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Imbalanced Data Classification using Optimized Support Vector Machine for IoMT Application

Imbalanced Data Classification using Optimized Support Vecto...

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Ambient Intelligence in Health Care (ICAIHC), International conference on

作者： Binod Kumar Pattanayak Mihir Narayan Mohanty Smitarani Satpathy Jay Bijay Arjun Das Dept. of CSE ITER Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Advanced Signal Processing Lab ITER Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India

In this digital age, most of the applications need to be Internet of Things based for easy access. Biomedical research has made significant growth related to it. The visual pathological information provides comparatively better information as compared to signals that help physicians with further analysis and suggestions. Medical data often exhibit class imbalance, where the number of samples in different classes is not proportional. This imbalance can pose significant challenges to traditional classification algorithms. This report explores the application of Support Vector Machines (SVM) to imbalanced medical data classification, discussing the inherent issues, techniques for addressing class imbalance, and experimental results showcasing the effectiveness of SVM in handling imbalanced medical datasets. As a result, the retrieval process over the internet will be faster. In this paper, authors have considered three different cancerous image data of breast cancer, brain tumor, and liver cancer for analysis and detection using a machine learning approach. The data is collected from the UCI machine learning repository. The statistical features like class, radius, and area are considered and optimized using the Brain Storm Optimization algorithm for good accuracy. The optimized features are applied to the support vector machine classifier. Further, use for different kernels such as radial basis function (RBF), linear, polynomial, and sigmoid are used with SVM and verified for comparison. It is found that the RBF kernel provides SVM better accuracy as compared to other kernels.

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High Performance Front Camera ADAS Applications on TI's TDA3X Platform

High Performance Front Camera ADAS Applications on TI's TDA3...

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International conference on High Performance Computing

作者： Mihir Mody Pramod Swami Kedar Chitnis Shyam Jagannathan Kumar Desappan Anshu Jain Deepak Poddar Zoran Nikolic Prashanth Viswanath Manu Mathew Soyeb Nagori Hrushikesh Garud Automotive Processor Business Texas Instruments Inc. India

ISBN: (纸本)9781467384872

advanced driver assistance systems (ADAS) are designed to increase driver's situational awareness and road safety by providing essential information, warning and automatic intervention to reduce the possibility/severity of an accident. Of the various types of ADAS modalities available, camera based ADAS are being widely adopted for their usefulness in varied applications, overall reliability and adaptability to new requirements. But camera based ADAS also represents a complex, high-performance, and low-power compute problem, requiring specialized solutions. This paper introduces a high performance front camera ADAS based on a small area, low power System-on-Chip (SoC) solution from Texas Instruments called Texas Instruments Driver Assist 3x (TDA3x). The paper illustrates compute capabilities of the device in implementation of a typical front camera ADAS. The paper also introduces key programming concepts related to heterogeneous programmable compute cores in the SoC and the software framework to use those cores in order to develop the front camera solutions. These aspects will be of interest not only to the ADAS developers but for computer vision and compute intensive embedded system development.

关键词： Cameras Digital signal processing Software Hardware Software algorithms Vehicles Safety

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Automated Validation of Capillary Refill Time Measurements Using Photo-Plethysmogram from a Portable Device for Effective Triage in Children

Automated Validation of Capillary Refill Time Measurements U...

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IEEE Global Humanitarian Technology conference (GHTC)

作者： Walter Karlen Amelia Pickard Jeremy Daniels Arthur Kwizera Charles Ibingira Guy Dumont J. Mark Ansermino Electrical and Computer Engineering in Medicine group (ECEM) University of British Columbia Vancouver Canada Department of Anesthesiology Pharmacology and Therapeutics University of British Columbia Vancouver Canada Makerere University College of Health Sciences (MUCHS) Makerere University Kampala Uganda The University of British Columbia Faculty of Medicine Vancouver BC CA

Capillary refill time (CRT) is an important tool for the clinical assessment of trauma and dehydration. Indeed, it has been incorporated into advanced life support guidelines as part of the rapid assessment of critically ill patients. However, digitalized CRT techniques are not readily available and the standard assessment based on the visual inspection of CRT lacks standardization and is prone to a high inter-observer variability. We present an algorithm for the automatic validation of the CRT measurement on the finger using photo-plethysmogram recordings on a small portable device. It is based on a set of deterministic rules for the classification of finger pressure and regular plethysmographic pulses. Validation studies using the classification of 93 pediatric recordings from Canada and Uganda showed that the novel algorithm reliably detects invalid CRT measurements (sensitivity 98.4%). This includes patterns such as insufficient pressure, low perfusion signals, and artifacts. Since our device consists of widely available components already in use, the promising results suggest that the algorithm could be readily integrated in operating rooms and intensive care units around the world. This more robust assessment of CRT would produce a more powerful diagnostic tool for clinical triage in critical care settings.

关键词： signal processing algorithms Pressure measurement Pediatrics Sensitivity Educational institutions Time measurement Reliability

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Fast intra coding based on mode decision in high efficiency video coding

Fast intra coding based on mode decision in high efficiency ...

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2014 International conference on Artificial Intelligence and Industrial Application (AIIA2014)

作者： Q.Li G.S.Tian C.Q.Gao Chongqing Key Laboratory of Signal and Information Processing(CQKLS&IP) Chongqing University of Posts and Telecommunications (CQUPT)

ISBN: (纸本)9781784660529

The latest high efficiency video coding(HEVC) standard has a significantly improved compression performance relative to H.264/AVC, only requiring a 50% bit-rate at the equal perceptual video quality, but with a significant encoder complexity increase. Hence it is necessary and inevitable to develop fast HEVC encoding algorithms for potential market adoption. In this paper, we propose a fast intra mode decision(FMD) for a HEVC encoder, which aims at reducing computation time and keeping the coding performance at the same time. Firstly, we use edge information of the current prediction unit(PU) instead of only the modes of the neighbor PUs to choose a reduced set of directions from the 35 prediction mode directions. Next, we use an early termination rate-distortion optimized(RDO) to further reduce complexity. Different picture resolutions, ranging from 416×240 to 2560×1600 are tested and experimental results show that the proposed algorithm can reduce 32.64% encoding time with only a 1.45% increase in BD rate.

关键词： fast encoding algorithm HEVC intra prediction edge information

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Dynamic bandwidth scaling for embedded DSPs with 3D-stacked DRAM and wide I/Os 13

Dynamic bandwidth scaling for embedded DSPs with 3D-stacked ...

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IEEE International conference on Computer-Aided Design

作者： Daniel W. Chang Young Hoon Son Jung Ho Ahn Hoyoung Kim Minwook Ahn Michael J. Schulte Nam Sung Kim Department of Electrical and Computer Engineering University of Wisconsin – Madison Madison WI USA Department of Computer Science and Engineering Seoul National University Seoul South Korea Samsung Advanced Institute of Technology Samsung Electronics Company Yongin Kyunggi South Korea

ISBN: (纸本)9781479910694

3D main memory is an emerging technology that stacks DRAM dies underneath the processor die using through-silicon vias (TSVs). Prior studies assumed that such technology would decrease main memory access latency by 45% to 60%, while also allowing designers to increase main memory bandwidth. Although the latter is true, it was recently shown that the latency savings of 3D main memory is only 6.3%. In this paper, we first analyze memory latency reduction opportunities in a 3D main memory system with Wide I/O by taking better advantage of 3D integration technology and quantify their benefit. Specifically, redesigning the DRAM to memory controller synchronizers and placing the address, command, and data pads closer to the DRAM banks can decrease 3D main memory latency by 24.7%. We show that current 3D DRAM with Wide I/O can increase the geometric mean performance of an embedded processor that is similar to a Texas instrument C67x DSP by 9.7% (and up to 23.3%). Second, we observe that 3D DRAM with Wide IO can increase average system energy consumption of energy-constrained embedded DSPs by 2.6% (and up to 8.9%). To improve I/O energy efficiency, we propose to dynamically scale memory bandwidth (i.e. the I/O width) at runtime based on an application's program phases. Our dynamic bandwidth scaling algorithms increase average performance by 6.6% while increasing average energy consumption by only 0.5%.

关键词： Three-dimensional displays Bandwidth Random access memory Benchmark testing Memory management Heuristic algorithms Digital signal processing

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A Correlate-Based GPS Multipath Time Delay Estimation algorithm

A Correlate-Based GPS Multipath Time Delay Estimation algori...

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第五届中国卫星导航学术年会

作者： Jian Li Wenyi Wang Dan Lu Lu Wang Renbiao Wu Tianjin Key Lab for Advanced Signal Processing Civil Aviation University of China Tianjin China

ISBN: (纸本)9783642547362

Multipath effect of signals is one of the main causes of the global positioning system positioning error. Although the differential technology can improve the positioning accuracy of navigation system. However, due to the reference station and the user's geographical location is different;Differential GPS (DGPS) system still does not eliminate multipath effects of the satellite signal. The conventional narrow correlator method can reduce positioning error. But it assumes that the bandwidth of channel is unlimited. It can not be met in practice. That is its limitations. In this paper, we consider the characteristics of GPS signal model and the multipath effect In GPS system. We introduce a least-squares iterative multipath super-resolution (LIMS) delay estimation algorithm and propose a multipath signal delay estimation algorithm based on correlation model on this basis. The algorithm takes the correlation output of received signal correlates and the local C /A code as the model, estimates the direct signal and the multipath signal delay accurately in the condition of signal delay is unknown. As can be seen from the simulation results, the multipath interference suppression algorithm we propose outperforms the traditional narrow correlator method and LIMS algorithms.

关键词： Global Positioning System · Multipath effect·Time delay estimate

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A Faster Without Scarifying Accuracy Online Decomposition Approach For Higher-Order Tensors

A Faster Without Scarifying Accuracy Online Decomposition Ap...

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第九届网络分布式计算与知识发现国际会议( 2017 International conference on Cyber-enabled distributed computing and knowledge discovery)

作者： Hongtianchen Xie Lunke Qing Yiwei Xu Yonggen Gu Duc Minh Quan Do Department of computer science HangZhou DianZi UniversityZhe-Jiang China School of Information Engineering Huzhou UniversityZheJiang China A/DRsch Advanced Analytics Institute University of Technology SydneySydneyAustralia

Tensors could be very suitable for representing multidimensional *** recent years,CANDE-COMP/PARAFAC(CP)decomposition which is one of the most popular methods for Multidimensional Data Analysis has been widely studied and extensively ***,today's datasets will often change dynamically,and the amount of data is showing a trend of exponential *** is a very necessary and difficult task to perform a CP decomposition on a dynamically changing tensor with very large scale *** traditional and classic methods,such as Alternating Least Squares(ALS)algorithm,cannot be directly used to the dynamical tensor due to their huge consumption of time and *** addition,the existing online CP methods can only partially solve this problem and can only be applied to thir-dorder *** on the online CP method,we proposed a simplified online CP decomposition algorithm that can be a good solution to these *** not only has the similar decomposition accuracy rate with ALS algorithm but also the decomposition speed faster than the ALS algorithm hundreds of thousands of *** with other state-of-the-art online CP methods,it has better decomposition quality and decomposition *** experimental results of four methods show that,our approach reduces computational time significantly without scarifying *** approach has a similar accuracy rate,and the speed has increased by tens times than online CP *** in some datasets,the speed and accuracy of our approach are both better than the other approach.

关键词： Tensile stress Matrix decomposition Algorithm design and analysis signal processing algorithms Motion pictures Heuristic algorithms Feature extraction

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Modified Range-Doppler Imaging Method for the High Squint SAR

Modified Range-Doppler Imaging Method for the High Squint SA...

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IEEE Radar conference

作者： Shuyan Wang Zhigang Su Renbiao Wu Tianjin Key Lab for Advanced Signal Processing Civil Aviation University of China Tianjin Key Lab for Advanced Signal Processing Civil Aviation Universityof China

ISBN: (纸本)9781424458110

In this paper, a modified Range-Doppler (RD) algorithm with the Keystone Transform and the rank-deficient Capon is proposed for the shorter Synthetic Aperture Radar (SAR) imaging in the high squint mode. With the decrease of the aperture time under the squint mode, the linear range-walk becomes the dominant part of the range migration. The Keystone Transform is well suitable for removal of the range walk. In order to achieve higher resolution in the azimuth domain with the shorter SAR, the rank-deficient Capon which is an efficient non-diagonal loading spectral estimation based on rank-deficient sample covariance matrix is adopted. Simulation results can obtain the finer SAR images of the proposed approaches.

关键词： Synthetic aperture radar Radar scattering Azimuth signal processing algorithms Radar polarimetry Covariance matrix Brain modeling Geometry Radar imaging signal resolution

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EEG signal processing for Action Recognition Using Machine Learning Paradigms

EEG Signal Processing for Action Recognition Using Machine L...

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Information Technology (OCIT), OITS International conference on

作者： Abirami S P Misha Chandar B Karthikeyan G Elakkiya E Department of Computer Science and Engineering Coimbatore Institute of Technology Coimbatore Tamil Nadu School of Computer Science and Engineering VIT-AP University Andhra Pradesh India Department of Computer Science and Engineering SRM UniversityAP Andhra Pradesh India

ISBN: (数字)9798331510404

ISBN: (纸本)9798331510411

Many intriguing applications, such as the ability to move prosthetic limbs and enable more fluid man-machine contact, may be made possible by automatic interpretation of brain readings. The problem of precisely categorizing EEG signals linked with memory categories is tackled first in the inquiry. With the restricted availability of pre-trained models for such signal classification, a Convolution-based Neural Network (CNN) is constructed from scratch. By using EEG recordings from UC Berkeley's Bio-Sense Lab, this study seeks to improve memory recall using machine learning and precise feature selection. Fifteen participants' EEG data are converted into the frequency domain, and the amplitudes are used as key characteristics. The selection of these qualities is improved by a self-attention mechanism, which maximizes the distinction among various memory categories. The primary focus is to evaluate the performance of the most advanced algorithms, with the secondary objective of outperforming previous methods in terms of classification accuracy. A fine-tuned subset of the frequency-based characteristics is evaluated using a Support Vector Machine (SVM) classifier. By showcasing the efficiency of self-attention in honing feature subsets, this study highlights the significance of feature engineering in EEG-based memory classification. This method is positioned as a promising advancement in the analysis of EEG data since it improves the separation between memory categories through the application of frequency-domain modifications and SVM classifiers. Furthermore, investigating time series features shows how well they may capture intricate patterns, pointing to fresh avenues for future neuro-informatics and cognitive study.

关键词： Support vector machines Accuracy Time series analysis Pattern classification Brain modeling Electroencephalography Data models Real-time systems Recording Load modeling

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Performance of Mobile Networks with UAVs: Can Flying Base Stations Substitute Ultra-Dense Small Cells?

Performance of Mobile Networks with UAVs: Can Flying Base St...

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European Wireless 2017;23th European Wireless conference

作者： Zdenek Becvar Michal Vondra Pavel Mach Jan Plachy David Gesbert Dpt. of Telecommunication Engineering FEE Czech Technical University in Prague Communication Systems Department EURECOM

ISBN: (纸本)9781509038442

A crucial challenge for future mobile networks is to enable wide range of scenarios and use cases for different devices spanning from simple sensors to advanced machines or users devices. Such requirements call for highly flexible and scalable radio access network (RAN). To provide high flexibility and scalability in dynamic scenarios, flying base stations (FlyBSs), i.e., base stations mounted on general unmanned aerial vehicles, can be integrated into RAN. In this paper, implementation and operational issues related to the FlyBSs are discussed. Additionally scenarios where the FlyBS can be profitable are outlined. Furthermore, we define the architecture of a flying RAN (FlyRAN) encompassing the FlyBSs and enabling real-time control of whole RAN so that it can dynamically adapt to users' movement and changes in their communication activity. Our results show the superior efficiency of FlyBSs comparing to an ultra-dense deployment of static base stations (BSs) for a realistic scenario with moving users. Our simulations suggest that one FlyBS can provide throughput comparable to static BSs deployed with density corresponding to inter-site distance of 45 meters. At the same time, energy efficiency of the communication for the user equipment can be improved more than 5-times. This indicates that integration of the FlyBSs into mobile networks can be an efficient alternative to ultra-dense small cell deployment, especially in scenarios with users moving in crowds.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks signal processing algorithms

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