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2020 International Conference on Communication and Signal Processing (ICCSP)最新文献

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Ally - A Crowdsourced Distress Signal App 盟友-一个众包遇险信号应用程序
Pub Date : 2020-07-01 DOI: 10.1109/ICCSP48568.2020.9182243
A. Anand, S. Nishanth, P. Vamsi Krishna, S. Krishna, T. Anjali
It is a common belief that with the advent of technology the livelihood of people in a developing community tends to get better over time. It may be true in many cases but in cases of domestic and sexual violence against women there have been no significant development. With the benefit of women, elders and basically any person who is in distress in mind and also the need for a socially centralized social network we have put forward an idea which may help curb rising crime rates by solving various issues which have been unattended by existing methodologies. Ally is a distress signal application with newer and innovative approach to solving the age old problem of rapid redressal. Existing models fail to identify the location of a person if there is no network coverage thus failing ultimately which is why we have implemented a feature to constantly track the location of a person and give the updates to guardians on an half-hourly basis. Also existing models rely on the police or the guardians to help the person in distress whereas we have taken it a step forward to crowd source help in the hour of need by sending distress signal to all nearby Ally app users within a kilometer.
人们普遍认为,随着技术的出现,发展中社区人民的生活往往会随着时间的推移而变得更好。在许多情况下,这可能是正确的,但在对妇女的家庭暴力和性暴力方面,没有重大的发展。考虑到妇女、长者和任何处于困境的人的利益,以及建立一个社会集中化的社会网络的需要,我们提出了一个想法,通过解决现有方法未能解决的各种问题,可能有助于遏制不断上升的犯罪率。Ally是一个遇险信号应用程序,以更新和创新的方法来解决快速补救的老问题。如果没有网络覆盖,现有的模型就无法识别一个人的位置,因此最终会失败,这就是为什么我们实施了一个功能,不断跟踪一个人的位置,并每半小时向监护人更新一次。此外,现有的模式依赖于警察或监护人来帮助遇险的人,而我们已经向前迈进了一步,通过向附近一公里内的所有Ally应用程序用户发送遇险信号,在需要帮助的时刻提供人群帮助。
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引用次数: 1
Design of Seven-LP-Mode Compound-Index Few-Mode-Fiber for Mode-Division-Multiplexing Transmission 模分复用传输用7 - lp模复合折射率低模光纤的设计
Pub Date : 2020-07-01 DOI: 10.1109/ICCSP48568.2020.9182294
B. Behera, S. Varshney, M. Mohanty
In recent scenario realization of a high-capacity transmission system is one of the biggest challenges in the optical domain. Space-division multiplexing (SDM) and Mode-division multiplexing are the new age techniques those claim to establish high-speed transmission using Few-mode fibers (FMFs). FMFs have the potential to drastically improve the fiber capacity by enabling SDM and MDM. In this paper, we have proposed the design of an FMF with a compound refractive index profile to support and guide the first seven LP modes (LP01, LP11, LP12, LP02, LP21, LP31, LP41). The fiber parameters are examined to meet the design conditions to transmit seven-LP modes effectively with low bending loss, large effective-area, and a large-effective-index difference (Δn-eff) between the LP-modes to limit the mode coupling between the spatial modes for weakly-coupled MDM transmission.
在当前的场景中,实现高容量传输系统是光领域最大的挑战之一。空分复用(SDM)和模分复用(moddivision multiplexing)是新时代的技术,它们声称使用少模光纤(FMFs)建立高速传输。fmf有可能通过启用SDM和MDM来大幅提高光纤容量。在本文中,我们提出了一种具有复合折射率轮廓的FMF设计,以支持和引导前七种LP模式(LP01, LP11, LP12, LP02, LP21, LP31, LP41)。对光纤参数进行了检查,以满足有效传输7种lp模式的设计条件,这些模式具有低弯曲损耗、大有效面积和lp模式之间的大有效指数差(Δn-eff),以限制弱耦合MDM传输的空间模式之间的模式耦合。
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引用次数: 0
Dual Resonant DGS based Common-Mode Filter for High-Speed Digital Circuit Applications 高速数字电路中基于双谐振DGS的共模滤波器
Pub Date : 2020-07-01 DOI: 10.1109/ICCSP48568.2020.9182259
R. Savitha, Vasudevan Karuppiah
This paper proposes a miniature, dual resonant filter to suppress the common-mode noise for high-speed digital circuit applications. This is a DGS(Defected Ground Structure) based filter. The uniqueness of this paper is that the single unit-cell DGS produces dual resonance. Both the two resonance are nearer to each other to provide wide stop bandwidth for common-mode noise. From the simulated results it is evident that the proposed filter allows the differential signal and attenuates the common-mode noise over the frequency band of interest. The filter is compact and it can be fabricated by using a standard PCB fabrication process.
本文提出了一种用于高速数字电路中抑制共模噪声的微型双谐振滤波器。这是一个基于DGS(缺陷接地结构)的滤波器。本文的独特之处在于单胞DGS产生双共振。这两种共振都更靠近对方,为共模噪声提供更宽的停止带宽。从仿真结果可以明显看出,所提出的滤波器允许差分信号,并在感兴趣的频带上衰减共模噪声。该滤波器结构紧凑,可以使用标准PCB制造工艺制造。
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引用次数: 2
High Security Watermarking Techniques for Digital Rights Management: A Review 数字版权管理中的高安全性水印技术综述
Pub Date : 2020-07-01 DOI: 10.1109/ICCSP48568.2020.9182053
N.T Bushra Abdulla, K. A. Navas
Protection of data still remains as an anxiety to the researchers in spite of large number of techniques have been proposed in the literature to protect digital rights and authentication of documents. One of the methods to provide security to the right holders is digital watermarking; the technique of hiding secret message in the document to ensure authentication. Effectiveness of Watermarking depends on the robustness, imperceptibility and security. Presence of online data including audio, images, videos and diagrams in binary representation is fast increasing. New digitization techniques are capable of successfully attacking earlier watermarking techniques. This demands the need of developing new watermarking techniques to prevent the attacks on water-marked images. We attempted in this work to examine recently reported watermarking techniques in the literature which are claimed to be meritorious by the authors In this paper we discuss the merits and inefficiencies of the recently reported techniques which claim many merits. Identification of the room for research will be helpful to the researches to attempt on the development of new techniques.
尽管文献中提出了大量保护数字权利和文件认证的技术,但数据保护仍然是研究人员的一个焦虑。为权利人提供安全保护的方法之一是数字水印;在文档中隐藏秘密消息以确保身份验证的技术。水印的有效性取决于其鲁棒性、隐蔽性和安全性。在线数据包括二进制表示的音频、图像、视频和图表正在迅速增加。新的数字化技术能够成功地攻击早期的水印技术。这就要求开发新的水印技术来防止对水印图像的攻击。在这项工作中,我们试图研究文献中最近报道的被作者声称有价值的水印技术。在本文中,我们讨论了最近报道的声称有许多优点的技术的优点和低效。研究空间的确定将有助于研究人员尝试开发新技术。
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引用次数: 3
Mental Arithmetic Task Classification using Fourier Decomposition Method 基于傅立叶分解方法的心算任务分类
Pub Date : 2020-07-01 DOI: 10.1109/ICCSP48568.2020.9182149
Binish Fatimah, A. Javali, Haaris Ansar, B. Harshitha, Hemant Kumar
Solving an arithmetic problem is a complex task which involves fact retrieval, memory, sequencing and decision making. Automatic detection of such an activity from EEG signals will help in understanding of brain response to these cognitive tasks. In this work, we propose a mental arithmetic task detection algorithm from a single lead EEG signal. Fourier Decomposition method is used to decompose the signal into M uniform sub-bands and features, like energy, entropy, and variance, are computed from each of these sub-bands. Kruskal-Wallis method has been used to select only the statistically relevant features. These selected features are, then, used to classify the given EEG dataset into two classes using support vector machine with cubic kernel. To validate the efficacy of the proposed algorithm, simulation results are presented using dataset available on MIT PhysioNet, titled EEG during mental arithmetic task.
求解算术问题是一项复杂的任务,涉及事实检索、记忆、排序和决策。从脑电图信号中自动检测这种活动将有助于理解大脑对这些认知任务的反应。在这项工作中,我们提出了一种基于单导联脑电图信号的心算任务检测算法。采用傅里叶分解方法将信号分解为M个均匀的子带,并从每个子带中计算能量、熵和方差等特征。使用Kruskal-Wallis方法只选择统计相关的特征。然后,使用三次核支持向量机将给定的EEG数据集分为两类。为了验证该算法的有效性,利用MIT PhysioNet上的数据集“心算任务中的脑电图”给出了仿真结果。
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引用次数: 17
Hand Gesture Signal Classification using Machine Learning 使用机器学习的手势信号分类
Pub Date : 2020-07-01 DOI: 10.1109/ICCSP48568.2020.9182045
Athira Devaraj, Aswathy K. Nair
This research work focuses on identifying a specific hand gesture from the given EMG signal, acquired by sensor-based band. Surface EMG and machine learning techniques are used for the identification and classification purpose. The raw EMG signal captured using the sensor is initially passed through suitable preprocessing steps to avoid the noise artifacts. Followed by this, 8 different time-domain features are collected from these raw EMG signals, using which a feature matrix is created. SVM and KNN are the machine learning classifiers used here. The entire system is implemented in MATLAB 2019a. Using these methods, a promising accuracy of 93% is obtained through KNN and an accuracy of 83% using SVM.
这项研究工作的重点是从给定的肌电信号中识别特定的手势,这些信号是由基于传感器的频段获取的。表面肌电信号和机器学习技术用于识别和分类目的。使用传感器捕获的原始肌电信号最初通过适当的预处理步骤,以避免噪声伪影。然后,从这些原始肌电信号中收集8个不同的时域特征,利用这些特征矩阵创建特征矩阵。SVM和KNN是这里使用的机器学习分类器。整个系统在MATLAB 2019a中实现。使用这些方法,通过KNN和SVM分别获得了93%和83%的准确率。
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引用次数: 10
Analysis of Surface EMG Signals under Fatigue Conditions using Sum of Sines Models 用正弦和模型分析疲劳条件下表面肌电信号
Pub Date : 2020-07-01 DOI: 10.1109/ICCSP48568.2020.9182049
Divya Sasidharan, G. Venugopal
Muscle fatigue is a common experience for all age groups. In this work a model to fit the fatigue and non fatigue surface electromyography (sEMG) signals using sum of sines is proposed. Signals are recorded from Biceps Brachii muscle of five healthy volunteers until fatigue using a well defined protocol. The fatigue and non fatigue conditions are analysed separately by non linear dynamical model. The sum of sine model is selected for fitting the signals. The sin7 model is found to be the best non linear fit for non fatigue condition and sin8 for fatigue condition. The Root Mean Square Error (RMSE) of fatigue condition reduced by 4 from sin7 model to sin8 model. Also the fatigue signal tends to be periodic than non fatigue signal. This method may be further extended to the non linear analysis of muscular disorders.
肌肉疲劳是所有年龄组的共同经历。本文提出了一种基于正弦和的疲劳与非疲劳表肌电信号拟合模型。使用明确的协议记录5名健康志愿者肱二头肌的信号,直到疲劳。采用非线性动力学模型对疲劳工况和非疲劳工况进行了分析。选择正弦和模型拟合信号。结果表明,在非疲劳状态下,sin7模型的非线性拟合效果最好,而在疲劳状态下,sin8模型的非线性拟合效果最好。从sin7模型到sin8模型,疲劳状态的均方根误差(RMSE)减小了4。疲劳信号比非疲劳信号更具有周期性。该方法可进一步推广到肌肉疾病的非线性分析。
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引用次数: 2
Analysis and Characterization of Plant Diseases using Transfer Learning 植物病害的迁移学习分析与表征
Pub Date : 2020-07-01 DOI: 10.1109/ICCSP48568.2020.9182451
S. Bhimavarapu, P. Vinitha
Infrastructural defects to determine the sicknesses of the crop utilized within the agricultural quarter improvising special standards and solutions. The diagnosis of the different scenario and cause for diseases had been let to indulge in the current mobile technology suitable for the controlling of the disease using wireless scenario or switches. Our paper imparts on the current existing design technique as SVM, providing the mathematical and functional aspects of the design ensuring to improve the locating diseases using test and train scenarios. The setup for the SVM model is also taken in account for considerations of the different data sets of the images related different crops noting to provide the correct information of the problem scenario. These problems might exist due to natural or man-made for each set of the disease observed and identified. Hence recognition of the diseases would suffice the design criteria ensuring different parametric criteria for each level of training and test set provided. To ensure the novel and more accurate scenario different set of data set have been in consideration for different test and train images providing higher and reliable accuracy for the proposed model as part of CNN applying as Transfer learning. Different scenarios of the plant disease image have been considered as data set of 15617 images under restricted cases improvising a train model on CNN with transfer learning. The accuracy observed from the design model is observed 98.56% on the considered test vectors providing required feasibility. These designs also provide a better and convenient solutions for the people utilizing the current technologies.
确定农区内利用的作物病害的基础设施缺陷,制定特殊标准和解决方案。对疾病的不同情况和原因的诊断已经沉迷于当前适合使用无线场景或交换机控制疾病的移动技术。本文以现有的支持向量机设计技术为基础,从数学和功能两个方面进行设计,保证通过测试和训练场景来提高疾病的定位能力。SVM模型的设置也考虑到不同作物相关图像的不同数据集,以提供问题场景的正确信息。这些问题的存在可能是由于自然的或人为的,对于每一组观察和确定的疾病。因此,疾病的识别将满足设计标准,确保为每个级别的训练和测试集提供不同的参数标准。为了确保新颖和更准确的场景,我们考虑了不同的数据集用于不同的测试和训练图像,为所提出的模型作为CNN的一部分应用迁移学习提供了更高和可靠的精度。将植物病害图像的不同场景作为限定情况下15617张图像的数据集,利用迁移学习在CNN上临时建立训练模型。在提供所需可行性的考虑测试向量上,从设计模型观察到的准确性为98.56%。这些设计也为利用当前技术的人们提供了更好、更方便的解决方案。
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引用次数: 8
Analysis of Student Feedback and Recommendation to Tutors 学生反馈分析及导师推荐
Pub Date : 2020-07-01 DOI: 10.1109/ICCSP48568.2020.9182270
K. Karunya, S. Aarthy, R. Karthika, L. Jegatha Deborah
An important criterion in teaching is to analyze how well the teaching has been effective for the student’s. In order to do such analysis student’s feedback is obtained which would depict the quality and quantity of teaching. The existing evaluation technique tells about the opinion levels but does not clearly inform is it necessary to bring immediate changes in teaching or can proceed with the current teaching strategy. To address this drawback an automated ideology is proposed to initially analyze the student feedback comments and further based on the analysis introduce a recommendation system that would give a clear idea whether to bring in changes or proceed with the currently adopted teaching technique. This would provide tutors insight about opinion and allow them to make professionally sound decision so as to upgrade the performance of students.
教学的一个重要标准是分析教学对学生的效果如何。为了做这样的分析,学生的反馈可以反映教学的质量和数量。现有的评价方法只反映了意见水平,但并没有明确指出是否有必要立即改变教学,或者是否可以继续当前的教学策略。为了解决这一缺陷,提出了一种自动化的意识形态,首先分析学生的反馈意见,然后在分析的基础上引入一个推荐系统,该系统将给出一个明确的想法,即是否引入变化或继续使用目前采用的教学技术。这将为导师提供洞察意见,使他们能够做出专业合理的决策,从而提升学生的表现。
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引用次数: 4
Deep Learning based Hybrid Precoding for mmWave Massive MIMO system using ComcepNet 基于深度学习的ComcepNet毫米波大规模MIMO系统混合预编码
Pub Date : 2020-07-01 DOI: 10.1109/ICCSP48568.2020.9182336
C. Sidharth, S. Hiremath, S. K. Patra
Millimeter Wave (mmWave) and massive MIMO (Multiple Input Multiple Output) are promising solutions for 5G communications. Hybrid precoding architecture (analog and digital) is generally employed to resolve high hardware complexity and energy consumption issues. The current hybrid precoding architectures are computationally complex. This proposes a novel deep neural network based precoding architecture named ‘ComcepNet’. The network combines the features of Complex Convolution blocks and Inception Network. The network is observed to deliver superior performance in terms of accuracy and achievable datarate compared to the present Autoprecoder network.
毫米波(mmWave)和大规模MIMO(多输入多输出)是5G通信的有前途的解决方案。通常采用混合预编码架构(模拟和数字)来解决高硬件复杂性和能耗问题。目前的混合预编码体系结构计算复杂。提出了一种新的基于深度神经网络的预编码体系结构“ComcepNet”。该网络结合了复杂卷积块和盗梦网络的特点。与目前的Autoprecoder网络相比,该网络在准确性和可实现的数据方面具有优越的性能。
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引用次数: 4
期刊
2020 International Conference on Communication and Signal Processing (ICCSP)
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