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This research investigated the presence of virulence genes encoding F41, K99, eae, Stx1, Stx2 and STa and the antimicrobial resistance of animal Escherichia coli (E. coli) isolates. Clinical isolates (n:233) were evaluated from faecal samples of cattle, sheep, goats, horses, cats and dogs collected between the years of 2010 to 2015 from Turkey. Enterohaemorrahic E.coli (EHEC) O157:H7 was detected by using cefixime tellurite sorbitol MacConkey agar (CT-SMAC) and Wellcollex E. coli (Remel®). The Kirby-Bauer disc diffusion test was performed to detect the resistance pattern of the isolates to ampicillin, Amoxycillin/clavulanic acid, enrofloxacin, ceftiofur, trimethoprim/sulfamethoxazole and tetracycline. The results showed that 40% of the ruminant isolates were identified as Shiga-toxin producing Escherichia coli (STEC). Enterotoxigenic E. coli (ETEC) was detected in samples from cattle (0.9%) and sheep (12%). Enteropathogenic E.coli (EPEC) was detected in samples from cattle (0.9%) and dogs (11.4%). EHEC O157:H7 was not detected any of the isolates. Among all E. coli isolates that carried at least one virulence gene, 8 (19%) were resistant to more than three antimicrobials, 7 (16.7%) were resistant to at least one antimicrobial and 27 (64.3%) were susceptible to all antimicrobials.

Saksagan (Corvidae: Pica pica), Turkiye’nin kirsal ve sehirlesmis alanlarinda yaygin olarak bulunan bir kus turudur. Bu kuslar sehirlesmis alanlarda bulunduklarindan dolayi, evcil hayvanlar ve insanlarla iliskili bazi enfeksiyoz etkenleri tasima potansiyeline sahip olabilmektedir. Bu durumu belirlemek icin, bir yil suresince tibbi bakima muhtac bir halde hayvan hastanesine getirilen sekiz adet saksagan, ic parazitler ve bakteriler yonunden muayene edilmistir. Yapilan nekropside ic parazitik, sitolojik ve mikrobiyal muayeneyi takiben, ilave olarak ilgili organlarda histopatolojik muayeneler de yapilmistir. Nekropsiler sonucunda, iki helmint ve bir protozoondan olusan uc tur parazit (sirasiyla Passerilepis sp., Brachylaima sp. ve Isospora rochalimai) teshis edilmis ve bes tur bakteri izole edilmistir (Staphylococcus xylosus, S. sciuri, Escherichia coli, Klebsiella pneumonia, Salmonella spp.). Histopatolojide subakut fokal mikotik pnomoni, kronik nonpurulent granulomatoz gastroenteritis, verminoz enteritis ve karacigerde paratifoid nodullerin varligi gozlenmistir. Belirlenen bu enfeksiyoz etkenler, diger hayvanlar ve insanlar icin potansiyel bir kontaminasyon kaynagi teskil edebilmektedir. Tespit edilen tum parazit ve bakteriler, Turkiye’nin yabani kuslarinin helmint ve bakteri faunasi icin ilk defa bildirilmektedir.

Raw GNSS measurement APIs (Application Programming Interfaces) in the Android system are a bridge between the advances of positioning techniques and the applications of positioning for billions of Android users in the mass market. The publication trend since the debut of these APIs in 2016 has shown an increasing attention from both academia and industry. Among all GNSS topics, high precision positioning on smartphones may be the most attractive one, not just because it spawns over 1/3 of publications, but more importantly, it may trigger a plethora of possible novel applications, such as lane-level driving, mapping, and precise augmented reality. To facilitate this process, in this paper, Google releases 60+ datasets collected from phones in the Android GPS team, together with corrections from SwiftNavigation Inc. and Verizon Inc. These datasets were collected on highways in the US San Francisco Bay Area in the summer of 2020. They will be released at g.co/gnsstools by November 2020. Ground truth files collected by a NovAtel SPAN system will also be provided in NMEA file format. Furthermore, Google also provides the source codes in Matlab to evaluate the positioning performance. This paper provides details of these datasets, corrections, ground truth files, and utilities.

Bu çalışmanın amacı, evcil hayvan orjinli E. coli izolatlarında PCR yöntemi ile Stx1, Stx2, eae, STa, F41 ve K99ʼu kodlayan virulens genlerinin varlığını belirlemekti. Bu çalışmada 2010-2015 yılları arasında başta Bursa ili ve çevresi olmak üzere farklı bölgelerden, sığır, koyun, keçi, at, kedi ve köpeklere ait toplam 233 adet E. coli izolatı incelendi. Sonuç olarak, sığırlardan izole edilen 111 adet E. coli izolatı %5,4 oranında Stx1, eae ve Stx2 genlerini, %0,9 oranında Stx1 ve eae genlerini birarada ve %0,9 oranında da yalnızca STa ve eae genini taşıyordu. Toplam 25 adet koyun kökenli E. coli izolatı, %12 oranında Stx1 ve Stx2 genlerini birarada, %16 oranında Stx1 genini ve %12 oranında Stx2 ve %12 oranında STa genini taşıyordu. Keçi kökenli toplam 45 adet E. coli izolatı ise %4,4 oranında Stx1 ve Stx2 genlerini birarada, %22,2 oranında Stx1, %6,7 oranında ise Stx2 genini taşıyordu. Toplam 35 adet köpek kökenli E. coli izolatı ise %11,4 oranında eae genini taşıyordu. İncelenen örneklerin hiçbirisi F41 ve K99 genlerini taşımamaktaydı. E. coli O157:H7 serotipinin varlığını araştırmak amacıyla süpheli izolatlar Rapid Latex Agglutination Wellcollex E. coli (Remel®) Testi ile araştırıldı ve izolatlarda E. coli O157:H7 serotipi saptanmadı. Sığır, koyun ve keçilerde diarajenik E. coli varlığının göstergesi olan virulens genlerinin oranları sırası ile; Shiga toksijenik E. coli (STEC) %6,3, %40 ve %33,3; Enterotoksijenik E. coli (ETEC) %0,9, % 12 ve % 0 olarak saptandı. At ve kedilerde ise diarejenik E. coli saptanmadı. Sığır ve köpeklerde Enteropatojenik E. coli (EPEC) sırasıyla %0,9 ve %11,4 olarak saptanırken koyun, keçi, at ve kedilerde EPEC saptanmadı. The objective of this study was to determine the presence of virulence genes encoding Stx1, Stx2, eae, STa, F41 and K99 with PCR protocol from domestic animal E. coli isolates. In this study, a total of 233 E. coli isolates recovered from cattle, sheep, goat, horse, cat and dog between 2010-2015 from Bursa and surrounding provinces. As a result, among 111 cattle isolates, 5.4% carried Stx1, eae and Stx2 in combination, 0.9% carried Stx1 and eae, 0.9% carried STa, and 0.9% carried eae gene. Out of 25 sheep isolates, 16% carried Stx1, 12% carried Stx2, 12% carried Stx1 and Stx2 and 12% carried STa. Out of 45 goat isolates, 22.2% carried Stx1, 6.7% carried Stx2 and 4.4% carried Stx1 and Stx2 in combination. Out of 35 dog isolates, 11.4% carried eae. None of the tested samples were positive for F41 or K99 genes. To confirm the presence of E. coli O157:H7 serotype, suspected isolates were investigated by using rapid latex agglutination test Wellcollex E. coli (Remel®) and all isolates were negative. Virulence genes specific for diarrheagenic E. coli were detected in the following percentages of the cattle, sheep and goat: Shiga toxin- producing E. coli (STEC) in 6.3%, 40% and 33.3%; enterotoxigenic E. coli (ETEC) in 0.9%, 12% and 0% respectively. Diarrheagenic E. coli was not detected in horse and cat. Enteropathogenic E. coli (EPEC) was detected only in cattle and dogs 0.9%, 11.4% respectively, and not detected in sheep, goats, and cats. 124

Pedestrian navigation in challenging areas where global navigation satellite systems (GNSSs) lack the required accuracy and availability, such as indoor and urban canyons, is becoming increasingly important. Multisensor navigation is one of the techniques that has shown promising positioning accuracy in such environments. Being able to appropriately fuse GNSS pseudoranges in a multisensor positioning system is advantageous as it allows us to make use of fewer than four detected satellite signals and to incorporate more accurate estimation models. In this study, a particle filter-based pedestrian positioning system is enhanced to use pseudorange measurements of a GNSS receiver instead of direct position solutions. By using correctly modelled pseudoranges, a single satellite visible over a certain time period might improve positioning accuracy and robustness when combined with measurements from other positioning sensors, like a foot-mounted inertial measurement unit. Additionally in this study, a statistical multipath error model for pseudoranges is integrated. Promising results have been achieved in a challenging indoor environment where blockage of satellites' signals and multipath are common issues.

A movement model that realistically imitates real pedestrian movement can be used for numerous applications such as transport infrastructure design, evacuation planning, architecture, human like robot movement or indoor/outdoor navigation. Within the scope of this paper, the purpose of such models is to quantitatively represent the stochastic nature of pedestrian movement in order to generate a pedestrian movement model for sequential Bayesian filtering techniques, such as particle-filtering. Within the work that has led to this paper we have been particularly interested in finding suitable movement models for further use in a sequential Bayesian estimation algorithm for navigation purposes in 2D and 3D. A movement model in the sense of a first order Markov process can, therefore, be used to represent and predict the current set of human motion and behavioral parameters as a function of previous parameters and other affecting states. The prediction stage of sequential Bayesian estimation depends entirely on the movement model to determine the probability density function of the pedestrian’s location and motion at each time step. A movement model that accurately models the pedestrian’s motion strongly determines the performance of the sequential Bayesian estimation algorithm, and ensures that measurement data used for positioning is correctly weighted with the movement model prediction. Furthermore, the model has to be efficiently implemented to that it can be employed in realizations such as Particle Filters. We note that the model does not need to predict the motion of a single pedestrian accurately in any singular experiment; it needs to correctly model the expected motion in a probabilistic sense. In this paper, a three dimensional movement model at the microscopic level that is suitable for pedestrian navigation will be illustrated. A combination of three dimensional movement models will be used to model the pedestrian movement. The constituents are a three dimensional Stochastic Behavioral Movement Model and a three dimensional Targeted Movement Model. Some specific constraints are applied on the pedestrian movement while moving on stairs to have a realistic stairs movement. A three dimensional Stochastic Behavioral Movement Model Human movement is parameterized by physical parameters such as speed, direction and as a result the position. Building layouts are obviously amongst the main parameters that affect the movement of the pedestrian. For instance, the pedestrian cannot penetrate a wall under any normal circumstances. In order to add the third dimension, the model was extended to be able to predict the height of the pedestrian at each time step. A linear speed function is used for modeling the height. This speed is designed to be a function of time, steepness of the stairs and activeness of the pedestrian. Accordingly, the distance moved in the Z-direction could be predicted in addition to the distances in X and Y. The direction of vertical movement could also be modeled, but in order to have a more realistic movement in the stairs area, the direction is predicted using the Targeted Movement Model. Outside the stairs area, the height is assumed to be constant. A three dimensional Target Driven Movement Model To overcome the problem of tending to stay too long in rooms or displaying motion that is not goal orientated, the diffusion movement model is applied. This model is derived from the gas diffusion in space studied in thermodynamics and is a standard solution for path finding of robots: The idea is to have a source continuously effusing gas that disperses in free space and which gets absorbed by walls and other obstacles. A path towards this source is computed by following the steepest gradient, starting at the current position. To model the stochastic nature of a human’s motion, the destination points are chosen randomly, and a Markov process models the fact that the destination may change more or less frequently. In order to add the third dimension, the set of destinations are spread over all the floors. The stairs area is projected into a 2D area that can be included in the respective floor plan of each floor. Accordingly, the diffusion matrix calculation could be started at any of the floors. The diffusion matrix at the stairs area of the destination floor is calculated for the stairs going up and down and then copied to the stairs areas of the respective neighboring floors. The diffusion matrix is then calculated from the stairs area to the rest of the respective floor. The stairs diffusion matrix of the next upper or lower stairs is calculated using the values of the current floor and so on. Paths to the destinations are found in the same 2D manner but continuing to the upper or lower floors until the destination is reached. Combined Model If the pedestrian is outside the stairs area a top-level Markov process is used to determine whether to use the stochastic behavioral or the diffusion model; therefore, the model switches between motion that is more goal oriented or stochastic. The destination point for the diffusion model is kept until the destination is reached or until the top-level Markov process determines that the stochastic behavioral movement model is again used. When applying the diffusion model the path is computed in two steps: the direction is chosen to follow the gradient of the gas diffusion towards the target while the speed of the pedestrian is predicted with the stochastic behavioral movement model. If the pedestrian enters the stairs area then the three dimensional Stochastic Movement Model will be used to predict distance moved in the Z-direction. This distance is passed to the Targeted Movement Model to calculate distances moved in X, and Y and additionally the directions. A realistic pedestrian movement in the stairs is more target driven and that is why we are more biased toward the Targeted Movement Model while being in the stairs area.

The aim of this study was to evaluate the tracheobronchoscopic, cytological and microbiological results of tracheal and bronchial collapse in dogs. In total, 8 dogs were included in the study. Clinically, tracheal palpations of the dogs were reflective of tracheal disease, and all dogs coughed on tracheal palpation. Vital parameters and hematological values of the dogs were within the normal ranges. Radiological views of the respiratory tracts and thorax were largely normal, but distinctive tracheal contours were noted in cases 3 and 6. Tracheobronchoscopy was performed under general anesthesia, and endoscopic findings (mucosal surfaces and color, prominent appearance of vessels, chondral ring abnormalities of the trachea, and the presence of bronchial and tracheal collapse) were scored. Bronchoalveolar lavage (BAL) was performed to collect samples for cytological and microbiological analysis. Five cases had tracheal collapse, and two cases had right bronchial collapse. Concurrent tracheal and right bronchial collapse were diagnosed in one case. Cytological results were not indicative of inflammation or infection, but Escherichia coli was isolated from case 2 (bronchial collapse) and case 3 (tracheal collapse). Antibiotic susceptibility results revealed that the organisms were susceptible to sulfamethoxazole/trimethoprim. Statistically, there were no significant differences between the cases in terms of total endoscopic scores. In conclusion, tracheal and/or bronchial collapse should only be diagnosed by tracheobronchoscopic examination. Cytological and microbiological analyses of the BAL fluid in these cases do not always provide valuable data for clinical practitioners. .

The aims of this study are (i) to identify the bovine subclinical mastitis cases of dairy cattles in bacteriological and mycological manner, (ii) to determine antibiotic susceptibility patterns of the isolates. For these purposes, 6400 quarters of 1600 cattle from 50 different herds were scanned with California Mastitis Test (CMT) in Bursa and vicinity. 480 milk samples within bovine subclinical mastitis cases investigated by bacteriological and mycological analysis. Gram-positive cocci and Gram-negative bacilli were identified by API-Staphy ® (bioMérieux) and API-20E ® (bioMérieux) commercial identification panels, respectively and the results were evaluated by API-web system. Out of 201 bacteria isolated from samples, 48 (23.88%) and 153 (76.11%) were identified as CNS and other genus of bacteria, respectively. S.xylosus, S.epidermidis from CoNs and Streptococcus spp., E.coli from other bacteria genuses were mostly isolated forms. Beside this, 58 yeast and fungi were also identified within the investigated samples. Kirby-Bauer Antibiotic Susceptibility Test was applied with 14 different antibiotics from 8 different groups to determine the antimicrobial susceptibility patterns of the isolates and the results were evaluated according to the guideline of Eucast 2012. Out of S.hominis, all CoNs isolates showed extremely high resistance to the antibacterials based on findings. As a result, 23 of CoNs and 26 placed in the other genus of bacteria were found to be resistant to two or more antimicrobial agents. It may be concluded that they have multiple antibiotic resistance (MDR) patterns., Bu çalışmada subklinik mastitisli sığır sütlerinin bakteriyolojik ve mikolojik yönden tanımlanması ve elde edilen izolatların antibiyotik duyarlılıklarının belirlenmesi hedeflendi. Bu amaçla Bursa ili ile çevre illerdeki 50 farklı sürüden 1600 adet sığıra ait 6400 meme lobu California Mastitis Testi (CMT) ile tarandı. Subklinik mastitisli olduğu tespit edilen sığırlara ait 480 adet süt örneği bakteriyolojik ve mikolojik yönden incelendi. Gram pozitif koklar API-Staphy ® (bioMérieux) ve Gram negatif basiller ise API- 20E® (bioMérieux) ticari identifikasyon panelleri ile identifiye edildi ve sonuçlar API-web sistemi ile değerlendirildi. Örneklerden izole edilen 201 adet bakterinin 48 adedi (% 23.88) Koagulaz Negatif Staphylococcus spp. (KNS) ve 153 adedi (%76.11) diğer genuslardan bakteriler olarak tanımlandı. S.xylosus ve S.epidemidis en fazla izole edilen KNS ve Streptococcus spp. ve E.coli’de KNS’ler dışında en fazla izole edilen genus olarak tanımlandılar. İncelenen süt örneklerinde ayrıca 58 adet mantar ve maya türü saptandı. Bakteriyel izolatların antimikrobiyallere karşı duyarlılığını saptamak amacıyla sekiz farklı gruptan 14 antibiyotik diski ile Kirby-Bauer Antibiyotik Duyarlılık Testi uygulandı ve sonuçlar Eucast 2012 direktiflerine göre değerlendirildi. S.hominis dışında identifiye edilen KNS’lerin tümünde çeşitli grup antibakteriyellere yüksek oranda direnç geliştiği gözlemlendi. Sonuçta iki veya daha fazla gruptaki antimikrobiyal ajana dirençli olduğu saptanan 23 adet KNS ile 26 adet diğer gruplara ait bakterinin çoklu antibiyotik direncine (MDR) sahip olduğu belirlendi

We present a Simultaneous Localization and Mapping (SLAM) algorithm based on measurements of the ambient magnetic field strength (MagSLAM) that allows quasi-real-time mapping and localization in buildings, where pedestrians with foot-mounted sensors are the subjects to be localized. We assume two components to be present: firstly a source of odometry (human step measurements), and secondly a sensor of the local magnetic field intensity. Our implementation follows the FastSLAM factorization using a particle filter. We augment the hexagonal transition map used in the pre-existing FootSLAM algorithm with local maps of the magnetic field strength, binned in a hierarchical hexagonal structure. We performed extensive experiments in a number of different buildings and present the results for five data sets for which we have ground truth location information. We consider the results obtained using MagSLAM to be strong evidence that scalable and accurate localization is possible without an a priori map.

The use of foot-mounted inertial measurement units (IMUs) has shown promising results in providing accurate human odometry as a component of accurate indoor pedestrian navigation. The specifications of these sensors, such as the sampling frequency have to meet requirements related to human motion.

Received signal strengths have been widely exploited in indoor positioning due to the massive presence of wireless local networks in buildings. Theoretical propagation models such as the path-loss model can be used in order to avoid long training phases as in fingerprinting approaches. The main issue concerning the employiment of the path-loss model is that the values of some parameters, i.e., the transmit power and the decay exponent, depend on many factors, such as the device, building structure and other environmental features. In this paper, we propose a Bayesian positioning algorithm based on the Rao-Blackwellized particle filter, where the parameters of the path-loss model are estimated independently for each AP in addition to localizing the user. Both parameters are described by discrete random variables with uniform priors. We validate ou proposal by means of simulations and two different experiments; finally, some remarks on complexity are also given.

The Extended Kalman Filter (EKF) has been the state of the art in Pedestrian Dead-Reckoning for foot-mounted Inertial Measurements Units. However due to the non-linearity in the propagation of the orientation the EKF is not the optimal Bayesian filter. We propose the usage of the Unscented Kalman Filter (UKF) as the integration algorithm for the inertial measurements. The UKF improves the mean and covariance propagation needed for the Kalman filter. Although the UKF provides a better estimate of the orientation, with Zero velocity UPdaTes (ZUPT) measurements, the yaw and the bias in the gyroscope associated with it becomes unobserved and might generate errors in the positioning. We studied the changes in the magnetic field during the stance phase and their relationship with the turn rates to propose three measurements using the magnetometer signal that will be called Magnetic Angular Rate Updates (MARUs). The first measurement uses the change in the angle of the magnetic field in the horizontal plane to measure the change in the yaw and provides a simple measurement for the UKF implementation. The second measurement relates the change in the magnetic field vector to the turn rate and provides information on the bias of the gyroscope for an UKF. The last measurement uses a first order approximation to generate a linear relationship with the gyroscope bias and therefore it can be used in an EKF. Finally we proposed a metric for the reliability of the stance as a way to use the pre and post stance information but adjusting the covariance of the measurements gradually from swing to stance. These methods were tested on real and simulated signals and they have shown improvements over the original PDR algorithms.

Global navigation satellite systems (GNSSs) can deliver very good position estimates under optimum conditions. However, especially in urban and indoor scenarios with severe multipath propagation and blocking of satellites by buildings the accuracy loss can be very large. Often, a position with GNSS is impossible in these scenarios. On the other hand, cellular wireless communication systems such as the third generation partnership project (3GPP) long-term evolution (LTE) provide excellent coverage in urban and most indoor environments. Thus, this paper researches timing based positioning algorithms, in this case time difference of arrival (TDoA), using 3GPP-LTE measurements. Several approaches and algorithms exist to solve the navigation equation for cellular systems, for instance Bayes filtering methods such as Kalman or particle filter. This paper specifically considers and develops a particle filter for 3GPP-LTE TDoA positioning. To obtain better positioning results, a 3GPP-LTE TDoA error model is derived. This error model is afterwards included in the likelihood function of the particle filter. The last part of this paper, evaluates the positioning performances of the developed particle filter in an indoor scenario. These evaluations show clearly the possibility of using 3GPP-LTE measurements for indoor positioning.

By incorporating known floor-plans in sequential Bayesian positioning estimators such as Particle Filters (PF), long term positioning accuracy can be achieved as long as the map is sufficiently accurate and the environment sufficiently constraints pedestrians' motion. Instead of using binary decisions to eliminate particles when crossing a wall as several authors do, a maps-based angular probability density function (PDF) is used in this paper that is capable of weighting the possible headings of the pedestrian according to local infrastructure. We will show that the angular PDF will help to obtain better performance in critical multi-modal navigation scenarios.

Foot-mounted indoor positioning systems work remarkably well when using additionally the knowledge of floor-plans in the localization algorithm. Walls and other structures naturally restrict the motion of pedestrians. No pedestrian can walk through walls or jump from one floor to another when considering a building with different floor-levels. By incorporating known floor-plans in sequential Bayesian estimation processes such as particle filters (PFs), long-term error stability can be achieved as long as the map is sufficiently accurate and the environment sufficiently constraints pedestrians' motion. In this article, a new motion model based on maps and floor-plans is introduced that is capable of weighting the possible headings of the pedestrian as a function of the local environment. The motion model is derived from a diffusion algorithm that makes use of the principle of a source effusing gas and is used in the weighting step of a PF implementation. The diffusion algorithm is capable of including floor-plans as well as maps with areas of different degrees of accessibility. The motion model more effectively represents the probability density function of possible headings that are restricted by maps and floor-plans than a simple binary weighting of particles (i.e., eliminating those that crossed walls and keeping the rest). We will show that the motion model will help for obtaining better performance in critical navigation scenarios where two or more modes may be competing for some of the time (multi-modal scenarios).

In this paper we present a reference data set that we are making publicly available to the indoor navigation community [8]. This reference data is intended for the analysis and verification of algorithms based on foot mounted inertial sensors. Furthermore, we describe our data collection methodology that is applicable to the analysis of a broad range of indoor navigation approaches. We employ a high precision optical reference system that is traditionally being used in the film industry for human motion capturing and in applications such as analysis of human motion in sports and medical rehabilitation. The data set provides measurements from a six degrees of freedom foot mounted inertial MEMS sensor array, as well as synchronous high resolution data from the optical tracking system providing ground truth for location and orientation. We show the use of this reference data set by comparing the performance of algorithms for an essential part of pedestrian dead reckoning systems for positioning, namely identification of the rest phase during the human gait cycle.

Indoor and urban canyons are application areas that are becoming increasingly important for navigation application. However, achieving the required accuracy and availability is still a challenge. Multisensor navigation is one of the techniques that has shown promising results in addressing the challenges of such areas. Being able to incorporate raw low-level sensor data is advantageous as it allows to incorporate all available information and more accurate estimation models. In this paper a Particle Filter based multisensor positioning system is extended to use pseudorange measurements of a GPS sensor instead of a calculated position solution. Using pseudoranges, any number of visible satellites can improve positioning accuracy, when combined with measurements from other sensors like an electronic compass, a barometric altimeter or a foot mounted inertial measurement unit (IMU). Additionally, statistical error models for pseudoranges are integrated and tested. Our results show that by using the models within the Bayesian framework yields promising results in terms of error mitigation.

In this paper we present an extension to odometry based SLAM for pedestrians that incorporates human-reported measurements of recognizable features, or “places” in an environment. The method which we have called “PlaceSLAM” builds on the Simultaneous Localization and Mapping (SLAM) principle in that a spatial representation of such places can be built up during the localization process. We see an important application to be in mapping of new areas by volunteering pedestrians themselves, in particular to improve the accuracy of “FootSLAM” which is based on human step estimation (odometry). We present a description of various flavors of PlaceSLAM and derive a Bayesian formulation and particle filtering implementation for the most general variant. In particular we distinguish between two important cases which depend on whether the pedestrian is required to report a place's identifier or not. Our results based on experimental data show that our approach can significantly improve the accuracy and stability of FootSLAM and this with very little additional complexity. After mapping has been performed, users of such improved FootSLAM maps need not report places themselves.

Supporting the humanitarian community in crisis situations worldwide is becoming increasingly important as the frequency end extent of crises are growing. The effectiveness of humanitarian aid and rescue missions is dependent on timely and reliable information. After a disaster has happened time is critical. Intervention within the first 48 hours is crucial to save lives. At the same time it is often difficult to understand how best to send in rescue teams, since in most sudden onset natural disaster the overall situation is complex. In major disasters the requirement for coordination does not cease after the first 48 hours. Instead, many large scale international humanitarian support missions just start after this period. In all cases, information on the location of the event, the amount of damage/casualties and the transport infrastructure still available are critical to send in help. The operational support of humanitarian relief efforts during crisis situations with rapid mapping and communications and navigation is becoming more and more important. Communication between relief forces in the field is essential for coordination as is dissemination of aggregated situation information into the field. Recent work has demonstrated the use of web mapping and satellite based communication services as useful tools. This is reflected in initiatives and projects like the International Charter ‘Space and Major Disasters’ or the GSE RESPOND. Nevertheless, there is still a need for an improvement of the products provided so far and an extension of services. Today most relief organizations employ one or more of the existing satellite communication networks, mostly for voice communications between local and central headquarters. Receivers for GPS (and Galileo in future) are widespread and provide personal navigation in an often unfamiliar environment. Earth observation satellites provide overhead imagery to show type of damage and precise damage location, mostly used in headquarters for assistance with strategic decisions. However, the potential of combining the individual systems to an integrated infrastructure is only utilized to a minimal extent. However, if done optimally it can provide many benefits such as a more accurate damage assessment and the selecting the transport infrastructure that should be used by the rescue teams. A major field for improvements is the extension of the information flow to and from the individual members of a relief team. Our work addresses the existing lack of rapidly deployable infrastructures in order to support the efforts of the relief teams in disaster management. We have been working on such rapidly deployable infrastructures within recent and ongoing projects. Our work builds on both existing and innovative solutions and services to assist the post disaster stages of the crisis life cycle. In this paper we are presenting a disaster management tool “DMT” that is being developed in the framework of the LIMES project and has the following objectives: • Advance the coordination and data sharing of crisis relevant information within the European and international context to minimize time losses between data acquisition and information extraction • Development and integration of dedicated telecommunication tools in crisis management for robust bi-directional exchange of information between headquarters and field teams, including transfer of vector/raster information for situation assessment as well as robust communications and information exchange between teams in the field • A system that is fully accepted by professional disaster management teams for its usability and usefulness. Accordingly, end users have been closely involved starting from the initial concept and are consulted for feedback during the entire implementation. Analysis of rescue operations and interviews with rescue workers were done to derive a comprehensive list of mandatory requirements that have to be met by our system, in order to become operational. As an example of striving to meet such requirements, the system is designed for “zero-configuration” upon setting up when arriving at an incident. In this paper, background information about the need of DMT, purpose and functionality, system design and implementation aspects (software and hardware) will be explained in details. Additionally, details on the communications and navigation tools, the smart rapid mapping concept and the different hardware flavors will be illustrated. Field experiences and user feedback from our demonstrations of the DMT in the Assessment Mission Course (AMC) in Cyprus in 2008 and 2009 will be shown. Finally, an outlook of the future work towards extending the system’s capabilities will be given.

Self-protection is of rescue teams has absolute priority over all other objectives. Nevertheless rescue workers, such as fire fighters often face conditions that impose a combination of threats on them: severe physical and mental stress, limited or no visibility, unknown layout of buildings may induce disorientation, which, in combination with excessive heat, toxic gases, fumes or other substances, can turn a rescue operation into a tragedy. Obviously, a system capable of continuously locating all members of a rescue team could help a rescue worker to maintain orientation, and in cases of accidents, help other team members or operations controllers to localize colleagues in danger. Several research projects, primarily in the fields of wearable computing and indoor navigation, have taken the described application as their reference case. However, few operational systems have been fielded or have undergone sustained usage. In this paper we will show, that a successful operational system for continuous navigation of rescue teams can hardly be based on one sensor alone, but requires a combination of several sensors, motion models, computing, communication means, and human machine interfaces. Based on an analysis of rescue operations and interviews with rescue workers we will derive and present a comprehensive list of mandatory requirements that have to be met by any system that aims to become operational. We will use this list to pinpoint the shortcomings of systems that are "single sensor" (GNSS, UWB, INS), neglect initialization, lack reliable communication means for difficult channels or fail to adequately present the information to rescuers or controllers. We will then outline a reference architecture for an operational system for continuous navigation of rescue teams and discuss its implementation and feasibility aspects. We will show in how far the required technological components are available and affordable and where shortcomings have to be resolved by future research and development. We hope that our findings can contribute to guideline the future research in fields, such as motion modeling, sensor fusion or location visualization, towards advances that, eventually, will lead to operational systems that will improve the safety, efficiency and effectiveness of rescue workers.

In this paper we discuss the use of Particle Filtering to estimate the values of several state variables describing a user’s context. Since Particle Filtering algorithms are computationally efficient realizations of Bayesian Filters they perform exceptionally well to optimally combine the a priori knowledge stemming from behavioral models, such as movement models, and the noisy measurements from sensors. The estimate at each time step is obtained in the form of a probability density function that represents the entire information and quantifies the inherent uncertainty about the context. The concept has been realized in simulations and experiments. In this paper, the applied movement model is presented with simulated measurements from GPS and compass sensors to illustrate the concept.

Bu çalışmada subklinik mastitisli sığır sütlerinin bakteriyolojik ve mikolojik yönden tanımlanması ve elde edilen izolatların antibiyotik duyarlılıklarının belirlenmesi hedeflendi. Bu amaçla Bursa ili ile çevre illerdeki 50 farklı sürüden 1600 adet sığıra ait 6400 meme lobu California Mastitis Testi (CMT) ile tarandı. Subklinik mastitisli olduğu tespit edilen sığırlara ait 480 adet süt örneği bakteriyolojik ve mikolojik yönden incelendi. Gram pozitif koklar API-Staphy ® (bioMérieux) ve Gram negatif basiller ise API- 20E® (bioMérieux) ticari identifikasyon panelleri ile identifiye edildi ve sonuçlar API-web sistemi ile değerlendirildi. Örneklerden izole edilen 201 adet bakterinin 48 adedi (% 23.88) Koagulaz Negatif Staphylococcus spp. (KNS) ve 153 adedi (%76.11) diğer genuslardan bakteriler olarak tanımlandı. S.xylosus ve S.epidemidis en fazla izole edilen KNS ve Streptococcus spp. ve E.coli’de KNS’ler dışında en fazla izole edilen genus olarak tanımlandılar. İncelenen süt örneklerinde ayrıca 58 adet mantar ve maya türü saptandı. Bakteriyel izolatların antimikrobiyallere karşı duyarlılığını saptamak amacıyla sekiz farklı gruptan 14 antibiyotik diski ile Kirby-Bauer Antibiyotik Duyarlılık Testi uygulandı ve sonuçlar Eucast 2012 direktiflerine göre değerlendirildi. S.hominis dışında identifiye edilen KNS’lerin tümünde çeşitli grup antibakteriyellere yüksek oranda direnç geliştiği gözlemlendi. Sonuçta iki veya daha fazla gruptaki antimikrobiyal ajana dirençli olduğu saptanan 23 adet KNS ile 26 adet diğer gruplara ait bakterinin çoklu antibiyotik direncine (MDR) sahip olduğu belirlendi. The aims of this study are (i) to identify the bovine subclinical mastitis cases of dairy cattles in bacteriological and mycological manner, (ii) to determine antibiotic susceptibility patterns of the isolates. For these purposes, 6400 quarters of 1600 cattle from 50 different herds were scanned with California Mastitis Test (CMT) in Bursa and vicinity. 480 milk samples within bovine subclinical mastitis cases investigated by bacteriological and mycological analysis. Gram-positive cocci and Gram-negative bacilli were identified by API-Staphy ® (bioMérieux) and API-20E ® (bioMérieux) commercial identification panels, respectively and the results were evaluated by API-web system. Out of 201 bacteria isolated from samples, 48 (23.88%) and 153 (76.11%) were identified as CNS and other genus of bacteria, respectively. S.xylosus, S.epidermidis from CoNs and Streptococcus spp., E.coli from other bacteria genuses were mostly isolated forms. Beside this, 58 yeast and fungi were also identified within the investigated samples. Kirby-Bauer Antibiotic Susceptibility Test was applied with 14 different antibiotics from 8 different groups to determine the antimicrobial susceptibility patterns of the isolates and the results were evaluated according to the guideline of Eucast 2012. Out of S.hominis, all CoNs isolates showed extremely high resistance to the antibacterials based on findings. As a result, 23 of CoNs and 26 placed in the