Development of a Web-based Multi-criteria Spatial Decision Support System for the assessment of environmental sustainability of dairy farms The assessment of the environmental sustainability of agricultural infrastructures involves the use of multiple evaluation criteria and the analysis of geographical information. A Geographic Information System (GIS) is a computer system capable of assembling, storing, analyzing, and displaying geographically referenced information.However, the GIS technology still suffers from several shortcomings due in large part to a lack of capable analytical capacity of supporting spatial decision problems. The most Spatial decision problems in agriculture and other areas often require that a large number of alternatives are evaluated based on multiple criteria. Geographic Information Systems (GIS) are a powerful tool for analysing spatial data and establishing a process for decision support. Multicriteria Decision Aid (MCDA) methods can facilitate decision making in situations where several solutions are available, various criteria have to be taken into account and decision makers are in conflict (Dias et al., 2002) .. The combination of spatial analysis with MCDA has allowed the creation of Multicriteria Spatial Decision Support Systems (MC-SDSS), whose aim is to formulate and support spatial decision problems. This process involves the use of geographical data, the decision maker's (DM) preferences and the manipulation of the data and preferences according to specified decision rules (Sharifi and Retsios, 2004; Malczewski, 2006) .. The integration of MCDA tools in GIS has been used in several projects and studies from different areas over the last twenty years as evidenced by the survey by Malczewski (2006) . One of the most remarkable features of the GIS-MCDA approaches is the wide range of decision and management situations in which they have been applied, such as environment/ecology, transportation, urban/regional planning, waste management, hydrology, agriculture, forestry, geology, or site selection. Among some works, we highlight the works of Joerin et al. (2001) , Gilliams et al. (2005) , Aydin et al. (2010) , Marinoni (2004) , Eldrandaly et al. (2005) , Boroushaki and Malczewski (2008) , Vogel (2008) , applied in different areas. In these applications the flexibility in representing and analysing spatial information is particularly pertinent as it is assumed that about 80% of the data used by decision-maker (DM) in decision processes are geographically interrelated (Worrall, 1991) .. Current developments in computational speed, storage volumes, World Wide Web (WWW) global access and software integrated development environments (IDE) provide opportunities to develop SDSS exploring both the advantage of information dissemination for DMs and the integration of GIS-MCDA. One of the greatest benefits of using Web Services in spatial decision making is the potential to overcome limited resources in terms of time, data and communication. The web enabled GIS facilitates decision making and serves as a gateway for decision makers and general users to access the system conveniently and effectively.. The typical Web SDSS is a web-based GIS, where GIS information implemented in World Wide Web environment (Google Maps, and others) and Open Source GIS software is used, where MCDA methods are integrated. In this paper we develop a distinct Web SDSS: a web-based Multicriteria Decision Aid in GIS software. This Web MC-SDSS integrates an MCDA method which is solved by a Web-based Algorithms Server that contains various MCDA tools, according to a clearly defined communication protocol. This integration uses the ArcGIS commercial software as user front-end. The Web MC-SDSS interface created named ELECTRE TRI in ArcGIS is a full integration of the MCDA outranking ELECTRE TRI method and GIS through the construction of a macro written in Visual Basic for Applications (VBA) programmed in ArcGIS 9.3 of ESRI. This interface is capable of: 1) providing mechanisms for the input of spatial data; 2) allowing representation of the spatial relations and structures; 3) applying the analytical techniques of spatial and geographical analysis; 4) providing output in a variety of spatial forms, including maps; 5) performing sensitivity analysis.. The resulting Web MC-SDSS was developed to address a real-world case study of decision analysis to assess environmental sustainability of dairy farms in Portuguese region, although it can be applied to other studies in different areas. Namely, the system was used to classify 1705 dairy farms in the Entre-Douro-e-Minho (EDM) Region according to environmental sustainability criteria. Seven environmental criteria were defined by three experts from Environmental and Zoo-technic areas. The classification allows determining which farms are sustainable from an environmental perspective, which ones are not sustainable, and, as an intermediate category, which ones are barely sustainable. This paper is divided into five sections. Sections 2 e 3 offers a brief literature review regarding the Multicriteria Spatial Decision Support Systems, characterizing their types and directions of integration of MCDA and GIS as well as integrations available in GIS software and the development of Web MC-SDSS. In section 4, the case study with description of problem and the criteria involved as well as the characterization of the chosen method, ELECTRE TRI, is presented. In section 5, we introduce the MC-SDSS approach, enhancing the type of developed integration of GIS-MCDA, as well as the created architecture of MC-SDSS. Finally, in section 6 the conclusions that have been drawn from the study are presented encouraging the opportunities for expanding the work. Spatial and multicriteria aspects of the studied problem led us to develop a spatial decision support system. This system incorporates ELECTRE TRI method into ArcGIS 9.3 of ESRI. The power of this method lies in the aggregation mode of decision-maker performances and the assignment of the potential alternatives to predefined categories.. The developed system is of special importance insofar as it integrates GIS functionalities and MCDA methods in a single framework.. This paper presents a tool that integrates GIS and MCDA. GIS was used as the core of the integrated system and the MCDA models were integrated to the GIS using the programming facilities provided by the GIS software. The developed ELECTRE TRI in ArcGIS, VBA macro integrates all the components of a fully-integrated system:. geographical data management and analysis tools, MCDA models and user interface. It is a user-friendly interface for configuration, prediction, visualization and analysis of the model outcomes in the same environment and thereby allowing an evaluation process which is uniform, transparent and demands less technical effort from decision makers. The exploitation of graphical display potentialities of this system provides the decision maker with information increasingly richer and easier to grasp. With GIS, data may be available in a format which will be easily interpreted, can be interactively displayed, is ready to digital processing and can be easily updated. The design and implementation of ELECTRE TRI in ArcGIS is an innovative conceptual framework for application of MCDA in spatial problems, with recourse to the Algorithm Server for ELECTRE TRI method application.. Considering the case study, one notes the worrying situation in which many farms in the EDM Region are found regarding their environmental sustainability. The interface allows analysing the geographical distribution of the environmental sustainability classification of dairy farms. Overall results show that MC-SDSS represents valuable decision support tools by providing a platform for the integration of information, models and methods necessary to assess the environmental sustainability of dairy farms.. This MC-SDSS can be easily adapted to other applications in many areas and other MCDA Algorithm Servers.. This approach, however, still presents the following limitations: the centralized processing system requires an internet connection at least to initialize the server and to obtain the results; and the developed integration may no longer work if there are changes in the communication protocol or if a particular method is no longer available on the server. However, this is compensated by the gains in computer performance and the avoided time costs in code programming and debugging a MCDA method that others have already developed and optimized.. In the future, this research can be extended to the application of other MCDA methods by: (i) using the communication protocol of algorithm server; (ii) inserting methods for eliciting the parameters of MCDA method chosen (Figueira and Roy, 2002; Dias et al., 2002) ; (iii) extending to other real problems to assess sustainability (or other context). This methodology can also be extended to group decision-making domain by considering a group opinion and web-collaborative service. The current last version of ArcGIS (version10) includes compatibility for VBA, but ESRI announced the end of the support for VBA in ArcGIS Desktop in future versions. In this case the VBA code developed can be migrated to .NET or re-written in Python language (the new programming language available to customize and extend ArcGIS).

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


Operation Mechanism of the Driving Force System of Ecosystem of Cyber-society Based on the System Dynamics Abstract: Operation of the driving force system of Ecosystem of Cyber-society needs a scientific mechanism of intervention and regulation to solve the integration problem of a variety of organizations and forces within the Ecosystem of Cyber-society, shorten the process from uncoordination to coordination, promote the orderly operation of the driving force system of Ecosystem of Cyber-society, make the system play a strong force, in order to promote the formation and rapid development of Ecosystem of Cyber-society. We analyze the driving force system of Ecosystem of Cyber-society using the theory of System Dynamics and propose a theoretical framework, and then present its operation mechanism systematically. The operation of the driving force system needs certain operation mechanism, which refers to create interaction relationships between the driving forces, establish a fulcrum, platform and regulation for the driving forces, so that the driving force system can rely on the environment of the driving force system, and make the driving forces function effectively. Similarly, the operation of the driving force system of Ecosystem of Cyber-society also needs a scientific mechanism of intervention and regulation to solve the integration problem of a variety of organizations and forces within the Ecosystem of Cyber-society, shorten the process from uncoordination to coordination, promote the orderly operation of the driving force system of Ecosystem of Cybersociety, make the system play a strong force, in order to promote the formation and rapid development of Ecosystem of Cyber-society. However, since the driving force system consists of a lot of driving forces, its hierarchy is very complex with multi-levels, and different structures may emerge unexpected functions, so we need to find out an effective way to analyze it.. Currently, among the literature can be found around the world, although some scholars have put forward the concept of ecological networks from different perspectives and gradually realized the importance of this research area, there is still not much comprehensive and systematic research about the cyber-society from the perspective of ecosystem. And there is no literature that has proposed the concept of driving force system of Ecosystem of Cyber-society and studied its mechanism systemically from the perspective of the ecosystem for the development of cybersociety. It is a new research area.. The related research mainly focuses on the sociology of network and social ecology. And among them, different scholars have different views about the concept of sociology of network.. About the research on the sociology of network, some scholars advocated classifying it into the area of information science, while some other scholars emphasized the unique features of the network society in the media and dissemination, and claimed to study the evolution of the network society from the perspective of media and dissemination, and one of the representatives is an American social scientist Manuel Custer. He thought that the network society is a new social form of society that different from the reality, and pointed out the network constructs the new form of our society, and the spread of network logic has changed the operating result of production, experience, rights and culture. And it is characterized by social forms than the superiority of social action [1] ; While Gong Qi considered the network society as a virtual space of human and humans life, study and work in this alternative space [2] .. And the research on the social ecology started earlier. For example, Brown who comes from American Cornell University had analyzed the human activities in social life from the perspective of the natural ecology [3] . Developed so far, the research of this discipline gradually divided into two directions, one is to analyze the phenomenon of human social life using related theories and methods of natural ecology, such as the human activities, social development and so on [4] [5] , and the other one is to research the coordinated development between the society, economics and resources quantitatively and qualitatively based on the theory of ecology [6] [7] [8]. The concept of driving force system of Ecosystem of Cyber-society that proposed in this paper is a cross research between the above two disciplines. It not only emphasizes on analyzing the network space from a sociological perspective, but also reflects the theory of system dynamics in the ecology. Therefore, although the concept of driving force system of Ecosystem of Cyber-society is new, since that the research is a frontier that based on the current disciplines and research achievements, the development status and trends of related disciplines are still significant to our research [9] .. The organization of this paper is as follows. In Section 2 we propose a theoretical framework of the driving force system of Ecosystem of Cyber-society, and analyze its structure, functions and characteristics. Then, in Section 3, we analyzed the operation environment and formation process of the driving forces. And finally in Section 4 we present the operation mechanism of the driving force system systematically.. 2 The Driving Force System of Ecosystem of Cyber-society We propose a basic theoretical framework of the driving force system of Ecosystem of Cybersociety and present its operation mechanism using the theory of System Dynamics in this paper. The driving force system of Ecosystem of Cyber-society is constituted by the subsystem of driving forces, stimulate subsystem of driving forces and carrier subsystem of driving forces, which is a virtual manual system with the characteristics of integrity, structure hierarchy, orderliness and openness. Its operation mechanism mainly includes the mechanism of push and pull, mechanism of organization and conduction, mechanism of Integration and collaboration, and mechanism of innovation and development.. The formation and development of Ecosystem of Cyber-society is the function result of a variety of driving forces together. There is no one single driving force can independently control the formation and development of Ecosystem of Cyber-society. Only through the coordination Operation Mechanism of the Driving Force System of Ecosystem of Cyber-society Based on the System Dynamics 823 between the driving forces within and outside the system, then it can generate new driving force structures and joint force, improve the operation efficiency of the driving force system, and thus promote the fast forward development of Ecosystem of Cyber-society with its powerful functions.

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


DEMON: preemptive route recovery for AODV in multi-hop wireless networks based on performance degradation monitoring Reactive routing protocols like ad hoc on-demand distance vector (AODV) have been widely proposed for multi-hop wireless networks (MWNs). However, these types of routing protocols only recover routes after route break detection. Considerable research efforts have been devoted to minimizing the route recovery delay or to anticipating link breaks by using preemptive mechanisms. To the best of our knowledge, state-of-the-art solutions in this space are mainly focused on mobility prediction. However, as we argue in this paper, other phenomena like interference and congestion should also be taken into account, since they can also negatively affect the performance of routes and even cause disconnections. This article presents a novel preemptive solution for AODV called performance degradation monitoring, which allows preemptive route recovery based on passive estimation of link data loss rate. Extensive simulations demonstrate that our proposal, which is sensitive to link quality degradation regardless of its nature, improves network performance in a wide range of scenarios. Routing in multi-hop wireless networks (MWNs) requires two main mechanisms: route discovery and route maintenance. Route discovery is carried out by using a routing algorithm and a routing metric. The former aims at finding available routes, while the latter seeks to select the optimal route based on certain criteria such as hop count, link loss rate, link data rate, and node congestion or interference caused by active flows [1, 2] . However, the routing protocol cannot assure that the optimality of the selected route will be maintained in time. Uncontrolled phenomena like fading, external interference, and node mobility could severely degrade link performance and even cause route disconnections [3, 4] . In addition, the unpredictable arrival of new flows in the network may cause congestion or inter-flow interference on the flows being routed [5, 6] . Thus, route maintenance mechanisms are required.. Route maintenance in on-demand routing protocols is limited to link break detection in order to recover disconnected routes. For instance, most implementations of ad hoc on-demand distance vector (AODV) detect link breaks when a defined number of consecutive Hello messages are lost [7] . By using this recovery procedure, a flow may undergo a large interval of performance degradation until the detection of the link break and the rediscovery of the new route [8] .. The aforementioned problem can be significantly mitigated by means of preemptive route maintenance [9] . This technique allows nodes to monitor the quality of the links that participate in active routes, decide when the quality is no longer acceptable, and, in that case, trigger route recovery immediately, before an actual route break occurs. To the best of our knowledge, stateof-the-art solutions in this area are limited to using link break predictors and anticipating route recovery with the objective of reducing route disconnections due to node mobility [9] [10] [11] [12] [13] [14] [15] [16] [17] . Nevertheless, as we argue in this paper, a comprehensive solution is required which considers other causes of route performance degradation like interference or congestion.. In this paper, we present the following contributions:. A comprehensive study of the route maintenance mechanisms used by on-demand routing protocols for MWNs and the main preemptive route recovery proposals of the literature. The design of the DEMON solution, which performs preemptive route recovery by using information about the data loss rate of the links. We have designed and evaluated DEMON as an extension of AODV, although it could also be applied to other reactive protocols. An evaluation of DEMON by means of extensive simulations in a wide range of scenarios. Results show that DEMON significantly improves network performance in all the scenarios considered.. The remainder of the paper is organized as follows: Section 2 surveys existing route maintenance mechanisms of reactive routing protocols for MWNs. Section 3 describes our solution and its design principles, Section 4 presents the evaluation of DEMON by means of extensive simulations, focusing on its performance in different IEEE 802.11 MWN scenarios. Finally, Section 5 concludes the paper with the main remarks from our work. In this paper, we present a novel preemptive route recovery extension of AODV called DEMON. The design of DEMON was motivated by the fact that, to the best of our knowledge, state-of-the-art preemptive route recovery solutions for on-demand MWN routing protocols are only designed with the objective of minimizing route disconnections due to node mobility. However, a comprehensive preemptive solution should consider other causes of route performance degradation, such as inter-flow interference or congestion, and have appropriate route maintenance mechanisms in order to re-route active flows if their performance becomes compromised.. DEMON uses pETX, a link quality metric based on a passive estimation of link data loss rate for monitoring the performance of active links. When a node detects that link quality falls below a threshold (which can be statically or dynamically configured), route recovery is triggered in order to find a new route for the affected flow whose recovery optimizes network performance. DEMON performs preemptive, source-based route recovery due to any cause of link quality degradation. In contrast with state-of-the-art solutions, DEMON can operate regardless of the link layer implementation since it only uses information available at the network layer.. We study the performance of DEMON in IEEE 802.11-based MWNs by means of simulation, to which end we consider a wide range of scenarios, each of them with particular characteristics in terms of offered load, number of flows, spatial node distribution, link rates, mobility, and use of single-or multi-radio nodes. According to the results, DEMON outperforms default AODV in all the scenarios used in the evaluation due to its preemptive recovery of degraded routes. In mobile scenarios, DEMON can provide an increase of up to 90% of goodput by anticipating link breaks and minimizing route disconnections. The improvement is equal to or greater than that achieved by state-of-the-art preemptive solutions according to the literature. In stationary networks, the average improvement is smaller, about 10% to 30%, since as load increases, congestion and interference leave little margin for improving performance by changing the flow distribution in the network. In the absence of mobility, the performance of state-of-the-art preemptive solutions would be analogous to that of default AODV.. With regard to the link quality thresholds used in DEMON, fixed thresholds set to high values obtain good results under low-load or high-mobility conditions, since they provide a fast reaction to performance degradation. However, in congested networks, fixed thresholds set to high values may lead to excessive route recoveries, which become counterproductive. On the other hand, fixed thresholds set to low values are less sensitive to performance degradation under low load or high mobility; however, under high load, they are more consistent with actual link qualities and thus give rise to a low number of route recoveries, which leads to good performance. In most considered cases, the best performance is obtained by using a fixed threshold appropriately tuned to the scenario. Nevertheless, the dynamic threshold performs reasonably well in all the scenarios and load conditions. Even so, we plan to study enhancements to the dynamic threshold in order improve its adaptability to the characteristics of a scenario. In particular, networks of varying conditions constitute a challenge.. We analyze the behavior of DEMON when two different state-of-the-art routing metrics are used for route discovery, ETT and WCIM, which are link quality and load aware, respectively. In most cases, WCIM obtains better results than ETT, since its load awareness leads to better route selection. However, results show that in some cases, the performance of DEMON improves by using the ETT metric for route discovery. This is an interesting feature, since the use of load-aware metrics can lead to network instability under highly variable network conditions. By using DEMON, the routing metric can remain load-unaware, as is ETT, while route recovery can be load-aware by means of the link quality estimation mechanism based on pETX. In fact, according to the obtained results, we can conclude that the route recovery mechanisms have a greater influence on the performance of the routed flows than the routing metrics used for route discovery. This is remarkable, since the state-of-the-art on preemptive and route recovery solutions is scarce compared to the wide literature on routing metrics and route discovery solutions.. Finally, we evaluate the performance of DEMON in combination with TCP congestion control mechanisms. DEMON can provide an average increase of up to 5% to 10% of network goodput in the presence of TCP flows. However, we find that in mobile scenarios, TCP congestion control mechanisms dramatically decrease the packet sending rate, which reduces the accuracy of DEMON and limits its benefits. A future work item is the evaluation of DEMON with state-of-the-art TCP improvements for wireless multi-hop networks. Also, we will study the addition of cross-layer mechanisms for DEMON at the end nodes, making use of transport layer information in order to detect performance degradation.. Future work will also include investigating strategies for using DEMON as the basis of a channel assignment mechanism for multi-radio MWNs. In this case, instead of recovering the whole route when performance becomes degraded, it is possible to assign a new channel for the degraded link by exploiting the multi-radio capabilities of the nodes. In order to illustrate the purpose of our solution, we introduce an example of performance degradation which is not caused by mobility. For this example, a 64-node grid using the basic version of AODV was simulated a (see Figure 2 ). At second 200, a flow f1 with a data rate of 1 Mbps was initiated and routed through initial route. Then, at second 250, a highly loaded flow of 5 Mbps, called f2, was initiated. Note that in such a scenario, regardless of the routing metric in use, f2 would degrade the performance of f1, since the source of f2 was a hidden node for several nodes traversed by f1. Thus, in order to avoid the interference of f2, f1 should be rerouted after f2 activation. However, as previously mentioned, basic AODV only performs route recovery after the detection of a link break.. After repeating the experiment 20 times with different seeds, we obtained two different types of results. In the first one, f1 traversed the initial route during all the simulation times. As shown in Figure 3a , due to the high contention and interference of f2, the throughput of f1 became reduced approximately in one half. In the second one, the initial route became disconnected after a long period of performance degradation due to the interference of f2 and AODV finally re-routed f1 through recovered route (see Figure 3b ). The latter route did not suffer the influence of the interfering flow. However, route recovery was only triggered after three consecutive Hello message losses, which occurred after roughly 1 min of performance degradation.. Note that in the presented scenario, where the reasons for performance degradation are contention and interference, preemptive solutions based on received signal strength [9, 10, [13] [14] [15] 17] , node position [11] , or link data rate [12] would behave analogously to basic AODV, since the interfering flow does not affect the signal strength of successfully received packets, while the position and the link data rate of the nodes are fixed. Therefore, we designed DEMON as a preemptive route recovery extension of AODV which is aware of flow performance degradation due to any reason and aims at allowing a fast route recovery. In the following subsections, we will describe its components in detail.

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


Google Generation II: web behaviour experiments with the BBC Purpose -The purpose of this paper is to report on continuing research undertaken on the way the Google Generation behave on the internet and to compare this with an earlier highly publicised study by the paper's authors. Design/methodology/approach -This research use a televised practical experiment and a remote web global test incorporating search, working memory and multi-tasking experiments. Findings -The Google Generation appears to behave very differently from older generations. By their own admission they are less confident about their searching prowess and this is also demonstrated by the fact that they viewed fewer pages, visited fewer domains and undertook fewer searches. Also, tellingly, their search statements were much more the product of cut and paste. The Google Generation also have poorer working memories and are less competent at multi-tasking, both of which may have implications for researching in an online environment. Originality/value -The paper introduces of multi-tasking and cognitive measurement in evaluating and describing information-seeking behaviour; comparing the web behaviour of young and old; the first time this has been shown on public television. The virtual revolution is in full swing and it is transforming many aspects of our lives: the ways in which we socialise, shop, entertain ourselves, obtain knowledge and information, manage our health, and interact with public services have all undergone profound change. These transformations have taken place in a remarkably short period of time, leading many to wonder how today's children and teenagers, the "Google Generation", who have little or no recollection of a life before broadband, mobile technologies and ubiquitous search (Google) will cope. The big question that fascinates (or worries) everyone -parents, teachers, lecturers and employers -is whether this generation, when they hit university and the workplace, will turn out to be fundamentally different from older generations in their attitudes, expectations, behaviour and even in the way they "think" -Nicholas Carr (2010) , for instance, argues that their brains are being "rewired". If this indeed turns out to be the case then existing institutions such as schools, universities and libraries, are going to have to undergo fundamental change or face marginalisation. These and questions like them, drive CIBER's Google Generation Research programme. In 2008 we published our early research in this journal (Rowlands et al., 2008) . That paper was the most downloaded Aslib Proceedings article since and the report (CIBER, 2008) on which the article was based one of the most downloaded JISC (2007) reports ever. In this paper we return to a topic that has captivated readers, the profession and the media and report on continuing Google Generation research work undertaken as part of the BBC's award winning Virtual Revolution Series (BBC, 2009 ). How then did the BBC pilot experiment further our understanding of the Google Generation? Most importantly of all, it provided confirmation that there were profound and, possibly, concerning, differences between younger and older members of the general public in terms of their web behaviour. Critically, also it provided us with some important explanations of why this might be so. Thus, as the logs had previously demonstrated, the Google Generation proved to be the quickest information searchers, spending the least amount of time on a question (a fraction of the time spent by older adults), in the case of two questions just half a minute each! The knee-jerk "digital natives" interpretation of these findings is obvious: young people are whizzes at technology, and searching information is almost as natural as breathing to them. This, unsurprisingly, does not appear to be the case, as by their own admission, they were the least confident about their answers. The reasons for their lack of confidence might well be explained by their behaviour onlinethey viewed fewer pages, visited fewer domains and undertook fewer searches in answering the questions. Similarly, tellingly, their search statements (as demonstrated by our edit distance metric) were much closer textually to the question posed, making the Google Generation also the "cut and paste", fast information generation. It seemed that for a number of the Google Generation participants the experiment was a race (the first to the finishing line) and once they felt they had won they returned to their docking bayFaceBook, and returned to real life! Hurried and unconfident searching might well be a function of the amount of time they spend searching, they spent a fraction of the time spent by older adults and despite rating searching the web almost as highly as social networking they spent half as much time on it.. As for the crowd sourcing that comes from social media this was not evidenced in the tests, probably because they were tests, but certainly the Google Generation rated social media most highly. As regards multitasking, in which anecdote has it the Google Generation excel, it was true that they turned in much higher scores than the oldest generation (X) but recorded still significantly lower scores than the intermediate Generation Y. There is also evidence to suggest they do not multitask very well.. The propensity to rush, rely on point-and-click, first-up-on-Google answers, along with growing unwillingness to wrestle with nuances or uncertainties (a consequence of laziness?) or inability to evaluate information, keeps the young especially stuck on the surface of the "information" age, too often sacrificing depth for breadth.. Not surprisingly then, there is much speculation about whether the digital and the way we use it (doing many things at the same time) is making us all stupid; indeed actually damaging our brain. Neuroscientists who are increasingly called in to comment believe that it is changing how the brain works, it changes the pattern of connectionsintroducing new ones and dispensing with old ones (BBC, 2010a) -and because of the plasticity of young people's brains theirs change more quickly, but no damage has been detected yet! However, according to Nicholas Carr (2010) the skittering and viewing that are endemic in the virtual world have serious consequences for some fundamental human skills or at least skills we once regarded as fundamental. Carr believes that the way we, young and old, behave in the digital world is chipping away at our capacity to concentrate and contemplate, which leads to problems with us (not) reading. Recent news reports suggest that the writing might in fact already be on the wall. Thus it is reported that in the UK primary school reading levels are falling for the second year running (The Telegraph, 2010) and that public library lending has dropped by as much as a third in the past few years (BBC, 2010b). Carr believes this is just the beginning (of the end!).. Possibly the most interesting development to emerge from the BBC web behaviour experiment has been the interest that has been shown by industry, professions and policy makers in the implications and opportunities there is for them in the findings. The experiment has clearly helped in knowledge transfer from researchers to practitioners.. Much of what we have learned about the Google Generation comes from self-report questionnaires and we know that people have poor recall when it comes to what they did in the virtual space (which tends to lead to exaggeration or falsehoods) and it is not easy to craft questions in this arena; for these reasons we need to treat these data with AP 63,1 care and triangulate it with evidence based findings. Thus, for this study we have combined questionnaire data with log analysis and practical tests. However, finally, a word of warning, we are just presenting pilot data here, albeit data that dovetail with what we have discovered elsewhere on very large-scale projects, such as The Information Behaviour of the Researcher of the Future study (CIBER, 2008) . For confirmation of the data and further insights we must await the analysis of the Lab UK test which will be published in 2011. Although the main objective of the study was to determine whether the Google Generation was using the web and searching for information in distinctive ways this, of course, could only be achieved by making comparisons with other generations. This is especially important because a big mistake made by many commentators is to assume that older age groups are not shaped and changed by the same factors as the young. To avoid the danger of stereotyping on the basis of age, something that we are all guilty of doing, the original intention was to cluster the users in order to define groups of users by common attributes and behavioural patterns and then see whether the key differences were age/generation related. This proved not to be possible for the pilot data as the relatively small numbers of people recruited to the pilot meant there were too many missing cells in the spreadsheet. The alternative approach taken therefore was to divide the responses into three categories by age:. (1) Google Generation -born after 1993 (GG). This last group was in fact more diverse, the oldest participant being 83. Thus, it includes not only "Generation X" but also "Baby Boomers" and "Silver Surfers", perhaps it is better labelled "Generation Xþþ". We are describing here a pilot study whose intention was to inform and shape the main experiment, in particular by signalling possible major differences. The data therefore presented in this paper should be regarded as informative and illustrative rather than definitive: the definitive analysis will be furnished in the main experiment, when we can also return to the clustering approach mentioned earlier.. Three metrics are used throughout the following analyses: two covered use, regularity and time; and the third was importance. The scales for regularity and importance are as follows.. (1) Regularity measured on a six-point scale, where: 0 ¼ never; 1 ¼ irregularly; 2 ¼ monthly; 3 ¼ weekly; 4 ¼ daily; 5 ¼ hourly; and (2) Importance measured on a ten-point scale, where 10 is very important.. For each analysis we have used symbols to denote the level of statistical significance of the differences between generations of users: The data are complex as there are three things to compare: GG, GY and GX. An overall statistic that shows significant differences (e.g. the four asterisks) does not give enough information to make a clear interpretation. If the research question is simply "are there differences between generations?" then a single statistic is enough. Either the generations are different, or not different. But if there are differences, which way do the differences go? Is it the case that GX and GY are much the same, but both are very different from GG; or that there is clear blue water between all three? In order to determine this we have introduced 95 per cent confidence limits (the upper and lower bounds) for each analysis. In the first analysis we show how to interpret the confidence levels.. Where differences between the three generations are shown, these should be interpreted as age-related differences. The point is that these people are at different stages in their lives and are using the internet for different purposes and in different contexts. The findings should not be interpreted as indicating real generational differences. A simple example should make the point: at a given point in time, it will be observed that baby boys drink milk and eat rusks. Men drink beer and eat meat pies. This does not mean one should rush out and sell shares in Guinness and buy Farley's, come back in 20 years and the babies will be swilling lager top! We have no strong baseline evidence to track whether today's Google Generation is fundamentally any different from where we were at the same age but what we can determine is how the same thing (the digital) is impacting on us all and how this impact varies by age.. Four aspects of behaviour were investigated: (1) general purposes to which the internet is used; (2) multi-tasking; (3) characteristics of information seeking; and (4) working memory.. The multi-tasking and working memory aspects were exploratory to see whether there were generational differences and, if so, whether these variables could be examined in the main test in order to help explain web behaviour and searching style.. The purposes to which the internet is put Broad questions were asked about searching, e-mailing, blogging, social networking and posting information on the web. There were also questions on shopping, banking, making travel plans and listening to music in the pilot test, which is not discussed here.. There are clear age-related differences in the purposes for which people use the internet and the importance they attach to those activities. The pilot study involved a filmed practical experiment incorporating searching, working memory and multi-tasking tests. Session participants were seated at a PC in the UCL Library. The PCs were set up as for a normal student user with full access to the web with a Firefox browser. The only modification was the addition of a Firefox "plugin" developed by BBC Lab UK which captured the click-stream data from the Firefox browser. We were thus able to record time taken, URL's entered, and use of features such as the back button. The data collected from all participants was then processed using log analysis software developed at UCL.. Search questions were piloted and tested before the live sessions -the type of questions and reasons for choosing are discussed later. Working memory tests were developed by the BBC Lab UK for the Brain Training and the Multi-tasking tests were AP 63,1 undertaken with the aid of University of Stanford researchers who had developed a relatively straightforward scoring system for measuring the extent of and proficiency in multitasking (Ophir et al., 2009) .

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


A Sketching Interface for Sitting Pose Design in the Virtual Environment Abstract-Character pose design is one of the most fundamental processes in computer graphics authoring. Although there are many research efforts in this field, most existing design tools consider only character body structure, rather than its interaction with the environment. This paper presents an intuitive sketching interface that allows the user to interactively place a 3D human character in a sitting position on a chair. Within our framework, the user sketches the target pose as a 2D stick figure and attaches the selected joints to the environment (e.g., the feet on the ground) with a pin tool. As reconstructing the 3D pose from a 2D stick figure is an ill-posed problem due to many possible solutions, the key idea in our paper is to reduce solution space by considering the interaction between the character and environment and adding physics constraints, such as balance and collision. Further, we formulated this reconstruction into a nonlinear optimization problem and solved it via the genetic algorithm (GA) and the quasi-Newton solver. With the GPU implementation, our system is able to generate the physically correct and visually pleasing pose at an interactive speed. The promising experimental results and user study demonstrates the efficacy of our method. The core of our character-posing system is the reconstruction of a 3D pose from a 2D stick figure. Previous works on pose reconstruction from a single image may not work well to the hand-drawn stick figure due to the imprecise nature of the stick figure.. We formulate the pose reconstruction problem as an optimization problem. The input of the reconstruction algorithm is the 2D positions of the joints in the stick figure (s i ) , and the output is the joint angles of the reconstructed 3D character pose (q i ). We represent each joint angle with angle vectors with the dimension of the DOF of the joint. We use Euler angles to parameterize joint rotation as it is intuitive to place limits on the legal range of motion for them. Besides, the axis angle vector is a more appropriate parameterization for differential control with inverse kinematics [14] . The objective function evaluates the match between the projected 3D pose and the 2D input sketch, the plausibility of the pose, and the distance between the pinned joints and their bases. Collision handling is done separately. In the following, we first describe the details of the objective function and then describe how we solve this optimization problem. Finally, we describe how we handle collisions in this framework. This paper presented an intuitive sketching interface for a sitting pose design in a virtual environment. Our interface only requires the users to draw a simple 2D stick figure on the screen space without changing the viewing direction. Following this sketch, physically correct and visually pleasing 3D poses are reconstructed, automatically, at an interactive speed. Our system is novel in that it takes into account the interaction between the character and environment, which is helpful in solving the ill-posed 2D-to-3D reconstruction problem. The promising experimental results and the user study demonstrate that our method is efficient, intuitive, and effective and allows the users to quickly design the desired sitting pose in a complex virtual environment.. Of note, our current framework focuses only on a sitting pose design. However, it can be easily extended for other static pose design tasks such as lying or standing as shown in Fig. 25 . We can also choose to specify other joints as the main pivot by making the joint the root of the skeleton. Finally, the technique described in [26] could be used for handling such a structure-varying skeleton. Ying He received the BS and MS degrees in electrical engineering from Tsinghua University, China, and the PhD degree in computer science from the State University of New York (SUNY), Stony Brook. He is currently an assistant professor at the School of Computer Engineering, Nanyang Technological University, Singapore. His research interests fall in the broad area of visual computing. He is particularly interested in the problems that require geometric computation and analysis. He is a member of the IEEE. More information about his research can be found at http://www.ntu.edu.sg/home/yhe. We developed a prototype system in C++ on a workstation with an Intel Xeon 2.67-GHz CPU, NVIDIA Quadro FX 580 GPU. We conducted experiments in various virtual environments. See Figs. 1, 2, 9, 10, 14, and 16 for some examples of constructed 3D poses. As shown in Fig. 17 , a speedup of 3-5 can be obtained by using the proposed GPU solver, compared to the original CPU solver [2] . We also evaluated the reconstruction accuracy with respect to the population size. We run 50 reconstructions for each population size and computed the average fitness value and the standard deviation. As shown in Fig. 18 , the bigger the population size, the smaller the fitness value and the standard deviation. Based on the above analysis, we set the default value of main population size to 1,024, which leads to accurate results at interactive speed (1-2 seconds to generate a pose). To investigate the effect of collision handling strategy on the convergence of the genetic solver, we conducted a test to reconstruct poses from the input in Fig. 2 with/without collision handling. As shown in Fig. 19 , the collision handling strategy works pretty well as its convergence rate is very similar to the one without collision handling. We also compared the reconstructed result with the ground truth data. We first synthesized a 2D stick figure in the screen space from a posed character with 170 cm (see Fig. 20a ). Then, we apply our algorithm on the synthesized stick figure to generate a reconstructed 3D pose (the pink one in Figs. 20b and 20c) . The reconstruction error is 7.8 cm, which is computed as the average euclidean distances of 3D joints between the ground truth data and the reconstructed pose. Inverse kinematic [3] , is a widely used technique for character pose design. In spite of its popularity, IK is known to be almost always underdetermined. Thus, lots of previous efforts [4] , [5] have been made to restrict the solution space with various constraints that lead to feasible solutions. As discussed in Section 1, the inverse kinematicsbased pose design systems often require the users to interactively position the extreme joints of a character. These positioning procedures may be awkward if the character is in a complicated environment, since the occluded joint(s) cannot be adequately revealed from many different viewing directions.. Traditionally, animators often began work by quickly sketching 2D stick figures in key poses to capture the character's overall motion. Inspired by this, several sketching interfaces have been developed to facilitate the user's input. For example, Davis et al. [6] reconstructed a 3D pose from an artist-drawn 2D stick figure and provided a complementary alternate for 3D pose design. Wei and Chai [7] formulated the interactive character posing problem via a maximum posteriori framework and also discussed direct manipulation interfaces and sketching interfaces. Jain et al. [8] proposed a method to generate 3D animation of human motion from traditional hand-drawn frames that leverage motion capture data as a source of domain knowledge. Hardware input device has also been proposed to intuitively control character pose [9] . Of note, we adopted a similar sketching interface as [6] . However, our method is different from previous work in two aspects: 1) we focused more on the interaction between the character and the environment and 2) we formulated the 3D pose reconstruction as an optimization problem with both sketching and physical constraints.. Our work is also closely related to the reconstruction of 3D poses from monocular images. Most existing works have focused on using various domain constraints to solve the Fig. 1 . Various sitting poses designed by our system. The user sketches the 2D stick figures on the screen space to specify the desired poses in a virtual environment (see the inset of each subfigure), and our system automatically generates the physically correct and visually pleasing 3D poses at interactive speed.. underconstrained depth ambiguity problem. These works can be roughly classified into either model-based technique [10] , [11] , [12] or probabilistic learning-based techniques [13] . However, our work is different than the previous methods in that 1) our method takes advantage of physical constraints and the interactions between the character and environment to eliminate inappropriate solutions and 2) our input is a hand-drawn stick figure, which is usually imprecise and needs special treatment.

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


Strategies for conducting situated studies of technology use in hospitals Abstract Ethnographic methods are widely used for understanding situated practices with technology. When authors present their data gathering methods, they almost invariably focus on the bare essentials. These enable the reader to comprehend what was done, but leave the impression that setting up and conducting the study was straightforward. Text books present generic advice, but rarely focus on specific study contexts. In this paper, we focus on lessons learnt by non-clinical researchers studying technology use in hospitals: gaining access; developing good relations with clinicians and patients; being outsiders in healthcare settings; and managing the cultural divide between technology human factors and clinical practice.Drawing on case studies across various hospital settings, we present a repertoire of ways of working with people and technologies in these settings. These include engaging clinicians and patients effectively, taking an iterative approach to data gathering and being responsive to the demands and opportunities provided by the situation. The main contribution of this paper is to make visible many of the lessons we have learnt in conducting technology studies in healthcare, using these lessons to present strategies that other researchers can take up. Research methods are at the heart of research practice: they underpin the process that delivers research outcomes. Researchers learn from, build on, test and refine the findings of others; it should also be possible to learn from, build on, test and refine the methods applied by others. There is an established tradition of presenting and reflecting on research methods in healthcare (e.g. Malterud 2001) and in social sciences (e.g. Braun and Clarke 2006) , and increasingly in HCI and Human Factors (e.g. Millen 2000; Rode 2011; Furniss et al. 2011b) . By reporting on methods explicitly, the research community can learn from and improve on those methods. In this paper, we focus on strategies for conducting research into the situated use of technology in hospitals.. Healthcare is evolving in many ways, including becoming increasingly reliant on interactive technologies. Yet many current technologies are difficult to use or not fit for purpose, compromising patient safety . To address these challenges, an increasing number of HCI and Technology Human Factors (THF) researchers are moving to work in this area, bringing their skills in human factors and in observational studies, but with little prior experience of the healthcare domain. The focus of this paper is on strategies for HCI/THF researchers conducting situated studies in healthcare, with the aim of improving patient safety, and patients' and clinicians' experiences, by making future health technologies more fit for purpose. In this paper, we have highlighted challenges and provided strategies for conducting situated studies of technology use in hospitals. We have emphasised the importance of building rapport with participants and of valuing their expertise that complements our own. We have also emphasised the value of good preparation together with a flexible attitude, identifying and working with opportunities (such as times of enforced reflection) that the nature of the work affords, rather than fighting against situational constraints. This involves studying activity in the setting on its own terms, as also reported by O'Brien and Rodden (1997) . This eliminates power relationships between researcher and situation. Ultimately, as a researcher, you create a dialogue with the situation, working with it, responding to it and picking up on opportunities, not expecting to impose your will or your plan on it.. Being responsive to the situation can sometimes conflict with cultural expectations of planning, conducting, and reporting studies, which typically expect precision about processes and outcomes. We have drawn out differences between planning and practice and highlighted strategies for exploiting opportunities in unexpected places. Our aim has been to make visible many of the challenges faced by HCI/THF researchers conducting observational studies in healthcare and propose an initial repertoire of strategies for addressing those challenges. We have described lessons we have learnt about issues that need to be considered in conducting technology studies in healthcare and presented strategies that other researchers can use. In this discussion, we reflect on three themes that cut across those issues and strategies: managing the gulf between intention and practice; benefits of engaging in observational studies in healthcare; and an agenda for the future. This paper is not the outcome of a single study, but of the authors reflecting on experiences of conducting situated studies in healthcare. It has hallmarks of a confessional ethnography (Rode 2011) : where researchers reflect on their relationship with people in practice, how they conducted themselves in practice, and how this affected data gathering and analysis, to demystify the fieldwork process.. This paper has had a long gestation period. Themes for this paper were initially identified through discussion between Blandford, Furniss, and Rajkomar at UCL, early in 2012, including both broad themes (e.g. gaining access, respecting privacy, and managing potential patient and clinician concerns) and vignettes (stories of incidents that illustrated or teased out important points). As we recognised important gaps in experience, we recruited further authors: Berndt, O'Kane, and Owen were junior researchers studying technology use by clinicians and patients, bringing their recent experiences as novices in both situated studies and healthcare; Catchpole, Mentis, and Randell are established researchers in healthcare who brought years of experience of conducting situated studies across different clinical settings in the UK and the USA; and Mayer is a consultant oncologist with experience of facilitating studies. The expanded team of authors iteratively validated and extended the narrative through both discussions and exchanges of partial documents. It became apparent that there were important differences between:. • studies that involved clinical professionals, where patients were involved by virtue of their treatment, and studies where the main engagement was with lay people; • studies of novel technologies in clinical use and of clinical practice with existing technologies; and • the experiences of HCI/THF researchers and of clinicians as observers.. In order to be concise, this paper focuses on HCI/THF researchers studying the use of existing technologies by clinicians in hospital contexts.. While working on early versions of this paper, it became clear that many other researchers also have valuable experiences to report. This encouraged us to propose a workshop on this theme at the CHI 2013 conference; the output of that workshop is two books (Furniss et al. 2014, forthcoming) authored by the workshop participants. We have intentionally kept the development of this paper and the books separate, so that each offers a different (but complementary) perspective on strategies for conducting situated studies of technology use in healthcare.. Through iterative development, we aimed to eliminate generic themes pertaining to situated studies across contexts (though we recognise that the themes that remain do generalise in many ways to other settings). We also removed themes that related to generic human factors studies in healthcare, including obtaining ethical clearance and informed consent. The remaining themes were gradually refined through discussion of experiences and the identification of more focused challenges and solutions.. We have structured the paper according to key themes that were identified, including vignettes of experience to illustrate the issues and approaches to addressing those issues: getting started; managing relationships with clinicians and patients; being in the healthcare setting; and cultural divides in reporting.

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


A cross-Layer diversity technique for multicarrier OFDM multimedia networks Abstract-Diversity can be used to combat multipath fading and improve the performance of wireless multimedia communication systems. In this work, by considering transmission of an embedded bitstream over an orthogonal frequency division multiplexing (OFDM) system in a slowly varying Rayleigh faded environment, we develop a cross-layer diversity technique which takes advantage of both multiple description coding and frequency diversity techniques. More specifically, assuming a frequency-selective channel, we study the packet loss behavior of an OFDM system and construct multiple independent descriptions using an FEC-based strategy. We provide some analysis of this cross-layer approach and demonstrate its superior performance using the set partitioning in hierarchical trees image coder.Index Terms-Cross-layer design, diversity, frequency diversity, multimedia communications, multiple description coding, orthogonal frequency division multiplexing (OFDM), progressive transmission, wireless video. We studied an OFDM system supporting multimedia communications. In particular, assuming a slowly varying Rayleigh fading environment, we investigated the packet loss probability mass function for an OFDM system with different coherence bandwidths, and hence different numbers of correlated subcarriers. We then proposed a cross-layer diversity transmission scheme incorporating both physical layer and application layer diversity. More specifically, based on the frequency selectivity of the OFDM system, we constructed multiple descriptions employing an FEC-based approach. We demonstrated the superior performance of this adaptive cross-layer approach using the SPIHT image coder. We compared the performance against an OFDM system that does not use multiple description coding. Results indicate improvement can be achieved by constructing multiple independent bitstreams using UEP techniques.

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Improving the Efficiency in Halftone Image Generation Based on Structure Similarity Index Measurement This paper presents two halftoning methods to improve efficiency in generating structurally similar halftone images using Structure Similarity Index Measurement (SSIM). Proposed Method I reduces the pixel evaluation area by applying pixel-swapping algorithm within intercorrelated blocks followed by phase block-shifting. The effect of various initial pixel arrangements is also investigated. Proposed Method II further improves efficiency by applying bit-climbing algorithm within intercorrelated blocks of the image. Simulation results show that proposed Method I improves efficiency as well as image quality by using an appropriate initial pixel arrangement. Proposed Method II reaches a better image quality with fewer evaluations than pixel-swapping algorithm used in Method I and the conventional structure aware halftone methods. In the field of halftoning, the conventional methods such as ordered dithering, error diffusion, and so on [1] - [6] mainly focus on preserving tone similarity with their original grayscale images. These methods use various threshold matrixes to generate halftone images and are easy to implement. The images generated by error diffusion methods preserve good texture contents, especially for less-structured smooth images. However, error diffusion has the tendency to enhance edges in an image at the expense of gray level reproduction accuracy. It also suppresses the appearance of artifacts at the cost of over-blurring. Hence, they fail to represent the detailed structures of an image.. In the halftoning problem, an N-gray tone image must be portrayed as an n-gray tone image, where n < N. There are generally two approaches for halftoning. One approach uses filters which are directly applied to the N-gray tone image to generate a halftone image [1] - [6] . Hence, their pixel allocation locks into a regular stable pattern and these generated images fail to simultaneously maintain tone and detailed structure similarity with their original images. The second approach searches directly for the optimum halftoning image having the input N-gray tone image as reference. Our work adopts the latter approach.. W. Pang et al. [7] first proposed a direct search structure aware halftoning technique that uses Structure Similarity Index Measurement (SSIM) [8] in the objective function. This technique uses random black-white pixel pair swapping algorithm which minimizes an objective function that accounts for tone as well as structure similarity. It is applied to an arbitrary binary image. This method's major advantage is that it can generate high-quality images preserving tone and structure similarity even in the fine detailed regions of an image. Compared to the standard ordered dither and the state-of-the-art error diffusion, it preserves better structure content which is sensitive to the Human Visual System (HVS). However, the paper does not clearly mention the computational efficiency or the MSSIM (mean SSIM) values of the resultant images. Moreover, as the random pixel pairs are picked and swapped from within the whole area of the image, it uses a substantial number of evaluations to generate images with high quality. Also, as it uses an arbitrary binary image, the generated images vary in quality based on the binary image used.. In this paper, we proposed two halftoning methods that overcome the above mentioned drawbacks by improving the image quality as well as efficiency. In proposed Method I, we reduced the search area of random pixel pair selection by applying pixel swapping algorithm within inter-correlated blocks. We also applied phase block shifting in order to use pixels from the adjacent blocks and thus accelerated the image quality improvement. The same objective function as the conventional structure aware halftoning method [7] is used for pixel evaluation. We investigated the effectiveness of reducing search area by block division and phase block shifting. We also investigated the role of an appropriate initial pixel arrangement in generating structurally similar halftone images.. In proposed Method II, to further improve efficiency, we used bit-climbing algorithm within inter-correlated blocks. Each pixel of the block is flipped to the opposite color and evaluated to find an improved objective function value. This ensures that all the pixels in a block get a fair chance to be evaluated and also allows to make appropriate change in grayness where required. We investigate the effectiveness of pixel flipping over pixel swapping and also the role of initial pixel arrangements.. In this paper, first we describe about the relevant background information, followed by two proposed halftoning methods. Then we show some simulation results for each method and include discussions within the sections. Finally, we conclude the main findings of this work followed by future works. To improve the efficiency of generating structure similarity based halftone images, we proposed two halftoning methods. Firstly, we reduced the evaluation area by applying pixel swapping algorithm within inter-correlated blocks and showed the effect of using an appropriate initial pixel arrangement to improve efficiency in proposed Method I. Secondly, we replaced the pixel swapping algorithm with pixelflipping (bit-climbing algorithm) in proposed Method II. We could show that pixel flipping further improved the efficiency and was independent from the effect of initial pixel arrangement. It also contributed to achieving a better objective function value in the generated images. As future works, the effect of changing the objective function parameter weights adaptively based on the local image features should be brought into consideration. Also, the effects of employing other scan orders except the raster scan order for bit flipping within blocks should be investigated. Furthermore, the extension to color image halftoning should be investigated. In our experiments, we used original images of size 256 × 256 pixels with N = 256 gray levels and the generated images were bi-level halftone images. The block size used was 16 × 16 with equal weighting factors, w g = w c = 0.5 for the objective function unless mentioned otherwise. We mainly described the results using "Snail" and "Ribbon" as test images that were used in [7] .

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