Renar och vindkraft II : Vindkraft i drift och effekter på renar och renskötsel

Utbyggnaden av vindkraft inom renskötselområdet har ökat markant det senaste decenniet, trots att kunskapen om påverkan av vindkraftsetableringar ännu inte är fullt utredd och dokumenterad. I den här rapporten beskriver vi framförallt hur vindkraftparker i driftsfas påverkar renarna och renskötseln i tre olika områden. I Malå sameby har vi studerat kalvningsområdet kring Storliden och Jokkmokkslidens vindkraftparker. I Vilhelmina Norra sameby har vi studerat vinterbetesområdet kring Stor-Rotlidens vindkraftpark, samt Lögdeålandets betesområde med Gabrielsbergets vindkraftpark som används av Byrkije reinbetesdistrikt från Norge. För att få en helhetsbild av hur renarna använder sitt betesområde är det viktigt att studera renarnas betes- och förflyttningsmönster långsiktigt och över hela deras betesområde och inte bara inom det lokala området nära parken. Det är också viktigt att ta hänsyn till att renarnas betesutnyttjande skiftar från år till år och mellan olika årstider beroende på väderlek och andra yttre förutsättningar. Vi vill också understryka vikten av att kombinera den traditionella kunskapen från renskötarna med vedertagna vetenskapliga analysmetoder för att besvara de frågor som är viktiga för att kunna bedriva en hållbar renskötsel. Vi har undersökt renarnas användning av områdena genom att utföra spillningsinventeringar under åren 2009-2015 (endast i Malå sameby), och genom att följa renar utrustade med GPS-halsband under åren 2005-2015. Datat är insamlat före och under byggfas och under driftsfas (för Gabrielsberget finns GPS-data endast för driftsfasen). Vi har analyserat data genom att utveckla statistiska modeller för val av betesområde för varje område där vi har beräknat hur renarna förhåller sig till vindkraftparksområdet före, under och efter byggnation, och på Gabrielsberget när parken varit avstängd under 40 dagar och under drift vid olika renskötselsituationer. Genom intervjuer, möten och samtal, samt information från Gabrielsbergets vindkraftparks kontrollprogram, har vi tagit del av renskötarnas erfarenheter av hur renarnas beteende, och därmed även renskötseln, påverkats av vindkraftsutbyggnaden i respektive område. Våra resultat visar att renarna både på kalvnings- och på vinterbetesområden påverkas negativt av vindkraftsetableringarna (Tabell a). Renarna undviker att beta i områden där de kan se och/eller höra vindkraftsverken och föredrar att vistas i områden där vindkraftverken är skymda. I kalvningsområdet i Malå ökade användningen av skymda områden med 60 % under driftsfas. I vinterbetesområdet på Gabrielsberget, när renarna utfodrades i parken och kantbevakades intensivt för att stanna i parkområdet under driftsfas, ökade användningen av skymda områden med 13 % jämfört med när de inte var utfodrade och fick ströva mer fritt. Resultaten visar också att renarna minskar sin användning av området nära vindkraftparkerna. I kalvningslandet i Malå minskar renarna sin användning av områden inom 5 km från parkerna med 16-20 %. Vintertid vid Gabrielsbergets vindkraftpark undvek renarna parken med 3 km. Våra resultat visar även att renarnas betesro minskar inom en radie på 4 km från vindkraftparkerna under kalvningsperioden och tiden därefter i jämförelse med perioden före byggfas. Exakta avstånd som renarna påverkas beror på förutsättningarna i respektive område, exempelvis hur topografin ser ut eller om området är begränsat av stängsel eller annan infrastruktur. Förändringarna i habitatutnyttjande i våra studieområden blev tydligare när parkerna var centralt belägna i renarnas betesområde, som i kalvningsområdet i Malå eller i vinterbeteslandet på Gabrielsberget, medan det inte var lika tydliga effekter kring Stor-Rotlidens park, som ligger i utkanten av ett huvudbetesområde. Oftast är snöförhållandena bättre ur betessynpunkt högre upp i terrängen än nere i dalgångarna, på grund av stabilare temperatur, vind som blåser bort snötäcket och mer variation i topografin. Därför kan etablering av vindkraftparker i höglänta områden försämra möjligheten att använda sådana viktiga reservbetesområden under vintrar med i övrigt dåliga snöförhållanden, vilka blir allt vanligare i och med klimatförändringarna. Våra resultat tyder inte direkt på att renarna påverkats negativt under dåliga betesvintrar men fler år av studier behövs för att ytterligare klargöra hur vindkraft påverkar renarna under dessa vintrar. Våra studier har visat att etablering av vindkraft har konsekvenser för renskötseln under både barmarkssäsongen och under vintern, men effekterna förmodas få störst inverkan inom vinterbetesområdet där det är svårt att hitta alternativa betesområden för renarna. Under sommaren är betestillgången oftast mindre begränsad och renarna kan lättare hitta alternativa områden. En direkt konsekvens av Gabrielsbergets vindkraftpark som är placerad mitt i ett vinterbetesområde har blivit att renarna behöver tillskottsutfodras och bevakas intensivare för att de inte ska gå ut ur området. När den naturliga vandringen mellan olika betesområden störs för att renarna undviker att vistas i ett område kan det leda till att den totala tillgången till naturligt bete minskar och att man permanent måste tillskottsutfodra, alternativt minska antalet renar. Annan infrastruktur som vägar och kraftledningar påverkar också renarna. Vid Storliden och Jokkmokksliden och vid Stor-Rotliden där data samlats in innan vindkraftparken uppfördes visar våra resultat att renarna undviker de omkringliggande landsvägarna redan innan parkerna etablerades. Vid Stor-Rotliden ökar dock renarna användningen av områden nära vägarna efter att parken är byggd. På Gabrielsberget, där vi endast har data under drifttiden, är renarna närmare vägarna (även stora vägar som E4) när renskötarna minskar på kantbevakningen för att inte hålla renarna nära parken. Detta ökar naturligtvis risken för trafikolyckor och innebär att renskötarna måste bevaka dessa områden intensivare. Sist i rapporten presenterar vi förslag till åtgärder som kan användas för att underlätta arbetet för renskötseln om det är så att en vindkraftpark redan är byggd. Några exempel på åtgärder som är direkt kopplat till parken är att stänga av vägarna in i vindkraftparken för att förhindra nöjeskörning med skoter och bil under den tiden renarna vistas i området samt tät dialog mellan vindkraftsbolag och sameby angående vinterväghållningen av vägarna till och inom vindkraftparken. Andra mer regionala åtgärder för att förbättra förutsättningarna för renskötselarbetet på andra platser för samebyn, kan vara att sätta stängsel längst större vägar och järnvägar (t.ex. E4:an eller stambanan) i kombination med strategiskt utplacerade ekodukter. Detta för att underlätta och återställa möjligheterna till renarnas fria strövning och renskötarnas flytt av renar mellan olika betesområden.   

Characters Extraction for Traffic Sign Destination boards in video and still images

Traffic Control Signs or destination boards on roadways offer significant information for drivers. Regulation signs tell something like your speed, turns, etc; Warning signs warn drivers of conditions ahead to help them avoid accidents; Destination signs show distances and directions to various locations; Service signs display location of hospitals, gas and rest areas etc. Because the signs are so important and there is always a certain distance from them to drivers, to let the drivers get information clearly and easily even in bad weather or other situations. The idea is to develop software which can collect useful information from a special camera which is mounted in the front of a moving car to extract the important information and finally show it to the drivers. For example, when a frame contains on a destination drive sign board it will be text something like "Linkoping 50",so the software should extract every character of "Linkoping 50", compare them with the already known character data in the database. if there is extracted character match "k" in the database then output the destination name and show to the driver. In this project C++ will be used to write the code for this software.

Road and Traffic Signs Recognition using Vector Machines

Intelligent Transportation System (ITS) is a system that builds a safe, effective and integrated transportation environment based on advanced technologies. Road signs detection and recognition is an important part of ITS, which offer ways to collect the real time traffic data for processing at a central facility.This project is to implement a road sign recognition model based on AI and image analysis technologies, which applies a machine learning method, Support Vector Machines, to recognize road signs. We focus on recognizing seven categories of road sign shapes and five categories of speed limit signs. Two kinds of features, binary image and Zernike moments, are used for representing the data to the SVM for training and test. We compared and analyzed the performances of SVM recognition model using different features and different kernels. Moreover, the performances using different recognition models, SVM and Fuzzy ARTMAP, are observed.

A Unified Load Generator for Geographically Distributed Generation ofNetwork Traffic

During the last decade, the Internet usage has been growing at an enormous rate which has beenaccompanied by the developments of network applications (e.g., video conference, audio/videostreaming, E-learning, E-Commerce and real-time applications) and allows several types ofinformation including data, voice, picture and media streaming. While end-users are demandingvery high quality of service (QoS) from their service providers, network undergoes a complex trafficwhich leads the transmission bottlenecks. Considerable effort has been made to study thecharacteristics and the behavior of the Internet. Simulation modeling of computer networkcongestion is a profitable and effective technique which fulfills the requirements to evaluate theperformance and QoS of networks. To simulate a single congested link, simulation is run with asingle load generator while for a larger simulation with complex traffic, where the nodes are spreadacross different geographical locations generating distributed artificial loads is indispensable. Onesolution is to elaborate a load generation system based on master/slave architecture.

A Contour-based Separation of VerticallyAttached Traffic Signs

This report presents an algorithm for locating the cut points for and separatingvertically attached traffic signs in Sweden. This algorithm provides severaladvanced digital image processing features: binary image which representsvisual object and its complex rectangle background with number one and zerorespectively, improved cross correlation which shows the similarity of 2Dobjects and filters traffic sign candidates, simplified shape decompositionwhich smoothes contour of visual object iteratively in order to reduce whitenoises, flipping point detection which locates black noises candidates, chasmfilling algorithm which eliminates black noises, determines the final cut pointsand separates originally attached traffic signs into individual ones. At each step,the mediate results as well as the efficiency in practice would be presented toshow the advantages and disadvantages of the developed algorithm. Thisreport concentrates on contour-based recognition of Swedish traffic signs. Thegeneral shapes cover upward triangle, downward triangle, circle, rectangle andoctagon. At last, a demonstration program would be presented to show howthe algorithm works in real-time environment.

Real-Time Recognition System for Traffic Signs

The aim of this thesis project is to develop the Traffic Sign Recognition algorithm for real time. Inreal time environment, vehicles move at high speed on roads. For the vehicle intelligent system itbecomes essential to detect, process and recognize the traffic sign which is coming in front ofvehicle with high relative velocity, at the right time, so that the driver would be able to pro-actsimultaneously on instructions given in the Traffic Sign. The system assists drivers about trafficsigns they did not recognize before passing them. With the Traffic Sign Recognition system, thevehicle becomes aware of the traffic environment and reacts according to the situation.The objective of the project is to develop a system which can recognize the traffic signs in real time.The three target parameters are the system’s response time in real-time video streaming, the trafficsign recognition speed in still images and the recognition accuracy. The system consists of threeprocesses; the traffic sign detection, the traffic sign recognition and the traffic sign tracking. Thedetection process uses physical properties of traffic signs based on a priori knowledge to detect roadsigns. It generates the road sign image as the input to the recognition process. The recognitionprocess is implemented using the Pattern Matching algorithm. The system was first tested onstationary images where it showed on average 97% accuracy with the average processing time of0.15 seconds for traffic sign recognition. This procedure was then applied to the real time videostreaming. Finally the tracking of traffic signs was developed using Blob tracking which showed theaverage recognition accuracy to 95% in real time and improved the system’s average response timeto 0.04 seconds. This project has been implemented in C-language using the Open Computer VisionLibrary.

QoS Evaluation of BandwidthSchedulers in IPTV Networks OfferedSRD Fluid Video Traffic

Internet protocol TV (IPTV) is predicted to be the key technology winner in the future. Efforts to accelerate the deployment of IPTV centralized model which is combined of VHO, encoders, controller, access network and Home network. Regardless of whether the network is delivering live TV, VOD, or Time-shift TV, all content and network traffic resulting from subscriber requests must traverse the entire network from the super-headend all the way to each subscriber's Set-Top Box (STB).IPTV services require very stringent QoS guarantees When IPTV traffic shares the network resources with other traffic like data and voice, how to ensure their QoS and efficiently utilize the network resources is a key and challenging issue. For QoS measured in the network-centric terms of delay jitter, packet losses and bounds on delay. The main focus of this thesis is on the optimized bandwidth allocation and smooth datatransmission. The proposed traffic model for smooth delivering video service IPTV network with its QoS performance evaluation. According to Maglaris et al [5] First, analyze the coding bit rate of a single video source. Various statistical quantities are derived from bit rate data collected with a conditional replenishment inter frame coding scheme. Two correlated Markov process models (one in discrete time and one incontinuous time) are shown to fit the experimental data and are used to model the input rates of several independent sources into a statistical multiplexer. Preventive control mechanism which is to be include CAC, traffic policing used for traffic control.QoS has been evaluated of common bandwidth scheduler( FIFO) by use fluid models with Markovian queuing method and analysis the result by using simulator andanalytically, Which is measured the performance of the packet loss, overflow and mean waiting time among the network users.

QoS evaluation of bandwidth schedulersin IPTV networks offered SRD fluidvideo traffic: a simulation study

IPTV is now offered by several operators in Europe, US and Asia using broadcast video over private IP networks that are isolated from Internet. IPTV services rely ontransmission of live (real-time) video and/or stored video. Video on Demand (VoD)and Time-shifted TV are implemented by IP unicast and Broadcast TV (BTV) and Near video on demand are implemented by IP multicast. IPTV services require QoS guarantees and can tolerate no more than 10-6 packet loss probability, 200 ms delay, and 50 ms jitter. Low delay is essential for satisfactory trick mode performance(pause, resume,fast forward) for VoD, and fast channel change time for BTV. Internet Traffic Engineering (TE) is defined in RFC 3272 and involves both capacity management and traffic management. Capacity management includes capacityplanning, routing control, and resource management. Traffic management includes (1)nodal traffic control functions such as traffic conditioning, queue management, scheduling, and (2) other functions that regulate traffic flow through the network orthat arbitrate access to network resources. An IPTV network architecture includes multiple networks (core network, metronetwork, access network and home network) that connects devices (super head-end, video hub office, video serving office, home gateway, set-top box). Each IP router in the core and metro networks implements some queueing and packet scheduling mechanism at the output link controller. Popular schedulers in IP networks include Priority Queueing (PQ), Class-Based Weighted Fair Queueing (CBWFQ), and Low Latency Queueing (LLQ) which combines PQ and CBWFQ.The thesis analyzes several Packet Scheduling algorithms that can optimize the tradeoff between system capacity and end user performance for the traffic classes. Before in the simulator FIFO,PQ,GPS queueing methods were implemented inside. This thesis aims to implement the LLQ scheduler inside the simulator and to evaluate the performance of these packet schedulers. The simulator is provided by ErnstNordström and Simulator was built in Visual C++ 2008 environmentand tested and analyzed in MatLab 7.0 under windows VISTA.

An Upgrade of Network Traffic Recognition System for SIP/VoIP Traffic Recognition

The purpose of this project is to update the tool of Network Traffic Recognition System (NTRS) which is proprietary software of Ericsson AB and Tsinghua University, and to implement the updated tool to finish SIP/VoIP traffic recognition. Basing on the original NTRS, I analyze the traffic recognition principal of NTRS, and redesign the structure and module of the tool according to characteristics of SIP/VoIP traffic, and then finally I program to achieve the upgrade. After the final test with our SIP data trace files in the updated system, a satisfactory result is derived. The result presents that our updated system holds a rate of recognition on a confident level in the SIP session recognition as well as the VoIP call recognition. In the comparison with the software of Wireshark, our updated system has a result which is extremely close to Wireshark’s output, and the working time is much less than Wireshark. In the aspect of practicability, the memory overflow problem is avoided, and the updated system can output the specific information of SIP/VoIP traffic recognition, such as SIP type, SIP state, VoIP state, etc. The upgrade fulfills the demand of this project.

Analysis of EnterpriseVoIP Traffic from aWire line IMS System

With the rapid development of telecommunication industry, the IP multimedia Subsystem (IMS) could very well be the panacea for most telecom operators. It is originally defined as the core network for 3G mobile systems by the 3rd Generation Partnership Project (3GPP), the more recent development is merging between fixed line network and wireless networkd This report researchs the characteristic of the IMS data and proposes an IMS characterization analysis. We captured the IMS traffic data with 10 tousands users for about 41 hours. By analyzing the characteristics of the IMS, we know that the most important application in the IMS is VoIP call. Then we use the tool designed by Tsinghua University & Ericsson Company to recognize the data, and the results we got can be used to build the traffic models. From the results of the traffic models, I will get some reasons and conclusion. The traffic model gives out the types of session and types of VoIP call. I bring into a concept—busy hour. This concept is very important because it can help us to know which period is the peak of the VoIP call. The busy hour is from 10:00 to 11:00 in the morning. I also bring into another concept—connection ratio. This concept is significant because it can evaluate whether the VoIP call is good when it use IMS network. By comparing the traffic model with other one’s models, we found the different results from them, both the accuracy and the busy hour. From the contract, we got the advantages of our traffic models.

Evaluation of Red Colour Segmentation Algorithms in Traffic Signs Detection

Colour segmentation is the most commonly used method in road signs detection. Road sign contains several basic colours such as red, yellow, blue and white which depends on countries.The objective of this thesis is to do an evaluation of the four colour segmentation algorithms. Dynamic Threshold Algorithm, A Modification of de la Escalera’s Algorithm, the Fuzzy Colour Segmentation Algorithm and Shadow and Highlight Invariant Algorithm. The processing time and segmentation success rate as criteria are used to compare the performance of the four algorithms. And red colour is selected as the target colour to complete the comparison. All the testing images are selected from the Traffic Signs Database of Dalarna University [1] randomly according to the category. These road sign images are taken from a digital camera mounted in a moving car in Sweden.Experiments show that the Fuzzy Colour Segmentation Algorithm and Shadow and Highlight Invariant Algorithm are more accurate and stable to detect red colour of road signs. And the method could also be used in other colours analysis research. The yellow colour which is chosen to evaluate the performance of the four algorithms can reference Master Thesis of Yumei Liu.

Expert system to calculate the cofficient of friction : an approach to enhance traffic safety

Friction plays a key role in causing slipperiness as a low coefficient of friction on the road may result in slippery and hazardous conditions. Analyzing the strong relation between friction and accident risk on winter roads is a difficult task. Many weather forecasting organizations use a variety of standard and bespoke methods to predict the coefficient of friction on roads. This article proposes an approach to predict the extent of slipperiness by building and testing an expert system. It estimates the coefficient of friction on winter roads in the province of Dalarna, Sweden using the prevailing weather conditions as a basis. Weather data from the road weather information system, Sweden (RWIS) was used. The focus of the project was to use the expert system as a part of a major project in VITSA, within the domain of intelligent transport systems

QoS evaluation of Bandwidth Schedulers in IPTV Networks Offered SRD Fluid Video Traffic

Internet protocol TV (IPTV) is predicted to be the key technology winner in the future. Efforts to accelerate the deployment of IPTV centralized model which is combined of VHO, encoders, controller, access network and Home network. Regardless of whether the network is delivering live TV, VOD, or Time-shift TV, all content and network traffic resulting from subscriber requests must traverse the entire network from the super-headend all the way to each subscriber's Set-Top Box (STB). IPTV services require very stringent QoS guarantees When IPTV traffic shares the network resources with other traffic like data and voice, how to ensure their QoS and efficiently utilize the network resources is a key and challenging issue. For QoS measured in the network-centric terms of delay jitter, packet losses and bounds on delay. The main focus of this thesis is on the optimized bandwidth allocation and smooth data transmission. The proposed traffic model for smooth delivering video service IPTV network with its QoS performance evaluation. According to Maglaris et al [5] first, analyze the coding bit rate of a single video source. Various statistical quantities are derived from bit rate data collected with a conditional replenishment inter frame coding scheme. Two correlated Markov process models (one in discrete time and one in continuous time) are shown to fit the experimental data and are used to model the input rates of several independent sources into a statistical multiplexer. Preventive control mechanism which is to be including CAC, traffic policing used for traffic control. QoS has been evaluated of common bandwidth scheduler( FIFO) by use fluid models with Markovian queuing method and analysis the result by using simulator and analytically, Which is measured the performance of the packet loss, overflow and mean waiting time among the network users.

Reliability of GPS based traffic data: an experimental evaluation

GPS tracking of mobile objects provides spatial and temporal data for a broad range of applications including traffic management and control, transportation routing and planning. Previous transport research has focused on GPS tracking data as an appealing alternative to travel diaries. Moreover, the GPS based data are gradually becoming a cornerstone for real-time traffic management. Tracking data of vehicles from GPS devices are however susceptible to measurement errors – a neglected issue in transport research. By conducting a randomized experiment, we assess the reliability of GPS based traffic data on geographical position, velocity, and altitude for three types of vehicles; bike, car, and bus. We find the geographical positioning reliable, but with an error greater than postulated by the manufacturer and a non-negligible risk for aberrant positioning. Velocity is slightly underestimated, whereas altitude measurements are unreliable.

Benchmark Evaluation of HOG Descriptors as Features for Classification of Traffic Signs

The purpose of this paper is to analyze the performance of the Histograms of Oriented Gradients (HOG) as descriptors for traffic signs recognition. The test dataset consists of speed limit traffic signs because of their high inter-class similarities.   HOG features of speed limit signs, which were extracted from different traffic scenes, were computed and a Gentle AdaBoost classifier was invoked to evaluate the different features. The performance of HOG was tested with a dataset consisting of 1727 Swedish speed signs images. Different numbers of HOG features per descriptor, ranging from 36 features up 396 features, were computed for each traffic sign in the benchmark testing. The results show that HOG features perform high classification rate as the Gentle AdaBoost classification rate was 99.42%, and they are suitable to real time traffic sign recognition. However, it is found that changing the number of orientation bins has insignificant effect on the classification rate. In addition to this, HOG descriptors are not robust with respect to sign orientation.