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IEEE International Conference on Data Mining (ICDM)

作者： Junliang Yu Min Gao Hongzhi Yin Jundong Li Chongming Gao Qinyong Wang School of Information Technology and Electrical Engineering The University of Queensland School of Big Data and Software Engineering Chongqing University Department of Electrical and Computer Engineering University of Virginia Department of Computer Science and School of Data Science University of Virginia

Most of the recent studies of social recommendation assume that people share similar preferences with their friends and the online social relations are helpful in improving traditional recommender systems. However, this assumption is often untenable as the online social networks are quite sparse and a majority of users only have a small number of friends. Besides, explicit friends may not share similar interests because of the randomness in the process of building social networks. Therefore, discovering a number of reliable friends for each user plays an important role in advancing social recommendation. Unlike other studies which focus on extracting valuable explicit social links, our work pays attention to identifying reliable friends in both the observed and unobserved social networks. Concretely, in this paper, we propose an end-to-end social recommendation framework based on Generative Adversarial Nets (GAN). The framework is composed of two blocks: a generator that is used to produce friends that can possibly enhance the social recommendation model, and a discriminator that is responsible for assessing these generated friends and ranking the items according to both the current user and her friends' preferences. With the competition between the generator and the discriminator, our framework can dynamically and adaptively generate reliable friends who can perfectly predict the current user' preference at a specific time. As a result, the sparsity and unreliability problems of explicit social relations can be mitigated and the social recommendation performance is significantly improved. Experimental studies on real-world datasets demonstrate the superiority of our framework and verify the positive effects of the generated reliable friends.

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AIM 2020 Challenge on Image Extreme Inpainting 16th

AIM 2020 Challenge on Image Extreme Inpainting

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Workshops held at the 16th European Conference on computer Vision, ECCV 2020

作者： Ntavelis, Evangelos Romero, Andrés Bigdeli, Siavash Timofte, Radu Hui, Zheng Wang, Xiumei Gao, Xinbo Shin, Chajin Kim, Taeoh Son, Hanbin Lee, Sangyoun Li, Chao Li, Fu He, Dongliang Wen, Shilei Ding, Errui Bai, Mengmeng Li, Shuchen Zeng, Yu Lin, Zhe Yang, Jimei Zhang, Jianming Shechtman, Eli Lu, Huchuan Zeng, Weijian Ni, Haopeng Cai, Yiyang Li, Chenghua Xu, Dejia Wu, Haoning Han, Yu Nadim, Uddin S. M. Jang, Hae Woong Ahmed, Soikat Hasan Yoon, Jungmin Jung, Yong Ju Li, Chu-Tak Liu, Zhi-Song Wang, Li-Wen Siu, Wan-Chi Lun, Daniel P. K. Suin, Maitreya Purohit, Kuldeep Rajagopalan, A.N. Narang, Pratik Mandal, Murari Chauhan, Pranjal Singh Computer Vision Lab ETH Zürich Zürich Switzerland CSEM Neuchâtel Switzerland School of Electronic Engineering Xidian University Xi’an China Image and Video Pattern Recognition Laboratory School of Electrical and Electronic Engineering Yonsei University Seoul Korea Republic of Baidu Inc. Beijing China Beijing China Dalian University of Technology Dalian China Adobe San Jose United States Rensselaer Polytechnic Institute Troy United States Peking University Beijing China Lab Gachon University Seongnam Korea Republic of Centre for Multimedia Signal Processing Department of Electronic and Information Engineering The Hong Kong Polytechnic University Hong Kong China Indian Institute of Technology Madras Chennai India BITS Pilani Pilani India MNIT Jaipur Jaipur India

ISBN: (纸本)9783030670696

This paper reviews the AIM 2020 challenge on extreme image inpainting. This report focuses on proposed solutions and results for two different tracks on extreme image inpainting: classical image inpainting and semantically guided image inpainting. The goal of track 1 is to inpaint large part of the image with no supervision. Similarly, the goal of track 2 is to inpaint the image by having access to the entire semantic segmentation map of the input. The challenge had 88 and 74 participants, respectively. 11 and 6 teams competed in the final phase of the challenge, respectively. This report gauges current solutions and set a benchmark for future extreme image inpainting methods. © 2020, Springer Nature Switzerland AG.

关键词： Semantic Segmentation

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On the Privacy-Preserving Outsourcing Scheme of Reversible Data Hiding over Encrypted Image Data in Cloud Computing

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computers, Materials & Continua 2018年第6期55卷 523-539页

作者： Lizhi Xiong Yunqing Shi School of Computer and Software Nanjing University of Information Science and TechnologyNo.219Ningliu RoadNanjing 210044China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyUniversity Heights NewarkNew Jersey 07102USA

Advanced cloud computing technology provides cost saving and flexibility of services for *** the explosion of multimedia data,more and more data owners would outsource their personal multimedia data on the *** the meantime,some computationally expensive tasks are also undertaken by cloud ***,the outsourced multimedia data and its applications may reveal the data owner’s private information because the data owners lose the control of their ***,this thought has aroused new research interest on privacy-preserving reversible data hiding over outsourced multimedia *** this paper,two reversible data hiding schemes are proposed for encrypted image data in cloud computing:reversible data hiding by homomorphic encryption and reversible data hiding in encrypted *** former is that additional bits are extracted after decryption and the latter is that extracted before ***,a combined scheme is also *** paper proposes the privacy-preserving outsourcing scheme of reversible data hiding over encrypted image data in cloud computing,which not only ensures multimedia data security without relying on the trustworthiness of cloud servers,but also guarantees that reversible data hiding can be operated over encrypted images at the different *** analysis confirms the correctness of the proposed encryption model and justifies the security of the proposed *** computation cost of the proposed scheme is acceptable and adjusts to different security levels.

关键词： Cloud data security re-encryption reversible data hiding cloud computing privacy-preserving.

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Quantum algorithm for finding the negative curvature direction in non-convex optimization

arXiv

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arXiv 2019年

作者： Zhang, Kaining Hsieh, Min-Hsiu Liu, Liu Tao, Dacheng UBTECH Sydney AI Centre School of Computer Science Faculty of Engineering and Information Technologies University of Sydney Australia Centre for Quantum Software and Information Faculty of Engineering and Information Technology University of Technology Sydney Australia

We present an efficient quantum algorithm aiming to find the negative curvature direction for escaping the saddle point, which is the critical subroutine for many second-order nonconvex optimization algorithms. We prove that our algorithm could produce the target state corresponding to the negative curvature direction with query complexity Õ(polylog(d)Ε−1), where d is the dimension of the optimization function. The quantum negative curvature finding algorithm is exponentially faster than any known classical method which takes time at least O(dΕ−1/2). Moreover, we propose an efficient quantum algorithm to achieve the classical read-out of the target state. Our classical read-out algorithm runs exponentially faster on the degree of d than existing counterparts. Copyright © 2019, The Authors. All rights reserved.

关键词： Quantum theory

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Single image super-resolution via squeeze and excitation network 29

Single image super-resolution via squeeze and excitation net...

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29th British Machine Vision Conference, BMVC 2018

作者： Jiang, Tao Zhang, Yu Wu, Xiaojun Rao, Yuan Zhou, Mingquan Key Laboratory of Modern Teaching Technology Ministry of Education Shaanxi Normal University Xi'an710062 China Engineering Laboratory of Teaching Information Technology of Shaanxi Province SNNU Xi'an710119 China School of Computer Science Shaanxi Normal University Xi'an710119 China School of Software School Xi'an Jiaotong University Xi'an710049 China

Single Image Super-Resolution (SISR) has obtained unprecedented breakthrough with the development of Convolutional Neural Networks (CNN). A majority of these methods try to increase the depth of the network to obtain a larger receptive field. However, we found that blindly stacking feature maps and the simple cascading structure can not achieve a high rate of utilization in super-resolution reconstruction. In this paper, we propose a refined fully convolutional network for Single Image Super Resolution. Based on the assumption that features maps from different depths or the same depth but different channels have different contributions during image reconstruct, we introduce the Squeeze and Excitation (SE) network to evaluate the importance of different feature maps while building the network. Besides, densely connection operation is also conducted in the framework for a better use of the contextual information and feature maps. Extensive experiments demonstrates that the proposed method can enhance the restoration performance and achieve the state-of-the-art results in super-resolution task. © 2018. The copyright of this document resides with its authors.

关键词： Convolution

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Tethered Balloon technology for Green Communication in Smart Cities and Healthy Environment 1

Tethered Balloon Technology for Green Communication in Smart...

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1st International Conference of Intelligent Computing and engineering, ICOICE 2019

作者： Alsamhi, S.H. Mohsen Aljabali, Hasan Najim, Mohd Srivastava, Ashutosh Samar Ansari, Mohd Zhao, Liang Nguyen Van, Sau Gupta, S.K. Alammari, Amr A. Hatem Saber, Akram Hebah, Mohammed Y.A.M. Ahmed Abdullah Alasali, Marwan IBB University Yemen and Aligarh Muslim University Dept. of Electronics Engineering Ibb Yemen Aligarh Muslim University Department of Electrical Engineering Aligarh India University of Jaddah Department of Electrical and Electronics Engineering Jaddah Saudi Arabia Department of Electrical Engineering Varanasi India Software Research Institute Athlone Institute of Technology Athlone Ireland School of Computer Science Shenyang Aerospace University Shenyang China Biomedical of Information Technology Shenzhen Insitutes of Advanced Technology UCAS Shenzhen China School of Electronics and Communication Engineering Shri Mata Vaishno Devi University Katra India

ISBN: (纸本)9781728144870

The development and adopting of advanced communication technologies provide mobile users more convenience to connect any wireless network anytime and anywhere. Therefore, a large number of base stations (BS) are demanded keeping users connectivity, enhancing network capacity, and guarantee a sustained users Quality of Experiences (QoS). However, increasing the number of BS leads to an increase in the ecological ad radiation hazards. In order to green communication, many factors should be taken into consideration, i.e., saving energy, guarantee QoS, and reducing pollution hazards. Therefore, we propose tethered balloon technology that can replace a large number of BS and reduce ecological and radiation hazards due to its high altitude and feasible green and healthy broadband communication. The main contribution of this paper is to deploy tethered balloon technology at different altitude and measure the power density. Furthermore, we evaluate the measurement of power density from different height of tethered balloon comparison with traditional wireless communication technologies. The simulation results showed that tethered balloon technology can deliver green communication effectively and efficiently without any hazardous impacts. © 2019 IEEE.

关键词： Smart city

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Automatic Summarization Generation technology of Network Document Based on Knowledge Graph 1

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2nd EAI International Conference on Advanced Hybrid information processing, ADHIP 2018

作者： Wu, Yuezhong Chen, Rongrong Li, Changyun Chen, Shuhong Zou, Wenjun College of Artificial Intelligence Hunan University of Technology Zhuzhou412007 China Intelligent Information Perception and Processing Technology Hunan Province Key Laboratory Zhuzhou412007 China College of Business Hunan University of Technology Zhuzhou412007 China School of Computer Science and Educational Software Guangzhou University Guangzhou510006 China School of Computer and Communication Hunan Institute of Engineering Xiangtan411104 China

ISBN: (数字)9783030190866

ISBN: (纸本)9783030190859

The Internet has become one of the important channels for users to access to information and knowledge. It is crucial that how to acquire key content accurately and effectively in the events from huge amount of network information. This paper proposes an algorithm for automatic generation of network document summaries based on knowledge graph and TextRank algorithm which can solve the problem of information overload and resource trek effectively. We run the system in the field of big data application in packaging engineering. The experimental results show that the proposed method KG-TextRank extracts network document summaries more accurately, and automatically generates more readable and coherent natural language text. Therefore, it can help people access information and knowledge more effectively. © 2019, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Knowledge graph

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Luna-TX: An Optimized Transactional Mechanism for Persistent Memory

Luna-TX: An Optimized Transactional Mechanism for Persistent...

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IEEE Non-Volatile Memory Systems and Applications Symposium (NVMSA)

作者： Hongping Shu Hao Liu Hongyu Chen Youyou Lu Jiwu Shu School of Software Engineering Chengdu University of Information Technology Chengdu China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9781728138558

At present, most existing persistent memory programming libraries use write-ahead-logging(WAL) technology to ensure the consistency of memory allocating and updating process. In the application where persistent memory is frequently updated, this approach will bring a serious impact on system performance. In this work, we carefully analyzed the actual requirements of the applications and propose an optimized release mechanism for persistent memory called Luna_TX. In the improved mechanism, we remove the memory releasing phases of logs and objects from the critical path and generating in the process of update and release of transactions is delayed to the execution out of the transaction, which reduces the performance overhead on the critical paths. The experimental results have shown that the proposed mechanism can reduce the transaction delay significantly and boost up the whole transaction performance at 59%.

关键词： Resource management Libraries Nonvolatile memory Instruction sets Memory management Programming computer crashes

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Efficacy of Grayscaling Photoglottography Using High-Speed Videolaryngoscopic Images in the Evaluation of Vocal Fold Vibration

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Journal of Voice 2025年

作者： Lee, Chang Yoon Lee, Jin-Choon Shin, Sung-Chan Cheon, Yong il Kim, Seon-Jong Kwon, Soon-Kak Lee, Dong-Seok Kim, Jaewon Jang, Dae-Ik Kim, Geun-Hyo Lim, Dong-Won Son, Hee Young An, Soo-Youn Kwon, Soon-Bok Department of Otorhinolaryngology Dongnam Institute of Radiological and Medical Sciences Busan South Korea Department of Otorhinolaryngology-Head and Neck Surgery School of Medicine Pusan National University Yangsan Hospital Gyeongsangnam-do Yangsan South Korea Department of Otorhinolaryngology-Head and Neck Surgery College of Medicine Pusan National University and Biomedical Research Institute Pusan National University Hospital Busan South Korea Department of Applied IT and Engineering Pusan National University Gyeongsangnam-do Miryang South Korea Department of Computer Software Engineering Dong Eui University Busan South Korea AI Grand ICT Research Center Dong Eui University Busan South Korea Department of Otorhinolaryngology-Head and Neck Surgery Pusan National University Yangsan Hospital Gyeongsangnam-do Yangsan South Korea Department of Otorhinolaryngology-Head and Neck Surgery Kosin University Gospel Hospital Busan South Korea Department of Otorhinolaryngology-Head and Neck Surgery Pusan National University Hospital Busan South Korea Department of Humanities Language and Information Pusan National University Busan South Korea

Objectives: Methods for evaluating vocal fold vibration can be divided into indirect methods and directly observed vocal fold vibration. Indirect methods that can monitor the real-time opening and closing movements of the vocal folds include glottal inverse filtering, electroglottography (EGG), and photoglottography (PGG), with near-infrared PGG recently being reported. This study aimed to evaluate the usefulness of grayscaling photoglottography (GSP) to analyze vocal fold vibration. We compared the analysis accuracy of vocal fold oscillatory behavior with EGG and glottal area waveform (GAW). Study Design: Cross-sectional comparative study Methods: Participants included 10 normophonic men and 10 normophonic women. Another 10 participants had unilateral vocal fold paralysis, plus one participant each had spasmodic dysphonia, muscle tension dysphonia, and essential vocal tremors. High-speed videolaryngoscopy (HSV) was performed using a high-speed camera capable of recording at 1500 to 2000 frames per second for 10 seconds. Participants were asked to utter the sustained vowel /e/ at low pitch. EGG and voice signals were connected to a PC quirer and measured simultaneously with HSV. Data were analyzed in Praat. Results: GAW and GSP showed significant differences in voice onset and offset times, but no significant differences were observed in any other parameters. Significant differences were observed in the results for amplitude periodicity, closed quotient, open quotient, speed quotient (SQ), and speed index (SI), and voice onset and offset time between GAW and EGG. Significant differences were found in the results for amplitude periodicity, SQ, SI, and voice onset and offset time between GSP and EGG. GAW exhibited the longest duration. Regarding voice onset and offset time, GAW exhibited the longest duration, followed by GSP and EGG. The only method available to verify the vertical-level difference between the right and left vocal fold was GSP. Conclusions: We compare

关键词： Grayscaling photoglottography—Dysphonia—Vocal fold vibration

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A multi-view approach for predicting microbedisease associations by fusing the linear and nonlinear features

A multi-view approach for predicting microbedisease associat...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Ming Liu Wei Dai Wei Peng Yu Fu Yi Pan Faculty of Information Engineering and Automation Kunming University of Science and Technology Computer Technology Application Key Lab of Yunnan Province Kunming University of Science and Technology Kunming China Medical school Kunming University of Science and Technology Kunming China Georgia State University Atlanta GA USA

ISBN: (数字)9781728162157

ISBN: (纸本)9781728162164

Microbes play a crucial role in human health and disease. Understanding the relationship between microbes and diseases is conducive to the treatment and diagnosis of diseases. Recently, many computational methods have been proposed to predict disease-microbe associations. However, most of the existing methods only consider a single model and explore the disease-microbe associations from a single view. To improve the prediction accuracy, we propose a novel multi-view approach that fuses the linear and nonlinear features to predict new potential associations between diseases and microbes. We first design a non-negative matrix tri-factorization method to extract the linear features of diseases and microbes. We input the linear features from the non-negative matrix tri-factorization model and bi-random walk model into a capsule neural network to obtain the diseases and microbes' nonlinear features. Finally, we leverage a logistic regression model to combine the non-negative matrix tri-factorization model predictions, bi-random walk model predictions and the capsule neural network predictions to obtain the final association scores between microbes and diseases. We apply our method to predict human microbedisease associations. Experimental results show that our fusion model outperforms the non-negative matrix tri-factorization model, bi-random walk model and other existing models.

关键词： Diseases Predictive models Neural networks Feature extraction Computational modeling Logistics Kernel

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