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VGGSOUND: A LARGE-SCALE AUDIO-VISUAL DATASET

VGGSOUND: A LARGE-SCALE AUDIO-VISUAL DATASET

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ieee International conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Chen, Honglie Xie, Weidi Vedaldi, Andrea Zisserman, Andrew Univ Oxford VGG Dept Engn Sci Oxford England

ISBN: (纸本)9781509066315

Our goal is to collect a large-scale audio-visual dataset with low label noise from videos `in the wild' using computer vision techniques. The resulting dataset can be used for training and evaluating audio recognition models. We make three contributions. First, we propose a scalable pipeline based on computer vision techniques to create an audio dataset from open-source media. Our pipeline involves obtaining videos from YouTube;using image classification algorithms to localize audio-visual correspondence;and filtering out ambient noise using audio verification. Second, we use this pipeline to curate the VGGSound dataset consisting of more than 200k videos for 300 audio classes. Third, we investigate various Convolutional Neural network (CNN) architectures and aggregation approaches to establish audio recognition baselines for our new dataset. Compared to existing audio datasets, VGGSound ensures audio-visual correspondence and is collected under unconstrained conditions.

关键词： audio recognition audio-visual correspondence large-scale dataset convolutional neural network

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Fine-grained Spatiotemporal Features-Based for Anomaly Detection in Microservice Systems

Fine-grained Spatiotemporal Features-Based for Anomaly Detec...

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ieee International conference on High Performance Computing and Communications (HPCC)

作者： Xikang Yang Juan Wang Biyu Zhou Wang Wang Wantao Liu Yangchen Dong Chinese Academy of Sciences Institute of Information Engineering School of Cyber Security University of Chinese Academy of Sciences China Academy of Information and Communications Technology Beijing China

More and more applications use microservice architecture. Protecting the reliability of the microservice system is very important for the stable operation of applications. However, the complexity of microservice systems poses a great challenge to operation and maintenance. Researchers have proposed a series of anomaly detection algorithms, which can automatically detect the anomalies of cloud systems in time. However, for the microservice system with a complex spatial structure, there is no effective method to represent the fine-grained features of the internal metric level of the microservice. To solve this problem, we propose a fine-grained metric-level spatial feature graph TopoMetrics and use a spatiotemporal neural network STAD to obtain the spatiotemporal features of microservices, which can accurately detect the anomalies of complex microservices. We compare STAD with the most advanced algorithms in three open microservice workloads. The experimental results show that the average precision of STAD is significantly higher than that of the most advanced baseline method.

关键词： Measurement network topology Neural networks Microservice architectures Maintenance engineering Feature extraction Spatiotemporal phenomena

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Implementing Multiple-Social-network Meta-APIs to Support OSINT programming 12

Implementing Multiple-Social-Network Meta-APIs to Support OS...

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12th International conference on Advanced Infocomm Technology, ICAIT 2020

作者： Buccafurri, Francesco De Angelis, Vincenzo Idone, Maria Francesca University of Reggio Calabria Reggio Calabria89122 Italy

ISBN: (纸本)9781728183848

open source intelligence (OSINT) collects a set of approaches, methodologies, and tools, to make investigation about individuals on the basis of information publicly available over the Internet. For this important task, online social networks (OSN) represent nowadays the main source of information, so that large attention should be devoted to any approach that improves the capabilities of investigating over OSNs. The aim of this paper is to highlight that, despite the availability of tools and platforms for OSINT which also exploit OSNs, there is a gap in terms of software engineering perspective. Indeed, there is no a programming paradigm oriented to the abstract concept of online social network, independent of the specific instance of this concept. This resumes the multiple-social-network perspective in a software engineering key, and translates into the definition of a set of meta-APIs allowing the programmer to write generic and polymorphic code, naturally oriented to social-network investigation. This paper, born through the experience of an industrial project, shows the above claim by choosing some relevant fragments of the proposed framework. © 2020 ieee.

关键词： Social networking (online)

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SLPal: Accelerating Long Sequence Alignment on Many-Core and Multi-Core architectures

SLPal: Accelerating Long Sequence Alignment on Many-Core and...

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ieee International conference on Bioinformatics and Biomedicine (ieee BIBM)

作者： Xu, Xiaoming Chan, Yuandong Xu, Kai Zhang, Jikai Wang, Xiaoning Yin, Zekun Liu, Weiguo Shandong Univ Sch Software Jinan Peoples R China Shandong Univ Shenzhen Res Inst Jinan Peoples R China

ISBN: (纸本)9781728162157

Biological Sequence alignment is a fundamental application in bioinformatics. It can be used to identify functionally conserved sequences and find evolutionary relationships between species. To compare entire genomes from different species, biologists increasingly need alignment methods that are efficient enough to handle long sequences, and accurate enough to correctly align the conserved biological features between distant species. Global alignments are important because they reveal the shared order of biological features in the compared species, and produce a more accurate alignment at the base-pair level when the features are in the same order. The best known global alignment algorithm is Needleman-Wunsch, later, BitPAl, a bit parallel algorithm for general, integer scoring global algorithm, provides a new implementation of Needleman-Wunsch algorithm (BitNW). Compared with original Needleman-Wunsch algorithm, BitNW is significantly faster by exploiting bit parallelism. A number of parallel strategies have been proposed to accelerate exact alignment methods. However, most of them failed to align long biological sequences due to quadratic time complexity. In this paper, we propose SLPal, a fast bit-parallel algorithm for accelerating long DNA sequence comparison on Intel many-core and multi-core architectures. In order to fully exploit the computing power of many cores and the 512-bit vector processing units (VPUs), we use a two-level parallelism scheme: coarse-grained thread level and fine-grained VPU level approaches. In thread level, the alignment scoring matrix will be split into small tiles and multiple threads will process these small tiles currently by using Intel TBB library. In the VPU level, the computing kernels are implemented using the Single Instruction Multiple Data (SIMD) instructions, thus, 16 independent integers reside in a 512-bit vector register can be processed simultaneously. The evaluation reveals that our algorithm achieves a stable perfor

关键词： bit parallelism global alignment many-core and multi-core architectures

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Co-Exploration of Neural architectures and Heterogeneous ASIC Accelerator Designs Targeting Multiple Tasks 57

Co-Exploration of Neural Architectures and Heterogeneous ASI...

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57th ACM/ieee Design Automation conference (DAC)

作者： Yang, Lei Yan, Zheyu Li, Meng Kwon, Hyoukjun Lai, Liangzhen Krishna, Tushar Chandra, Vikas Jiang, Weiwen Shi, Yiyu Univ Notre Dame Notre Dame IN 46556 USA Facebook Menlo Pk CA USA Georgia Inst Technol Atlanta GA 30332 USA

ISBN: (纸本)9781728110851

Neural Architecture Search (NAS) has demonstrated its power on various AI accelerating platforms such as Field Programmable Gate Arrays (FPGAs) and Graphic Processing Units (GPUs). However, it remains an open problem how to integrate NAS with Application-Specific Integrated Circuits (ASICs), despite them being the most powerful AI accelerating platforms. The major bottleneck comes from the large design freedom associated with ASIC designs. Moreover, with the consideration that multiple DNNs will run in parallel for different workloads with diverse layer operations and sizes, integrating heterogeneous ASIC sub-accelerators for distinct DNNs in one design can significantly boost performance, and at the same time further complicate the design space. To address these challenges, in this paper we build ASIC template set based on existing successful designs, described by their unique dataflows, so that the design space is significantly reduced. Based on the templates, we further propose a framework, namely ASICNAS, which can simultaneously identify multiple DNN architectures and the associated heterogeneous ASIC accelerator design, such that the design specifications (specs) can be satisfied, while the accuracy can be maximized. Experimental results show that compared with successive NAS and ASIC design optimizations which lead to design spec violations, ASICNAS can guarantee the results to meet the design specs with 17.77%, 2.49 x, and 2.32x reductions on latency, energy, and area and less than 1.6% accuracy loss. To the best of the authors' knowledge, this is the first work on neural architecture and ASIC accelerator design co-exploration.

关键词： Application specific integrated circuits

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Energy Efficiency Enhancement in 5G Heterogeneous Cellular networks Using System Throughput Based Sleep Control Scheme 22

Energy Efficiency Enhancement in 5G Heterogeneous Cellular N...

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22nd ieee International conference on Advanced Communication Technology (ICACT)

作者： Dataesatu, Arif Boonsrimuang, Pornpawit Mori, Kazuo Boonsrimuang, Pisit King Mongkuts Inst Technol Ladkrabang KMITL Fac Engn Bangkok 10520 Thailand Suan Sunandha Rajabhat Univ Fac Ind Technol Bangkok 10300 Thailand Mie Univ Grad Sch Engn Elect & Elect Engn Tsu Mie 5148507 Japan

ISBN: (纸本)9791188428045

Currently, Cellular architectures are designed with an efficient providing infrastructure is one of the critical challenges in 5G dense heterogeneous cellular networks (HetNets). By adding many small base stations (SBSs) in a macro base station (MBS) is one way to support the rapid growth of mobile data communication, high data rate services and to provide continuous coverage. The high number of network elements leads to a significant increase in power consumption. To solve the problem, the SBS on/off algorithm has been introduced to reduce power consumption but also reduced energy efficiency as we called the conventional schemes. This paper we proposed as the SBS switching to sleep state algorithm based on the system throughput (MBS cell throughput and SBS cell throughput) is used the decision criteria for SBS to be in the sleep state. The simulation results, The proposed scheme can reduce the total power consumption of the network and enhance energy efficiency more than the conventional schemes.

关键词： Small cell Sleep control Energy efficiency Power consumption System throughput 5G Heterogeneous cellular network

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Designing Engineering Onboarding for 60+Nationalities 15

Designing Engineering Onboarding for 60+Nationalities

引用

15th ACM/ieee International conference on Global Software Engineering (ICGSE)

作者： Harty, Julian Open Univ Commercetest Ltd High Wycombe Bucks England

ISBN: (纸本)9781450370936

A large international engineering office in Germany needed to double in size in 12 months. We designed an onboarding programme within 3 months to help it do so efficaciously. We wanted to optimize for: fast iterations in the programme rollout, to keep the 'flywheel spinning' by reducing drag on current staff, rapid acceleration where new hires contributed quickly, and smooth integration where new hires adapted to the engineering, company, and country cultures. To reduce drag we onboarded in cohorts and involved existing practitioners in the design and discussion. To encourage contributions quickly we built contributions into the sessions, we also streamlined IT Support. To help new hires adopt the culture we encouraged help and mentoring within and across cohorts. For fast iterations, we incorporated existing islands of onboarding, involved local technical staff in design and delivery of hands-on training, and applied analytics to help improve the practice. And we launched early to bootstrap our learning and evaluation. Our approach worked;new hires were able to make meaningful contributions within a week and they scored the onboarding programme positively (8.5 NPS).

关键词： Collaborative learning Collaboration in software development Mob programming Onboarding

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Total Solar Irradiance Forecasting with Keras Recurrent Neural networks 20th

Total Solar Irradiance Forecasting with Keras Recurrent Neur...

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20th International conference on Computational Science and Its Applications (ICCSA)

作者： Muralikrishna, Amita Vieira, Luis E. A. dos Santos, Rafael D. C. Almeida, Adriano P. Natl Inst Space Res Av Astronautas 1758 Sao Jose Dos Campos Brazil Fed Inst Educ Sci & Technol Sao Paulo Route Presidente Dutra Km 145 Sao Jose Dos Campos Brazil

ISBN: (纸本)9783030588144;9783030588137

The prediction of solar irradiance at the top of the atmosphere is useful for research that analyzes the behavior and response of the different layers of the Earth's atmosphere to variations in solar activity. It would also be useful for the reconstruction of the measurement history (time series) of different instruments that suffered from time failures and discrepancies in scales due to the calibration of equipment. In this work we compare three Keras recurrent neural network architectures to perform forecast of the total solar irradiance. The experiments are part of a larger proposal for modularization of the prediction workflow, which uses digital images of the Sun as input, and aims to make the process modular, accessible and reproducible.

关键词： Recurrent neural network Total solar irradiance Keras

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Asymmetric CDC ROADM Architecture for Efficient Support of Bi-Directional Asymmetric Traffic Demands 22

Asymmetric CDC ROADM Architecture for Efficient Support of B...

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22nd International conference on Transparent Optical networks (ICTON)

作者： Lu, Longjin Li, Yongcheng Zong, Liangjia Mukherjee, Biswanath Shen, Gangxiang Soochow Univ Inst Broadband Res & Innovat IBRI Suzhou Jiangsu Peoples R China Soochow Univ Suzhou Key Lab Adv Opt Commun Network Technol Suzhou Jiangsu Peoples R China Huawei Transmiss Technol Res Dept Shenzhen Guangdong Peoples R China

ISBN: (纸本)9781728184234

New technologies and applications such as data centers and Internet of things keep on emerging in 5G era. Internet traffic is experiencing not only an explosive growth but also an increasing asymmetry in the upstream and downstream directions. However, today most network architectures and optimization approaches are based on the assumption of bi-directionally symmetric traffic demands This choice can cause significant wastage of network capacity when carrying bi-directionally asymmetric traffic demands. To avoid this wastage, in this paper, we propose a novel asymmetric CDC ROADM architecture to efficiently carry bi-directionally asymmetric traffic demands This architecture is flexible to adjust the numbers of ingress and egress fibers in each nodal degree as well as the numbers of transmitters and receivers in each add/drop module according to actual asymmetric traffic demands The new architecture can therefore significantly reduce hardware cost compared to the symmetric architecture. By solving the routing and spectrum assignment (RSA) problem in an elastic optical network (EON), we evaluate the performance of the new ROADM architecture in comparison with the symmetric architecture. Simulation studies show that the asymmetric ROADM architecture can perform close to the symmetric architecture while significantly reducing the numbers of fibers and transmitters/receivers.

关键词： asymmetric ROADM network optimization

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Toward high accuracy and visualization: An interpretable feature extraction method based on genetic programming and non-overlap degree

Toward high accuracy and visualization: An interpretable fea...

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ieee International conference on Bioinformatics and Biomedicine (ieee BIBM)

作者： Li, Zhuang He, Jie Zhang, Xiaotong Fu, Huadong Qin, Jingyan Univ Sci & Technol Beijing Sch Comp & Commun Engn Beijing Peoples R China Univ Sci & Technol Beijing Shunde Grad Sch Foshan Peoples R China Univ Sci & Technol Beijing Beijing Key Lab Knowledge Engn Mat Sci Beijing Peoples R China Univ Sci & Technol Beijing Beijing Adv Innovat Ctr Mat Genome Engn Beijing Peoples R China Univ Sci & Technol Beijing Inst Adv Mat & Technol Beijing Peoples R China Univ Sci & Technol Beijing Sch Mech Engn Beijing Peoples R China

ISBN: (纸本)9781728162157

Genetic programming (GP) has shown promising results in interpretable feature extraction, but few works considered both classification accuracy and data visualization as objectives. Evaluating the extracted features based on the combination of accuracy measures and visualization measures can help to achieve the two objectives simultaneously. However, the exploitation of improper visualization measures and combination methods will decrease the classification accuracy. In this paper, a novel feature extraction method based on GP and non-overlap degree is proposed to extract interpretable features for high accuracy and visualization. And a novel function that maximizes the product of the accuracy of a linear classifier and the non-overlap degree is proposed to evaluate the extracted features. The proposed method, named GP-ANO, is compared with other methods on five medical datasets by six common machine learning methods. The experimental results demonstrate that the GP-ANO method outperforms other compared methods in terms of both classification accuracy and data visualization.

关键词： feature extraction interpretation genetic programming non-overlap degree data visualization

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