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arXiv 2019年

作者： Niven, Timothy Kao, Hung-Yu Intelligent Knowledge Management Lab Department of Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan

We are surprised to find that BERT’s peak performance of 77% on the Argument Reasoning Comprehension Task reaches just three points below the average untrained human baseline. However, we show that this result is entirely accounted for by exploitation of spurious statistical cues in the dataset. We analyze the nature of these cues and demonstrate that a range of models all exploit them. This analysis informs the construction of an adversarial dataset on which all models achieve random accuracy. Our adversarial dataset provides a more robust assessment of argument comprehension and should be adopted as the standard in future work. Copyright © 2019, The Authors. All rights reserved.

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A Task Allocation Method for Stream Processing with Recovery Latency Constraint

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Journal of computer science & Technology 2018年第6期33卷 1125-1139页

作者： Hong-Liang Li Jie Wu Zhen Jiang Xiang Li Xiao-Hui Wei College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education Changchun 130012 China Department of Computer and Information Sciences Temple University Philadelphia PA 19122 U.S.A. Department of Computer Science West Chester University of Pennsylvania West Chester PA 19383 U.S.A.

Stream processing applications continuously process large amounts of online streaming data in real time or nearreal time. They have strict latency constraints. However, the continuous processing makes them vulnerable to any failures,and the recoveries may slow down the entire processing pipeline and break latency constraints. The upstream backupscheme is one of the most widely applied fault-tolerant schemes for stream processing systems. It introduces complexbackup dependencies to tasks, which increases the difficulty of controlling recovery latencies. Moreover, when dependenttasks are located on the same processor, they fail at the same time in processor-level failures, bringing extra recovery latencies that increase the impacts of failures. This paper studies the relationship between the task allocation and therecovery latency of a stream processing application. We present a correlated failure effect model to describe the recoverylatency of a stream topology in processor-level failures under a task allocation plan. We introduce a recovery-latency awaretask allocation problem （RTAP） that seeks task allocation plans for stream topologies that will achieve guaranteed recoverylatencies. We discuss the difference between RTAP and classic task allocation problems and present a heuristic algorithmwith a computational complexity of O（n log2 n） to solve the problem. Extensive experiments were conducted to verify thecorrectness and effectiveness of our approach. It improves the resource usage by 15%-20% on average.

关键词： stream processing task allocation fault-tolerance upstream backup, recovery latency

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Predictive analytics and the return of "research" information to participants 1

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AHFE Virtual Conference on the Human Side of Service engineering, 2020

作者： Wang, Shengzhi Lee, Ellen E. Zywicki, Benjamin Kim, Ho-Cheol Jeste, Dilip Nebeker, Camille Computer Science and Engineering Jacobs School of Engineering University of California San Diego La Jolla CA United States Department of Psychiatry School of Medicine University of California San Diego La Jolla CA United States Sam and Rose Stein Institute for Research on Aging University of California San Diego La Jolla CA United States Scalable Knowledge Intelligence IBM Research-Almaden San JoseCA United States Department of Neuroscience School of Medicine University of California San Diego La Jolla CA United States Department of Family Medicine and Public Health School of Medicine University of California San Diego La Jolla CA United States

ISBN: (数字)9783030510572

ISBN: (纸本)9783030510565

The World Health Organization (WHO) estimates older adults aged 60+ will double by 2050 with 80% living in low to moderate income countries. As remote research studies supported by digital devices increase separation between researchers and participants, it is important to maintain participant trust. Research participants have expressed an interest in accessing both group and individual level results, which are not readily available. To bridge this gap, we engaged residents of a local continuing care senior housing community (CCSHC) to co-design documents used to convey information about study results. The process informed the refinement of informational materials for communicating scientific research that the CCSHC community considers accessible and meaningful. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.

关键词： Digital devices

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Genomic perspective on sociosexual behavior: Quantitative analysis of receptor sequences in vertebrates

Next Research

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Next Research 2025年第2期2卷

作者： Moumita Sil Debaleena Nawn Sk. Sarif Hassan Subhajit Chakraborty Arunava Goswami Pallab Basu Lalith Roopesh Emma Wu Kenneth Lundstrom Vladimir N. Uversky Biological Science Division Indian Statistical Institute 203 B.T Road Kolkata 700108 West Bengal India Department of Computer Science and Engineering Adamas University Adamas Knowledge City Barasat - Barrackpore Road Kolkata 700126 West Bengal India Department of Mathematics Pingla Thana Mahavidyalaya Maligram Paschim Medinipur 721140 West Bengal India School of Physics University of the Witwatersrand Johannesburg Braamfontein 2000 South Africa Department of Molecular Medicine Morsani College of Medicine University of South Florida Tampa FL 33612 USA PanTherapeutics Rte de Lavaux 49 Lutry CH1095 Switzerland

Research has shown that genetics and epigenetics regulate mating behavior across multiple species. Previous studies have generally focused on the signaling pathways involved and spatial distribution of the associated receptors. However a thorough quantitative characterization of the receptors involved may offer deeper insight into mating behavioral patterns. Here oxytocin, arginine-vasopressin 1a, dopamine 1, and dopamine 2 receptors were investigated across 76 vertebrate species. The receptor sequences were characterized by polarity-based randomness, amino acid frequency-based Shannon entropy and Shannon sequence variability, intrinsic protein disorder, binding affinity, stability and pathogenicity of homology-based SNPs, structural and physicochemical features. Hierarchical clustering of species was derived based on structural and physicochemical features of the four receptor sequences separately, which eventually led to proximal relationships among 29 species. Humans were found to be significantly distant phylogenetically from the prairie voles, a representative of monogamous species based on sociosexual behavior. Furthermore, the mouse (polygamous), the prairie deer mouse (polygamous), and the prairie vole (monogamous) although being proximally related (based on quantitative genomics of receptors), differed in their sociosexual behavioral pattern, mostly, due to behavioral epigenetic regulations. This study adds a perspective that receptor genomics does not directly translate to behavioral patterns.

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A biofuel-powered study with deep learning neural networks and Dragonfly Algorithm: Optimizing CRDi engine performance with ZnO nanoparticles and cotton seed methyl ester

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Energy 2025年 332卷

作者： Manzoore Elahi M. Soudagar Hua-Rong Wei Asif Afzal Vikram Sundara Yasser Fouad Fahad Awjah Almehmadi Sagar Shelare Shubham Sharma Teku Kalyani Yashwant Singh Bisht Saiful Islam College of Engineering Lishui University 323000 Lishui Zhejiang China Lishui Industrial Technology Research Institute Lishui University Lishui 323000 Zhejiang China Centre for Promotion of Research Graphic Era (Deemed to be University) Clement Town Dehradun India Department of Photoelectric Engineering Lishui University Lishui 323000 China University Centre for Research & Development Department of Computer Science and Engineering Chandigarh University Gharuan Mohali Punjab India Centre for Research Impact and Outcome Chitkara University Institute of Engineering and Technology Chitkara University Rajpura 140401 Punjab India Department of Applied Mechanical Engineering College of Applied Engineering Muzahimiyah Branch King Saud University P.O. Box 800 11421 Riyadh Saudi Arabia Mechanical Engineering Department Priyadarshini College of Engineering Hingna Road Nagpur 440019 Maharashtra India Research and Innovation Cell Rayat Bahra University Mohali Punjab India Research and Innovation Cell Bahra University Waknaghat Himachal Pradesh Solan India Department of Technical Sciences Western Caspian University Baku Azerbaijan Department of Mechanical Engineering Lloyd Institute of Engineering & Technology Knowledge Park II Greater Noida Uttar Pradesh 201306 India Department of Mechanical Engineering Raghu Engineering College Dakamarri 531162 Andhra Pradesh India Department of Mechanical Engineering Uttaranchal Institute of Technology Uttaranchal University Dehradun 248007 India Civil Engineering Department College of Engineering King Khalid University Abha 61421 Saudi Arabia

Biodiesel is a non-toxic, carbon-neutral alternative to petroleum diesel that works with existing engines. Wide acceptance is hindered by excessive viscosity, poor cold flow, and weak oxidative stability. Incorporating nanomaterials, such as ZnO nanoparticles, has shown potential in enhancing biodiesel's properties. Previous studies have improved biofuel formulations or engine optimization, but a comprehensive strategy using advanced modeling and optimization techniques is lacking. In the present investigation, the fuel properties were enhanced by addition of ethanol as oxygenated additives and zinc oxide (ZnO) nanoparticles. The engine combustion characters are modelled using deep learning neural networks (DNN) and single-layered neural networks (ANN). Using wider network topology, experimentation with different number of neurons of hidden layer is performed to obtain the optimal coefficient of determination (R-squared). Engine characteristics like brake thermal efficiency (BTE), carbon monoxide (CO), smoke, Hydrocarbon (HC), and ignition delay (ID) are optimized using dragonfly algorithm (DA). Single objective optimization using DA and multi-objective optimization using DA (MODA) is carried out. The DA and MODA are executed for number of cycles and the optimal values and pareto fronts are analyzed. ANN modelling has shown lower in prediction of the engine combustion characters while DNN is a big success. Deep learning models accurately predicted key engine parameters like heat release rate (HRR) and in-cylinder pressure (ICP), achieving R 2 > 0.95. The engine emissions are within an acceptable range, and the BTE is within the range of 20 %–32 % as a result of the engine performance optimization. The optimization of engine characteristics is achieved through the incorporation of nanoparticles in biodiesel. This study underscores the potential of combining advanced biofuel formulations, machine learning, and nature-inspired optimization to create eco-friendly and e

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A Markov Traffic Model for Signalized Traffic Networks Based on Bayesian Estimation

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IFAC-PapersOnLine 2020年第2期53卷 15029-15034页

作者： S.Y. Liu S. Lin Y.B. Wang B. De Schutter W.H.K. Lam School of Computer Science and Technology University of Chinese Academy of Sciences Beijing 100089 China Key Lab of Big Data Mining and Knowledge Management Chinese Academy of Sciences College of Civil Engineering and Architecture Zhejiang University PR China Delft Center for Systems and Control Delft University of Technology The Netherlands Department of Civil and Structural Engineering The Hong Kong Polytechnic University Hong Kong SAR China

In order to better understand the stochastic dynamic features of signalized traffic networks, we propose a Markov traffic model to simulate the dynamics of traffic link flow density for signalized urban traffic networks with demand uncertainty. In this model, we have four different state modes for the link according to different congestion levels of the link. Each link can only be in one of the four link state modes at any time, and the transition probability from one state to the other state is estimated by Bayesian estimation based on the distributions of the dynamic traffic flow densities, and the posterior probabilities. Therefore, we use a first-order Markov Chain Model to describe the dynamics of the traffic flow evolution process. We illustrate our approach for a small traffic network. Compared with the data from the microscopic traffic simulator SUMO, the proposed model can estimate the link traffic densities accurately and can give a reliable estimation of the uncertainties in the dynamic process of signalized traffic networks.

关键词： Markov traffic model Traffic signals Bayesian Urban traffic network

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Endurable SSD-Based Read Cache for Improving the Performance of Selective Restore from Deduplication Systems

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Journal of computer science & Technology 2018年第1期33卷 58-78页

作者： Jian Liu Yun-Peng Chai Xiao Qin Yao-Hong Liu Division of Computer Science and Engineering Louisiana State University Baton Rouge LA 70803 U.S.A. Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education of China Beijing 100872 China School of Information Renmin University of China Beijing 100872 China Shelby Center for Engineering Technology Department of Computer Science and Software Engineering Samuel Ginn College of Engineering Auburn University Auburn AL 368~9-53~7 U.S.A.

Deduplication has been commonly used in both enterprise storage systems and cloud storage. To overcome the performance challenge for the selective restore operations of deduplication systems, solid-state-drive-based （i.e., SSD-based） re^d cache cm, be deployed for speeding up by caching popular restore contents dynamically. Unfortunately, frequent data updates induced by classical cache schemes （e.g., LRU and LFU） significantly shorten SSDs＇ lifetime while slowing down I/O processes in SSDs. To address this problem, we propose a new solution -- LOP-Cache to greatly improve tile write durability of SSDs as well as I/O performance by enlarging the proportion of long-term popular （LOP） data among data written into SSD-based cache. LOP-Cache keeps LOP data in the SSD cache for a long time period to decrease the number of cache replacements. Furthermore, it prevents unpopular or unnecessary data in deduplication containers from being written into the SSD cache. We implemented LOP-Cache in a prototype deduplication system to evaluate its pertbrmance. Our experimental results indicate that LOP-Cache shortens the latency of selective restore by an average of 37.3% at the cost of a small SSD-based cache with only 5.56% capacity of the deduplicated data. Importantly, LOP-Cache improves SSDs＇ lifetime by a factor of 9.77. The evidence shows that LOP-Cache offers a cost-efficient SSD-based read cache solution to boost performance of selective restore for deduplication systems.

关键词： data deduplication solid state drive （SSD） flash cache endurance

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Improved reinforcement learning with curriculum

arXiv

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arXiv 2019年

作者： West, Joseph Maire, Frederic Browne, Cameron Denman, Simon School of Electrical Engineering and Computer Science Queensland University of Technology BrisbaneQLD4500 Australia Department of Data Science and Knowledge Engineering Maastricht University Maastricht6211 Netherlands

Humans tend to learn complex abstract concepts faster if examples are presented in a structured manner. For instance, when learning how to play a board game, usually one of the first concepts learned is how the game ends, i.e. the actions that lead to a terminal state (win, lose or draw). The advantage of learning end-games first is that once the actions which lead to a terminal state are understood, it becomes possible to incrementally learn the consequences of actions that are further away from a terminal state - we call this an end-game-first curriculum. Currently the state-of-the-art machine learning player for general board games, AlphaZero by Google DeepMind, does not employ a structured training curriculum;instead learning from the entire game at all times. By employing an end-game-first training curriculum to train an AlphaZero inspired player, we empirically show that the rate of learning of an artificial player can be improved when compared to a player not using a training curriculum. Copyright © 2019, The Authors. All rights reserved.

关键词： Curricula

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Using restart heuristics to improve agent performance in angry birds

arXiv

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arXiv 2019年

作者： Liu, Tommy Renz, Jochen Zhang, Peng Stephenson, Matthew Research School of Computer Science Australian National University CanberraACT Australia Department of Data Science and Knowledge Engineering Maastricht University Maastricht Netherlands

Over the past few years the Angry Birds AI competition has been held in an attempt to develop intelligent agents that can successfully and efficiently solve levels for the video game Angry Birds. Many different agents and strategies have been developed to solve the complex and challenging physical reasoning problems associated with such a game. However none of these agents attempt one of the key strategies which humans employ to solve Angry Birds levels, which is restarting levels. Restarting is important in Angry Birds because sometimes the level is no longer solvable or some given shot made has little to no benefit towards the ultimate goal of the game. This paper proposes a framework and experimental evaluation for when to restart levels in Angry Birds. We demonstrate that restarting is a viable strategy to improve agent performance in many cases. Copyright © 2019, The Authors. All rights reserved.

关键词： Birds

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Additively LWE based homomorphic encryption for compact devices with enhanced security

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International Journal of Network Security 2019年第3期21卷 378-383页

作者： Challa, Ratnakumari Kumari, Gunta Vijaya Department of Computer Science Engineering Rajiv Gandhi University of Knowledge Technologies IIIT-AP RKValley Kadapa Dist Andhra Pradesh India Department of Computer Science Engineering Jawaharlal Nehru Technological University Hyderabad Kukatpally Hyderabad Telangana India

LWE based homomorphic encryption scheme has been proven as secured technique and consequently widely implemented since the last decade. However, the scheme is not considered to be practical because of its larger size of public keys and ciphertexts. In this paper, LWE based additively homomorphic encryption technique is further modified to enhance the performance in minimizing the space required for public keys and ciphertext without compromising the security of the scheme. This makes the scheme suitable for implementation in low space devices. The practical implementation of the scheme is explored and its performance analysis has been presented here. The scheme is also compared with the standard LWE. © 2019, International Journal of Network Security.

关键词： Additives

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