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20th IEEE Symposium on Computers and Communication, ISCC 2015

作者： Stihler, Maicon Santin, Altair O. Marcon, Arlindo L. Federal Center for Technological Education-CEFET-MG Department of Computing and Mechanics LeopoldinaMG Brazil Pontifical Catholic University of Parana-PUCPR Graduate Program on Computer Science-PPGIa CuritibaPR Brazil

ISBN: (纸本)9781467371940

Managing UCONabc policies in modern distributed computing systems is a challenge for traditional approaches. The provisioning model has trouble to keep track and to synchronize large numbers of distributed policies, outsourcing model may suffer from network overhead and single point of failure. This paper describes an approach to manage distributed UCONabc policies, derived from the combination of authorization assertions and policy templates. It combines the benefits of provisioning and outsourcing, eliminating their respective drawbacks. Prototyping details and performance evaluation are shown, messages are 42.7% smaller than provisioning and response times are faster than outsourcing. © 2015 IEEE.

关键词： Outsourcing

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Improvement of Spatial Ambiguity in Multi-Channel Speech Separation Using Channel Attention

Improvement of Spatial Ambiguity in Multi-Channel Speech Sep...

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2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2021

作者： Hong, Qian-Bei Wu, Chung-Hsien Nguyen, Thanh Binh Wang, Hsin-Min National Cheng Kung University and Academia Sinica Graduate Program of Multimedia Systems and Intelligent Computing Tainan Taiwan National Cheng Kung University Department of Computer Science and Information Engineering Tainan Taiwan

ISBN: (纸本)9789881476890

Multi-channel speech separation has been successfully applied in a complex real-world environment such as the far-field condition. The common solution to deal with the far-field condition is using a multi-channel signal captured by a structured microphone array and leveraging the inner difference between channels to enhance the speech separation performance. The spatial feature has been widely used in recent speech separation research. This feature appears to be insufficient when the location information becomes ambiguous. This is known as the spatial ambiguity problem. In order to deal with the spatial ambiguity problem, this study proposes an attention mechanism for the Temporal-Spatial Neural Filter (TSNF), in which the channel attention on merged features and the feature map of 1D convolution block in the temporal convolution network is proposed. The proposed method is evaluated on the multi-channel reverberant dataset which is built based on the WSJ0-2mix dataset. The dataset is simulated in the real-environment room by using the Room Impulse Response generator. In the experimental results, the proposed methods produced the SI -SNR improvement of about 1.2dB in close speakers' case, while a small decrease of 0.1dB in other cases. © 2021 APSIPA.

关键词： Convolution

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The power of fair information practices – A control agency approach 26

The power of fair information practices – A control agency ...

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26th Australasian Conference on Information Systems, ACIS 2015

作者： Libaque-Saenz, Christian Fernando Chang, Younghoon Wong, Siew Fan Lee, Hwansoo School of Engineering Universidad del Pacífico Lima Peru Department of Computing and Information Systems Sunway University Selangor Malaysia IT Law Program Graduate School Dankook University Yongin Korea Republic of

ISBN: (纸本)9780646953373

Most companies’ new business practices are based on customer data. These practices have raised privacy concerns because of the associated risks. Privacy laws require companies to gain customer consent before using their information, which stands as the biggest roadblock to monetise this asset. Privacy literature suggests that reducing privacy concerns and building trust may increase individuals’ intention to authorise the use of personal information. Fair information practices (FIPs) are potential means to achieve this goal. However, there is lack of empirical evidence on the mechanisms through which the FIPs affect privacy concerns and trust. This research argues that FIPs load individuals with control, which has been found to influence privacy concerns and trust level. We will use an experimental design methodology to conduct the study. The results are expected to have both theoretical and managerial implications. © 2015 Libaque-Saenz et al.

关键词： Data privacy

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Audio-Driven Facial Landmark Generation in Violin Performance using 3DCNN Network with Self Attention Model 48

Audio-Driven Facial Landmark Generation in Violin Performanc...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Lin, Ting-Wei Liu, Chao-Lin Su, Li Taiwan International Graduate Program Social Networks and Human-Centered Computing Taiwan Academia Sinica Institute of Information Science Taipei Taiwan National Chengchi University Department of Computer Science Taipei Taiwan

ISBN: (纸本)9781728163277

In a music scenario, both auditory and visual elements are essential to achieve an outstanding performance. Recent research has focused on the generation of body movements or fingering from audio in music performance. The audio-driven face generation technique in music performance is still deficient. In this paper, we compile a violin soundtrack and facial expression dataset (VSFE) for modeling facial expressions in violin performance. To our knowledge, this is the first dataset mapping the relationship between violin performance audio and musicians' facial expressions. We then propose a 3DCNN network with self-attention and residual blocks for audio-driven facial expression generation. In the experiments, we compare our methods with three baselines on talking face generation. The codes and dataset are available on the Github (https://***/kevinlin91/icassp-music2face). © 2023 IEEE.

关键词： Music

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Climate Precipitation Prediction by Neural Network

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Journal of Mathematics and System Science 2015年第5期5卷 207-213页

作者： Juliana Aparecida Anochi Haroldo Fraga de Campos Velho Applied Computing Graduate Program National Institute for Space Research (INPE) Brazil. Associated Laboratory for Computing and Applied Mathematics National Institute for Space Research (INPE).

In this work a neural network model for climate forecasting is presented. The model is built by training a neural network with available reanalysis data. In order to assess the model, the development methodology considers the use of data reduction strategies that eliminate data redundancy thus reducing the complexity of the models. The results presented in this paper considered the use of Rough Sets Theory principles in extracting relevant information from the available data to achieve the reduction of redundancy among the variables used for forecasting purposes. The paper presents results of climate prediction made with the use of the neural network based model. The results obtained in the conducted experiments show the effectiveness of the methodology, presenting estimates similar to observations.

关键词： Climate Prediction Neural Networks Rough Sets Theory

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Accuracy-Exploration Model for Low-Energy and Gates-Free Approximate Adder Compressors

Accuracy-Exploration Model for Low-Energy and Gates-Free App...

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IEEE International Conference on Electronics, Circuits and Systems (ICECS)

作者： Leonardo Antonietti Morgana da Rosa Eduardo da Costa Rafael Soares Graduate Program on Computing - Federal University of Pelotas (UFPel) Pelotas Brazil Gruduate Program on Electronic Engineering and Computing - Catholic University of Pelotas (UCPel) Pelotas Brazil

ISBN: (数字)9798350377200

ISBN: (纸本)9798350377217

This paper proposes a model for accurately exploring approximate adder compressors (AxAC) utilizing gates-free logic. As case studies, we explore energy-efficient architectures of approximate 3–2 (Ax3-2), 4–2 (Ax4-2), and 5–2 (Ax5-2) adder compressors (AC), focusing exclusively on gates-free in the critical path. This model for the accuracy analysis of AxACs is essential for estimating the optimal arrangements with repetition (AR) of inputs that are the way outputs for these compressors. For instance, the exact 4–2 AC has five inputs (A, B, C, D, and Cin) and three outputs (Cout, Carry, and Sum). Specifically, the Ax3-2 AC generates nine possible architectural-space gates-free AR, the Ax4-2 AC generates 125, and the Ax5-2 AC generates 2, 401 possible output AR. To estimate all output AR, we implemented the accuracy-exploration model in Python. After identifying the best AR, we created a Pareto front addressing the trade-offs between accuracy, energy, and area. The Ax3-2, Ax4-2, and Ax5-2 proposals demonstrate substantial energy and area efficiency improvements while maintaining high accuracy.

关键词： Analytical models Accuracy Focusing Logic gates Compressors Energy efficiency Proposals Integrated circuit modeling Adders Electronic circuits

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A Physical-Based Artificial Neural Networks Compact Modeling Framework for Emerging FETs

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IEEE Transactions on Electron Devices 2024年第1期71卷 223-230页

作者： Yang, Ya-Shu Li, Yiming Kola, Sekhar Reddy Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory The Institute of Communications Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Institute of Communications Engineering Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan

We report a compact modeling framework based on the Grove-Frohman (GF) model and artificial neural networks (ANNs) for emerging gate-all-around (GAA) MOSFETs. The framework consists of two ANNs;the first ANN constructed with the drain current model not only can capture the main trend of device I - V characteristics but also can predict its variation even when the amount of training data for the ANN is insufficient or outside the range of applied biases. The second one is then designed to improve the model accuracy by further minimizing the errors between the target and the model outputs. We implement the proposed framework to accurately model emerging GAA nanosheet (NS) MOSFETs and complementary FETs (CFETs) without suffering from divergent issues in circuit simulation. In addition, nonphysical behaviors, such as nonzero current at zero bias, do not occur in the modeling framework. Compared to recently reported machine-learning (ML) models, our approach can achieve a similar level of model accuracy with merely 20% amount of the training data. © 1963-2012 IEEE.

关键词： Neural networks

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ERP-Based CTU Splitting Early Termination for Intra Prediction of 360 videos

ERP-Based CTU Splitting Early Termination for Intra Predicti...

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IEEE Visual Communications and Image Processing (VCIP)

作者： Bernardo Beling Iago Storch Luciano Agostini Bruno Zatt Sergio Bampi Daniel Palomino Video Technology Research Group (ViTech) Graduate Program in Computing (PPGC) Federal University of Pelotas (UFPel) Brazil Graduate Program in Computing (PPGC) Federal University of Rio Grande do Sul (UFRGS) Brazil

ISBN: (数字)9781728180687

ISBN: (纸本)9781728180694

This work presents an Equirectangular projection (ERP) based Coding Tree Unit (CTU) splitting early termination algorithm for the High Efficiency Video Coding (HEVC) intra prediction of 360-degree videos. The proposed algorithm adaptively employs early termination in the HEVC CTU splitting based on distortion properties of the ERP projection, that generate homogeneous regions at the top and bottom portion of a video frame. Experimental results show an average of 24% time saving with 0.11% coding efficiency loss, significantly reducing the encoding complexity with minor impacts in the encoding efficiency. Besides, solution presents the best results considering the relation between time saving and coding efficiency when compared with all related works.

关键词： Videos Encoding Complexity theory Distortion Two dimensional displays Prediction algorithms Standards

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HAEE: Question Classification Using Hierarchical Intra-Attention Enhancement Encoder

HAEE: Question Classification Using Hierarchical Intra-Atten...

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26th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2021

作者： Wang, Jen-Wei Chen, Kai-Hsiang Huang, Jen-Wei National Cheng Kung University Department of Electrical Engineering Tainan Taiwan National Cheng Kung University and Academia Sinica Graduate Program for Multimedia Systems and Intelligent Computing Taiwan

ISBN: (纸本)9781665408257

With the development of E-commerce, an Automated Question-Answering system takes a crucial part in customer service. Question classification, which assigns labels to questions according to the answer types, is one of the tasks in question answering. Previous methods usually used handcraft features like named entity recognition, but it needs the predefined dictionary or tools. The machine learning approaches are recently applied to this task and achieve high accuracy. In this paper, we proposed HAEE, a Hierarchical intra-Attention Enhancement Encoder which composed of bidirectional GRUs and intra-attentions. In addition, we adopt the character input to address the issue of the OOV (Out-Of-Vocabulary) problem and create multiple intra-attentions to simulate the certain relationships between characters (Chinese) or words (English) to enhance the influence of tokens on the sentence. We evaluate the HAEE model in an actual corporate setting and several datasets. As shown in the experimental results, our HAEE model outperforms the existing state-of-the-art models on question classification tasks, especially for the Chinese corpus. © 2021 IEEE.

关键词： Signal encoding

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An Energy Efficient Mesh LNN Routing Protocol Based on Ant Colony optimization

An Energy Efficient Mesh LNN Routing Protocol Based on Ant C...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Vinícius de Figueiredo Marques Janine Kniess Rafael Stubs Parpinelli Graduate Program in Applied Computing Santa Catarina State University Joinville SC Brazil

Low-power and Lossy network (LNN) is commonly deployed in Internet of Things applications. It consists of a considerable amount of devices, also known as motes, with sensory capacity and wireless connectivity deployed in a wide geographical area. Such devices face limitations in terms of energy, memory and processing. A common topology in LNN is a mesh-like one. The communication between nodes often happens in a multi-hop fashion due to their limited transmission range. There is a need of efficient routing protocols, in terms of energy consumption. The present paper depicts a routing algorithm based on ant colony optimization. It also shows details about its implementation in the Contiki OS network system and analysis of its performance in comparison with the default Contiki's mesh routing protocol. Results shown that the proposed algorithm had a better performance in terms of packet delivery rate, duty cycling and energy consumption.

关键词： Routing protocols Energy consumption Routing Measurement Mathematical model Ant colony optimization Wireless sensor networks

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