Spatial experience based route finding using ontologies

Spatial experiences in route finding, such as the ability of finding low‐traffic routes, exert a significant influence on travel time in big cities; therefore, the spatial experiences of seasoned individuals such as taxi drivers in route finding can be useful for improving route‐finding algorithms and preventing using routes having considerable traffic. In this regard, a spatial experience‐based route‐finding algorithm is introduced through ontology in this paper. To this end, different methods of modeling experiences are investigated. Then, a modeling method is chosen for modeling the experiences of drivers for route finding depending on the advantages of ontology, and an ontology based on the taxi drivers’ experiences is proposed. This ontology is employed to create an ontology‐based route‐finding algorithm. The results are compared with those of Google maps in terms of route length and travel time at peak traffic time. According to the results, although the route lengths of route‐finding method based on the ontology of drivers’ experiences in three cases (from nine cases) are greater than that based on Google maps, the travel times are shorter in most cases, and in some routes, the difference in travel time reaches only 10 minutes.     

Analyzing the Video Popularity Characteristics of Large-Scale User Generated Content Systems

User generated content (UGC), now with millions of video producers and consumers, is reshaping the way people watch video and TV. In particular, UGC sites are creating new viewing patterns and social interactions, empowering users to be more creative, and generating new business opportunities. Compared to traditional video-on-demand (VoD) systems, UGC services allow users to request videos from a potentially unlimited selection in an asynchronous fashion. To better understand the impact of UGC services, we have analyzed the world's largest UGC VoD system, YouTube, and a popular similar system in Korea, Daum Videos. In this paper, we first empirically show how UGC services are fundamentally different from traditional VoD services. We then analyze the intrinsic statistical properties of UGC popularity distributions and discuss opportunities to leverage the latent demand for niche videos (or the so-called "the Long Tail" potential), which is not reached today due to information filtering or other system scarcity distortions. Based on traces collected across multiple days, we study the popularity lifetime of UGC videos and the relationship between requests and video age. Finally, we measure the level of content aliasing and illegal content in the system and show the problems aliasing creates in ranking the video popularity accurately. The results presented in this paper are crucial to understanding UGC VoD systems and may have major commercial and technical implications for site administrators and content owners.     

Semantic similarity analysis of user-generated content for theme-based route planning

Several technical approaches to a touristic tour planning, which connect popular points and routes of interest or provide locations related to specific themes, have been published in recent years. Hereby, points of interest are found and evaluated on the basis of user-generated web content. However, no approach exists to the author's knowledge, which allows truly individual theme route planning. Individual means, that a user flexibly defines start point and destination and receives an optimised route, which will guide him through a townscape/landscape with most interesting features being situated along the proposed way. We introduce two methods to find such an individual theme route based on user-generated content. The basis for both methods is the determination of semantic similarity between a selected Wikipedia concept (e.g. a specific architectural style) and other geo-referenced Wikipedia concepts (e.g. a building). The first method has been termed the continuum method: it uses semantic similarity measures together with a density distribution from theme-related, geo-tagged photos in the web, in order to create a continuous ‘surface of attractiveness’. Such a conceptual continuum can – together with the static geometric length of network features – form the basis of an assignment of impedance values to a navigation graph. The second method has been termed the spot sequence method: it models the theme route as a specific version of the travelling salesman problem. A route is composed by sequentially adding visit points to a navigation graph from the start to the end point. Priorities are derived from the ranked semantic similarity values. The achieved results have been compared and evaluated on a basis of a user survey.     

Stability-based routing,link scheduling and channel assignment in cognitive radio mobile ad-hoc networks

One fundamental issue in cognitive radio mobile ad hoc networks (CR-MANETs) is the selection of a stable path between any source and destination node to reduce the end-to-end delay and energy consumption arisen from route reconstruction. In this way, we analyse the link stability by calculating the link life time that is dependent on failures caused by secondary users’ (SUs) movements and primary users’ (PUs) activities. We propose a joint stability-based routing, link scheduling and channel assignment (SRLC) algorithm in CR-MANETs, which is benefited from considering the link life time, amount of interference imposed on PUs and energy consumption. The proposed algorithm selects a frequency channel/time slot in a way that channel utilization and previous behaviours of SUs and PUs, are taken into account. In the proposed SRLC, the concept of load balancing is applied by avoiding to route packets through SUs with insufficient energy. The effectiveness of the proposed algorithm is verified by evaluating the aggregate interference energy, end-to-end delay, goodput and the energy usage per packet transmission under three different scenarios. The results show our proposed scheme finds better routes compared to the recently proposed joint stable routing and channel assignment protocol.

     

A medical digital library to support scenario and user-tailoredinformation retrieval

Current large-scale information sources are designed to support general queries and lack the ability to support scenario-specific information navigation, gathering and presentation. As a result, users are often unable to obtain desired specific information within a well-defined subject area. Today's information systems do not provide efficient content navigation, incremental appropriate matching or content correlation. We are developing the following innovative technologies to remedy these problems: (1) scenario-based proxies, enabling the gathering and filtering of information customized for users within a pre-defined domain; (2) context-sensitive navigation and matching, providing approximate matching and similarity links when an exact match to a user's request is unavailable; (3) content correlation of documents, creating semantic links between documents and information sources; and (4) user models for customizing the retrieved information and the presentation of results. A digital medical library is currently being constructed using these technologies to provide customized information for the user. The technologies are general in nature and can provide custom and scenario-specific information in many other domains (e.g. crisis management)     

Personalised routing for wheelchair navigation

Wheelchair users are confronted with many outdoor obstacles in everyday travel that can make the task arduous and unsafe, especially in unfamiliar environments. However, if wheelchair users are provided with routes that can safely, accurately and efficiently guide them to their destinations, then the difficulty and danger associated with traveling might be significantly reduced. In this article, we present a routing method suitable for wheelchair users by taking into account sidewalk obstacles such as slope, steps, sidewalk condition and sidewalk traffic as are preferred by users. Our method calculates impedance scores for each sidewalk segment, which are then used to determine an optimal route between any given pair of origin-destination addresses in a sidewalk network. We first discuss sidewalk network parameters and a spatial database suitable for wheelchair navigation. Then we discuss our personalised routing approach. We also describe three methods to weight the impedance level of each sidewalk segment and compare the effectiveness of each method through experimentation using the sidewalk network for the University of Pittsburgh campus area.     

An artificial intelligence-based spectrum sensing methodology for LoRa and cognitive radio networks

The artificial intelligence-based spectrum sensing approach is extremely important in terms of effective bandwidth utilization for low power wide area networks (LPWANs) based on cognitive radio networks (CRNs). Most studies perform spectrum detection with CRNs using optimization or deep neural network methods. However, optimization-based spectrum detection approaches based on current LPWANs are scarce. For this purpose, in this study, a hybrid optimization methodology integrated with CRNs is proposed for LoRa, which is one of the most compatible LPWAN technologies in the Internet of Things (IoTs) recently. In the particle swarm optimization (PSO) part of this hybrid methodology, agent users are created so that secondary users (SUs) could use the licensed band of primary users (PUs) in cognitive radio. On the genetic algorithm side, LoRa error rates are minimized in order to further improve the performance of the proposed method. In this way, effective spectrum sensing is performed in the LoRa network. Various LoRa-CRN experiments have been carried out in the simulation environment, and the probability of detection and false alarm performances have been compared with both theoretical and proposed approaches in terms of quality estimation parameters. It is clear from the results that the proposed methods give successful results for the LoRa-CRNs.     

Provision of the required navigation characteristics of satellite radio navigation systems in unfavorable helio-geophysical conditions

A detailed review of domestic and foreign scientific publications, dedicated to the influence of geomagnetic disturbances and powerful bursts of the Sun’s radio radiation on the operation quality of satellite radio navigation systems (SRNS) and their functional additions, is performed. It is shown that existing methods of providing the required radio navigation characteristics during operation of the SRNS user’s device in the autonomous and differential modes do not fully satisfy modern requirements to SRNS in the conditions of influence of unfavorable helio-geophysical factors. A system of organization-technical measures targeted at provision of the required precision and continuity of the position determination of SRNS users under influence of geomagnetic disturbances and bursts of solar radio radiation is considered. For the practical realization of these measures an approximate structure of the complex system to provide the required characteristics of SRNS in unfavorable helio-geophysical conditions is suggested. This system may be considered as a necessary component of the perspective service of global monitoring and forecasting of the SRNS operation quality.     

Collective Surface Enabling an Ultralong Life of LiCoO2 at High Voltage and Elevated Temperature

Rapidly increasing demand for energy density in consumer electronics is eager for developing high-voltage LiCoO₂ (LCO). However, some great challenges such as severe phase transition and surface instability negate the cycle life of LCO operated at high-voltages (≥4.6 V). Herein, a chemical reconstruction strategy is proposed to form a collective surface of LCO through an interdiffusion reaction of MgHPO₄·3H₂O (MP) so as to extend the cycle life of high-voltage LCO. The collective surface renders a three-layer configuration that demonstrates an amorphous Li₃PO₄ outmost layer, a spinel-like layer beneath, and a Mg diffusion layer within LCO bulk. MP with relatively low hardness enables the uniform precoating via mechanical mixing, followed by a sintering process to undergo an interdiffusion reaction. Li₃PO₄ is an intrinsic electrochemical stabilizer against interfacial side reactions. The spinel-like compounds build a high-voltage-stable surface against irreversible O₂ release. In addition, Mg diffuses into the bulk lattice to suppress irreversible phase transition during the deep delithiation of LCO. Therefore, such modified LCO with a collective surface exhibits ultralong life with capacity retention of 82% after 1000 cycles at 1 C within 3.0–4.6 V and stable operating at 4.7 V or elevated temperature (45 °C).     

Fair end‐to‐end window‐based congestion control in time‐varying data communication networks

Communication networks are time varying and, hence, fair sharing of network resources among the users in such a dynamic environment is a challenging task. In this context, a time‐varying network model is designed, and the shortest user's route is found. In the designed network model, an end‐to‐end window‐based congestion control scheme is developed with the help of internal nodes or router, and the end user can get implicit feedback (throughput). This scheme is considered as fair if the allocation of resources among users minimizes overall congestion or backlog in the networks. Window update approach is based on a multi‐class fluid model and is updated dynamically by considering delays (communication, propagation, and queuing) and the backlog of packets in the user's routes. Convergence and stability of the window size are obtained using a Lyapunov function. A comparative study with other window‐based methods is also provided.     

预测位置空间离散化的多航路中期冲突探测算法

为了解决高飞行密度空域中具有多段航路的飞机中期冲突探测算法的精度较低和效率不高的问题,本文提出了一种新的中期冲突探测算法。将两飞机的航路重新划分为一系列航路片段,使得在每一个航路片段中没有航向和速度的变化。基于Prandini瞬时冲突概率的思想,计算所有航路片段的最大瞬时冲突概率,并取冲突概率中的最大者作为两架飞机整个航路冲突发生可能性的一个极端情况的度量。其中提出了基于预测位置空间离散化的新算法来求航路片段的瞬时冲突概率,对两飞机预测位置空间进行离散,然后根据位置预测误差概率密度函数以及两飞机的相遇几何来求瞬时冲突概率。仿真结果表明,相对于Prandini随机化算法,本文的冲突探测算法计算效率和计算精度更高,能够满足高密度飞行下条件下具有多段航路飞机的实时冲突探测的要求。      

On spatial variation in the detectability and density of social media user protest supporters

Although much has been published regarding street protests on social media, few works have attempted to characterize social media users’ spatial behavior in such events. The research reported here uses spatial capture-recapture methods to determine the influence of the built environment, physical proximity to protest location, and collective posting rhythm on variations in users’ spatial detectability and density during a protest in Mexico City. The best-obtained model, together with explaining the spatial density of users, shows that there is high variability in the probability of detection of social media user protest supporters and that the collective posting rhythm and the day of observation are significant explanatory factors. The implication is that studies of collective spatial behavior would benefit by focussing on users’ activity centres and their urban environment, rather than their physical proximity to the protest location, the latter being unable to adequately explain spatial variations in users’ probability of detection and density during the protest event.     

基于动态领域模型的业务流程管理

在云计算环境下,业务流程会随着企业的业务流程发生变化。必须设计出可以在运行环境下动态修改的业务流程才能满足要求。金蝶公司设计了一个业务流程框架,可以实现业务流程的动态设计和解析。针对云计算环境下,业务流程中的动作很多,不易管理的情况,设计了一个三层业务流程模型。针对业务流程在不同组织间转移产生的权限问题,设计了单据的业务流程视图模式,赋予用户临时的单据访问权限。通过以上方法,很好的解决了云计算环境下业务流程设计中遇到的问题。     

Algorithm for scenario benefit route planning based on user’s requests

Most of the existing research for point of interest route planning only consider the static properties of POI,however,the congestion of the hot spots and users’ discontent may greatly reduce the travel quality.In order to increase the tourists’ satisfaction,the dynamic attributes of POI was considered and a route planning algorithm based on user’s requests was proposed.Firstly,Markov-GM(1,1) forecasting algorithm was designed to predict the number of people in each scenic spot.Markov-GM(1,1) could make the average predication error 12.2% lower than the GM(1,1) algorithm by introducing the predication residual.And then,the forward refinement (FR) algorithm was designed which could avoid visiting the unnecessary place and satisfy user’s requests as well.The average solving time of forward refinement algorithm was 9.4% lower than TMT algorithm under the same amount of user’s requests.Finally,based on the factors such as spot popularity,KL divergence of time,visiting order and distance et al,the scenic route profit planning algorithm which could make the number of Rank 1-5 spots 34.8% higher than Time_Based algorithm and 47.3% higher than Rand_GA algorithm.     

Emerging Clapping Synchronization From a Complex Multiagent Network With Local Information via Local Control

Recently, complex multiagent networks have received increasing attention from various fields of science and engineering. Synchronization is a typical collective behavior of complex multiagent networks that has extensively been investigated over the last decade. To reveal the dynamical mechanism of synchronization in complex multiagent networks, a simple complex multiagent network with local information is then further investigated. Based on a suitable model, we analyze the inherent key factors in the emerging clapping synchronization. In particular, we explore two challenging fundamental questions: 1) How does the number of informed agents (or backbones) affect the emerging clapping synchronization? 2) How does the distribution of informed agents (or backbones) affect the emerging clapping synchronization? Our results indicate that the emerging clapping synchronization has a great diversity of routes, uncertainty, and adaptability. Moreover, our model and approach provide a possible route for analyzing the other collective behaviors of complex multiagent networks with local information via local control.     

认知无线网络中基于主用户行为的联合路由和信道分配算法

针对认知无线网络中主用户行为将导致频谱瞬时变化而影响路由稳定性的问题,提出了一种基于主用户行为的路由和信道联合分配算法。该算法通过采用呼叫模型对主用户行为建模,并根据动态源路由协议的路由寻找机制,在目的节点等待多个路由请求分组后选择受主用户行为影响最小的路由,然后沿着所选定路径的反方向传送路由回复分组并完成信道分配。理论分析证明了算法中的链路平均持续时间期望与主用户活动概率成反比且具有与网络节点数成正比的计算复杂度。仿真结果表明,该算法具有比Gymkhana路由方案更高的分组投递率和更低的平均分组时延。     

Navigation Technologies for Autonomous Underwater Vehicles

With recent advances in battery capacity and the development of hydrogen fuel cells, autonomous underwater vehicles (AUVs) are being used to undertake longer missions that were previously performed by manned or tethered vehicles. As a result, more advanced navigation systems are needed to maintain an accurate position over a larger operational area. The accuracy of the navigation system is critical to the quality of the data collected during survey missions and the recovery of the AUV. Many different methods for navigation in different underwater environments have been proposed in the literature. In this correspondence paper, the state of the art in navigation technologies for AUVs is investigated for theoretical and operational systems. Their suitability for use in different environments is compared and current limitations of these methods are identified. In addition, new approaches to address these current problems and areas for future research are suggested. Finally, it is concluded that only geophysically referenced methods will enable AUVs to navigate accurately over large areas and that advances in underwater feature recognition are required before these methods can be implemented in operational AUVs.     

Autonomic Navigation System Based on Predicted Traffic and VANETs

To avoid an expected traffic jam, drivers make detours based on limited information; however, the majority following the alike routes may result in an unexpected congestion. Conventional navigation approaches are unable to respond to the unexpected congestion because these approaches do not consider the routes taken by other vehicles. Navigation systems that utilize global traffic information can improve gas consumption, CO₂ emissions and travel time. Therefore, in this paper, the authors propose an autonomic navigation system (ANS) operating over vehicular ad-hoc networks (VANETs). The proposed ANS adopts a hierarchical algorithm to plan vehicle routes. The proposed ANS imitates the human nervous system when managing the navigation system, in which vehicles monitor traffic via VANETs. Moreover, this paper proposes a time-dependent routing algorithm that uses a novel traffic prediction method based on the routes of vehicles. This paper adopts EstiNet as simulator tool that dominates hundreds or thousands of VANET-based vehicles routing in two maps, Manhattan area, and Taipei city. The results show that the proposed ANS improves the average speed by 60.02 % when compared with the shortest path first (SPF) algorithm and by 15.49 % when compared with the distributed method of a traffic simulation in the Manhattan area. The proposed ANS also improves the average speed by 30.5 % when compared with the SPF algorithm and by 15.8 % when compared with the distributed method of a traffic simulation in the Taipei area. Furthermore, to emulate real environments, there is a scenario in which only a portion of the vehicles complies with the proposed ANS.     

Robust throughput and routing for mobile ad hoc wireless networks

Flows transported across mobile ad hoc wireless networks suffer from route breakups caused by nodal mobility. In a network that aims to support critical interactive real-time data transactions, to provide for the uninterrupted execution of a transaction, or for the rapid transport of a high value file, it is essential to identify robust routes across which such transactions are transported. Noting that route failures can induce long re-routing delays that may be highly interruptive for many applications and message/stream transactions, it is beneficial to configure the routing scheme to send a flow across a route whose lifetime is longer, with sufficiently high probability, than the estimated duration of the activity that it is selected to carry. We evaluate the ability of a mobile ad hoc wireless network to distribute flows across robust routes by introducing the robust throughput measure as a performance metric. The utility gained by the delivery of flow messages is based on the level of interruption experienced by the underlying transaction. As a special case, for certain applications only transactions that are completed without being prematurely interrupted may convey data to their intended users that is of acceptable utility. We describe the mathematical calculation of a network’s robust throughput measure, as well as its robust throughput capacity. We introduce the robust flow admission and routing algorithm (RFAR) to provide for the timely and robust transport of flow transactions across mobile ad hoc wireless network systems.     

Choosing the scale and extent of maps for navigation with mobile computing systems

Unlike most paper maps used for navigation, digital maps when displayed on handheld, personal navigation systems do not show the entire mapped extent in a single view, nor are they limited to a fixed map scale. The mapped extent, or footprint of the earth, that appears in any given view is dictated by scale, and there are as many scales as zoom steps. But what drives the choice of scale? We investigate this question first through an assessment of currently available navigation systems, to analyse the consistency or variation among current practices. The vast range of scales and zoom steps found across six software packages indicates an absence of design guidelines, the consequence of which is that users will have a very different experience, with respect to the map, depending on what program they use. Since map representation has been shown to influence spatial behaviour and decision-making, such differences arising from map scale may lead to unintended consequences for navigation system users. We argue that meaningful scales and map extents that incorporate temporal and behavioural aspects of travel as cued by global position system (GPS), can actually convey relevant information to map users. Drawing upon time-geography concepts and real-time data from GPS signals, we explore time-scale bars and isochrones as potential methods of spatiotemporal information delivery to users of personal navigation systems.