6] .. Another novel approach in the literature that is worth comparing with our approach is the cognitive architecture CoJACK [33] . It is based on JACK, a Java-based Intelligent Agent Modeling Framework, and also makes use of the BDI paradigm. Similar to our approach, CoJACK extends this paradigm with biological and psychological factors underlying behavior. However, the intended applications of CoJACK are different: its main aim is the development of virtual agents within (military) simulation environments, whereas the current paper focuses on modeling the behavior of violent criminals. As a result, the biological and psychological factors considered are different. For example, CoJACK addresses concepts such as fatigue and fear, whereas the current approach addresses concepts that are specific for criminal behavior, such as aggressiveness and impulsiveness.. The current model forms a good basis for further development. It will not be difficult to take into account other or new useful literature on relevant (biological, cognitive, social) factors and their relationships as soon as it is made available. The model was kept simple in the generation of intentions for a given integrated desire: only one intention is possible per desire. When a number of intentions are possible for a given desire, then more specific decisionmaking aspects come into play, for example, involving utility-based (multi-objective) decision making, e.g. as described in [34] , or sophisticated planning mechanisms as described in [30] . Also such approaches can easily be added to the model. In the current model, only few quantitative aspects have been incorporated, but this can be extended easily, as is shown, for example, in [35] , where numerical adaptation techniques are part of the model. Also approaches, as proposed in [36] , can be incorporated.. In addition, the model may be extended with probabilistic notions. Although the presented version of the model incorporates only deterministic relationships, the latest version of LEADSTO [10] enables the modeler to specify non-deterministic dependencies of the format 1 1 21 6 22, where different probabilities can be attached to the consequents 21 and 22. This may be a promising direction, for example, to model biological processes for which only knowledge exists about rough correlations, instead of well-established causal relations. A drawback is, however, that this approach forces the analyst to perform a large number of simulations (as in Monte Carlo simulation) instead of just one. This direction will be further explored in future research.. The team of outstanding domain experts from psychology and criminology who have evaluated the work reported here considers it as quite valuable and promising. In their view this work is a substantial step to obtain a solid basis to develop future applications to support policy makers and practitioners who have to handle the problem of crime in society. However, still there is quite some way to go. The problem of crime in society has substantial complexity and is a major challenge to be addressed. Therefore steps in this direction are to be considered with an appropriate extent of modesty. At this point in time ready-to-use applications are asked far too much, as much more work on research and development has to be invested, both in modeling and in the empirical area. For the empirical area systematic validation experiments to be set up are a challenge by themselves. For the modeling area, given the modest perspective as sketched, dynamical models for criminal behavior of the types as discussed above can be useful in a number of ways. In the first place, as shown in the current paper, they can be used to simulate behavior for given scenarios of circumstances occurring over time. This can be used to establish for such a given scenario of circumstances whether a criminal of a certain type may show certain behavior under these given circumstances. Moreover, as to be explored further in future work, such a model can be used in the opposite direction, i.e. given a certain behavior, to determine what kind of scenario of circumstances could lead to this behavior. Some initial steps in this direction have been made in [37] . More generally, the model can be used in the situation that the circumstances and/or the behavior are only partially given. In that case, the model can be used to complete this partial information, i.e. to find out which (completed) behavior could be consistent (or inconsistent) with which (completed) circumstances, and to find out which additional information should be investigated to determine Volume 85, Number 10 SIMULATION 651 one or more completions of the partial information that are realistic [38] . Finally, such a model can be used for therapeutical reasoning. For example, it may be used to predict which behavior a certain type of criminal will show if circumstances are avoided or slightly changed ('what if' reasoning). Using this approach, the behavior of the subject can be modified by selecting or avoiding the appropriate circumstances. Another possible use of such a model in therapeutical reasoning is to determine a (cognitive) training program for the criminal to adapt the relationship between circumstances and behavior.

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 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 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 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 O O O O O O O O O O O O O O O O O O O O O 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Tight Upper Bounds on the Minimum Precision Required of the Divisor and the Partial Remainder in High-Radix Division Abstract-Digit-recurrence binary dividers are sped up via two complementary methods: keeping the partial remainder in redundant form and selecting the quotient digits in a radix higher than 2. Use of a redundant partial remainder replaces the standard addition in each cycle by a carry-free addition, thus making the cycles shorter. Deriving the quotient in high radix reduces the number of cycles (by a factor of about h for radix 2 h ). To make the redundant partial remainder scheme work, quotient digits must be chosen from a redundant set, such as [-2, 2] in radix 4. The redundancy provides some tolerance to imprecision so that the quotient digits can be selected based on examining truncated versions of the partial remainder and divisor. No closed form formula for the required precision in the partial remainder and divisor, as a function of the quotient digit set and the range of the partial remainder, is known. In this paper, we establish tight upper bounds on the required precision for the partial remainder and divisor. The bounds are tight in the sense that each is only one bit over a well-known simple lower bound. We also discuss the implications of these bounds for the quotient digit selection process. DIVISION is the most complex, and hence slowest, of the four basic arithmetic operations. Thus, techniques for speeding up division have been extensively studied by researchers in computer arithmetic [9] . Simple dividers are usually based on digitrecurrence algorithms employing repeated additions, while highperformance implementations tend to use multiplier-based convergence schemes. In digit-recurrence division [3] , digits of the quotient are derived one at a time, from the most to the least significant. For a k-digit quotient, there are at least k cycles in the division process; one cycle for producing each radix-r quotient digit, plus additional cycles for initialization, possible final correction, and rounding.. There are but two ways to speed up such an algorithm: reducing the number of cycles and making each cycle shorter in duration. The first implies higher radix division, while the second leads to several techniques, including keeping the partial remainder in redundant form so as to eliminate the relatively long delay of carry-propagate addition in each cycle. Regardless of the design choices at the algorithmic level, circuit techniques can be used to improve the divider speed and often have a significant impact on the resulting performance [5] . We do not deal with circuit techniques in this paper.. To make the use of redundant partial remainder possible, quotient digits must be chosen from a redundant set, such as [-2, 2] in radix 4. The redundancy provides some tolerance to imprecision so that the quotient digits can be selected based on examining truncated versions of the divisor and the partial remainder [12] , [1] . A redundant partial remainder that is truncated to a few bits can be quickly transformed into an estimate for the partial remainder or its bits used directly as inputs to a PLA or ROM table that spews out quotient digit values. Among other issues, the designer of a fast digit-recurrence divider determines the precision with which the divisor and the partial remainder must be examined in order to deduce the value of the next quotient digit. This precision, stated in the number of bits before and after the radix point, dictates the complexity of the PLA or the size of the ROM table yielding the quotient digit value. The PLA/ROM size influences not only the cost (VLSI area), but also the circuit speed, given that the quotient digit selection block is usually on the critical path.. Many practical aspects of the quotient digit selection process and associated hardware implementations have been discussed in the literature [13] , [3] , [7] . Particularly relevant to this work are the original analysis by Atkins [1] showing the minimal precision required and more recent contributions by Burgess and Williams [2] and Oberman and Flynn [8] elaborating on the selection criteria and trade offs. These latter contributions will be reviewed in Section 6 dealing with redundant representation of the partial remainder.. No closed form formula for the required precision in the divisor and the partial remainder, as a function of the quotient digit set and the range of the partial remainder, is known. So, the design process is often described as trial and error. In this paper, we establish tight upper bounds on the minimum precision required for the divisor and the partial remainder. The bounds are tight in the sense that each is only one bit over a well-known simple lower bound, leading to the requirement for just four trial points during the design process: the one represented by the lower bounds, one (or two) more bit(s) of precision for d, one more bit of precision for p. If none of these four points leads to a viable design, then one more bit of precision for both d and p is guaranteed to work. We also elaborate on the implications of these results on the design of practical SRT dividers that use a redundant representation for the partial remainder. The notation used in our analyses is listed in Table 1 for ready reference. In the literature on computer arithmetic, it is often mentioned that determining the precisions required of truncated versions of d and p to correctly choose the radix-r quotient digits from the digit set [-a, a] involves several iterations over the design space. In this paper, we have proven that the number of cases to be tried is limited to a handful, as listed in Table 2 and further augmented in Section 6, given choices for r (power-of-2 radix) and a (defining a symmetric, redundant digit set). Theorem 1, along with some of its implications to the design of high-radix dividers, constitutes the main contributions of this work.. Considering that the trials mentioned above are easily mechanized, as demonstrated in Fig. 4 , and that the choice of the radix r is quite limited by cost/performance requirements, the design process is not as cumbersome as one might have thought. This is true even after variations in the format of the redundant partial remainder (Fig. 5) are taken into account. It would be interesting to see if corresponding results for high-radix square-rooting, which is intimately related to SRT division, can be derived.. A possible area for future research is that of quotient digit-set encoding. In our derivations, the chosen quotient digit q i was treated as a single indivisible entity. However, a high-radix digit set must be encoded as a collection of bits. Possible choices include 2'scomplement representation, gray-code encoding [8] , and ad hoc sign-plus-weighted-bits encodings that facilitate the multiple generation process. With any particular choice of encoding, each bit in the representation of the selected quotient digit can be viewed as a separate function of the truncated divisor and partial remainder. Using separate logic circuits or tables to obtain these bits can potentially lead to savings in the total circuit complexity or table size.

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 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 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 B I I 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 O O 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


Investigating and exploiting the bias of the weighted hypervolume to articulate user preferences Optimizing the hypervolume indicator within evolutionary multiobjective optimizers has become popular in the last years. Recently, the indicator has been generalized to the weighted case to incorporate various user preferences into hypervolume-based search algorithms. There are two main open questions in this context: (i) how does the specified weight influence the distribution of a fixed number of points that maximize the weighted hypervolume indicator? (ii) how can the user articulate her preferences easily without specifying a certain weight distribution function?In this paper, we tackle both questions. First, we theoretically investigate optimal distributions of μ points that maximize the weighted hypervolume indicator. Second, based on the obtained theoretical results, we propose a new approach to articulate user preferences within biobjective hypervolumebased optimization in terms of specifying a desired density of points on a predefined (imaginary) Pareto front. Within this approach, a new exact algorithm based on dynamic programming is proposed which selects the set of μ points that maximizes the (weighted) hypervolume indicator. Experiments on various test functions show the usefulness of this new preference articulation approach and the agreement between theory and practice. In the context of evolutionary multiobjective optimization, the hypervolume indicator is a set quality measure being a refinement of the Pareto dominance, i.e., whenever a Pareto set approximation entirely dominates another one, then the measure of the former will be larger. Hence, maxPermission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. imizing the hypervolume indicator is, in general, in accordance to the Pareto dominance relation [15, 13, 20] . In recent years, this significant property has made the indicator popular as a selection criterion in evolutionary multiobjective optimizers [4, 14, 18] .. An important question in this context concerns the bias of the hypervolume indicator when introduced into search. In a recent study [2] , this bias has been investigated theoretically by characterizing the distribution of μ points that maximize the hypervolume indicator, so-called optimal μ-distributions. When hypervolume-based algorithms are employed, the inherent bias of the hypervolume indicator is often unwanted but rather the incorporation of the user's own preference into search is desired. Several approaches for articulating these user preferences are known from the literature, e.g., by defining preference points [11] , specifying preferred search directions [10] or defining linear minimum and maximum tradeoffs [6] . For a general overview of articulating user preferences, we refer to [16, 7, 17] .. Recently, a general framework to incorporate user preferences into hypervolume-based search algorithms has been proposed [18] . The so-called weighted hypervolume indicator allows stressing certain regions of the objective space by applying a weight distribution. It has been shown for three different weight distribution functions that optimizing the weighted hypervolume indicator results in solutions clustered in regions with higher weight whereas regions with low weight contain only a few solutions. Further work improved the applicability of this weighted hypervolume approach to problems with many objectives by means of Monte Carlo sampling [1] .. Two main questions arise in this context: (1) what is the bias of the weighted hypervolume indicator, i.e., how can the distribution of μ points maximizing the weighted hypervolume be characterized ? (2) how can the user articulate and integrate her preferences easily into the search without defining the weight distribution functions by hand?. Both questions are tackled in this paper. First, we investigate the optimal distribution of μ points optimizing the weighted hypervolume indicator; generalizing the results for the unweighted case presented in [2] to the weighted case. Second, we propose a new approach to articulate user preferences by defining a reference front and a desired density of points on that front. This user preference is automatically transferred into a weight distribution function for the weighted hypervolume of [18] , the optimization of which guarantees that the resulting distribution of solutions on the actual front follows the desired density. This paper is organized as follows: In Sec. 3 we generalize the theoretical results on optimal μ-distributions from [2] to the weighted hypervolume. Based on the theoretical results on optimal μ-distributions, we propose in Sec. 4 a new approach for articulating user preferences in terms of defining a desired density of points on a predefined front for biobjective problems. In Sec. 4.2 we incorporate the weighted hypervolume into search and propose a new exact algorithm for selecting the best q individuals from a set of p solutions that maximize the overall (weighted) hypervolume by means of dynamic programming for biobjective problems. In Sec. (5), we apply the new approach to several test problems for scenarios with known and unknown Pareto fronts. The hypervolume indicator has an inherent characteristic in terms of how a set of μ solutions, optimizing the hypervolume indicator, is distributed on the Pareto front, which has been expressed in terms of density in [2] . However, the bias can be modified by applying weight distribution functions as shown in [18] . Here, the two precursor studies have been combined to derive the density for the weighted case. On the one hand, this allows to determine the bias of the weighted hypervolume in a concise manner. On the other hand, the dual viewpoint has been taken to determine the weight distribution for a given density and front shape. This enables to express user preferences in a very precise way by a unary indicator.. To utilize the indicator for search, an approximation of the weight distribution function by means of piecewise constant rays has been suggested. It allows simplifying the hypervolume calculation while maintaining desirable properties. Additionally, an algorithm based on dynamic programming that selects solutions yielding maximal hypervolume value has been proposed. A visual comparison of the obtained Pareto front approximations with the expected densityprovided by the user-has shown the practical usefulness of the theoretical concept as well as the efficiency of the proposed algorithm. The approach is restricted to biobjective problems, though. Therefore, we should aim at extending it to more objectives in future studies. The approach has also to show its usefulness in real-world applications. In the following, the distribution of points obtained when using different weight functions and test problems are presented. To this end, a graphical representation is used that shows multiple elements (see Fig. 4(a) ): (i) the solutions found ( ) together with the Pareto front ( ); (ii) the front, specified by the user, that is used to calculate the weight rays ( ) if differing from the Pareto front; (iii) the weight per ray proportional to the length of gray bars ( ) and at intervals of 10. • the direction of the rays ( ) (iv) the density desired by the user ( ) as a function of the angle in polar coordinates with 0 lying at the radius where the weight bars start (e.g., at r = 1.2 for Fig. 4(a) ); and (v) the obtained density represented by the solutions in terms of a histogram ( ) in the same coordinate system than the desired density. In this section, the theoretical concept to model (Sec. 3) and to optimize (Sec. 4) user preferences by a weighted hypervolume indicator are examined by simulations. To this end, the algorithm and the test problems used are presented first. After that, the Pareto front approximations obtained by the algorithm are visually compared to the expected density that corresponds to the user's preference. The approach derived in Sec. 4 is applied to different test problems and user preferences. Unless noted otherwise, the latter is modeled by 90 stripes starting from the origin which corresponds to a resolution of 1. • , see Eq. 8. The reference point of the hypervolume is set to (1000, 1000) to ensure the extremes in the optimal μ-distribution if possible [2] .. The evolutionary algorithm in use first generates an initial population of α individuals that code potential solutions as real vectors. Thereafter, μ parent individuals are selected uniformly at random to generate λ offspring using the SBX crossover operator and the variable-wise polynomial mutation operator [9] . The recombination and mutation probabilities were set according to [12] . After that, non-dominated sorting and front-wise removal is carried out as in [18] . From the set F of equally ranked solutions, the omission of which would result in a population P that is smaller than α, the q = α − |P | solutions computed by Alg. 1 that solve the HSSP on F are taken to fill up the population to |P | = α. The above steps are repeated for N generations. In this study N = 1, 000 and α= λ= μ = 50. The main difference between the described algorithm and standard hypervolumebased algorithms such as SIBEA [18] is the environmental selection step where Alg. 1 is used instead of a greedy strategy to solve the HSSP.. As test problems, ZDT1 (front shape. 2 ), and ZDT3 (discontinuous front) [19] . l ← (0, . . . , 0) 6: . 5(a) to 5(f) as in 4(c)

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