Browsing by Subject "GPS"
Now showing items 1-11 of 11
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(2018)Personal mobility data can nowadays be easily collected by personal mobile phones and used for analytical modeling. To assist in such an analysis, a variety of computational approaches have been developed. The goal is to extract mobility patterns in order to provide traveling assistance, information, recommendations or on-demand services. While various computational techniques are being developed, research literature on destination and route prediction lacks consistency in evaluation methods for such approaches. This study presents a review and categorization of evaluation criteria and terminology used in assessing the performance of such methods. The review is complemented by experimental analysis of selected evaluation criteria, to highlight the nuances existing between the evaluation measures. The experimental study uses previously unpublished mobility data of 15 users collected over a period of 6 months in Helsinki metropolitan area in Finland. The article is primarily intended for researchers developing approaches for personalized mobility analysis, as well as a guideline for practitioners to select criteria when assessing and selecting between computational approaches. Our main recommendation is to consider user-specific accuracy measures in addition to averaged aggregates, as well as to take into consideration that for many users accuracy does not saturate fast and the performance keeps evolving over time. Therefore, we recommend using time-weighted measures. (c) 2017 Wiley Periodicals, Inc.
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(The Society of Forestry in Finland - The Finnish Forest Research Institute, 1998)Two methods of pre-harvest inventory were designed and tested on three cutting sites containing a total of 197 500 m3 of wood. These sites were located on flat-ground boreal forests located in northwestern Quebec. Both methods studied involved scaling of trees harvested to clear the road path one year (or more) prior to harvest of adjacent cut-blocks. The first method (ROAD) considers the total road right-of-way volume divided by the total road area cleared. The resulting volume per hectare is then multiplied by the total cut-block area scheduled for harvest during the following year to obtain the total estimated cutting volume. The second method (STRATIFIED) also involves scaling of trees cleared from the road. However, in STRATIFIED, log scaling data are stratified by forest stand location. A volume per hectare is calculated for each stretch of road that crosses a single forest stand. This volume per hectare is then multiplied by the remaining area of the same forest stand scheduled for harvest one year later. The sum of all resulting estimated volumes per stand gives the total estimated cutting-volume for all cut-blocks adjacent to the studied road. A third method (MNR) was also used to estimate cut-volumes of the sites studied. This method represents the actual existing technique for estimating cutting volume in the province of Quebec. It involves summing the cut volume for all forest stands. The cut volume is estimated by multiplying the area of each stand by its estimated volume per hectare obtained from standard stock tables provided by the governement. The resulting total estimated volume per cut-block for all three methods was then compared with the actual measured cut-block volume (MEASURED). This analysis revealed a significant difference between MEASURED and MNR methods with the MNR volume estimate being 30 % higher than MEASURED. However, no significant difference from MEASURED was observed for volume estimates for the ROAD and STRATIFIED methods which respectively had estimated cutting volumes 19 % and 5 % lower than MEASURED. Thus the ROAD and STRATIFIED methods are good ways to estimate cut-block volumes after road right-of-way harvest for conditions similar to those examined in this study.
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(2016)Objective: To explore how work experiences, professional issues and social support at work are associated with a need for clinical supervision (CS) among family physicians (FP). Methods: Web-based survey to FPs in Finland 2011 (response rate 68%; n = 165). Results: Among FPs, 36% needed CS, 35% had experience with CS, and 29% did not need CS. Feeling emotionally drained from work was associated with both needing and experience with CS. FPs needing CS felt callous and had committed a medical error in the recent past more often than those with CS experience. FPs expressing a need for CS felt greater uncertainty regarding their professional knowledge and more alone at work than FPs not needing CS. Rewarding work experiences were common. Conclusions: A large proportion of FPs expressed a need for CS. Need for CS is associated with feeling alone at work, experiences of callousness and uncertainty regarding medical knowledge. Experience of emotional drainage was associated with experience of and need for CS. Practice implications: Emotional drainage may signal a need for CS among FPs. CS might enhance FPs' emotional well-being at work. It should be more widely available to FPs and could be integrated into continuing professional development. (C) 2016 Elsevier Ireland Ltd. All rights reserved.
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(John Wiley & Sons, 2018)GPS SolutionsThis study provides information about the influence of various ionospheric spatial gradients on the thin layer ionospheric model (TLIM). Particular attention is paid to the errors caused by the slant total electron content (sTEC) when converted to the vertical total electron content (vTEC) by an elevation-dependent mapping function (MF), ignoring the satellite azimuth. We quantify the influence of the spatial gradient on ionospheric mapping using globally distributed GNSS measurements and the NeQuick2 ionospheric electron density model. The ionospheric mapping errors (IME) were confirmed using GNSS measurements that were observed for different solar activity conditions. It was found that the IME in the low latitudes were significantly higher than those at other latitudes, and the high-latitude region IME were more pronounced than those of the mid-latitude regions. A comprehensive simulation analysis based on the NeQuick2 model was conducted for different azimuth angles and geographical locations. It was found that the vTEC converted by the MF is smaller than the real value of vTEC in different spatial directions. The IME in the north-to-south direction were much higher than those in the east-to-west direction and were symmetrical north–south about the geomagnetic equator. The values of the IME had obviously seasonal variation characteristics: The IME in the spring and autumn were significantly higher than those in the winter and summer; however, in the low latitudes, the IME were abnormal and had larger values. There is an interesting phenomenon wherein the IME were symmetrical about the azimuth of 180°, and the value of the IME was less than 1 TECu when the satellite elevation was up to 50°. From the global perspective, when the thin layer height is at 400 km, the IME were relatively minimal. In addition, the modified single-layer model (MSLM) and Ou (Ou J) segmented mapping functions outperformed other mapping functions at low satellite elevations; however, when the elevation angle was increased to approximately 40°, the differences of the different MFs were small.
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(2018)Planning and management needs up-to-date, easily-obtainable and accurate information on the spatial and social aspects of visitor behaviour in order to balance human use and impacts, and protection of natural resources in public parks. We used a web-based public participation GIS (PPGIS) approach to gather citizen data on visitor behaviour in Helsinki's Central Park in order to aid collaborative spatial decision-making. The study combined smartphone GPS tracking, route drawing and a questionnaire to examine differences between user groups in their use of formal trails, off-trail behaviour and the motivations that affect it. In our sample (n = 233), different activity types were associated with distinctive spatial patterns and potential extent of impacts. The density mapping and statistical analyses indicated three types of behaviour: predominantly on or close to formal trails (runners and cyclists), spatially concentrated off-trail behaviour confined to a few informal paths (mountain bikers), and dispersed off trail use pattern (walkers and dog walkers). Across all user groups, off-trail behaviour was mainly motivated by positive attraction towards the environment such as scenic view, exploration, and viewing flora and fauna. Study findings lead to several management recommendations that were presented to city officials. These include reducing dispersion and the spatial extent of trampling impacts by encouraging use of a limited number of well-established informal paths away from sensitive vegetation and protected habitats. (C) 2017 Elsevier Ltd. All rights reserved.
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(MDPI AG, 2023)Remote SensingIn this work, a dedicated campaign by MetOp-A satellite is conducted to monitor the ionosphere based on radio-occultation (RO) measurements provided by the onboard GNSS (Global Navigation Satellite System) Receiver for Atmospheric Sounding (GRAS). The main goal is to analyze the capabilities of the collected data to represent the bending angle and scintillation profiles of the ionosphere. We compare the MetOp-A products with those generated by other RO missions and explore the spatial/temporal distributions sensed by the MetOp-A campaign. Validation of dual frequency bending angles at the RO tangent points, S4 index, and Rate of the Total electron content Index (ROTI) is performed against independent products from Fengyun-3D and FORMOSAT-7/COSMIC-2 satellites. Our main findings constitute the following: (1) bending angle profiles from MetOp-A agree well with Fengyun-3D measurements; (2) bending angle distributions show a typical S-shape variation along the altitudes; (3) signatures of the sporadic E-layer and equatorial ionization anomaly crests are observed by the bending angles; (4) sharp transitions are observed in the bending angle profiles above ~200 km due to the transition of the daytime/nighttime in addition to the transition of the bottom-side/top-side; and (5) sporadic E-layer signatures are observed in the S4 index distributions by MetOp-A and FORMOSAT-7/COSMIC-2, with expected differences in magnitudes between the GPS (Global Positioning System) L1 and L2 frequencies.
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(2013)In this article learning is studied in situations that involve sensors. The main questions are how to conceptualize experiential learning involving sensors and what kinds of learning applications using sensors already exist or could be designed. It is claimed that experiential learning, context information and sensor data supports 21st century learning. The concepts of context, technology-mediated experiences, shared felt experiences, and experiential learning theory will be used to describe a framework for sensor based mobile learning environments. Several scenarios and case examples using sensors and sensor data will be presented and they will be analyzed using the framework. Finally, the article contributes to the discussion concerning the role of technology-mediated learning experiences and collective sensor data in developing 21st century learning by characterizing what kinds of skills and competences are supported in learning situations that involve sensors.
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(Tartu Ülikooli Kirjastus, 2019)Knowledge on the spatiotemporal dynamics of people is important for public governance, policy-making, research and development. The Era of Big Data has provided unprecedented possibilities to track human mobility, and has also raised new risks and challenges. The Mobility Lab at the University of Tartu has 15 years of experience in making use of passive and active mobile positioning datasets in a wide variety of research directions. As a more recent spatiotemporal data type for the lab, the longitudinal GPS-tracking dataset has opened up new frontiers in studying human dynamics since 2013. The smart phone application MobilityLab, developed jointly by the Mobility Lab and Cambridge Computer Laboratory, collects various locational and behavioural data on a voluntary basis. MobilityLog surveys are complemented by qualitative interviews held both at the beginning and end of the automated data collection period. The interviews cover the semantics of visited places, travel behaviour, use of information and communication technology, main social contacts, and social characteristics of sample. The Mobility Lab has just started new GPS-based longitudinal surveys in the field of segregation, environmental exposure, and transnationality.
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(2020)This article provides an overview of the use of inertial and visual sensors and discusses their prospects in the Arctic navigation of autonomous vehicles. We also examine the fusion algorithms used thus far for integrating vehicle localization measurements as well as the map-matching (MM) algorithms relating position coordinates with road infrastructure. Our review reveals that conventional fusion and MM methods are not enough for navigation in challenging environments, like urban areas and Arctic environments. We also offer new results from testing inertial and optical sensors in vehicle positioning in snowy conditions. We find that the fusion of Global Navigation Satellite System (GNSS) and inertial navigation systems (INSs) does not provide the accuracy required for automated driving, and the use of optical sensors is challenged by snow covering the road markings. Although extensive further research is needed to solve these problems, the fusion of GNSS, INSs, and optical sensors seems to be the best option due to their complementary nature.
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Tuntemattomien kohtaaminen hybridikaupungissa : Millaista on sosiaalinen vuorovaikutus Grindrissä? (Helsingin yliopisto, 2017)Tämän pro gradu-tutkielman tutkimuskohteena on sosiaalinen vuorovaikutus kaupungissa, jossa informaatioteknologia on integroitunut osaksi fyysistä ympäristöä. Ennen älypuhelimia ihmisiä on kohdattu joko kasvotusten tai internetin välityksellä. GPS-teknologian ja älypuhelinsovellusten nopea kehittyminen on tehnyt ihmisten fyysisen kohtaamisen mahdolliseksi digitaalista ympäristöä hyödyntäen. Uudet tavat olla vuorovaikutuksessa sekä muiden ihmisten että ympäristön kanssa ovat tulleet luonnolliseksi osaksi todellisuudenkokemusta. Kaupunkitilasta on muodostunut fyysisen ja digitaalisen todellisuuden hybridi, jossa ihmisiä kohdataan uusin tavoin. Tavoitteena on selvittää, millaista sosiaalisuutta tällaisessa hybridikaupungissa rakentuu. Kasvoittain tapahtuva ja digitaalinen vuorovaikutus muodostavat yhdentymän, jonka puitteissa tuntemattomien kohtaaminen tapahtuu. Vuorovaikutuksen perinteiset ja digitaaliset käytännöt kohtaavat ensi kertaa tutkitun teknologian myötä muodostaen hybridin, jossa molemmat ehdollistavat toisensa. Teoreettisessa katsauksessa käsitellään tämän hybridin taustaa. Osiossa käydään läpi teknologian kehityksen historiaa ihmisen mekaanisista jatkeista tietokoneiksi sekä sosiaalisen murrosta digitaalisten vuorovaikutusteknologioiden kehityksen myötä. Lisäksi tehdään katsaus lokaatioperustaisten pelien sekä internetpohjaisten seuranhakupalveluiden tutkimukseen. Tutkimuskysymys on: Millaista on sosiaalinen vuorovaikutus Grindrissä? Grindr on miehistä kiinnostuneille miehille suunnattu geososiaalista paikannusta hyödyntävä älypuhelimissa toimiva seuranhakupalvelu. Aineistonkeruun aikaan se oli myös ainoa suurta suosiota saavuttanut paikannusta hyödyntävä seuranhakusovellus. Aineisto koostuu kolmestatoista Berliinissä tehdystä haastattelusta, jotka on kerätty vuoden 2014 aikana. Haastateltavat on rekrytoitu sovelluksen välityksellä. Aineistonkeruumenetelmänä on teemahaastattelu ja -analyysimenetelmänä teemoittelu. Kaikki haastattelut olivat 40–120 minuuttisia yksilöhaastatteluja, ja ne toteutettiin englannin kielellä. Tutkimustyön perusteella voidaan todeta seuraavia asioita: Tuntemattomia voi kohdata Grindrin välityksellä ajasta ja paikasta riippumatta. Viestintä perustuu enemmän kuviin kuin sanoihin. Identiteetti ja intressit määritellään digitaalisessa ympäristössä, ja niissä luodot käsitykset ohjaavat toimintaa vahvasti myös fyysisessä kohtaamisessa. Digitaalisessa ympäristössä on luonnollista ilmaista tarpeensa suoraviivaisesti ja siirtyä nopeasti eteenpäin, mikäli intressit eivät kohtaa. Perinteiset ympäristöt ja tavat kohdata tuntemattomia ovat menettäneet merkitystään. Sosiaalinen vuorovaikutus Grindrissä vaikuttaa sekä ihmisten käsityksiin itsestä että muista. Kasvottaisen ja digitaalisen vuorovaikutuksen käytännöt limittyvät ja vaikuttavat vastavuoroisesti toisiinsa hybridisosiaalisen kanssakäymisen myötä. Fyysinen olemus määrittää puitteet digitaalisen persoonan konstruktiolle, samaan aikaan kun digitaalinen identiteetti vaikuttaa siihen, miten itsensä esittää fyysisissä kohtaamisissa. Tämän seurauksena on syntynyt uudenlaista sosiaalisuutta. Fyysistä ja digitaalista vuorovaikutusta ei hybridikaupungissa ole mielekästä tarkastella toisistaan irrallaan niiden asettuessa kaksisuuntaiseen suhteeseen, jossa molemmat välittyvät erottamattomasti toisikseen.
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(2020)This paper aims to examine the role of global positioning system (GPS) sensor data in real-life physical activity (PA) type detection. Thirty-three young participants wore devices including GPS and accelerometer sensors on five body positions and performed daily PAs in two protocols, namely semi-structured and real-life. One general random forest (RF) model integrating data from all sensors and five individual RF models using data from each sensor position were trained using semi-structured (Scenario 1) and combined (semi-structured + real-life) data (Scenario 2). The results showed that in general, adding GPS features (speed and elevation difference) to accelerometer data improves classification performance particularly for detecting non-level and level walking. Assessing the transferability of the models on real-life data showed that models from Scenario 2 are strongly transferable, particularly when adding GPS data to the training data. Comparing individual models indicated that knee-models provide comparable classification performance (above 80%) to general models in both scenarios. In conclusion, adding GPS data improves real-life PA type classification performance if combined data are used for training the model. Moreover, the knee-model provides the minimal device configuration with reliable accuracy for detecting real-life PA types.
