Today, positioning with GPS and the advantages this entails are almost infinitive, which means that the technology can be utilized in a variety of applications. Unfortunately, there exists a lot of limitations in conjunction with the signals from the GPS can’t reach inside e.g. buildings or underground. This means that an alternative solution that works indoors needs to be developed. The report presents the four most common radio-based technologies, Bluetooth,Wi-Fi, UWB and RFID, which can be used to determine a position. These all have different advantages in cost, accuracy and latency, which means that there exist a number of different applications. The radio-based methods use the measurement techniques, RSSI, TOA, TDOA, Cell-ID, PD or AOA to gather data. The choice of measurement technique is mainly dependent of which radio-based method being used, since their accuracy depends on the quality of the measurements and the size of the detection area, which means that all measurement techniques have different advantages and disadvantages. The measurement data is processed with one of the positioning methods, LS, NLS, ML, Cell-ID, WC or FP, to estimate a position. The choice of positioning method also depends on the quality of the measurements in combination with the size of the detection area. To evaluate the different radio-based methods together with measurement techniques and positioning methods, accuracy, latency and cost are being compared. This is used as the basis for the choice of positioning method, since a general solution can get summarized by finding the least expensive approach which can estimate an unknown position with sufficiently high accuracy.

Osteopathic physician (D.O.) residency programs that do not achieve accreditation under the new Single Accreditation System (SAS) standards by June 30, 2020 will lose access to their share of more than $9,000,000,000 of public tax dollars. This U.S. Centers for Medicare & Medicaid Services (CMS) funding helps sponsoring institutions cover direct and indirect resident physician training expenses. A significant financial burden would then be shifted to marginal costs of the residency program’s sponsoring institution in the absence of CMS funding. The sponsoring institution’s ability or willingness to bare these costs occurs during a time when hospital operating margins are at historic lows (Advisory.com /Daily Briefing /May 18, 2017 | The Daily Briefing / Hospital profit margins declined from 2015 to 2016, Moody's finds). Loss of access to CMS funding may result in potentially cataclysmic reductions in the production and availability of primary care physicians for rural and urban underserved populations. Which osteopathic residency programs will be able to survive the new accreditation requirement changes by the 2020 deadline? What are some of the defining attributes of those programs that already have achieved “initial accreditation” under the new SAS requirements? How can the osteopathic programs in the process of seeking the new accreditation more effectively “pivot” by learning from those programs that have succeeded? What are the potential implications of SAS to both access and quality of health care to millions of Americans? This report is based upon a study that examined and measured how osteopathic physician residency programs in the U.S. are accommodating the substantive structural, financial, political and clinical requirements approximately half way through a five-year adaptation period. In 2014, US Graduate Medical Education (GME) physician program accreditation systems formally agreed to operate under a single accreditation system for all osteopathic (D.O) and allopathic (M.D.) programs in the U.S. Since July 1, 2015, the American Osteopathic Association (AOA) accredited training programs have been eligible to apply for Accreditation Council for Graduate Medical Education (ACGME) accreditation. This agreement to create a Single Accreditation System (SAS) was consummated among the AOA, the American Association of Colleges of Osteopathic Medicine (AACOM) and ACGME with a memorandum of understanding. As this research is published, the ACGME is transitioning to be the single accreditor for all US GME programs by June 30, 2020. At that time, the AOA would fully relinquish all its GME program accreditation responsibilities. The new SAS operates under published ACGME guidelines and governance. Business policy and health care resource allocation question motivated this research. Failure of osteopathic programs to “pivot” to the new standards could result in fewer licensed physicians being produced in the high demand primary care field. Potential workforce shortage areas include urban and especially rural populations (CRS Report 7-5700 R44376 Feb 12, 2016). Large physician shortages already have been projected to care for a rapidly aging US population without considering the impact of the GME accreditation changes currently underway (Association of American Medical Colleges 2017 Key Findings report www.aamc.org/2017projections). The goal of this research is to provide osteopathic GME programs practical insights into characteristics of a sample of osteopathic GME programs that have successfully made the “pivot” into SAS requirements and been accredited by ACGME and those that have not. The study seeks to better understand the experiences, decisions, challenges and expectations directly from osteopathic programs directors as they strive to meet the realities of the new SAS requirements. Do programs that are already accredited differ significantly from those that have not? How do characteristics such as program size, geographic locations, clinical program components, program sponsor structure, number and experience of faculty and administration, cost planning and perceived benefits of the movement to SAS factor into successfully meeting the new requirements before the 2020 closing date? A cross-sectional research survey was designed, tested and deployed to a national sample of currently serving osteopathic GME program directors. The survey elicited data about each program’s “pivot” from AOA GME accreditation practices and guidelines to the new Single Accreditation System (SAS). The survey instrument was designed to obtain information about patterns in osteopathic GME program curricula, administrative support functions, faculty training, compliance requirements and program director characteristics shared by those programs that have been granted “initial accreditation” by the Accreditation Council for Graduate Medical Education (ACGME) who administer SAS. Thirty five (35) osteopathic GME program directors responded to the 26 question survey in June 2017. Descriptive statistics were applied and central tendency measures determined. The majority of survey respondents were Doctors of Osteopathic Medicine (D.O.s) from specialty residency programs sponsoring an average of 16 residents. Respondents were mostly non-profit, urban, multi-facility health system locations with an existing affiliation with a research college or university. About half of the programs had completed some form of fiscal due diligence related to the potential cost impact of SAS. None of those surveyed reported utilizing outside consultants to assist in the SAS “pivot” process. Most programs plan to keep the same number of residents while others expressed an interest in expanding or contracting. None of the respondents planned to close their program. The dichotomous dependent variable (DV) was whether or not the Osteopathic GME program had “achieved or not yet achieved initial SAS accreditation” at the time of the survey. A cross tabulation analysis of the DV with potential predictive variables (IV) was conducted and Chi-square and various exact significance tests were applied to gage goodness of fit. Results were grouped into categories that aligned with the five research questions and hypotheses. Several characteristics were shared by those programs that achieved SAS. GME sponsor institutions that currently have dually accredited programs by the AOA and ACGME seemed to be at a distinct advantage. Although they represented a smaller number of total survey respondents (20%), all primary care program participants reported SAS achievement. Directors reported an average of six (6) full-time paid faculty members teaching in their programs and twice that number of preceptor volunteers in the total sample. Realization of any operational cost savings or efficiencies as a result of moving to a single accreditation system was a principle concern for the majority (86%) of GME program director respondents, regardless of current accreditation status, although most felt SAS would result in offering medical student graduates access to all accredited US GME residency and fellowships programs.

Modern indoor positioning systems encounter challenges inherent to indoor environments. Signal changes can stem from various factors like object movement, signal propagation, or obstructed line of sight. This thesis explores a supervised machine learning approach that integrates Bluetooth Low Energy (BLE) and inertial sensor data to achieve consistent angle and distance estimations. The method relies on BLE angle estimations and signal strength alongside additional sensor data from an Inertial Measurement Unit (IMU). Relevant features are extracted and a supervised learning model is trained and then validated on familiar environment tests. The model is then gradually introduced to more unfamiliar test environments, and its performance is evaluated and compared accordingly. This thesis project was conducted at the u-blox office and presents a comprehensive methodology utilizing their existing hardware. Several extensive experiments were conducted, refining both data collection procedures and experimental setups. This iterative approach facilitated the improvement of the supervised learning model, resulting in a proposed model architecture based on transformers and convolutional layers. The provided methodology encompasses the entire process, from data collection to the evaluation of the proposed supervised learning model, enabling direct comparisons with existing angle estimation solutions employed at u-blox. The results of these comparisons demonstrate more accurate outcomes compared to existing solutions when validated in familiar environments. However, performance gradually declines when introduced to a new environment, encountering a wider range of signal conditions than the supervised model had trained on. Distance estimations are then compared with the path loss propagation equation, showing an overall improvement. / Moderna inomhuspositioneringssystem möter utmaningar som förekommer i inomhusmiljöer. Signalförändringar kan bero på olika faktorer som objektets rörelse, signalutbredning eller blockerad siktlinje. Denna kandidat avhandling undersöker ett övervakat maskininlärningssätt som integrerar Bluetooth Low Energy (BLE) och tröghetssensorer för att uppnå konsekventa vinkel- och avståndsberäkningar. Metoden bygger på BLE-vinkelberäkningar och signalstyrka tillsammans med ytterligare sensordata från en Inertial Measurment Unit (IMU). Relevanta funktioner extraheras och en övervakad inlärningsmodell tränas och valideras sedan på tester i bekanta miljöer. Modellen introduceras sedan gradvis till mer obekanta testmiljöer, och dess prestanda utvärderas och jämförs därefter. Detta examensarbete genomfördes på u-blox kontor och presenterar en omfattande metodik som utnyttjar deras befintliga hårdvara. Flera omfattande experiment genomfördes, vilket förfinade både datainsamlingsprocedurer och experimentuppsättningar. Detta iterativa tillvägagångssätt underlättade förbättringen av den övervakade inlärningsmodellen, vilket resulterade i en föreslagen modellarkitektur baserad på transformatorer och konvolutionella lager. Den tillhandahållna metodiken omfattar hela processen, från datainsamling till utvärdering av den föreslagna övervakade inlärningsmodellen, vilket möjliggör direkta jämförelser med befintliga vinkelberäkningslösningar som används på u-blox. Resultaten av dessa jämförelser visar mer exakta resultat jämfört med befintliga lösningar när de valideras i bekanta miljöer. Dock minskar prestandan gradvis när den introduceras till en ny miljö, där den möter ett bredare spektrum av signalförhållanden än vad inlärningsmodellen har tränats på. Avståndsberäkningar jämförs sedan med en matematisk formel, kallat path loss propagation ekvationen, som ger distans som en funktion av uppmätt signalstyrka.

A wide range of services and applications become possible when accurate position information for a radio terminal is available. These include: location-based services; navigation; safety and security applications. The commercial, industrial and military value of radio-location is such that considerable research effort has been directed towards developing related technologies, using satellite, cellular or local area network infrastructures or stand-alone equipment. This work studies and investigates two location techniques. The first one presents an implementation scheme for a wideband transmission and direction finding system using OFDM multi-carrier communications systems. This approach takes advantage of delay discrimination to improve angle-of-arrival estimation in a multipath channel with high levels of additive white Gaussian noise. A new methodology is interpreted over the multi carrier modulation scheme in which the simulation results of the estimated channel improves the performance of OFDM signal by mitigating the effect of frequency offset synchronization to give error-free data at the receiver, good angle of arrival accuracy and improved SNR performance. The full system simulation to explore optimum values such as channel estimation and AoA including the antenna array model and prove the operational performance of the OFDM system as implemented in MATLAB. The second technique proposes a low cost-effective method of tracking and monitoring objects (examples: patient, device, medicine, document) by employing passive radio frequency identification (RFID) systems. A multi-tag, (totalling fifty-six tags) with known ID values are attached to the whole patient’s body to achieve better tracking and monitoring precision and higher accuracy. Several tests with different positions and movements are implemented on six patients. The aim is to be able to track the patient if he/she is walking or sitting; therefore, the tests considered six possible movements for the patient including walking, standing, sitting, resting, laying on the floor and laying on the bed, these placements are important to monitor the status of the patient like if he collapsed and fall on the ground so that the help will be quick. The collected data from the RFID Reader in terms of Time Stamp, RSS, Tag ID, and a number of channels are processed using the MATLAB code.

In passive target localization, source position is estimated by only using the source signal. In this thesis, position of a stationary target is estimated by using the data collected by a moving platform. Since the focus of the thesis is the location estimation, the parameters used for localization such as angle-of-arrival (AOA), time-difference-of-arrival (TDOA), Doppler frequency shift are assumed to be known. Different emitter localization methods are implemented in this thesis. Some of these methods are known in the literature and some are the modified or hybrid versions of these algorithms. Orthogonal Vector Estimator (OVE), Pseudolinear Estimator (PLE), Weighted Instrumental Variables Estimator (WIVE) and Maximum Likelihood Estimator (MLE) use only the AOA information. In MLE, Gauss Newton (GN) search algorithm is used to realize the search process effectively. AOA localization methods are also implemented together with the extended Kalman filter (EKF) realization. Doppler Shifted Frequency (DSF) based Least Squares (LS) and MLE are implemented which use Doppler frequency shift only. AOA-DSF combined hybrid algorithm is shown to perform better. LS and Maximum Likelihood (ML) TDOA localization methods are also implemented. AOA-DSF-TDOA combined hybrid algorithm is shown to perform better than the algorithms which use one type of parameter and AOA-DSF hybrid algorithm. Estimator performances are analyzed in this thesis. Error ellipsoid is a useful tool to evaluate an estimator

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Yes / The issue of asset tracking in dense environments where the performance of the global positioning system (GPS) becomes unavailable or unreliable is addressed. The proposed solution uses a low-profile array of antenna elements (sensors) mounted on a finite conducting ground. A compact-size sensor array of six electrically small dual-band omnidirectional spiral antenna elements was designed as a front end of a tracker to operate in the 402 and 837 MHz spectrum bands. For the lower band, a three-element superposition method is applied to support estimation of the angle of arrival (AOA), whereas all six sensors are employed for the higher band. A low complexity and accurate AOA determination algorithm is proposed, the projection vector (PV), and this is combined with the array mentioned. Orthogonal frequency division multiplexing (OFDM) is integrated with the PV technique to increase the estimation resolution. The system was found to be suitable for installation on the roof of vehicles to localize the position of assets. The proposed system was tested for the tracking of nonstationary sources, and then two scenarios were investigated using propagation modeling software: outdoor to outdoor and outdoor to indoor. The results confirm that the proposed tracking system works efficiently with a single snapshot. / European Union Horizon 2020 Research and Innovation Program; 10.13039/501100009928 - Higher Committee for Education Development (HCED), Iraq

ITC/USA 2006 Conference Proceedings / The Forty-Second Annual International Telemetering Conference and Technical Exhibition / October 23-26, 2006 / Town and Country Resort & Convention Center, San Diego, California / Telemetry data are usually collected for analysis at some later time and can be monitored to follow the progress of a test. In the case of an Air Data System the signals from the sensors are sent to a computer that calculates the air data parameters for use on multiple LabView-generated displays, as well as to the Data Acquisition System. The readouts on the multiple displays need to be real-time so they are useful to the flight crew. Equations that control the different air data values are determined by what telemetry data are available and the preference of those doing the test planning. These systems need to display the information in a format useful to the flight crew and be reliable.

Axial offset anomaly (AOA) in pressurized water reactors (PWR) refers to deviation of the measured neutron flux in the top half of the core from the predicted values. Among other difficulties, AOA reduces the shutdown margin, and may force the plant to reduce power output. AOA is believed to be caused by three related phenomena occurring in the core while operating at full power: sub-cooled nucleate boiling concentrated mainly in the upper half of the core, corrosion product deposition on the cladding surface (crud), and the deposition of boron within the porous crud layer in regions of vigorous sub-cooled boiling. This study replicates the conditions within the PWR primary coolant; specifically, the temperature, pressure, peak surface heat flux, coolant velocity and water chemistry are simulated in order to produce prototypical crud on an electrically heated Zircaloy-4 test element. At the conclusion of each test run, the heated Zircaloy-4 test element is rapidly isolated from the coolant in order to trap any soluble boron species that may be present in the crud layer. The results of this investigation indicate that prototypical crud with significant boron deposition can be produced. The deposited boron compound has been determined to be lithium tetraborate (Li2B4O7). Comparative experiments have been run to determine the effect of coolant pH, concentration and type of additives, and duration of exposure on the thickness of the crud deposit. The data obtained in this investigation can be used to validate mechanistic models for crud deposition and AOA in pressurized water reactors.

Passive source localization is the estimation of the positions of the sources or emitters given the sensor data. In this thesis, some of the well known methods for passive source localization are investigated and compared in a stationary emitter sensor framework. These algorithms are discussed in detail in two and three dimensions for both single and multiple target cases. Passive source localization methods can be divided into two groups as two-step algorithms and single-step algorithms. Angle-of-Arrival (AOA) based Maximum Likelihood (ML) and Least Squares (LS) source localization algorithms, Time- Difference-of-Arrival (TDOA) based ML and LS methods, AOA-TDOA based hybrid ML methods are presented as conventional two step techniques. Direct Position Determination (DPD) method is a well known technique within the single step approaches. In thesis, a number of variants of DPD technique with better computational complexity (the proposed methods do not need eigen-decomposition in the grid search) are presented. These are the Direct Localization (DL) with Multiple Signal Classification (MUSIC), DL with Deterministic ML (DML) and DL with Stochastic ML (SML) methods. The evaluation of these algorithms is done by considering the Cramer Rao Lower Bound (CRLB). Some of the CRLB expressions given in two dimensions in the literature are presented for threedimensions. Extensive simulations are done and the effects of different parameters on the performances of the methods are investigated. It is shown that the performance of the single step algorithms is good even at low SNR. DL with MUSIC algorithm performs as good as the DPD while it has significant savings in computational complexity. AOA, TDOA and hybrid algorithms are compared in different scenarios. It is shown that the improvement achieved by single-step techniques may be acceptable when the system cost and complexity are ignored. The localization algorithms are compared for the multiple target case as well. The effect of sensor deployments on the location performance is investigated.