Chaotic systems are extremely sensitive to initial conditions and system parameters, ergodicity, unpredictable, which are applied to the field of image encryption widely. This paper proposes a new scheme of combining chaos theory and image encryption–2D Chebyshev-Sine map. Through the analysis of the trajectory contours mapping and other chaos mappings, the method has a wide range of chaos and good ergodicity. And it is sensitive to initial conditions and system parameters, which cost relatively low. On this basis, a linear mixed layer image encryption algorithm is proposed. In this algorithm, row shift and column mixing are used to change the pixel space position and pixel frequency domain, And the diffusion principle of Chinese remainder theorem is applied. The results of simulation and analysis show that this encryption algorithm has low time efficiency, relatively high security, resistance to differential attack and performance against selective plaintext attack.
{"title":"2D Chebyshev-Sine Map for Image Encryption","authors":"Y. Zhong, Huayi Liu, Rushi Lan, Ting Wang, Xiyan Sun, Xiaonan Luo","doi":"10.1109/ICDH.2018.00008","DOIUrl":"https://doi.org/10.1109/ICDH.2018.00008","url":null,"abstract":"Chaotic systems are extremely sensitive to initial conditions and system parameters, ergodicity, unpredictable, which are applied to the field of image encryption widely. This paper proposes a new scheme of combining chaos theory and image encryption–2D Chebyshev-Sine map. Through the analysis of the trajectory contours mapping and other chaos mappings, the method has a wide range of chaos and good ergodicity. And it is sensitive to initial conditions and system parameters, which cost relatively low. On this basis, a linear mixed layer image encryption algorithm is proposed. In this algorithm, row shift and column mixing are used to change the pixel space position and pixel frequency domain, And the diffusion principle of Chinese remainder theorem is applied. The results of simulation and analysis show that this encryption algorithm has low time efficiency, relatively high security, resistance to differential attack and performance against selective plaintext attack.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"152 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116190740","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 ballistocardiogram (BCG) is a useful information signal reflecting the state of cardiovascular system. In order to improve the monitoring level of cardiovascular diseases in China, a wavelet-bispectrum analysis method was proposed to extract the characteristic of BCG signal. First, the BCG signal was preprocessed. Then, wavelet decomposition and reconstruction were performed by choosing the appropriate wavelet function and decomposing levels, and the sub-bands were bispectrum analyzed for reconstruction. Finally, the maximum amplitude of slice spectrum and energy of each sub-band of BCG signal were extracted. The results have shown that the method can obtain the high-order time-frequency information in the BCG signal, and has obvious advantage for the non-stationary and non-Gaussian processing of BCG signal, it also provide a reliable basis for the application of BCG signal in clinical diagnosis.
{"title":"A Method of Feature Extraction for BCG Signal Based on Wavelet and Bispectrum","authors":"Zimin Wang, Li Zeng, Yumeng Wang, Man Wang","doi":"10.1109/icdh.2018.00027","DOIUrl":"https://doi.org/10.1109/icdh.2018.00027","url":null,"abstract":"The ballistocardiogram (BCG) is a useful information signal reflecting the state of cardiovascular system. In order to improve the monitoring level of cardiovascular diseases in China, a wavelet-bispectrum analysis method was proposed to extract the characteristic of BCG signal. First, the BCG signal was preprocessed. Then, wavelet decomposition and reconstruction were performed by choosing the appropriate wavelet function and decomposing levels, and the sub-bands were bispectrum analyzed for reconstruction. Finally, the maximum amplitude of slice spectrum and energy of each sub-band of BCG signal were extracted. The results have shown that the method can obtain the high-order time-frequency information in the BCG signal, and has obvious advantage for the non-stationary and non-Gaussian processing of BCG signal, it also provide a reliable basis for the application of BCG signal in clinical diagnosis.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"284 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127557209","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}
In order to facilitate the generation of user interfaces from mockups, an approach was proposed to recommend User Interface (UI) layout based on Pairing Model. The absolute layout data of interfaces, including types, text, positions and sizes of components, are input into the model to generate layout. Paring Model is trained by machine-learning algorithms with features extracted from UI galleries. On the levels of functional and spatial relationship, the model decides pairing of input components and recommends a suitable layout. With use of component features, by machine-learning algorithms, the types of components are identified, which are the leaf nodes of the output layout hierarchy. The experiments on 3362 interface instances from 800 open source apps proved that the accuracy of the proposed approach, on average, exceeds 90%.
{"title":"User Interface Layout Recommendation Based on Pairing Model","authors":"Xiaohong Shi, Shuyi Huang, Yongsheng Rao, Xiangping Chen","doi":"10.1109/ICDH.2018.00041","DOIUrl":"https://doi.org/10.1109/ICDH.2018.00041","url":null,"abstract":"In order to facilitate the generation of user interfaces from mockups, an approach was proposed to recommend User Interface (UI) layout based on Pairing Model. The absolute layout data of interfaces, including types, text, positions and sizes of components, are input into the model to generate layout. Paring Model is trained by machine-learning algorithms with features extracted from UI galleries. On the levels of functional and spatial relationship, the model decides pairing of input components and recommends a suitable layout. With use of component features, by machine-learning algorithms, the types of components are identified, which are the leaf nodes of the output layout hierarchy. The experiments on 3362 interface instances from 800 open source apps proved that the accuracy of the proposed approach, on average, exceeds 90%.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128010454","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 research paper introduces a novel symmetry grid multi-wing chaotic system, whose dynamics support periodic and chaotic as certain parameters vary. By introducing a mirror symmetry conversion-based approach in a multi-wing chaotic system, various mirror symmetry grid multi-wing chaotic attractors can be simulated. Furthermore, the improved module-based circuit designs of multi-wing chaotic attractors and mirror symmetry grid multi-wing chaotic attractors are further presented. The proposed novel mirror symmetry multi-wing chaotic attractors are very useful for deliberate generation of chaos in applications.
{"title":"Simulation and Circuit Realization of a Novel Symmetry Grid Multi-wing Chaotic System","authors":"Chaoxia Zhang, Jinxin Ruan, Qiang Chen","doi":"10.1109/ICDH.2018.00031","DOIUrl":"https://doi.org/10.1109/ICDH.2018.00031","url":null,"abstract":"This research paper introduces a novel symmetry grid multi-wing chaotic system, whose dynamics support periodic and chaotic as certain parameters vary. By introducing a mirror symmetry conversion-based approach in a multi-wing chaotic system, various mirror symmetry grid multi-wing chaotic attractors can be simulated. Furthermore, the improved module-based circuit designs of multi-wing chaotic attractors and mirror symmetry grid multi-wing chaotic attractors are further presented. The proposed novel mirror symmetry multi-wing chaotic attractors are very useful for deliberate generation of chaos in applications.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121154409","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}
In past decades, there has been a growing interest in the research of underwater acoustic communication. Due to attenuation, low propagation speed of the sound and multipath of underwater acoustic channel, signal parameter estimation becomes challenging and significant. In this paper, a multi-parameter estimation method of underwater acoustic signal was proposed. This method can estimate the channel gain, Doppler shift and phase compensation for single carrier signal. Meanwhile, the Cramer-Rao lower bound for this estimation method was also derived.
{"title":"Multi-parameter Estimation and Its Cramer-Rao Lower Bound for Underwater Acoustic Signal","authors":"Liying Xie, Jinxin Ruan, Yilin Wu, Qiang Chen","doi":"10.1109/ICDH.2018.00026","DOIUrl":"https://doi.org/10.1109/ICDH.2018.00026","url":null,"abstract":"In past decades, there has been a growing interest in the research of underwater acoustic communication. Due to attenuation, low propagation speed of the sound and multipath of underwater acoustic channel, signal parameter estimation becomes challenging and significant. In this paper, a multi-parameter estimation method of underwater acoustic signal was proposed. This method can estimate the channel gain, Doppler shift and phase compensation for single carrier signal. Meanwhile, the Cramer-Rao lower bound for this estimation method was also derived.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"427 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123404710","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}
In recent years, watching educational videos online has become an important method of learning. The research purpose of this paper is to provide an efficient method to improve learning efficiency for users watching online educational videos. It is an effective way to help users understand video content by extracting key words of concern in the video, which is also a hot issue in video analysis. This paper proposes a solution to extract the expansion words from the video to help users understand and learn terminologies. The extracted expansion words help us quickly obtain the meaning of new words by knowledge base association, and further expand the depth and breadth of video content while learning the content in video. An improved keyword extraction algorithm is proposed in this paper, which redistributes the weights of extracted keywords to improve the recall of low frequency new words or terminologies. The experimental results show that the video expansion word extraction method proposed in this paper can effectively extract the proper nouns and terminologies in the video.
{"title":"An Efficient Expansion Word Extraction Algorithm for Educational Video","authors":"Lijie Shao, Fuwei Zhang, Ruomei Wang, Fan Zhou, Shujin Lin","doi":"10.1109/ICDH.2018.00032","DOIUrl":"https://doi.org/10.1109/ICDH.2018.00032","url":null,"abstract":"In recent years, watching educational videos online has become an important method of learning. The research purpose of this paper is to provide an efficient method to improve learning efficiency for users watching online educational videos. It is an effective way to help users understand video content by extracting key words of concern in the video, which is also a hot issue in video analysis. This paper proposes a solution to extract the expansion words from the video to help users understand and learn terminologies. The extracted expansion words help us quickly obtain the meaning of new words by knowledge base association, and further expand the depth and breadth of video content while learning the content in video. An improved keyword extraction algorithm is proposed in this paper, which redistributes the weights of extracted keywords to improve the recall of low frequency new words or terminologies. The experimental results show that the video expansion word extraction method proposed in this paper can effectively extract the proper nouns and terminologies in the video.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127002312","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 recommended algorithm is widely used in the path recommendation. In this paper, the exercise path recommendation algorithm is reported. The main factors considering in the exercise path recommendation include the frequency of path selection, starting point and ending point of exercise and the moving object. Compared with other algorithms, our path recommendation algorithm is low computation cost, and some personal factors are considered in the recommendation algorithm, the recommended path is most suitable for the individual requirement.
{"title":"Research and Implementation of Path Recommendation Algorithm Based on Exercise Record","authors":"Qiuyuan Luo, Linfa Lu, Guifeng Zheng, Jinlu Xue","doi":"10.1109/ICDH.2018.00049","DOIUrl":"https://doi.org/10.1109/ICDH.2018.00049","url":null,"abstract":"The recommended algorithm is widely used in the path recommendation. In this paper, the exercise path recommendation algorithm is reported. The main factors considering in the exercise path recommendation include the frequency of path selection, starting point and ending point of exercise and the moving object. Compared with other algorithms, our path recommendation algorithm is low computation cost, and some personal factors are considered in the recommendation algorithm, the recommended path is most suitable for the individual requirement.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126575129","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 action recognition of large animals plays an important role in the intelligent and modern farming. People often use the actions as the key factors to achieve scientific feeding and improve the animal welfare, and then the quality and productivity of animals are greatly promoted. However, most present action recognition methods focus on the actions of human (as pedestrian, athletes) or man-made objects (as cars, bikes). This paper proposes a benchmark to recognize and evaluate the actions of a kind of large animals namely the cows. First, we construct a dataset including 60 videos to describe the popular actions existing in the daily life of cows, and manually denote the target regions of cows on every frame in the dataset. Second, six famous trackers are evaluated on this dataset to compute the trajectory of cows which is the basis of actions recognition. Third, we define the method to recognize the actions of cows via the trajectories and validate the proposed method on our dataset. Many experiments demonstrate that our method of action recognition performs favorable in detecting the actions of cows, and the proposed dataset basically satisfies the action evaluations for farmers. The work in this paper provides an automatic and scientific method for famers to design a scheme to promote the quality and productivity of cows.
{"title":"A Benchmark for Action Recognition of Large Animals","authors":"Yun Liang, Fuyou Xue, Xiaoming Chen, Zexin Wu, Xiang Chen","doi":"10.1109/ICDH.2018.00020","DOIUrl":"https://doi.org/10.1109/ICDH.2018.00020","url":null,"abstract":"The action recognition of large animals plays an important role in the intelligent and modern farming. People often use the actions as the key factors to achieve scientific feeding and improve the animal welfare, and then the quality and productivity of animals are greatly promoted. However, most present action recognition methods focus on the actions of human (as pedestrian, athletes) or man-made objects (as cars, bikes). This paper proposes a benchmark to recognize and evaluate the actions of a kind of large animals namely the cows. First, we construct a dataset including 60 videos to describe the popular actions existing in the daily life of cows, and manually denote the target regions of cows on every frame in the dataset. Second, six famous trackers are evaluated on this dataset to compute the trajectory of cows which is the basis of actions recognition. Third, we define the method to recognize the actions of cows via the trajectories and validate the proposed method on our dataset. Many experiments demonstrate that our method of action recognition performs favorable in detecting the actions of cows, and the proposed dataset basically satisfies the action evaluations for farmers. The work in this paper provides an automatic and scientific method for famers to design a scheme to promote the quality and productivity of cows.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124482256","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}
Recently, deep convolutional neural networks (CNNS) have been revealed significant progress on single image super-resolution (SISR). Nevertheless, as the depth and width of the networks increase, CNN-based super-resolution (SR) methods have been confronted with the challenges of computational complexity and memory consumption in practice. In order to solve the above issues, we combine the Laplacian Pyramid with the previous methods to propose a convolutional neural network, which is able to reconstruct the HR image from low resolution image step by step. Our Laplacian-Pyramid structure allows each layer to share common parameters with other layers as well as its inner structure; this kind of characteristic reduces the number of parameters dramatically while still extracts sufficient features at the same time. In experiment part, we compare our method with the state-of-art methods. The results demonstrate that the proposed method is superior to the previous methods, furthermore our x2 model also gains an ideal effect.
{"title":"Single Image Super-Resolution via Laplacian Information Distillation Network","authors":"M. Cheng, Zhan Shu, Jiapeng Hu, Y. Zhang, Zhuo Su","doi":"10.1109/ICDH.2018.00012","DOIUrl":"https://doi.org/10.1109/ICDH.2018.00012","url":null,"abstract":"Recently, deep convolutional neural networks (CNNS) have been revealed significant progress on single image super-resolution (SISR). Nevertheless, as the depth and width of the networks increase, CNN-based super-resolution (SR) methods have been confronted with the challenges of computational complexity and memory consumption in practice. In order to solve the above issues, we combine the Laplacian Pyramid with the previous methods to propose a convolutional neural network, which is able to reconstruct the HR image from low resolution image step by step. Our Laplacian-Pyramid structure allows each layer to share common parameters with other layers as well as its inner structure; this kind of characteristic reduces the number of parameters dramatically while still extracts sufficient features at the same time. In experiment part, we compare our method with the state-of-art methods. The results demonstrate that the proposed method is superior to the previous methods, furthermore our x2 model also gains an ideal effect.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116143802","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}
How to generate well quality faces objects of automated processes has always been the focus on researchers. Recently, due to the deep generative networks have achieved impressive successes in data generative fields, researchers have tried to introduce deep learning into the 3d objects generate field, such as text2scene, slice-based object generate. However, the generative ability in 3D object is limited by the size of the feature space, because of computational space limitations on hardware. In this paper, we address the problem by reducing amount of calculated on process of learning, and thus generative newly different objects. The problem is intractable, since first the limiting of compute space is so hard that object can't be process in deep network due to the process need to compute many matrix multiplications. To resolve the problem, we propose a sparse representation-based method of generating well-quality faces object. Our method consists of two parts: sparse reconstruction and object generative. First, we verified the possibility of using sparse representations of 3D data by reconstructing 3D object. Second, we design a network architecture of deep adversarial network of generating new sparse representation and combined with the previous reconstruction method of generating new face object. Experiments show that our method has the ability to generate very different and well quality faces objects that contain tens of thousands of points and meshes. Our findings show that sparse representation can be used in 3D object reconstruction and generate via deep generative adversarial model.
{"title":"Sparse Representation-Based Face Object Generative via Deep Adversarial Network","authors":"Ye Yuan, Yong Zhang, Shaofan Wang, Baocai Yin","doi":"10.1109/ICDH.2018.00019","DOIUrl":"https://doi.org/10.1109/ICDH.2018.00019","url":null,"abstract":"How to generate well quality faces objects of automated processes has always been the focus on researchers. Recently, due to the deep generative networks have achieved impressive successes in data generative fields, researchers have tried to introduce deep learning into the 3d objects generate field, such as text2scene, slice-based object generate. However, the generative ability in 3D object is limited by the size of the feature space, because of computational space limitations on hardware. In this paper, we address the problem by reducing amount of calculated on process of learning, and thus generative newly different objects. The problem is intractable, since first the limiting of compute space is so hard that object can't be process in deep network due to the process need to compute many matrix multiplications. To resolve the problem, we propose a sparse representation-based method of generating well-quality faces object. Our method consists of two parts: sparse reconstruction and object generative. First, we verified the possibility of using sparse representations of 3D data by reconstructing 3D object. Second, we design a network architecture of deep adversarial network of generating new sparse representation and combined with the previous reconstruction method of generating new face object. Experiments show that our method has the ability to generate very different and well quality faces objects that contain tens of thousands of points and meshes. Our findings show that sparse representation can be used in 3D object reconstruction and generate via deep generative adversarial model.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127321837","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}