1,570 research outputs found
Improving performance, privacy and relevance of location-based services for mobile users
No full textLocation-based services are becoming increasingly popular due to the ubiquity of smartphones and the emergence of vehicular computing applications. Mobile clients have traditionally been consumers of location-based services, but various social applications have recently demonstrated that mobile clients can also be producers of location-based data. Our thesis is that the quality of the location-based services critically depends on the performance of the service, the privacy assurances offered to the clients, and the quality of the data provided by the service. In this dissertation, we propose three contributions addressing key aspects of these challenges: network performance, location privacy for the mobile clients, and relevance of data provided by the service. With respect to the wireless network performance for location-based services, we present Context-Aware Rate Selection (CARS), a rate adaptation algorithm that makes use of knowledge of speed and distance between communicating nodes to choose the optimum transmission rate. Our experimental evaluation in real outdoor vehicular environments shows that CARS adapts to changing link conditions at high vehicular speeds significantly faster than existing rate-adaptation algorithms. With respect to the client location privacy, we present SybilQuery, a fully decentralized and autonomous k-anonymity-based scheme that generates synthetic queries that resemble a real client query. Our experiments on real mobility traces of approximately 500 cabs in the San Francisco Bay area show that SybilQuery can efficiently generate synthetic queries and that these queries are indistinguishable from real queries. Finally, with respect to improving the relevance of location-based data, we present SocialTelescope, a novel location-based service that leverages user interactions in mobile social networks to infer people's preference for places. Our results evaluating the coverage and relevance of our system in comparison to current state-of-the-art approaches show that our approach returns results that are at least as relevant as those returned by current approaches, at a substantially lower cost. The main conclusion of this dissertation is that location-based services can become truly ubiquitous services by providing mobile clients with good network performance, privacy guarantees, as well as relevant results.Ph. D.Includes bibliographical referencesby Pravin Shanka
Supplement_Figure_1 - Patient-Reported Outcomes (PROs) in Acute Symptomatic Seizure (ASyS) Versus Patients With Established Epilepsy
No full textSupplement_Figure_1 for Patient-Reported Outcomes (PROs) in Acute Symptomatic Seizure (ASyS) Versus Patients With Established Epilepsy by Christopher R. Newey, Nicolas R. Thompson, Pravin George, Vineet Punia, Stephen Hantus, Brittany Lapin, Joao Gomes and Irene Katzan in The Neurohospitalist</p
Supplemental_Table - Patient-Reported Outcomes (PROs) in Acute Symptomatic Seizure (ASyS) Versus Patients With Established Epilepsy
No full textSupplemental_Table for Patient-Reported Outcomes (PROs) in Acute Symptomatic Seizure (ASyS) Versus Patients With Established Epilepsy by Christopher R. Newey, Nicolas R. Thompson, Pravin George, Vineet Punia, Stephen Hantus, Brittany Lapin, Joao Gomes and Irene Katzan in The Neurohospitalist</p
Data-Driven Approach for Modeling the Mixed Traffic Conditions Using Supervised Machine Learning
No full textThe article describes modeling vehicular movements using supervised machine learning algorithms with trajectory data from heterogeneous non-lane-based traffic conditions. The trajectory data on the mid-block road section of around 540 m is used in the study. Supervised machine learning algorithms are employed to model the vehicular positions. A set of parameters were identified for modeling the longitudinal and lateral positions. With the set of parameters, the algorithm’s potentiality for mimicking vehicular positions is evaluated. It was identified that supervised machine learning algorithms would model the vehicles’ positions with accuracy in the range of 20–60 mean absolute percentage error. The k-NN algorithm was marginally edging past all algorithms and acted as a promising candidate for modeling vehicular positions.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and Plannin
Welfare effects of preferential trade agreements under optimal tariffs
Get PDFIn a three country model with endogenous tariffs, this paper evaluates and contrasts the welfare effects of free trade agreements (FTAs) and customs unions (CUs) — the two most commonly occurring preferential trade agreements (PTAs). We show that if the external tariff of a PTA is not too high, it benefits both members and non-members. We also highlight the implications of a key (but commonly ignored) distinction between the two types of PTAs: while an FTA member can form an another (independent) FTA with an existing non-member, a CU member cannot. Under a pair of independent bilateral FTAs, the common member’s welfare is higher than that under free trade. Furthermore, if the common member is relatively efficient compared to the other two countries, such a ‘hub and spoke’ pattern of FTAs can yield higher global welfare than free trade. By contrast, such an outcome is never possible under a CU.Free Trade Agreements, Customs Unions, External Tariffs, Welfare, Intraindustry Trade, Oligopoly
Supplemental Material, sj-pdf-1-jic-10.1177_08850666211021561 - Mortality Trends of Oncology and Hematopoietic Stem Cell Transplant Patients Supported on Extracorporeal Membrane Oxygenation: A Systematic Review and Meta-Analysis
No full textSupplemental Material, sj-pdf-1-jic-10.1177_08850666211021561 for Mortality Trends of Oncology and Hematopoietic Stem Cell Transplant Patients Supported on Extracorporeal Membrane Oxygenation: A Systematic Review and Meta-Analysis by R. R. Pravin, Benjamin Xiongzheng Huang, Rehena Sultana, Chuen Wen Tan, Ken Junyang Goh, Mei-Yoke Chan, Heng Joo Ng, Ghee Chee Phua, Jan Hau Lee and Judith Ju-Ming Wong in Journal of Intensive Care Medicine</p
Multiwalled carbon nanotube - Strength to polymer composite
Get PDFCarbon nanotubes (CNTs), a rather fascinating material, are among the pillars of nanotechnology. CNTs exhibit unique electrical, mechanical, adsorption, and thermal properties with high aspect ratio, exceptional stiffness, excellent strength, and low density, which can be exploited in the manufacturing of revolutionary smart nano composite materials. The demand for lighter and stronger polymer composite material in various applications is increasing every day. Among all the possibilities to research and exploit the exceptional properties of CNTs in polymer composites we focused on the reinforcement of epoxy resin with different types of multiwalled carbon nano tubes (MWCNTs). We studied mechanical properties such as stress, strain, ultimate tensile strength, yield point, modulus and fracture toughness, and Young's modulus by plotting and calculating by means of the off-set method. The mechanical strength of epoxy composite is increased intensely with 1 and 3 wt.% of filler
6G internet of things networks for remote location surgery also a review on resource optimization strategies, challenges, and future directions
Get PDFRemote location surgery presents stringent requirements for wireless communication, particularly in terms of reliability, speed, and low latency. The emergence of sixth-generation (6G) wireless networks is expected to address these challenges effectively. With the rapid expansion of internet of things (IoT) applications in healthcare, maintaining real-time connectivity has become essential. Ensuring such performance in 6G-enabled IoT networks relies heavily on the implementation of advanced resource optimization techniques. Recent studies have focused on improving key performance metrics, including latency, reliability, energy efficiency, spectral efficiency, data rate, and bandwidth usage. Comprehensive reviews of these techniques reveal a growing emphasis on multi-objective optimization strategies to balance conflicting requirements. Research has also highlighted limitations in existing approaches, suggesting the need for further innovation, particularly for mission-critical applications like remote surgery. Within this context, 6G IoT systems have demonstrated the potential to maintain high data rates and stable throughput, both of which are essential for safe and responsive surgical operations conducted over long distances. These findings underscore the importance of continued development in resource management to fully enable remote healthcare delivery through advanced wireless technologies
DAYEM BRIDGE BASED NANOSQUID FOR HIGH SENSITIVE NANOSCALE APPLICATIONS
No full textDayem Bridge Based Nano-SQUID for High Sensitive Nanoscale Applications
A recent progress in nanotechnology formulates the fabrication of SQUIDs loop less than 100 nm; its obtaining an adequate sensitivity to detect the magnetic nano-objects. These nano-SQUIDs can be employed to measure small clusters of atomic magnetic moment, to obtain an inductive readout sensor in single-photon detectors and they have been proposed as a magnetic qubit for quantum computing.
The research activities at CNR-ICIB has been devoted to the design, fabrication and characterization of nano-SQUIDs based on niobium Dayem Bridge and its magnetization measurements of nanoparticles for advance study of nanomagnetism. Here, I have reported the designs, the fabrication processes and the experimental performances (voltage flux characteristics, spin noise performance) of these nano-devices and also the groundwork measurement of nanoparticles magnetization using switching current measurement method operating in CNR-ICIB laboratory.
Design and Fabrication: Many devices are fabrication using advanced electron beam lithography techniques with conventional photolithography, lift off and reactive ion etching techniques. The fabricated devices can be divided into two categories, first bilayer device or non hysteretic device and second single layer device or hysteretic device.
a)Non-Hysteretic Device: The bilayer device consists of a niobium loop with a hole of 200nm interrupted by two bridges having length and width dimensions of 100nm X 80nm, 80nm X 60nm etc. The superconducting loop has a washer shape in order to enhance the heat dissipation during the working operations when the sensor is current biased in resistive mode. The device includes a micrometric integrated niobium coil located very close to the nano-sensor in order to modulate, tune and operate the SQUID in FLL mode.
b)Hysteretic Device: The single layer devices having two Dayem Bridges of 90nm x 250nm and loop sizes of 2, 1 and 0.75μm, consist of a single niobium layer 20nm thick pattern by electron beam lithography and shaped by lift-off. The SQUIDs were designed to have a hysteretic current-voltage characteristic in order to work as a magnetic flux-current transducer.
Performances:
a)Non-Hysteretic Device: An intrinsic voltage swing and a maximum responsivity of 75 μV and 1.5 mV/Φ0 can be estimated from the experimental data. Our interest is focused on the characterization in small signal mode, because the magnetic flux coupled into device is expected to be much smaller than Ф0. In fact, such devices are designed to measure very small magnetic fields arising from a local nano-object. The sensor exhibits a magnetic flux noise level of 1.5μΦ0/Hz1/2 in the white region corresponding to a spin noise, in unit of Bohr magneton, of Sn1/2=2aSΦ1/2/(μBμ0)~60 spin/Hz1/2 where a is the radius of the SQUID loop, μ0 is the magnetic vacuum permeability and μB = 9.27 × 10−24 J/T. This value is comparable with the best value reported in the literature. It is worth noting that these sensors show a wide linear region in the V- Φ characteristics; the non-linearity effects are not evident up to 0.02 Φ0.
b)Hysteretic Device: The second single layer device shows hysteretic I-V characteristics which are used as magnetic flux-current transducer. The magnetic pattern determines the responsivity of the SQUID, defined as the variation of the critical current as function of the external magnetic flux variation dIc/dΦ; in the present work responsivity up to 30μA/Φ0 have been obtained. The maximum magnetic flux coupled to the 2 and 1 micron loop size is about 2 and 0.5 Φ0 respectively. A critical current modulation is about 20%. An intrinsic sensor magnetic flux resolution less than 1 mΦ0, can be estimated from the intrinsic current fluctuation. The main interest of such devices is magnetization measurement of small magnetic particles by switching current techniques.
Simulation Results: We have computed performance of nano-superconducting-quantum-interference devices (SQUIDs) in view of their employment in the detection of small spin populations. The analysis has been focused on nano-SQUID sensors having a square loop with a side length of 200 nm. We have calculated the spin sensitivity and the magnetic response relative to the single Bohr magneton (single spin), as a function of its position within the SQUID hole. The results predict that the SQUID response depends strongly on the spin position. The projected information’s are very useful to optimize the sensor performance in view of the most nanomagnetism applications.
Preliminary Measurements of Nanoparticle Magnetization: We have effectively employed non-hysteretic sensor for nanoparticle magnetization investigation in view of nano-magnetism applications. We have performed preliminary measurements with and without iron oxide nanoparticles on the SQUID loop showing that the presence of magnetic nanoparticles can be easily detected and the magnetic relaxation curve measured. To test the capability of our devices in order to detect the magnetization of nanoparticles, we deposited iron oxide nanoparticles, having an average diameter of about 16nm, on chips containing characterized sensors. Here we report the measurement performed on the device with 1μm loop. The presence of iron nanoparticles did not change appreciably the magnetic pattern obtained using the integrated coil (magnetic field normal to the SQUID plane), however the nanoparticle presence was evident by the critical current measurement performed with magnetic field generated using the external solenoid (magnetic field parallel to the SQUID plane). Using the measured responsivity for this particular device (27μA/Φ0) the critical current variation was converted to magnetic flux variation.
It is worth to note that with the present electronic at 100Hz to acquire 104 measurements it takes about 100s. The above results clearly indicating that the sensor can be effectively used in nano-magnetism applications
Author Correction: The isocyanide SN2 reaction
Get PDFIn this article the author name Katarzyna Kurpiewska was incorrectly written as Katarzyna Kurpiewsk. The original article has been corrected.</p
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