1,488 research outputs found

    Mapping DSP algorithms to a reconfigurable architecture Adaptive Wireless Networking (AWGN)

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    This report will discuss the Adaptive Wireless Networking project. The vision of the Adaptive Wireless Networking project will be given. The strategy of the project will be the implementation of multiple communication systems in dynamically reconfigurable heterogeneous hardware. An overview of a wireless LAN communication system, namely HiperLAN/2, and a Bluetooth communication system will be given. Possible implementations of these systems in a dynamically reconfigurable architecture are discussed. Suggestions for future activities in the Adaptive Wireless Networking project are also given

    An Investigation into the Performance Evaluation of Connected Vehicle Applications: From Real-World Experiment to Parallel Simulation Paradigm

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    A novel system was developed that provides drivers lane merge advisories, using vehicle trajectories obtained through Dedicated Short Range Communication (DSRC). It was successfully tested on a freeway using three vehicles, then targeted for further testing, via simulation. The failure of contemporary simulators to effectively model large, complex urban transportation networks then motivated further research into distributed and parallel traffic simulation. An architecture for a closed-loop, parallel simulator was devised, using a new algorithm that accounts for boundary nodes, traffic signals, intersections, road lengths, traffic density, and counts of lanes; it partitions a sample, Tennessee road network more efficiently than tools like METIS, which increase interprocess communications (IPC) overhead by partitioning more transportation corridors. The simulator uses logarithmic accumulation to synchronize parallel simulations, further reducing IPC. Analyses suggest this eliminates up to one-third of IPC overhead incurred by a linear accumulation model

    Body Motion Capture Using Multiple Inertial Sensors

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    Near-fall detection is important for medical research since it can help doctors diagnose fall-related diseases and also help alert both doctors and patients of possible falls. However, in peopleโ€™s daily life, there are lots of similarities between near-falls and other Activities of Daily Living (ADLs), which makes near-falls particularly difficult to detect. In order to find the subtle difference between ADLs and near-fall and accurately identify the latter, the movement of whole human body needs to be captured and displayed by a computer generated avatar. In this thesis, a wireless inertial motion capture system consisting of a central control host and ten sensor nodes is used to capture human body movements. Each of the ten sensor nodes in the system has a tri-axis accelerometer and a tri-axis gyroscope. They are attached to separate locations of a human body to record both angular and acceleration data with which body movements can be captured by applying Euler angle based algorithms, specifically, single rotation order algorithm and the optimal rotation order algorithm. According to the experiment results of capturing ten ADLs, both the single rotation order algorithm and the optimal rotation order algorithm can track normal human body movements without significantly distortion and the latter shows higher accuracy and lower data shifting. Compared to previous inertial systems with magnetometers, this system reduces hardware complexity and software computation while ensures a reasonable accuracy in capturing human body movements

    Designing Flexible, Energy Efficient and Secure Wireless Solutions for the Internet of Things

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    The Internet of Things (IoT) is an emerging concept where ubiquitous physical objects (things) consisting of sensor, transceiver, processing hardware and software are interconnected via the Internet. The information collected by individual IoT nodes is shared among other often heterogeneous devices and over the Internet. This dissertation presents flexible, energy efficient and secure wireless solutions in the IoT application domain. System design and architecture designs are discussed envisioning a near-future world where wireless communication among heterogeneous IoT devices are seamlessly enabled. Firstly, an energy-autonomous wireless communication system for ultra-small, ultra-low power IoT platforms is presented. To achieve orders of magnitude energy efficiency improvement, a comprehensive system-level framework that jointly optimizes various system parameters is developed. A new synchronization protocol and modulation schemes are specified for energy-scarce ultra-small IoT nodes. The dynamic link adaptation is proposed to guarantee the ultra-small node to always operate in the most energy efficiency mode, given an operating scenario. The outcome is a truly energy-optimized wireless communication system to enable various new applications such as implanted smart-dust devices. Secondly, a configurable Software Defined Radio (SDR) baseband processor is designed and shown to be an efficient platform on which to execute several IoT wireless standards. It is a custom SIMD execution model coupled with a scalar unit and several architectural optimizations: streaming registers, variable bitwidth, dedicated ALUs, and an optimized reduction network. Voltage scaling and clock gating are employed to further reduce the power, with a more than a 100% time margin reserved for reliable operation in the near-threshold region. Two upper bound systems are evaluated. A comprehensive power/area estimation indicates that the overhead of realizing SDR flexibility is insignificant. The benefit of baseband SDR is quantified and evaluated. To further augment the benefits of a flexible baseband solution and to address the security issue of IoT connectivity, a light-weight Galois Field (GF) processor is proposed. This processor enables both energy-efficient block coding and symmetric/asymmetric cryptography kernel processing for a wide range of GF sizes (2^m, m = 2, 3, ..., 233) and arbitrary irreducible polynomials. Program directed connections among primitive GF arithmetic units enable dynamically configured parallelism to efficiently perform either four-way SIMD GF operations, including multiplicative inverse, or a long bit-width GF product in a single cycle. This demonstrates the feasibility of a unified architecture to enable error correction coding flexibility and secure wireless communication in the low power IoT domain.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137164/1/yajchen_1.pd

    MEMS ์„ผ์„œ๋ฅผ ํ™œ์šฉํ•œ ๋ฉ€ํ‹ฐ๋กœํ„ฐํ˜• ๋ฌด์ธํ•ญ๊ณต๊ธฐ์˜ ์ €๋น„์šฉ ๋น„ํ–‰์ œ์–ด์‹œ์Šคํ…œ์˜ ์„ค๊ณ„์— ๊ด€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ณต๊ณผ๋Œ€ํ•™ ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€,2019. 8. ์—ฌ์žฌ์ต.ํ”ํžˆ ๋“œ๋ก (Drone)์ด๋ผ๊ณ  ๋ถˆ๋ฆฌ๋Š” ๋ฉ€ํ‹ฐ๋กœํ„ฐํ˜• ๋ฌด์ธํ•ญ๊ณต๊ธฐ๋Š” ์ €๋ ดํ•˜๊ณ  ์กฐ์ข…ํ•˜๊ธฐ ์‰ฌ์šฐ๋ฉฐ ๊ฐ„๋‹จํ•œ ๊ตฌ์กฐ์™€ ์ˆ˜์ง ์ด์ฐฉ๋ฅ™์ด ๊ฐ€๋Šฅํ•˜์—ฌ ๊ตฐ์‚ฌ์ ์ธ ์šฉ๋„๋ฅผ ๋น„๋กฏํ•˜์—ฌ ์ƒ์—…์ ์ธ ์šฉ๋„๋กœ ๋„๋ฆฌ ์“ฐ์ด๊ณ  ์žˆ๋‹ค. ๋ฉ€ํ‹ฐ๋กœํ„ฐํ˜• ๋ฌด์ธํ•ญ๊ณต๊ธฐ๋Š” ๊ฐ€์†๋„ ์„ผ์„œ, ์ž์ด๋กœ์Šค์ฝ”ํ”„ ์„ผ์„œ๋ฅผ ํฌํ•จํ•˜๋Š” ๊ด€์„ฑ ์ธก์ • ์œ ๋‹›(IMU)์„ ์ด์šฉํ•˜์—ฌ ์ง€ํ‘œ๋ฉด์— ๋Œ€ํ•œ ์ž์„ธ๋ฅผ ์ธก์ •ํ•˜์—ฌ ๊ฐ ๋ชจํ„ฐ์˜ ํšŒ์ „์†๋„๋ฅผ ์ œ์–ดํ•˜๋Š” ๋ฐฉ์‹์œผ๋กœ ๋น„ํ–‰ํ•˜๋ฉฐ, ๋น„ํ–‰ ๋ฐฉํ–ฅ์„ ์ถ”์ •ํ•  ์ˆ˜ ์žˆ๋Š” ์ง€์ž๊ธฐ ์„ผ์„œ์™€ ๊ณ ๋„๋ฅผ ์ธก์ •ํ•  ์ˆ˜ ์žˆ๋Š” ๊ธฐ์••๊ณ„๋ฅผ ๋‚ด์žฅํ•œ๋‹ค. ๋น„ํ–‰์ฒด์— ํƒ‘์žฌ๋˜๋Š” ๋น„ํ–‰์ œ์–ด์œ ๋‹›(Flight Control Unit, FCU)์€ ์ด๋Ÿฌํ•œ ์„ผ์„œ ๋ฐ์ดํ„ฐ์™€ ์กฐ์ข… ๋ช…๋ น์„ ์ด์šฉํ•˜์—ฌ ๊ฐ ๋ชจํ„ฐ๋ฅผ ์ œ์–ดํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ๊ณ„์‚ฐ์„ ์ˆ˜ํ–‰ํ•˜๊ธฐ ์œ„ํ•ด์„œ ๊ธฐ์กด์˜ ๋น„ํ–‰ ์ œ์–ด ์‹œ์Šคํ…œ์€ ํ•˜๋‚˜ ์ด์ƒ์˜ 32-bit ๋งˆ์ดํฌ๋กœํ”„๋กœ์„ธ์„œ๋ฅผ ์‚ฌ์šฉํ•˜๋ฉฐ ์ด์— ๋”ฐ๋ผ ๋น„ํ–‰์ œ์–ด๋ฅผ ์œ„ํ•œ ํŽŒ์›จ์–ด๋ฅผ ๊ฐœ๋ฐœํ•˜๋Š”๋ฐ ์žˆ์–ด ํšŒ๋กœ ๋ฐ ํŒจํ„ด ์„ค๊ณ„ ๋ฐ ์†Œํ”„ํŠธ์›จ์–ด ๊ฐœ๋ฐœ ํ™˜๊ฒฝ(SDK)์„ ๊ตฌ์„ฑํ•˜๋Š”๋ฐ ์žˆ์–ด ๋งŽ์€ ์‹œ๊ฐ„๊ณผ ์ธ๋ ฅ, ๋น„์šฉ์„ ํ•„์š”๋กœ ํ•˜์—ฌ ์ „์ฒด ์‹œ์Šคํ…œ์˜ ๊ฐ€๊ฒฉ์ด ์ €๋ ดํ•˜์ง€ ์•Š๋‹ค. ๋˜ํ•œ ์ž‘์€ ํฌ๊ธฐ์˜ ๋ฉ€ํ‹ฐ๋กœํ„ฐ์— ์‚ฌ์šฉ๋˜๋Š” ์ €๋ ดํ•œ ๋น„ํ–‰์ œ์–ด์œ ๋‹›์€ ํ”„๋กœ๊ทธ๋ž˜๋ฐ์ด ๋ถˆ๊ฐ€๋Šฅํ•˜๊ฑฐ๋‚˜ ํ™•์žฅ์„ฑ์— ์ œ์•ฝ์ด ์žˆ์–ด ํ•˜๋‚˜์˜ ์ œ์–ด ์‹œ์Šคํ…œ์œผ๋กœ ํ•˜๋‚˜์˜ ๋น„ํ–‰์ฒด ๋ชจ๋ธ์—๋งŒ ์ ์šฉํ•˜๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋น ๋ฅด๊ณ  ๊ฐ„ํŽธํ•˜๊ฒŒ ํ”„๋กœ๊ทธ๋ž˜๋ฐ์ด ๊ฐ€๋Šฅํ•˜๋ฉฐ ์ €๋ ดํ•˜๊ณ  ๊ตฌํ•˜๊ธฐ ์‰ฌ์šด 8-bit AVR ํ”„๋กœ์„ธ์„œ์™€ MEMS ์„ผ์„œ, C/C++์–ธ์–ด๋ฅผ ์ด์šฉํ•˜์—ฌ ๋น„ํ–‰์ œ์–ด์‹œ์Šคํ…œ์„ ๊ตฌ์„ฑํ•˜์˜€์œผ๋ฉฐ ๊ทธ ๊ฒฐ๊ณผ ํ™•์žฅ์„ฑ์„ ๊ฐ–์ถ”๋ฉด์„œ ๊ฐ€๊ฒฉ์ด ์ €๋ ดํ•˜๋ฉด์„œ ํšจ์œจ์ ์ธ ๋น„ํ–‰ ์ œ์–ด ์‹œ์Šคํ…œ์„ ๊ตฌ์„ฑํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋ถ€์กฑํ•œ 8-bit ํ”„๋กœ์„ธ์„œ์˜ ์„ฑ๋Šฅ์€ ํ”„๋กœ์„ธ์„œ์˜ ์ˆ˜๋Ÿ‰์„ ๋Š˜๋ฆฌ๋Š” ๋ณ‘๋ ฌ ์ปดํ“จํŒ… ๋ฐฉ๋ฒ•์œผ๋กœ ํ•ด๊ฒฐํ•  ์ˆ˜ ์žˆ์—ˆ์œผ๋ฉฐ ์ƒ๋ณดํ•„ํ„ฐ์˜ ๊ฐ„๊ฒฐํ•œ ๊ตฌ์กฐ๋กœ ์ธํ•ด 8-bit ํ”„๋กœ์„ธ์„œ์˜ ๋‚ฎ์€ ์ปดํ“จํŒ… ์„ฑ๋Šฅ์œผ๋กœ๋„ ์ดˆ๋‹น ์•ฝ 250Hz์˜ ์ œ์–ด ์ฃผ๊ธฐ๋ฅผ ๊ฐ€์งˆ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ž์„ธ ์ œ์–ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์œผ๋กœ Cascade controller๋ฅผ ์„ ํƒํ•˜์—ฌ ์™ธ๋ž€์— ๊ฐ•ํ•˜๋ฉฐ ๋น ๋ฅธ ์ œ์–ด ์†๋„๋ฅผ ์–ป์„ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ฒฐ๊ณผ์ ์œผ๋กœ ์ง„๋™์ด ์ƒ๋Œ€์ ์œผ๋กœ ํฐ ํŒœ ์‚ฌ์ด์ฆˆ์˜ ์ฟผ๋“œ๋กœํ„ฐ UAV์—์„œ๋„ ์•ˆ์ •์ ์ธ ๋น„ํ–‰ ์„ฑ๋Šฅ์„ ๊ตฌํ˜„ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค.1. Introduction ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 1 1. 1. About Research ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 4 1. 2. Basic Theory ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 6 1. 2. 1. Attitude Estimation ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 8 1. 2. 2. Cascade PID Controller ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 14 1. 3. Research Goal ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 17 2. Hardware Design ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 18 2. 1. PCB Design ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 20 2. 1. 1. Design of Flight Controller ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 20 2. 1. 2. Design of PMU for BLDC System ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 29 2. 2. Body Frame Design ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 33 2. 2. 1. DC Motor Powered Quadcopter ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 34 2. 2. 2. BLDC Motor Powered Hexacopter ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 36 3. Software Design ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 38 3. 1. Flight Software Design ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 38 3. 1. 1. Attitude Reference System ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 39 3. 1. 2. Cascade PID Controller ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 44 3. 1. 3. Bluetooth-based Control System ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 46 3. 2. IMU & Attitude Reference System ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 51 3. 2. Attitude Control Performance ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 51 4. Conclusion ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 53 ์ฐธ๊ณ ๋ฌธํ—Œ ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 55 Abstract ยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยทยท 57Maste

    Securing Wireless Communications of the Internet of Things from the Physical Layer, An Overview

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    The security of the Internet of Things (IoT) is receiving considerable interest as the low power constraints and complexity features of many IoT devices are limiting the use of conventional cryptographic techniques. This article provides an overview of recent research efforts on alternative approaches for securing IoT wireless communications at the physical layer, specifically the key topics of key generation and physical layer encryption. These schemes can be implemented and are lightweight, and thus offer practical solutions for providing effective IoT wireless security. Future research to make IoT-based physical layer security more robust and pervasive is also covered

    Efficient distribution of a computation intensive calculation on an Android device to external compute units with an Android API

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    Is transferring computation intensive calculations to external compute-units the next trend? This masterโ€™s thesis researches if it is worth the effort to transfer a matrix multiplication from an Android phone to a System-on-Chip (SoC), using Bluetooth or WebSocket as communication protocols. The SoC solution used in this work is an Intel Altera Cyclone V based board from TerASIC, equipped with a Field Programmable Gate Array (FPGA) including a Dualcore ARM A9 processor. Because the matrix size has a strong correlation to the number of calculations in a matrix multiplication, the calculation time on a CPU and FPGA will differ when the matrices grow in size. Comparing the multiplication times on Android and SoC, matrices with a matrix size above 1660x1660 are calculated faster on the SoC. The matrix multiplication is accelerated using an OpenCL kernel on the FPGA, guided by a host program on the processor programmed in C++. Experiments have shown that Bluetooth has a 500 times lower transfer rate than WebSocket, resulting in choosing only WebSocket for further investigations. Due to the transfer times, the minimum matrix size to win time by extending the multiplication to a SoC is 2338x2338. Although the implemented matrix multiplication does only support square matrices, future research could develop multiple kernels of different algorithms that support a variation in width and height

    Sensing and Signal Processing in Smart Healthcare

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    In the last decade, we have witnessed the rapid development of electronic technologies that are transforming our daily lives. Such technologies are often integrated with various sensors that facilitate the collection of human motion and physiological data and are equipped with wireless communication modules such as Bluetooth, radio frequency identification, and near-field communication. In smart healthcare applications, designing ergonomic and intuitive humanโ€“computer interfaces is crucial because a system that is not easy to use will create a huge obstacle to adoption and may significantly reduce the efficacy of the solution. Signal and data processing is another important consideration in smart healthcare applications because it must ensure high accuracy with a high level of confidence in order for the applications to be useful for clinicians in making diagnosis and treatment decisions. This Special Issue is a collection of 10 articles selected from a total of 26 contributions. These contributions span the areas of signal processing and smart healthcare systems mostly contributed by authors from Europe, including Italy, Spain, France, Portugal, Romania, Sweden, and Netherlands. Authors from China, Korea, Taiwan, Indonesia, and Ecuador are also included

    4. generรกciรณs mobil rendszerek kutatรกsa = Research on 4-th Generation Mobile Systems

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    A 3G mobil rendszerek szabvรกnyosรญtรกsa a vรฉgรฉhez kรถzeledik, legalรกbbis a meghatรกrozรณ kรฉpessรฉgek tekintetรฉben. Ezรฉrt lรฉtfontossรกgรบ azon technikรกk, eljรกrรกsok vizsgรกlata, melyek a kรถvetkezล‘, 4G rendszerekben meghatรกrozรณ szerepet tรถltenek majd be. Tรถbb ilyen kutatรกsi irรกnyvonal is lรฉtezik, ezek kรถzรผl projektรผnkben a fontosabbakra koncentrรกltunk. A kรถvetkezล‘ben felsoroljuk a kutatott terรผleteket, รฉs rรถviden รถsszegezzรผk az elรฉrt eredmรฉnyeket. Szรณrt spektrumรบ rendszerek Kifejlesztettรผnk egy รบj, rรกdiรณs interfรฉszen alkalmazhatรณ hรญvรกsengedรฉlyezรฉsi eljรกrรกst. Szimulรกciรณs vizsgรกlatokkal tรกmasztottuk alรก a megoldรกs hatรฉkonysรกgรกt. A projektben kutatรณkรฉnt rรฉsztvevล‘ Jeney Gรกbor sikeresen megvรฉdte Ph.D. disszertรกciรณjรกt neurรกlis hรกlรณzatokra รฉpรผlล‘ tรถbbfelhasznรกlรณs detekciรณs technikรกk tรฉmรกban. Az elรฉrt eredmรฉnyek Imre Sรกndor MTA doktori disszertรกciรณjรกba is beรฉpรผltek. IP alkalmazรกsa mobil rendszerekben Tovรกbbfejlesztettรผk, teszteltรผk รฉs รกltalรกnosรญtottuk a projekt keretรฉben megalkotott รบj, gyลฑrลฑ alapรบ topolรณgiรกra รฉpรผlล‘, a jelenleginรฉl nagyobb megbรญzhatรณsรกgรบ IP alapรบ hozzรกfรฉrรฉsi koncepciรณt. A tรฉmakรถrben Szalay Mรกtรฉ Ph.D. disszertรกciรณja mรกr a nyilvรกnos vรฉdรฉsig jutott. Kvantum-informatikai mรณdszerek alkalmazรกsa 3G/4G detekciรณra รšj, kvantum-informatikai elvekre รฉpรผlล‘ tรถbbfelhasznรกlรณs detekciรณs eljรกrรกst dolgoztunk ki. Ehhez รบj kvantum alapรบ algoritmusokat is kifejlesztettรผnk. Az eredmรฉnyeket nemzetkรถzi folyรณiratok mellett egy sajรกt kรถnyvben is publikรกltuk. | The project consists of three main research directions. Spread spectrum systems: we developed a new call admission control method for 3G air interfaces. Project member Gabor Jeney obtained the Ph.D. degree and project leader Sandor Imre submitted his DSc theses from this area. Application of IP in mobile systems: A ring-based reliable IP mobility mobile access concept and corresponding protocols have been developed. Project member Mรกtรฉ Szalay submitted his Ph.D. theses from this field. Quantum computing based solutions in 3G/4G detection: Quantum computing based multiuser detection algorithm was developed. Based on the results on this field a book was published at Wiley entitled: 'Quantum Computing and Communications - an engineering approach'
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