This paper proposes an adaptive integral sliding mode tracking control for robotic manipulators. Our proposed control method is developed based on the benefits of both integral sliding mode control and adaptive control, such as high robustness, high accuracy, and estimation ability. In this paper, an integral sliding mode controller is designed with the elimination of the reaching stage to provide better trajectory tracking accuracy and to stabilize the closed-loop system. To reduce the computation complexity, an adaptive controller with only one simple adaptive law is used to estimate the upper-bound values of the lumped model uncertainties. As a result, the requirement of their prior knowledge is eliminated and then decrease the computation cost. Consequently, this controller provides better tracking accuracy and handles the dynamic uncertainties and external disturbances more strongly. The system global stability of the controller is guaranteed by using Lyapunov criteria. Finally, the effectiveness of the proposed control method is tested by computer simulation for a PUMA560 robotic manipulator.
{"title":"An Adaptive Integral Sliding Mode Tracking Control for Robotic Manipulators","authors":"A. Vo, Hee-Jun Kang, T. Le","doi":"10.1145/3386164.3387260","DOIUrl":"https://doi.org/10.1145/3386164.3387260","url":null,"abstract":"This paper proposes an adaptive integral sliding mode tracking control for robotic manipulators. Our proposed control method is developed based on the benefits of both integral sliding mode control and adaptive control, such as high robustness, high accuracy, and estimation ability. In this paper, an integral sliding mode controller is designed with the elimination of the reaching stage to provide better trajectory tracking accuracy and to stabilize the closed-loop system. To reduce the computation complexity, an adaptive controller with only one simple adaptive law is used to estimate the upper-bound values of the lumped model uncertainties. As a result, the requirement of their prior knowledge is eliminated and then decrease the computation cost. Consequently, this controller provides better tracking accuracy and handles the dynamic uncertainties and external disturbances more strongly. The system global stability of the controller is guaranteed by using Lyapunov criteria. Finally, the effectiveness of the proposed control method is tested by computer simulation for a PUMA560 robotic manipulator.","PeriodicalId":231209,"journal":{"name":"Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129847616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mahmood Al-Tekreeti, S. Özyer, Can Özdemir, Altuğ Karadağ, Saad Al-Dakheel
In this paper, Unmanned Surface Vehicles (USV) prototype and system design have been presented for the rescue of human life at sea. The USV will be protected from obstacles that may cause a crash to the USV by avoiding the obstacles using many kinds of detection sensors. All of these sensors send results to Crash Avoidance System (CAS) and to the main computer to control the USV direction depends on the obstacle shape, size or if it is a moving obstacle or not. The sensors that will be used for this purpose are Light Detection and Ranging (LIDAR) sensor, LIDAR-Lite sensors and ultrasonic sensors. All the information that will be collected from all these types of sensors will be used to direct the USV to the safe path. This work is a part of the research and development project which is accepted in Turkey Government with the collaboration of the University and Industry.
{"title":"Unmanned Surface Vehicle Prototype with Obstacle Avoidance System Area: Applications and Evaluation of Real-Time Big Data Systems","authors":"Mahmood Al-Tekreeti, S. Özyer, Can Özdemir, Altuğ Karadağ, Saad Al-Dakheel","doi":"10.1145/3386164.3390514","DOIUrl":"https://doi.org/10.1145/3386164.3390514","url":null,"abstract":"In this paper, Unmanned Surface Vehicles (USV) prototype and system design have been presented for the rescue of human life at sea. The USV will be protected from obstacles that may cause a crash to the USV by avoiding the obstacles using many kinds of detection sensors. All of these sensors send results to Crash Avoidance System (CAS) and to the main computer to control the USV direction depends on the obstacle shape, size or if it is a moving obstacle or not. The sensors that will be used for this purpose are Light Detection and Ranging (LIDAR) sensor, LIDAR-Lite sensors and ultrasonic sensors. All the information that will be collected from all these types of sensors will be used to direct the USV to the safe path. This work is a part of the research and development project which is accepted in Turkey Government with the collaboration of the University and Industry.","PeriodicalId":231209,"journal":{"name":"Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128447547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tao He, Wenting Sheng, Shuaifang Wen, Xing Wang, Wenchao Liu, Liangen Yang
In the industrial production, both ceiling lighting and sunlight through the ceiling in the workshop can cause noise spots in the image acquired in the CCD laser online positioning system. Moreover, these ambient noise spots are interlaced with the positioning laser spots in the image, which makes it difficult to obtain the position information of the positioning laser spots accurately. Aiming at this problem, in this paper, according to the geometric characteristics of both positioning laser spots and ambient noise spot, a denoising localization algorithm for positioning laser spots and noise spots interlaced image is proposed, and the cylindrical bar positioning system is used as the experimental object to verify the algorithm. The algorithm steps are as follows, firstly the noise spot is located according to the geometric characteristics of the two kinds of spots, and the non-overlapping region of the two kinds of spots are identified at the same time. Secondly, the noise spots in the non-overlapping area are eliminated. Finally, the existing Blob positioning algorithm is slightly modified to complete the accurate extraction of the position coordinates of the positioning laser spots pixel. The algorithm can effectively eliminate the ambient noise spots on the premise of ensuring that the positioning laser spots are not damaged, and accurately realize the measurement of the position coordinates of the positioning laser spots pixel.
{"title":"Research on Denoising Localization Algorithm for Positioning Laser Spots and Noise Spots Interlaced Image","authors":"Tao He, Wenting Sheng, Shuaifang Wen, Xing Wang, Wenchao Liu, Liangen Yang","doi":"10.1145/3386164.3387258","DOIUrl":"https://doi.org/10.1145/3386164.3387258","url":null,"abstract":"In the industrial production, both ceiling lighting and sunlight through the ceiling in the workshop can cause noise spots in the image acquired in the CCD laser online positioning system. Moreover, these ambient noise spots are interlaced with the positioning laser spots in the image, which makes it difficult to obtain the position information of the positioning laser spots accurately. Aiming at this problem, in this paper, according to the geometric characteristics of both positioning laser spots and ambient noise spot, a denoising localization algorithm for positioning laser spots and noise spots interlaced image is proposed, and the cylindrical bar positioning system is used as the experimental object to verify the algorithm. The algorithm steps are as follows, firstly the noise spot is located according to the geometric characteristics of the two kinds of spots, and the non-overlapping region of the two kinds of spots are identified at the same time. Secondly, the noise spots in the non-overlapping area are eliminated. Finally, the existing Blob positioning algorithm is slightly modified to complete the accurate extraction of the position coordinates of the positioning laser spots pixel. The algorithm can effectively eliminate the ambient noise spots on the premise of ensuring that the positioning laser spots are not damaged, and accurately realize the measurement of the position coordinates of the positioning laser spots pixel.","PeriodicalId":231209,"journal":{"name":"Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126227830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper aims to evaluate singing performance based on deep metric learning. As the vocal sound will be the input, we will first need to separate that from a soundtrack. After the separation, the vocal audio will be represented by Mel-spectrogram as an input in our proposed model. The process to build up our model splits into pre-training and training steps. Meta learning is adopted for pre-training while deep metric learning is adopted for training. The output of the model is a Euclidean distance reflecting the singers' performance, which is determined by comparing their sounds to the originals. Experimental results show a stable and reliable singing evaluation.
{"title":"Singing Evaluation based on Deep Metric Learning","authors":"Terry Tan","doi":"10.1145/3386164.3389096","DOIUrl":"https://doi.org/10.1145/3386164.3389096","url":null,"abstract":"This paper aims to evaluate singing performance based on deep metric learning. As the vocal sound will be the input, we will first need to separate that from a soundtrack. After the separation, the vocal audio will be represented by Mel-spectrogram as an input in our proposed model. The process to build up our model splits into pre-training and training steps. Meta learning is adopted for pre-training while deep metric learning is adopted for training. The output of the model is a Euclidean distance reflecting the singers' performance, which is determined by comparing their sounds to the originals. Experimental results show a stable and reliable singing evaluation.","PeriodicalId":231209,"journal":{"name":"Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127764227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the fast development of Information Technology, program software and mobile applications have been widely used in the world, and are playing important roles in human's daily life. Thus, writing programming codes has been important work in many fields. however, it is a hard and time-cost task which presents a great amount of workload to programmers. To make programmers' work easier, intelligent code completion models have been a popular research topic in recent years. This paper designs Deep Learning based models to automatically complete programming codes, which are LSTM-based neural networks, and are combined with several techniques such as Word Embedding models in NLP (Natural Language Processing), and Multihead Attention Mechanism. Moreover, in the models, this paper raises a new algorithm of generating input sequences from partial AST (Abstract Syntax Tree) that have most relevance with nodes to be predicted which is named as RZT (Reverse Zig-zag Traverse) Algorithm, and is the first work of applying Multihead Attention Block into this task. This paper makes insight into codes of several different programming languages, and the models this paper presents show good performances in accuracy comparing with the state-of-art models.
随着信息技术的快速发展，程序软件和移动应用程序在世界范围内得到了广泛的应用，在人们的日常生活中发挥着重要的作用。因此，编写程序代码在许多领域都是很重要的工作。然而，这是一项困难且耗时的任务，给程序员带来了大量的工作量。为了使程序员的工作更容易，智能代码完成模型是近年来的一个热门研究课题。本文设计了基于深度学习的自动完成编程代码的模型，该模型是基于lstm的神经网络，并结合了NLP(自然语言处理)中的词嵌入模型和多头注意机制等技术。此外，在模型中，本文提出了一种从部分AST (Abstract Syntax Tree)生成与待预测节点最相关的输入序列的新算法，称为RZT (Reverse z -zag Traverse)算法，这是首个将多头注意力块应用于该任务的算法。本文深入研究了几种不同编程语言的代码，与目前的模型相比，本文提出的模型在精度上有良好的表现。
{"title":"Deep Learning Based Code Completion Models for Programming Codes","authors":"Shuai Wang, Jinyang Liu, Ye Qiu, Zhiyi Ma, Junfei Liu, Zhonghai Wu","doi":"10.1145/3386164.3389083","DOIUrl":"https://doi.org/10.1145/3386164.3389083","url":null,"abstract":"With the fast development of Information Technology, program software and mobile applications have been widely used in the world, and are playing important roles in human's daily life. Thus, writing programming codes has been important work in many fields. however, it is a hard and time-cost task which presents a great amount of workload to programmers. To make programmers' work easier, intelligent code completion models have been a popular research topic in recent years. This paper designs Deep Learning based models to automatically complete programming codes, which are LSTM-based neural networks, and are combined with several techniques such as Word Embedding models in NLP (Natural Language Processing), and Multihead Attention Mechanism. Moreover, in the models, this paper raises a new algorithm of generating input sequences from partial AST (Abstract Syntax Tree) that have most relevance with nodes to be predicted which is named as RZT (Reverse Zig-zag Traverse) Algorithm, and is the first work of applying Multihead Attention Block into this task. This paper makes insight into codes of several different programming languages, and the models this paper presents show good performances in accuracy comparing with the state-of-art models.","PeriodicalId":231209,"journal":{"name":"Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131798640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The authors attempted to construct a novel sensor networking system that estimates locations of sensor nodes as locations of humans wearing them via image processing. In this application, computationally efficient human localization is indispensable because the operation should be executed on embedded systems. To actualize human localization at a lower computational cost, this study proposes a novel tracking scheme using only detection results. Experimental results using the computer graphics (CG) dataset that was created using player locations of an actual soccer game showed that the proposed scheme outperformed existing schemes implemented in the OpenCV library.
{"title":"A Computationally Efficient Tracking Scheme for Localization of Soccer Players in an Aerial Video Sequence","authors":"R. Aoki, T. Oki, Hiro Yokokawa, R. Miyamoto","doi":"10.1145/3386164.3389091","DOIUrl":"https://doi.org/10.1145/3386164.3389091","url":null,"abstract":"The authors attempted to construct a novel sensor networking system that estimates locations of sensor nodes as locations of humans wearing them via image processing. In this application, computationally efficient human localization is indispensable because the operation should be executed on embedded systems. To actualize human localization at a lower computational cost, this study proposes a novel tracking scheme using only detection results. Experimental results using the computer graphics (CG) dataset that was created using player locations of an actual soccer game showed that the proposed scheme outperformed existing schemes implemented in the OpenCV library.","PeriodicalId":231209,"journal":{"name":"Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114393778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes a combination between a neural network and an adaptive sliding mode control for trajectory tracking control of a 3-DOF planar parallel manipulator. It has a complicated dynamic model, including modelling uncertainties, frictional uncertainties and external disturbances. The proposed control algorithm is to use a PID sliding mode surface, an adaptive sliding mode controller with a neural network to overcome the drawback of the traditional sliding mode controllers, such as slow response rate with variation of uncertainties and external disturbances, chattering, and upper bound values of undefined dynamics which affects system performance, high wear of moving mechanical parts and high heat losses in power circuits. The radial basis function neural network is designed to compensate for uncertainties and external disturbances, which allows small switching gain. Hence, the chattering can be significantly reduced. In addition, an adaptive control law is used to adaptively converge small switching gains of the sliding mode controller as the neural network reduces model uncertainties. The effectiveness of the proposed control strategy is demonstrated by simulations which are conducted by using the combination of Sim-Mechanics and SolidWorks.
{"title":"Adaptive Neural Sliding Mode Control for 3-DOF Planar Parallel Manipulators","authors":"Thanh Nguyen Truong, Hee-Jun Kang, T. Le","doi":"10.1145/3386164.3387261","DOIUrl":"https://doi.org/10.1145/3386164.3387261","url":null,"abstract":"This paper proposes a combination between a neural network and an adaptive sliding mode control for trajectory tracking control of a 3-DOF planar parallel manipulator. It has a complicated dynamic model, including modelling uncertainties, frictional uncertainties and external disturbances. The proposed control algorithm is to use a PID sliding mode surface, an adaptive sliding mode controller with a neural network to overcome the drawback of the traditional sliding mode controllers, such as slow response rate with variation of uncertainties and external disturbances, chattering, and upper bound values of undefined dynamics which affects system performance, high wear of moving mechanical parts and high heat losses in power circuits. The radial basis function neural network is designed to compensate for uncertainties and external disturbances, which allows small switching gain. Hence, the chattering can be significantly reduced. In addition, an adaptive control law is used to adaptively converge small switching gains of the sliding mode controller as the neural network reduces model uncertainties. The effectiveness of the proposed control strategy is demonstrated by simulations which are conducted by using the combination of Sim-Mechanics and SolidWorks.","PeriodicalId":231209,"journal":{"name":"Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124973286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The problem of large modeling error exists in the modeling and compensation of Fiber Optic Gyroscope (FOG) temperature drift by traditional polynomial fitting. In the case, a compensation method for FOG temperature drift error based on double-section polynomial fitting is studied, which can build the model of the FOG temperature drift error in both the startup section and the balanced section. Experimental results show that the new method can improve both the accuracy of modeling and the effect of compensation effectively.
{"title":"A Compensation Method for FOG Temperature Drift Error Based on Double-section Polynomial Fitting","authors":"Yang Li, Ke Chen, Liu-wei Mao","doi":"10.1145/3386164.3386179","DOIUrl":"https://doi.org/10.1145/3386164.3386179","url":null,"abstract":"The problem of large modeling error exists in the modeling and compensation of Fiber Optic Gyroscope (FOG) temperature drift by traditional polynomial fitting. In the case, a compensation method for FOG temperature drift error based on double-section polynomial fitting is studied, which can build the model of the FOG temperature drift error in both the startup section and the balanced section. Experimental results show that the new method can improve both the accuracy of modeling and the effect of compensation effectively.","PeriodicalId":231209,"journal":{"name":"Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123751453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cloud computing platform has powerful computing capacity and nearly infinite resource pool, which provides a strong guarantee for mass data storage and computing. Considering double security threats from malicious external attackers and "honest-but-curious" CSP (cloud service provider), users need to encrypt images to ensure the data security before outsourcing images to cloud. But encryption can have an impact on the necessary data services, such as content based image retrieval (CBIR). A secure CBIR method based on BoVW (Bag of Visual Words) model under cloud environment is proposed in the paper. Images are expressed as frequency histogram by BoVW model, orthogonal decomposition is utilized to divide it into two individual parts of component coefficients thus encryption operation and feature extraction operation can be executed separately, and orthogonal composition is used to fuse the encrypted operation results to construct secure image index. After encrypted image index and encrypted images are outsourced to CSP, distance comparison can be executed by CSP on feature extraction field without violating data privacy. Encrypted images with the closest distance to query trapdoor are returned to users to decrypt and obtain plain images. Any encryption algorithms can be used to encrypt images and search index by using orthogonal transformation, so that the proposed method is practicable. Retrieval precision is improved and better performance are achieved by using BoVW model. The security analysis and experimental results show our scheme has obvious advantages in security and retrieval performance.
云计算平台具有强大的计算能力和近乎无限的资源池，为海量数据的存储和计算提供了强有力的保障。考虑到恶意外部攻击者和“诚实但好奇”的云服务提供商CSP (cloud service provider)的双重安全威胁，用户在将图像外包给云之前，需要对图像进行加密，以确保数据安全。但是加密可能会对必要的数据服务产生影响，例如基于内容的图像检索(CBIR)。提出了一种基于BoVW (Bag of Visual Words)模型的云环境下安全的CBIR方法。采用BoVW模型将图像表示为频率直方图，利用正交分解将其分解为分量系数的两个独立部分，从而可以分别进行加密操作和特征提取操作，并利用正交组合将加密操作结果融合，构建安全的图像索引。加密图像索引和加密图像外包给CSP后，CSP可以在不侵犯数据隐私的情况下对特征提取领域进行距离比较。将与查询trapdoor距离最近的加密图像返回给用户解密，得到明文图像。任何加密算法都可以使用正交变换对图像进行加密和搜索索引，因此该方法是可行的。采用BoVW模型提高了检索精度，取得了较好的检索性能。安全性分析和实验结果表明，该方案在安全性和检索性能方面具有明显的优势。
{"title":"A Secure CBIR Method based on Bag-of-Visual-Words Model under Cloud Environment","authors":"Yanyan Xu, Xiao Zhao, Jiaying Gong","doi":"10.1145/3386164.3389099","DOIUrl":"https://doi.org/10.1145/3386164.3389099","url":null,"abstract":"Cloud computing platform has powerful computing capacity and nearly infinite resource pool, which provides a strong guarantee for mass data storage and computing. Considering double security threats from malicious external attackers and \"honest-but-curious\" CSP (cloud service provider), users need to encrypt images to ensure the data security before outsourcing images to cloud. But encryption can have an impact on the necessary data services, such as content based image retrieval (CBIR). A secure CBIR method based on BoVW (Bag of Visual Words) model under cloud environment is proposed in the paper. Images are expressed as frequency histogram by BoVW model, orthogonal decomposition is utilized to divide it into two individual parts of component coefficients thus encryption operation and feature extraction operation can be executed separately, and orthogonal composition is used to fuse the encrypted operation results to construct secure image index. After encrypted image index and encrypted images are outsourced to CSP, distance comparison can be executed by CSP on feature extraction field without violating data privacy. Encrypted images with the closest distance to query trapdoor are returned to users to decrypt and obtain plain images. Any encryption algorithms can be used to encrypt images and search index by using orthogonal transformation, so that the proposed method is practicable. Retrieval precision is improved and better performance are achieved by using BoVW model. The security analysis and experimental results show our scheme has obvious advantages in security and retrieval performance.","PeriodicalId":231209,"journal":{"name":"Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control","volume":"07 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127260378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The single-index model is a semi-parametric regression model that avoids the curse of dimensionality because of the linear combination of p-regression coefficients and covariates. Most of the works in this setting done for the homogenous single index models are limited and based on the minimum average conditional variance estimation (MAVE). To overcome these drawbacks, in this paper, we provide a robust and efficient estimate with modal regression for the single-index model under the existence of heteroscedasticity. The EM algorithm and bandwidth selection are employed to prepare the estimation method. Simulation studies demonstrate the performance of the proposed estimation; this method outperforms MAVE in various situations even if the errors are generated from a heavy-tailed distribution while it achieves the same efficiency as well as MAVE for the normally distributed errors. Finally, the application of the proposed method is illustrated by a real example of the heteroscedastic model.
{"title":"Modal Regression Estimation for Heteroscedastic Single-Index Model","authors":"Waled Khaled, Jinguan Lin","doi":"10.1145/3386164.3390517","DOIUrl":"https://doi.org/10.1145/3386164.3390517","url":null,"abstract":"The single-index model is a semi-parametric regression model that avoids the curse of dimensionality because of the linear combination of p-regression coefficients and covariates. Most of the works in this setting done for the homogenous single index models are limited and based on the minimum average conditional variance estimation (MAVE). To overcome these drawbacks, in this paper, we provide a robust and efficient estimate with modal regression for the single-index model under the existence of heteroscedasticity. The EM algorithm and bandwidth selection are employed to prepare the estimation method. Simulation studies demonstrate the performance of the proposed estimation; this method outperforms MAVE in various situations even if the errors are generated from a heavy-tailed distribution while it achieves the same efficiency as well as MAVE for the normally distributed errors. Finally, the application of the proposed method is illustrated by a real example of the heteroscedastic model.","PeriodicalId":231209,"journal":{"name":"Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126833730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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