CIICT 2009 Proceedings

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GPS/RFID/Self-contained Sensor System, ICAT2006,LNCS 4282,pp.1310–1321,2006.[4] Tracy Ross, Andrew May, and Simon Thompson.The Use of Landmarks in Pedestrian NavigationInstructions and the Effects of Context,MobileHCI 2004,LNCS 3160,pp.300–304,2004[5] Christian Gaisbauer and Andrew U.Frank.Wayfinding Model for Pedestrian Navigation.Proc. Of 11th AGILE International Conference onGeographic Information Science 2008.[6] Hao wang, Changcheng Huang, James Yan. AFeedback Control Model for Multiple-LinkAdaptive Bandwidth Provisioning Systems. 2006IEEE International Conference onCommunications, Volume 3, June 2006, pp.987-993.[7] Yu Chen, Qionghai Dai. A feedback controlmodel for resource management on streamingmedia servers. Video Image Processing andMultimedia Communications, 2003, 4 th EURASIPConference, Volume 2, 2-5 July 2003 pp.835-840.[8] Jeongho Hong, James C. Akers, RavinderVenugopal, Miin-Nan Lee, etc. Modeling,Identification, and Feedback Control of Noise inan Acoustic Duct. Control Systems Technology,IEEE Transactions on Control SystemsTechnology, Volume 4, No. 3, May 1996, pp.283-291.[9] B.G. Kim. Theoretic Framework for FeedbackControl Models in High-Speed Networks.Database and Expert Systems Applications, 2003.<strong>Proceedings</strong>. 1-5 Sept. 2003. pp.134-138.28
Tram and Bus Tracker: A Dynamic Web Application for Public TransitReliabilityBashir Shalaik and Adam C. WinstanleyDepartment of Computer Science, National University of Ireland, Maynooth, Co. Kildare, Irelandbsalaik@cs.nuim.ieAbstract—Currently transit quality informationsuch as timetable adherence, bus arrival times androute performance has usually been disseminatedthrough static environments on web-pages, paperdocuments or other different media. This paperdescribes a dynamic Geographic Information SystembasedWeb application which displays the sameinformation through a dynamic web application. Usingdata collected from an Automatic Vehicle LocationSystem (AVL), a map-based interface has been createdto allow travellers and operators to see routes, stopsand buses in motion. The collected information isarchived for off-line analysis. The system allows usersto query and display day-to-day management ofoperations as well as to generate static performancereports to provide a complete view of the transit systemreliability.I. I INTRODUCTIONEnvironmental occurrences such as trafficcongestion or urban construction present new obstaclesfor transportation. Designing and implementation of adistributed transit vehicle information system will helpreduce stress as well as improve confidence in andperception of transit systems [1]. Tram and BusTracker delivers real-time transit vehicle location andprogress information highlighting any deviations fromthe published time-table or any bad services symptomssuch as bunching of vehicles due to traffic conditionsor incidents. Recent advanced techniques incommunications, computing technology have madereal-time transit information system an interesting areaof research. In this project a web based applicationsystem has been developed to explore techniques ofshowing transit vehicle performance. This system wasbuilt using the PHP scripting language, a MySQLdatabase, client-side JavaScript, XML and MicrosoftVirtual Earth API.This system has the ability to display transit vehicleslocations in near-real-time on a map and offers user andoperator interactive querying on a specific bus or route.In addition, it allows the operator to monitor andmeasure the vehicle fleet so as to improve the transitservices provided.II TRANSIT SYSTEM’S RELIABILITY INDICATORSImproving the reliability of services is one of themain objectives of transit agencies. Many performanceindicators have been developed to assess transitperformance, the choice of which indicator dependingon the frequency of the service. For high-frequencyroutes (a vehicle at least every ten minutes) theseinclude Excess Waiting Time (EWT) [2], HeadwayRegularity Index (R)[3], Headway Reliability (RH)[4]and Travel Time Reliability (RT)[4]. On highfrequency routes passengers are more concerned withregularity, whereas for low frequency their concern ismore with punctuality.EWT [2] is defined as “the measure of the additionalwait experienced by passengers due to irregularspacing of buses or those that failed to run”. EWT canbe calculated by subtracting scheduled waiting time(SWT) from average waiting time (AWT) i.e.EWT = AWT − SWT (1)The term headway is used for the time intervalbetween successive vehicles on the same route and inthe same direction as they pass a particular point onthat route [5].The headway regularity index is a reliabilityperformance indicator for buses at a stop, route, orsystem level [3]. Service regularity is measured bycomparing the actual with the scheduled headway. Ahigh headway index (R) indicates a regular servicewhereas low numbers indicate headway irregularities.R =− 2n∑r=1hnr(− H )r2* H1 (2)where:r rank of headway (1..n)n total number of headway measureshr series of headwaysH mean headway29
Page 3 and 4: CIICT 2009Proceedings of the China-
Page 5 and 6: ForewordOn behalf of the organising
Page 7 and 8: TABLE OF CONTENTSSection 1A: ANTENN
Page 9 and 10: Section 3B: COMPUTER VISION 133A ne
Page 11 and 12: Section 1AANTENNAS AND CIRCUITS 11
Page 13 and 14: A block diagram of the platform is
Page 15 and 16: These two paths are averaged to red
Page 18 and 19: 4 mm -10 0 , -8 0 , -3 mm -8 0 , -6
Page 20 and 21: The results show that the separatio
Page 22 and 23: same size of annular-ring outer rad
Page 25 and 26: [4] C.Y.Sim, K.W.Lin, J.S.Row, Desi
Page 27 and 28: Interpretation of Spatial Movement
Page 30 and 31: III.DATA COLLECTIONAccurate spatial
Page 32 and 33: navigation. We define a walking are
Page 34 and 35: one’s body position, movement and
Page 36 and 37: world and will result in them being
Page 40 and 41: When the headway measures are equal
Page 42 and 43: [4] R.Liu, and S. Sinha, “Modelli
Page 44 and 45: Digital Audio Watermarking by Magni
Page 46 and 47: j 2 πβND = e(2)The frequency depe
Page 48 and 49: accurate in identifying the compone
Page 50 and 51: Furthermore, the decode experiment
Page 52 and 53: exists no spatial information of th
Page 54 and 55: iteration, one NMF for each frame.
Page 56 and 57: 7. CONCLUSIONSIn this paper we empl
Page 58 and 59: Dej 2 πβN= (1)The frequency depen
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Page 62 and 63: Computing Modified Bessel functions
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Page 68 and 69: puncturing some parity RSDT columns
Page 70 and 71: [5] O'Droma M. S. and I. Ganchev.
Page 72 and 73: Administrations (CEPT) has proposed
Page 74 and 75: Figure 3 Proposed Test PlatformThe
Page 76 and 77: ACKNOWLEDGEMENTSThe authors wish to
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However, individual sensor measurem
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Position Of Test Phone CallPosition
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vol. 6, no. 3, pp. 30-38, 2007.[11]
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environment’. The report states t
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awareness communications about Twit
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2.2 Flight route planningFlight rou
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Spatial - temporal Simulation and P
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and serious ones in turn. Overall,
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[3] Cheng Weiming, Zhou Chenghu, an
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(a) 1973 (b) 1990 (c) 2000Figure 1.
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Effect of Hard RTOS on DPDC SCADA S
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Therefore, this solution is not fea
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already done on error free system o
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8 PROPOSED REAL-TIME OPERATING SYST
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HYBRID DECODING SCHEMES FOR TURBO-C
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L a(u k ) SOVA/Log-MAPLog-MAP Inter
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JavaScript code Fragment Analyzingf
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The external JavaScript itself, whi
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Section 3ACHANNELS AND PROPAGATION1
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The DCF is assumed to have negligib
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When m=6, the fluctuation have been
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Across a 5 MHz spectrum, the maximu
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Fig 6 shows the time variant charac
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In the system, the RF signal is dir
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of the different speeds UWB standar
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3dB higher for the laser biased at
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information for inter domain pre-au
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In addition, the opendiameter imple
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A new algorithm of edge detection b
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Control structure elements of shape
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3D TOOTH RECONSTRUCTIONWITH MULTIPL
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3.1 Topological structure and base
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Automatic Recognition of Head Movem
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threshold model λ is created to ca
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Dirt and Sparkle Detection for Film
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[4] T. Komatsu, T. Saito, “Detect
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Lightweight Signal Processing Algor
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a two element PIR sensor, to obtain
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the sensor node can readily be chec
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parameters may not lead to simple a
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0 (1 dR1)(1 dR2) 1[1]where d is t
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epeatability is normally defined as
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Integrated air quality monitoring:
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colour coded data that are used to
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Approximate Analysis of Fibre Delay
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Virtual Traffic SourceA*f( t)= A* e
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Section 4AANTENNAS AND CIRCUITS 217
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Primary SpiralSecondary SpiralCoCbL
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[4] A H Miklich, J X Przybysz, T J
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ased on the ABCD transmission matri
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RRe( Y3 _ LowFreq)=s(19)2 2 2Rs+ ω
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Section 4BeLearning180
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were investigated as important inpu
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Time [min]1009080706050403020100Loc
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Mean Rating for Different Encoding
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Billing Issues when Accessing Perso
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data consumed, for example 0.2€/M
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and returns billing plans the learn
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lecture size and the price per quan
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Section 5ARADIO SYSTEMS 2196
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and is uniformly distributed in the
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When the number of users is 2, and
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III.BLUETOOTH OPERATIONS IN SNIFF M
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traffic or for POLL and NULL packet
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Necessity for an Intelligent Bandwi
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Spruce: Spruce has been one of the
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Fig. 5 Comparison of bandwidth calc
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Section 5BCOMPUTER NETWORKS 2212
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2.1 CNFThe Content Navigating Funct
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User BGF PD-FE CSCF CNF(AS) HSSPeer
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5 ConclusionThis paper proposed an
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d( X − X ) + ( Y −Y)= ∑ ∑2
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Program Dependence Graph Generation
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CDGPDGFigure 2. Program Dependence
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Section 6ADIGITAL HOLOGRAPHY226
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away. Immediately behind this plane
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While this is not ideal as hair is
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Figure 12. 3-D visualisation of 200
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Speed up of Fresnel transforms for
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[9]L. Onural and H. Ozaktas, "Signa
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2009 China-Ireland International Co
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2009 China-Ireland International Co
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that enables the complete separatio
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developed in the literature to remo
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Section 6BINTELLIGENT SYSTEMS246
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the vectors remain just form the in
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d d x,y . If x and y don’t belon
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Investigating the Influence of Popu
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TABLE I.EXPERIMENTAL RESULTS FOR 26
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Intelligent Learning Systems Where
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FuzzyLogicBayesianReasoningClassifi
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AN IMPROVED HAPTIC ALGORITHM FOR VI
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Fig. 2. Proxy ImmersionFig. 1. Prox
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1Corpus Design Techniques for Irish
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