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NTIRE 2023 Quality Assessment of Video Enhancement Challenge

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arXiv 2023年

作者： Liu, Xiaohong Min, Xiongkuo Sun, Wei Zhang, Yulun Zhang, Kai Timofte, Radu Zhai, Guangtao Gao, Yixuan Cao, Yuqin Kou, Tengchuan Dong, Yunlong Jia, Ziheng Li, Yilin Wu, Wei Hu, Shuming Deng, Sibin Xiao, Pengxiang Chen, Ying Li, Kai Zhao, Kai Yuan, Kun Sun, Ming Cong, Heng Wang, Hao Fu, Lingzhi Zhang, Yusheng Zhang, Rongyu Shi, Hang Xu, Qihang Xiao, Longan Ma, Zhiliang Agarla, Mirko Celona, Luigi Rota, Claudio Schettini, Raimondo Huang, Zhiwei Li, Yanan Wang, Xiaotao Lei, Lei Liu, Hongye Hong, Wei Chuang, Ironhead Lin, Allen Guan, Drake Chen, Iris Lou, Kae Huang, Willy Tasi, Yachun Kao, Yvonne Fan, Haotian Kong, Fangyuan Zhou, Shiqi Liu, Hao Lai, Yu Chen, Shanshan Wang, Wenqi Wu, Haoning Chen, Chaofeng Zhu, Chunzheng Guo, Zekun Zhao, Shiling Yin, Haibing Wang, Hongkui Meftah, Hanene Brachemi Fezza, Sid Ahmed Hamidouche, Wassim Déforges, Olivier Shi, Tengfei Mansouri, Azadeh Motamednia, Hossein Bakhtiari, Amir Hossein Aznaveh, Ahmad Mahmoudi Shanghai Jiao Tong University China ETH Zürich Switzerland University of Würzburg Germany Department of Tao Technology Alibaba Group China Kuaishou Technology China Interactive Entertainment Group of Netease Inc Guangzhou China Transsion China Vrobotit Lab Beijing University of Posts and Telecommunications China Hefei University of Technology China Department of Informatics Systems and Communication University of Milano - Bicocca Italy Xiaomi Inc. China China Ji Liang University China FreeTech China Advanced Research Center KKCompany Taiwan ByteDance China MGTV China Fuzhou University China Shopee Information Technology Co. Ltd. China S-Lab Nanyang Technological University Singapore Hunan University China Hangzhou Dianzi University China INSA Rennes CNRS IETR - UMR 6164 Rennes France National Higher School of Telecommunications and ICT Oran Algeria BUAA China Department of Electrical and Computer Engineering Faculty of Engineering Kharazmi University Tehran Iran High Performance Computing Laboratory School of Computer Science Institute for Research in Fundamental Sciences Tehran Iran Cyberspace Research Institute Shahid Beheshti University Tehran Iran

This paper reports on the NTIRE 2023 Quality Assessment of Video Enhancement Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) at CVPR 2023. This challenge is to address a major challenge in the field of video processing, namely, video quality assessment (VQA) for enhanced videos. The challenge uses the VQA Dataset for Perceptual Video Enhancement (VDPVE), which has a total of 1211 enhanced videos, including 600 videos with color, brightness, and contrast enhancements, 310 videos with deblurring, and 301 deshaked videos. The challenge has a total of 167 registered participants. 61 participating teams submitted their prediction results during the development phase, with a total of 3168 submissions. A total of 176 submissions were submitted by 37 participating teams during the final testing phase. Finally, 19 participating teams submitted their models and fact sheets, and detailed the methods they used. Some methods have achieved better results than baseline methods, and the winning methods have demonstrated superior prediction performance. Copyright © 2023, The Authors. All rights reserved.

关键词： Image enhancement

Weight learning in a probabilistic extension of answer set programs

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arXiv 2018年

作者： Lee, Joohyung Wang, Yi School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ United States

LPMLN is a probabilistic extension of answer set programs with the weight scheme derived from that of Markov Logic. Previous work has shown how inference in LPMLN can be achieved. In this paper, we present the concept of weight learning in LPMLN and learning algorithms for LPMLN derived from those for Markov Logic. We also present a prototype implementation that uses answer set solvers for learning as well as some example domains that illustrate distinct features of LPMLN learning. Learning in LPMLN is in accordance with the stable model semantics, thereby it learns parameters for probabilistic extensions of knowledge-rich domains where answer set programming has shown to be useful but limited to the deterministic case, such as reachability analysis and reasoning about actions in dynamic domains. We also apply the method to learn the parameters for probabilistic abductive reasoning about actions. Copyright © 2018, The Authors. All rights reserved.

关键词： Markov processes

Local descent for temporal logic falsification of cyber-physical systems (extended technical report)

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arXiv 2018年

作者： Yaghoubi, Shakiba Fainekos, Georgios School of Computing Informatics Decision Systems Engineering Arizona State University TempeAZ United States

One way to analyze Cyber-Physical systems is by modeling them as hybrid automata. Since reachability analysis for hybrid nonlinear automata is a very challenging and computationally expensive problem, in practice, engineers try to solve the requirements falsification problem. In one method, the falsification problem is solved by minimizing a robustness metric induced by the requirements. This optimization problem is usually a non-convex non-smooth problem that requires heuristic and analytical guidance to be solved. In this paper, functional gradient descent for hybrid systems is utilized for locally decreasing the robustness metric. The local descent method is combined with Simulated Annealing as a global optimization method to search for unsafe behaviors. Copyright © 2018, The Authors. All rights reserved.

关键词： Crime

Construction and usage of a human body common coordinate framework comprising clinical, semantic, and spatial ontologies

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arXiv 2020年

作者： Börner, Katy Quardokus, Ellen M. Herr, Bruce W. Cross, Leonard E. Record, Elizabeth G. Ju, Yingnan Bueckle, Andreas D. Sluka, James P. Silverstein, Jonathan C. Browne, Kristen M. Jain, Sanjay Wasserfall, Clive H. Jorgensen, Marda L. Spraggins, Jeffrey M. Patterson, Nathan H. Musen, Mark A. Weber, Griffin M. Department of Intelligent Systems Engineering Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN United States Department of Biomedical Informatics University of Pittsburgh School of Medicine PittsburghPA United States Department of Health and Human Services National Institute of Allergy and Infectious Diseases National Institutes of Health BethesdaMD United States Department of Medicine Washington University School of Medicine Saint LouisMO United States Departments of Pathology and Pediatrics University of Florida GainesvilleFL United States Mass Spectrometry Research Center Vanderbilt University NashvilleTN United States Stanford Center for Biomedical Informatics Research Stanford University StanfordCA United States Department of Biomedical Informatics Harvard Medical School BostonMA United States

The National Institutes of Health’s (NIH) Human Biomolecular Atlas Program (HuBMAP) aims to create a comprehensive high-resolution atlas of all the cells in the healthy human body. Multiple laboratories across the United States are collecting tissue specimens from different organs of donors who vary in sex, age, and body size. Integrating and harmonizing the data derived from these samples and "mapping" them into a common three-dimensional (3D) space is a major challenge. The key to making this possible is a "Common Coordinate Framework" (CCF), which provides a semantically annotated, 3D reference system for the entire body. The CCF enables contributors to HuBMAP to "register" specimens and datasets within a common spatial reference system, and it supports a standardized way to query and "explore" data in a spatially and semantically explicit manner. This paper describes the construction and usage of a CCF for the human body and its reference implementation in HuBMAP. The CCF consists of (1) a CCF Clinical Ontology, which provides metadata about the specimen and donor (the "who");(2) a CCF Semantic Ontology, which describes "what" part of the body a sample came from and details anatomical structures, cell types, and biomarkers (ASCT+B);and (3) a CCF Spatial Ontology, which indicates "where" a tissue sample is located in a 3D coordinate system. CCF design starts with domain experts manually selecting terms from existing ontologies and organizing them in so called ASCT+B tables that guide the development of the CCF Semantic Ontology. The ASCT+B tables also guide the design of the HuBMAP CCF Reference Object Library which was initially populated with 3D reference organ models obtained from the Visible Human project provided by the National Library of Medicine;the CCF Spatial Ontology represents the spatial size, position, and orientation of tissue data in relationship to the reference organ. The CCF Clinical Ontology is a proper subset of clinical metadata associated w

关键词： Ontology

Solar Energy Harvesting Assessments from Migrating Northern Elephant Seals

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Solar Energy Harvesting Assessments from Migrating Northern ...

OCEANS - Europe

作者： Michael W. Shafer Lauren Adoram-Kershner Colt Morris Michael Eck Paul G. Flikkema Rachel Holser Daniel Costa Department of Mechanical Engineering Northern Arizona University School of Informatics Computing and Cyber Systems Northern Arizona University Costa Lab University of California Santa Cruz

Marine wildlife telemetry systems are constrained in many of the same ways as their terrestrial and avian counterparts. Battery limitations, deployment duration, data sampling and communication energy requirements, and wide dispersion or migration routes conspire to reduce the fidelity of the data records. Terrestrial and avian wildlife telemetry modules can utilize solar power for some species to supply or supplement tag energy budgets. However, photovoltaic cells are absent from the majority of marine telemetry modules, both wildlife-mounted and robotic. In this paper, we present the development and deployment of custom photovoltaic assessment modules (CPAMs) designed to measure solar power in the marine environement. These devices collected current-voltage measurements on a monocrystalline silicon solar cell once per second over the course of four months. This work discusses the device functionality and design updates, calibration procedures, and the results of an oceanic deployment. During this deployment, CPAMs were mounted to four adult female northern elephant seals (Mirounga angustirostris) at the colony at Año Nuevo State Reserve (CA, USA) prior to their spring migration in the Pacific Ocean. Deployment results, including power production and energy results from the CPAM data record are presented. The elephant seals were at sea for between 76 and 107 days and provided measurements from a large geographic area between Santa Cruz, California and the Aleutian Islands of Alaska at depths up to 1287 m. We highlight how the recorded energy collection capacity of this cell compares to the daily energy usage of typical marine telemetry modules and show that even for animals that briefly surface, power harvesting electronics should be optimized for the surface environment.

关键词： Temperature measurement Sea measurements Voltage measurement Seals Ocean temperature Resistors Sea surface

Thermosim: Deep learning based framework for modeling and simulation of thermal-aware resource management for cloud computing environments

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arXiv 2020年

作者： Gill, Sukhpal Singh Tuli, Shreshth Toosi, Adel Nadjaran Cuadrado, Felix Garraghan, Peter Bahsoon, Rami Lutfiyya, Hanan Sakellariou, Rizos Rana, Omer Dustdar, Schahram Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom Delhi India Faculty of Information Technology Monash University ClaytonVIC Australia Spain School of Computing and Communications Lancaster University United Kingdom School of Computer Science University of Birmingham Birmingham United Kingdom Department of Computer Science University of Western Ontario LondonON Canada School of Computer Science University of Manchester Oxford Road ManchesterUK United Kingdom School of Computer Science and Informatics Cardiff University CardiffUK United Kingdom Distributed Systems Group Vienna University of Technology Vienna Austria Laboratory School of Computing and Information Systems University of Melbourne Australia

Current cloud computing frameworks host millions of physical servers that utilize cloud computing resources in the form of different virtual machines. Cloud Data Center (CDC) infrastructures require significant amounts of energy to deliver large scale computational services. Moreover, computing nodes generate large volumes of heat, requiring cooling units in turn to eliminate the effect of this heat. Thus, overall energy consumption of the CDC increases tremendously for servers as well as for cooling units. However, current workload allocation policies do not take into account effect on temperature and it is challenging to simulate the thermal behaviour of CDCs. There is a need for a thermal-aware framework to simulate and model the behaviour of nodes and measure the important performance parameters which can be affected by its temperature. In this paper, we propose a lightweight framework, ThermoSim, for modelling and simulation of thermal-aware resource management for cloud computing environments. This work presents a Recurrent Neural Network based deep learning temperature predictor for CDCs which is utilized by ThermoSim for lightweight resource management in constrained cloud environments. ThermoSim extends the CloudSim toolkit helping to analyse the performance of various key parameters such as energy consumption, service level agreement violation rate, number of virtual machine migrations and temperature during the management of cloud resources for execution of workloads. Further, different energy-aware and thermal-aware resource management techniques are tested using the proposed ThermoSim framework in order to validate it against the existing framework (Thas). The experimental results demonstrate the proposed framework is capable of modelling and simulating the thermal behaviour of a CDC and ThermoSim framework is better than Thas in terms of energy consumption, cost, time, memory usage and prediction accuracy. Copyright © 2020, The Authors. All rights rese

关键词： Cloud computing

Identifying Bottlenecks in Serial Production Lines with Geometric Machines: Indicators and Rules

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IFAC-PapersOnLine 2017年第1期50卷 13952-13957页

作者： Kang, Yunyi Ju, Feng School of Computing Informatics and Decision Systems Engineering Arizona State University State Key Laboratory of Automotive Simulation and Control Jilin University TempeChangchun85281 AZ United States School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ85281 United States

In this paper, we develop a practical decision making tool to analyze and detect system bottlenecks for serial production lines with multiple Geometric machines and finite buffers. Systematic approaches are investigated to quantify the overall system performance-the production rate and its interactions with characteristics of individual machines. Two types of bottlenecks are defined and their corresponding indicators are derived to provide guidelines on improving system performance. These methods provide quantitative tools for modeling, analyzing, and improving manufacturing systems where machine's downtime is significantly longer than the cycle time. © 2017

关键词： Geometry decision making Manufacture Bottleneck analysis decision making tool Finite buffer Improving systems Production rates Quantitative tool Serial production line Throughput analysis

Plan explanations as model reconciliation - An empirical study

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arXiv 2018年

作者： Chakraborti, Tathagata Sreedharan, Sarath Grover, Sachin Kambhampati, Subbarao School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ85281 United States

Recent work in explanation generation for decision making agents has looked at how unexplained behavior of autonomous systems can be understood in terms of differences in the model of the system and the human's understanding of the same, and how the explanation process as a result of this mismatch can be then seen as a process of reconciliation of these models. Existing algorithms in such settings, while having been built on contrastive, selective and social properties of explanations as studied extensively in the psychology literature, have not, to the best of our knowledge, been evaluated in settings with actual humans in the loop. As such, the applicability of such explanations to human-AI and human-robot interactions remains suspect. In this paper, we set out to evaluate these explanation generation algorithms in a series of studies in a mock search and rescue scenario with an internal semi-autonomous robot and an external human commander. We demonstrate to what extent the properties of these algorithms hold as they are evaluated by humans, and how the dynamics of trust between the human and the robot evolve during the process of these interactions. Copyright © 2018, The Authors. All rights reserved.

关键词： Human robot interaction

Tenant-based access control model for multi-tenancy and sub-tenancy architecture in Software-as-a-Service

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Frontiers of Computer Science 2017年第3期11卷 465-484页

作者： Qiong zuo Meiyi XIE Guanqiu QI Hong ZHU School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ 85287 USA

Software-as-a-Service （SaaS） introduces multi- tenancy architecture （MTA）. Sub-tenancy architecture （STA）, is an extension of MTA, allows tenants to offer services for subtenant developers to customize their applications in the SaaS infrastructure. In a STA system, tenants can create sub- tenants, and grant their resources （including private services and data） to their subtenants. The isolation and sharing re- lations between parent-child tenants, sibling tenants or two non-related tenants are more complicated than those between tenants in MTA. It is important to keep service components or data private, and at the same time, allow them to be shared, and support application customizations for tenants. To ad- dress this problem, this paper provides a formal definition of a new tenant-based access control model based on administra- tive role-based access control （ARBAC） for MTA and STA in service-oriented SaaS （called TMS-ARBAC）. Autonomous areas （AA） and AA-tree are proposed to describe the auton- omy of tenants, including their isolation and sharing relation- ships. Authorization operations on AA and different resource sharing strategies are defined to create and deploy the access control scheme in STA models. TMS-ARBAC model is ap- plied to design a geographic e-Science platform.

关键词： Software-as-a-Service （SaaS） multi-tenancy architecture （MTA） sub-tenancy architecture （STA） rolebased access control （RBAC） model tenant-based access control model