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Vehicle-to-Vehicle Driver Safety-Related data Transmission and Reception Using Li-Fi Technology

Vehicle-to-Vehicle Driver Safety-Related Data Transmission a...

引用

International conference on signal and data processing, ICSDP 2019

作者： Pacharne, Snehal Kulkarni, Vinayak VLSI and Embedded Systems MIT Academy of Engineering Pune Alandi India School of Electrical Engineering MIT Academy of Engineering Pune Alandi India

ISBN: (纸本)9789811583902

Light Fidelity Technology is also known as Visible light communication is the form of wireless communication which uses visible light to transfer information such as digital data, Audio and video as well. Light is modulated and amplified to attain desired speed and distance. Vehicle-to-vehicle communication is the technology in which one vehicle transmits and receives data to and from other vehicle so that they share data between each other and will be able to assist each other. Proposed system uses Li-Fi for vehicle-to-vehicle communication system uses Li-Fi module which can be mounted in the Headlamp as well as tale-lamps of the Four-wheeler which will help to transmit real-time information such as speed data, anti-lock braking data, Turn indication, certain emergencies in car, tire related data. System is made for such small applications which can be directly implemented in car with little modifications in Hardware and Software. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Visible light communication

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Localization of Near-Field Sources in Sonar data Using the Sparse Representation Framework

Localization of Near-Field Sources in Sonar Data Using the S...

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MTS/IEEE OCEANS conference

作者： Zhao, Yinghui Dinstel, Amanda Azimi-Sadjadi, Mahmood R. Wachowski, Neil Chinese Acad Sci Ctr Earth Observat & Digital Earth Beijing 100094 Peoples R China Colorado State Univ Dept Elect & Comp Engn Ft Collins CO 80523 USA

ISBN: (纸本)9780933957398

This paper uses the sparse representation framework to investigate localization of near-field sources (e. g., underwater bottom or buried targets) from the data captured using two uniform linear sensor (hydrophone) subarrays. The connection between the two array steering transformation matrices of the near-field sources corresponding to the two subarrays are first analyzed using the second Taylor expansion. This connection allows the construction of a new equivalent far-field steering matrix for each near-field source, hence converting the near-field source localization problem to a more convenient far-field one. Next, the relationship between the signals observed by the two subarrays and by the new constructed far-field directional matrix is examined, leading to the conclusion that the angle of arrival (AoA) estimation can be cast into finding a solution to a sparse representation problem, where the actual AoA is considered as an entry in a complete dictionary formed by assuming a source is present in every angle. Simulation results are presented to demonstrate the effects of different noise levels and number of sensors on the accuracy of the AoA estimation. Finally, the effectiveness of the developed method is demonstrated on a sonar data set collected in a controlled environment to detect and localize several minelike objects placed proud on the pond floor.

关键词： Near-field source localization angle of arrival estimation sparse representation sonar signal processing

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Fibered fluorescence microscopy (FFM) of intra epidermal nerve fibers-translational marker for peripheral neuropathies in preclinical research: processing and analysis of the data

Fibered fluorescence microscopy (FFM) of intra epidermal ner...

引用

conference on Applications of Digital Image processing XXXI

作者： Cornelissen, Frans De Backer, Steve Lemeire, Jan Torfs, Bert Nuydens, Rony Meert, Theo Schelkens, Peter Scheunders, Paul Janssen Pharmaceut Turnhoutseweg 30 B-2340 Beerse Belgium Univ Antwerp IBBT Visionlab Dept Phys B-2610 Antwerp Belgium Vrije Univ Brussel IBBT ETRO B-1050 Brussels Belgium

ISBN: (纸本)9780819472939

Peripheral neuropathy can be caused by diabetes or AIDS or be a side-effect of chemotherapy. Fibered Fluorescence Microscopy (FFM) is a recently developed imaging modality using a fiber optic probe connected to a laser scanning unit. It allows for in-vivo scanning of small animal subjects by moving the probe along the tissue surface. In preclinical research, FFM enables non-invasive, longitudinal in vivo assessment of intra epidermal nerve fibre density in various models for peripheral neuropathies. By moving the probe, FFM allows visualization of larger surfaces, since, during the movement, images are continuously captured, allowing to acquire an area larger then the field of view of the probe. For analysis purposes, we need to obtain a single static image from the multiple overlapping frames. We introduce a mosaicing procedure for this kind of video sequence. Construction of mosaic images with sub-pixel alignment is indispensable and must be integrated into a global consistent image aligning. An additional motivation for the mosaicing is the use of overlapping redundant information to improve the signal to noise ratio of the acquisition, because the individual frames tend to have both high noise levels and intensity inhomogeneities. For longitudinal analysis, mosaics captured at different times must be aligned as well. For alignment, global correlation-based matching is compared with interest point matching. Use of algorithms working on multiple CPU's (parallel processor/cluster/grid) is imperative for use in a screening model.

关键词： Fibered fluorescence microscopy peripheral neuropathies translational marker epidermal nerve fibers

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Benefits of Ultra-Dense 3D Spatial Sampling for Seismic processing and Interpretation

Benefits of Ultra-Dense 3D Spatial Sampling for Seismic Proc...

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2021 Abu Dhabi International Petroleum Exhibition and conference, ADIP 2021

作者： Mahgoub, Mohamed Cambois, Guillaume Cowell, James Khoori, Suaad ADNOC ADNOC Onshore

ISBN: (纸本)9781613998342

The advances in seismic acquisition systems, especially onshore nodes, have made it possible to acquire ultra-dense 3D surveys at a reasonable cost. This new design enables accurate processing sequences that deliver higher resolution images of the subsurface. These images in turn lead to enhanced structural interpretation and better prediction of rock properties. In 2019, ADNOC and partners acquired an 81 square kilometer ultra-high density pilot survey onshore Abu Dhabi. The receivers were nimble nodes laid out on a 12.5x12.5m grid, which recorded continuously and stored the data on a memory chip. The sources were heavy vibrators sweeping the 2-110 Hz frequency range in 14 seconds on a 12.5x100m grid. 184 million traces per square kilometers did make such small area, the densest 3D seismic survey ever recorded. The single sensor data were expectedly very noisy and the unconstrained simultaneous shooting required elaborate deblending, but we managed these steps with existing tools. The dense 3D receiver grid actually enabled the use of interferometry-based ground-roll attenuation, a technique that is rarely used with conventional data due to inadequate sampling, but that resulted in increased signal-to-noise ratio. The data were migrated directly to depth using a velocity model derived after five iterations of tomographic inversion. The final image gathers were made of 18 reciprocal azimuths with 12.5m offset increment, resulting in 5,000 fold on a 6.25x6.25m grid. The main structural interpretation was achieved during the velocity model building stage. Key horizons were picked after the tomographic iterations and the velocity model was adjusted so that their depth matched the well markers. Anisotropic parameters were adjusted to maintain gather flatness and the new model was fed to the next iteration. This ultimately resulted in flat image gathers and horizons that tied to the wells. The final high-resolution data provided a much crisper image of the target clinofo

关键词： signal to noise ratio

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Design of Automatic Detection System for Onboard data Processor Based on Optical Fiber Interface 6th

Design of Automatic Detection System for Onboard Data Proces...

引用

6th conference on signal and Information processing, Networking and Computers, ICSINC 2019

作者： Qu, Zexu Yuan, Suchun Wang, Junfeng Xi’an710000 China

ISBN: (纸本)9789811541629

As the amount of data on satellite payloads soars, traditional data interfaces are no longer sufficient for engineering applications. The fiber optic interface has the advantages of high speed, small size, and long transmission, and will be used on satellites. Due to the extremely high speed of the fiber interface, a large amount of data is generated in a short time. If you use the first drop and then analyze, you need a large hard disk. This will result in a huge amount of test work and will not meet real-time testing requirements. The fiber detection system studied in this paper can perform real-time automatic detection on the onboard processor, improve the test coverage and test intensity of the onboard equipment, and ensure the reliability and stability of the onboard equipment to the utmost extent. At the same time, the system has the advantages of simple operation, easy expansion, low cost and convenient carrying. Through testing and verification, the system achieves the expected goal. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Optical fibers

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Research on the Key Technology of Network Security Based on Machine Learning

Research on the Key Technology of Network Security Based on ...

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6th International conference on Intelligent Computing and signal processing (ICSP)

作者： Yong He School of Preschool Education Jiangxi Teachers College

ISBN: (纸本)9781665447300

With the continuous development of information technology, the huge number of network devices, applications, and the explosive expansion of network data have made the network environment increasingly complex, posing huge potential risks to network security. The targets of cyber attackers are no longer limited to cyber attacks on ordinary users, but they have shifted their targets to network environments with related backgrounds such as enterprises, governments, and countries. The diversification of network services has generated massive amounts of Internet data, and traditional network security technologies have been difficult to meet the current needs of network security in terms of performance and self-adaptability. Research on network security based on machine learning has achieved many results, showing strong capabilities in processing massive data, automatic learning, detection and identification, and broadening the development of ideas in the field of network security. In this paper, we combine machine learning-related technologies to improve intrusion detection performance and alarm correlation automation, and investigate key technologies such as machine learning-based network security situational awareness methods and dynamic data stream classification methods based on judgment feedback, in order to improve the detection performance, adaptive and generalization capabilities of machine learning-based network security technologies.

关键词： Knowledge engineering Correlation Network intrusion detection Machine learning signal processing Internet Security

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Integrated model of acoustics and language using semantic classification trees

Integrated model of acoustics and language using semantic cl...

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Proceedings of the 1996 IEEE International conference on Acoustics, Speech, and signal processing, ICASSP. Part 1 (of 6)

作者： Noeth, E. De Mori, R. Fischer, J. Gebhard, A. Harbeck, S. Kompe, R. Kuhn, R. Niemann, H. Mast, M. Universitaet Erlangen-Nuernberg Erlangen Germany

We propose Multi-level Semantic Classification Trees to combine different information sources for predicting speech events (e.g. word chains, phrases, etc.). Traditionally in speech recognition systems these information sources (acoustic evidence, language model) are calculated independently and combined via Bayes rule. The proposed approach allows one to combine sources of different types - it is no longer necessary for each source to yield a probability. Moreover the tree can look at several information sources simultaneously. The approach is demonstrated for the prediction of prosodically marked phrase boundaries, combining information about the spoken word chain, word category information, prosodic parameters, and the result of a neural network predicting the boundary on the basis of acoustic-prosodic features. The recognition rates of up to 90% for the two class problem boundary vs. no boundary are already comparable to results achieved with the above mentioned Bayes rule approach that combines the acoustic classifier with a 5-gram categorical language model. This is remarkable, since so far only a small set of questions combining information from different sources have been implemented.

关键词： data structures

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Radar automatic target recognition for alterable noise environment

Radar automatic target recognition for alterable noise envir...

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IET International Radar conference 2009

作者： Hou, Q.Y. Liu, H.W. Chen, F. Bao, Z. National Laboratory of Radar Signal Processing XiDian University Tai Bai South Road 2 XianShaanxi China

ISBN: (纸本)9781849190107

Noise level of radar target returned echoes is an essential issue for HRRP automatic target recognition, which will deteriorate recognition performance if test sample have different noise level compared with the training samples. Assuming that HRRP contains additive Gaussian white noise and HRRP signals of range cells are jointly Gaussian-distributed, this paper selects PPCA-subspace model to describe HRRP. The main contribution is a promising adaptive method to deal with alterable noise environment between training phase and test phase for HRRP statistical recognition. To make the algorithm more practical, an approximate algorithm is presented to accelerate the original one while keeping the sacrifice of recognition precision very small. Simulated recognition experiments based on measured data illustrate our proposed method's effectiveness.

关键词： Automatic target recognition

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Design of On-Orbit Monitoring Method for small Satellite Payload Equipment Based on Grey Prediction 8th

Design of On-Orbit Monitoring Method for Small Satellite Pay...

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8th International conference on signal and Information processing, Network and Computers, ICSINC 2021

作者： Han, Yandong Shi, Jian Yan, Guorui Lv, Da Ma, Lei DFH Satellite Co. Ltd. Beijing100094 China

ISBN: (纸本)9789811933868

The realization of the on-orbit function of small satellites mainly depends on the normal operation of payload equipment. At present, the number of small satellites in orbit is increasing, same as the tasks of the on-orbit management are increasing. At the same time, many factors, such as the large differences between payload equipment, the high proportion of overseas work, and the working environment of short-term power on orbit, are not conducive to the on-orbit health monitoring of payload equipment. In order to find out the potential faults of payload equipment in time, a kind of on-orbit monitoring method based on grey prediction is proposed. The method optimizes the normal monitoring method and makes grey prediction analysis after data processing of the original telemetry information. At the same time, the monitoring criteria are adjusted autonomously according to the analysis results, so as to achieve early warning and reduce the operation process of ground personnel. High precision and high feasibility of the grey prediction model are verified through simulation by selecting the telemetry information of a satellite. This monitoring method can be further extended to the parameter monitoring of other single equipment and the applications of other types of satellite missions. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Forecasting

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A Bayesian approach to extended object tracking and tracking of loosely structured target groups

A Bayesian approach to extended object tracking and tracking...

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International conference on Information Fusion

作者： W. Koch R. Saul FGAN-FKIE Wachtberg Germany

In algorithms for tracking and sensor data fusion the targets to be tracked are usually considered as point source objects; i.e., compared to the sensor resolution their extension is neglected. Due to the increasing resolution capabilities of modern sensors, however, this assumption is often not valid: different scattering centers of an object can cause distinct detections when passing the signal processing chain. Examples of extended targets are found in short-range applications (littoral surveillance, autonomous weapons, or robotics). As an extended target also a collectively moving, loosely structured group can be considered. This point of view is all the more appropriate, the smaller the mutual distances between the individual targets are due to the resulting data association and resolution conflicts any attempt of tracking the individual objects is no longer reasonable. With simulated sensor data produced by a partly resolvable aircraft formation the addressed phenomena are illustrated and a Bayesian solution to the resulting tracking problem is proposed. Ellipsoidal object extensions are modeled by random matrices and treated as additional state variables to be estimated or 'tracked'. We expect that the resulting tracking algorithms are relevant also for tracking large, collectively moving target swarms.

关键词： Target tracking Bayesian methods signal processing algorithms Sensor fusion signal resolution Scattering Object detection signal processing Surveillance Weapons

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