scholarly journals Performance Estimation Based Multicriteria Partitioning Approach for Dynamic Dataflow Programs

2016 ◽  
Vol 2016 ◽  
pp. 1-15
Author(s):  
Małgorzata Michalska ◽  
Nicolas Zufferey ◽  
Marco Mattavelli
Keyword(s):  
Design Space ◽  
Performance Estimation ◽  
Experimental Results ◽  
High Quality ◽  
Data Throughput ◽  
Target Architecture ◽  
Execution Model ◽  
Np Complete ◽  
Virtual Platform ◽  
Difficult Challenge

The problem of partitioning a dataflow program onto a target architecture is a difficult challenge for any application design. In general, since the problem is NP-complete, it consists of looking for high quality solutions in terms of maximizing the achievable data throughput. The difficulty is given by the exploration of the design space which results in being extremely large for parallel platforms. The paper describes a heuristic partitioning methodology applicable to dynamic dataflow programs. The methodology is based on two elements: an execution model of the dynamic dataflow program which is used as estimation of the performance for the exploration of the large design space and several partitioning algorithms competing to lead to specific high quality solutions. Experimental results are validated with executions on a virtual platform.

Detecting “DeepFakes” in H.264 Video Data Using Compression Ghost Artifacts

2020 ◽  
Vol 2020 (4) ◽  
pp. 116-1-116-7
Author(s):  
Raphael Antonius Frick ◽  
Sascha Zmudzinski ◽  
Martin Steinebach
Keyword(s):  
Image Forensics ◽  
Video Data ◽  
Experimental Results ◽  
Video Sequences ◽  
The Internet ◽  
Video Content ◽  
High Quality ◽  
The Public

In recent years, the number of forged videos circulating on the Internet has immensely increased. Software and services to create such forgeries have become more and more accessible to the public. In this regard, the risk of malicious use of forged videos has risen. This work proposes an approach based on the Ghost effect knwon from image forensics for detecting forgeries in videos that can replace faces in video sequences or change the mimic of a face. The experimental results show that the proposed approach is able to identify forgery in high-quality encoded video content.

scholarly journals PCDRN: Progressive Cascade Deep Residual Network for Pansharpening

2020 ◽  
Vol 12 (4) ◽  
pp. 676 ◽  
Author(s):  
Yong Yang ◽  
Wei Tu ◽  
Shuying Huang ◽  
Hangyuan Lu
Keyword(s):  
High Resolution ◽  
Loss Function ◽  
High Frequency ◽  
Experimental Results ◽  
Superior Performance ◽  
Residual Network ◽  
High Quality ◽  
Convolution Approach ◽  
Visual Assessments ◽  
Coarse To Fine

Pansharpening is the process of fusing a low-resolution multispectral (LRMS) image with a high-resolution panchromatic (PAN) image. In the process of pansharpening, the LRMS image is often directly upsampled by a scale of 4, which may result in the loss of high-frequency details in the fused high-resolution multispectral (HRMS) image. To solve this problem, we put forward a novel progressive cascade deep residual network (PCDRN) with two residual subnetworks for pansharpening. The network adjusts the size of an MS image to the size of a PAN image twice and gradually fuses the LRMS image with the PAN image in a coarse-to-fine manner. To prevent an overly-smooth phenomenon and achieve high-quality fusion results, a multitask loss function is defined to train our network. Furthermore, to eliminate checkerboard artifacts in the fusion results, we employ a resize-convolution approach instead of transposed convolution for upsampling LRMS images. Experimental results on the Pléiades and WorldView-3 datasets prove that PCDRN exhibits superior performance compared to other popular pansharpening methods in terms of quantitative and visual assessments.

scholarly journals Grounding Action Descriptions in Videos

2013 ◽  
Vol 1 ◽  
pp. 25-36 ◽  
Author(s):  
Michaela Regneri ◽  
Marcus Rohrbach ◽  
Dominikus Wetzel ◽  
Stefan Thater ◽  
Bernt Schiele ◽  
...  
Keyword(s):  
Natural Language ◽  
Recent Work ◽  
Visual Information ◽  
General Purpose ◽  
Experimental Results ◽  
High Quality ◽  
Improve Model ◽  
Model Predictions ◽  
Static Images

Recent work has shown that the integration of visual information into text-based models can substantially improve model predictions, but so far only visual information extracted from static images has been used. In this paper, we consider the problem of grounding sentences describing actions in visual information extracted from videos. We present a general purpose corpus that aligns high quality videos with multiple natural language descriptions of the actions portrayed in the videos, together with an annotation of how similar the action descriptions are to each other. Experimental results demonstrate that a text-based model of similarity between actions improves substantially when combined with visual information from videos depicting the described actions.

scholarly journals Network Threats Mitigation Using Software-Defined Networking for the 5G Internet of Radio Light System

2019 ◽  
Vol 2019 ◽  
pp. 1-22 ◽  
Author(s):  
Krzysztof Cabaj ◽  
Marcin Gregorczyk ◽  
Wojciech Mazurczyk ◽  
Piotr Nowakowski ◽  
Piotr Żórawski
Keyword(s):  
Communication Networks ◽  
Denial Of Service ◽  
Experimental Results ◽  
The Internet ◽  
5G Networks ◽  
Security Framework ◽  
High Quality ◽  
User Experiences ◽  
Wide Range ◽  
Near Future

Currently 5G communication networks are envisioned to offer in a near future a wide range of high-quality services and unfaltering user experiences. In order to achieve this, several issues including security, privacy, and trust aspects need to be solved so that the 5G networks can be widely welcomed and accepted. Considering above, in this paper, we take a step towards these requirements by proposing a dedicated SDN-based integrated security framework for the Internet of Radio Light (IoRL) system that is following 5G architecture design. In particular, we present how TCP SYN-based scanning activities and DHCP-related network threats like Denial of Service (DoS), traffic eavesdropping, etc. can be detected and mitigated using such an approach. Enclosed experimental results prove that the proposed security framework is effective and efficient and thus can be considered as a promising defensive solution.

Language-Independent Type Inference of the Instances from Multilingual Wikipedia

2019 ◽  
Vol 15 (2) ◽  
pp. 22-46 ◽  
Author(s):  
Tianxing Wu ◽  
Guilin Qi ◽  
Bin Luo ◽  
Lei Zhang ◽  
Haofen Wang
Keyword(s):  
Knowledge Base ◽  
State Of The Art ◽  
The State ◽  
Type Inference ◽  
Experimental Results ◽  
High Quality ◽  
New Approach ◽  
Semantic Associations ◽  
Quality Type ◽  
Type Information

Extracting knowledge from Wikipedia has attracted much attention in recent ten years. One of the most valuable kinds of knowledge is type information, which refers to the axioms stating that an instance is of a certain type. Current approaches for inferring the types of instances from Wikipedia mainly rely on some language-specific rules. Since these rules cannot catch the semantic associations between instances and classes (i.e. candidate types), it may lead to mistakes and omissions in the process of type inference. The authors propose a new approach leveraging attributes to perform language-independent type inference of the instances from Wikipedia. The proposed approach is applied to the whole English and Chinese Wikipedia, which results in the first version of MulType (Multilingual Type Information), a knowledge base describing the types of instances from multilingual Wikipedia. Experimental results show that not only the proposed approach outperforms the state-of-the-art comparison methods, but also MulType contains lots of new and high-quality type information.

scholarly journals Practical Aspects of Multiwavelength Analytical Ultracentrifugation

Instruments ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 23 ◽  
Author(s):  
Joseph Pearson ◽  
Helmut Cölfen
Keyword(s):  
Open Source ◽  
Broad Spectrum ◽  
Analytical Ultracentrifugation ◽  
Experimental Results ◽  
Research Groups ◽  
High Quality ◽  
Detection Systems ◽  
Operational Information ◽  
Optical Alignment ◽  
Scientific Fields

Open-source Multiwavelength Analytical Ultracentrifugation (MWL-AUC) detection systems have been evolving for over a decade. Continual advances emerging out of several research groups have brought the instrumentation technology to increasingly higher levels of performance. The capabilities of MWL-AUC have been documented in many publications, demonstrating the applicability of broad spectrum absorbance acquisitions in analytical ultracentrifugation to a wide array of scientific fields. Despite numerous examples of the usefulness and unique advantages of MWL-AUC, the adoption of the technology by more research groups has been slow. The complexity of the hardware, integration within an ultracentrifuge platform and lack of practical construction and operational information is the likely source of reluctance. Here, we clearly describe the challenges facing a researcher considering adopting MWL-AUC technology in their own laboratories, and provide the information necessary to implement and operate a MWL-AUC system. The discussion includes details of detector assembly, optical alignment, and acquisition parameter settings necessary to achieve high quality experimental results.

scholarly journals Dialogue Generation: From Imitation Learning to Inverse Reinforcement Learning

2019 ◽  
Vol 33 ◽  
pp. 6722-6729 ◽  
Author(s):  
Ziming Li ◽  
Julia Kiseleva ◽  
Maarten De Rijke
Keyword(s):  
Reinforcement Learning ◽  
State Of The Art ◽  
The State ◽  
Experimental Results ◽  
Imitation Learning ◽  
Local Optimum ◽  
Inverse Reinforcement Learning ◽  
High Quality ◽  
Overall Performance

The performance of adversarial dialogue generation models relies on the quality of the reward signal produced by the discriminator. The reward signal from a poor discriminator can be very sparse and unstable, which may lead the generator to fall into a local optimum or to produce nonsense replies. To alleviate the first problem, we first extend a recently proposed adversarial dialogue generation method to an adversarial imitation learning solution. Then, in the framework of adversarial inverse reinforcement learning, we propose a new reward model for dialogue generation that can provide a more accurate and precise reward signal for generator training. We evaluate the performance of the resulting model with automatic metrics and human evaluations in two annotation settings. Our experimental results demonstrate that our model can generate more high-quality responses and achieve higher overall performance than the state-of-the-art.

Coating Nano-TiO2 on Optical Fiber with Al(H2PO4)3 Adhesive

2007 ◽  
Vol 280-283 ◽  
pp. 485-488 ◽  
Author(s):  
Yu Hong Zhao ◽  
Jia Chen Liu ◽  
Shun Li ◽  
Yi Rong Liu
Keyword(s):  
Optical Fiber ◽  
Process Parameters ◽  
Coating Thickness ◽  
Fiber Surface ◽  
Tio2 Coating ◽  
Experimental Results ◽  
Coating Process ◽  
High Quality ◽  
Tio2 Photocatalysis

To meet the need of optical fiber photoreactor designed by mechanism of TiO2 photocatalysis, nanometer TiO2 was coated on the surface of optical fiber by dipping nude fibers into an Al(H2PO4)3-contained TiO2 slurry. Effects of slurry conditions, including content of TiO2 and addition of Al(H2PO4)3 adhesive, on coating thickness and quality were determined. Coating process, especially the effect of coating times, was also concerned. Based on the experimental results, fitting slurry conditions and process parameters were suggested for obtaining high-quality TiO2 coating on optical fiber surface.

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