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IEEE International Conference on Information Communication and Software Engineering (ICICSE)

作者： Ren, ChengQian Shang, Ying Beijing Univ Chem Technol Dept Comp Sci Beijing 100029 Peoples R China

ISBN: (纸本)9781665419192

Bug reproduction is an important task for uncovering the causes of the bug and providing appropriate fixes. However, this task is usually labor-intensive and time-taking. Several solutions have been proposed to automate this task. The proposed solutions typically either use program runtime data, or bug stack traces to generate a test case that triggers the represented bug. In this paper, we propose a novel bug reproduction approach that combines the bug information and extended finite state machine model to generate effective test cases needed to reproduce a bug. The experimental results of 15 bugs in four common systems show that the proposed method can quickly and accurately reproduce bugs.

关键词： bug reproduction EFSM model test case generation searching algorithm

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An effective coded exposure photography framework using optimal fluttering pattern generation

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OPTICS AND LASERS IN ENGINEERING 2021年 139卷 106489-106489页

作者： Cui, Guangmang Ye, Xiaojie Zhao, Jufeng Zhu, Liyao Chen, Ying Zhang, Yu Hangzhou Dianzi Univ Sch Elect & Informat Hangzhou 310018 Peoples R China Hangzhou Dianzi Univ Zhejiang Prov Key Lab Equipment Elect Hangzhou 310018 Peoples R China

Motion blurring often occurs during camera imaging process due to the relative motion between the scene and imaging sensor, which would degrade the quality of captured image. In this paper, an effective coded exposure photography framework is proposed to help obtain better motion deblurring results. An integrated optimal fluttering pattern generation criterion with several factors is designed to guarantee the limited frequency information loss using coded exposure photography. Furthermore, an effective fluttering code sequence search algorithm is put forward to obtain the optimal code sequence quickly with perfect balance consideration of global search and local search. The differential evolution algorithm is utilized to carry out effective global searching. Meanwhile, simulate annealing algorithm is introduce to implement supplementary local optimal search, which could help avoid falling into local optimizations and reduce the iteration numbers significantly. Various groups of synthetic and real-world deblurring experiments are carried out to verify the effectiveness of the designed imaging framework. Experimental results demonstrate that the optimal fluttering pattern could be calculated quickly by the presented approach and the deblurring images have superior subjective visual perception and objective image quality assessment performance.

关键词： coded exposure optimal fluttering sequence searching algorithm motion deblurring image quality assessment

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Evolutionary Approach for the Multi-objective Bike Routing Problem 11th

Evolutionary Approach for the Multi-objective Bike Routing P...

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11th International Conference on Computational Logistics (ICCL)

作者： Nunes, Pedro Moura, Ana Santos, Jose Univ Aveiro Aveiro Portugal

ISBN: (纸本)9783030597474;9783030597467

In this paper, a multi-objective approach for the bike routing problem is presented. Bike routing represents specific challenges, since cyclists have different experiences, concerns, and route preferences. Our approach considers two criteria: the total traveled distance and the cyclists safety. Finding the optimal Pareto set is computationally unfeasible for these problems, therefore, the goal of this work is to create a non-exact method capable of producing a set of quality solutions in a timely manner. A heuristic that modifies the multi-label setting algorithm is used to create an initial population and a genetic elitist algorithm is used to find an approximated Pareto set of optimal routes. The proposed methodology is applied on a practical case study, in which real data from OpenStreetMaps (OSM) and Shuttle Radar Topography Mission (SRTM) was used to model the graph for the road network of the city of Aveiro, with 9506 nodes and 21208 edges. The results show that the approach is fast enough for interactive use in a planning tool and produces a set of quality solutions, regarding two criteria, the traveled distance and the safety of the path.

关键词： Genetic algorithm Bike routing Multi-objective searching algorithm Heuristic

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searching for optimal quantum secret sharing scheme based on local distinguishability

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QUANTUM INFORMATION PROCESSING 2020年第10期19卷 368-368页

作者： Dou, Zhao Xu, Gang Chen, Xiu-Bo Niu, Xin-Xin Yang, Yi-Xian Yang, Yu Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Informat Secur Ctr Beijing 100876 Peoples R China Guizhou Univ State Key Lab Publ Big Data Guiyang 550025 Guizhou Peoples R China Beijing Univ Posts & Telecommun Sch Cyberspace Secur Beijing 100876 Peoples R China

The (k, n)-threshold quantum secret sharing scheme is an important and difficult field in quantum information processing and quantum cryptography. In this paper, the (k, n)-threshold quantum secret sharing scheme based on local operations and classical communication (LOCC-QSS) is investigated. Firstly, in order to effectively study the LOCC-QSS scheme, digital and graphical representations of judgement space are introduced creatively. These representations are simple and convenient. Secondly, an algorithm is designed to search optional states for any given k and n. For optional states, the unambiguous probability equals 0 when x participants cooperate (x

关键词： Security Quantum secret sharing Local distinguishability Optimal scheme searching algorithm

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New and improved search algorithms and precise analysis of their average-case complexity

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2019年 95卷 743-753页

作者： Amrahov, Sahin Emrah Mohammed, Adnan Saher Celebi, Fatih V. Ankara Univ Comp Engn Dept TR-06830 Ankara Turkey Al Kitab Univ Dept Comp Engn Technol Coll Engn Tech Kirkuk Iraq Ankara Yildirim Beyazit Univ Comp Engn Dept Fac Engn & Nat Sci Ankara Turkey

In this paper, we consider the searching problem over ordered sequences. It is well known that Binary Search (BS) algorithm solves this problem with very efficient complexity, namely with the complexity theta(log(2)n). The developments of the BS algorithm, such as Ternary Search (TS) algorithm do not improve the efficiency. The rapid increase in the amount of data has made the search problem more important than in the past. And this made it important to reduce average number of comparisons in cases where the asymptotic improvement is not achieved. In this paper, we identify and analyze an implementation issue of BS. Depending on the location of the conditional operators, we classify two different implementations for BS which are widely used in the literature. We call these two implementations weak and correct implementations. We calculate precise number of comparisons in average case for both implementations. Moreover, we transform the TS algorithm into an improved ternary search (ITS) algorithm. We also propose a new Binary-Quaternary Search (BQS) algorithm by using a novel dividing strategy. We prove that an average number of comparisons for both presented algorithms ITS and BQS is less than for the case of correct implementation of the BS algorithm. We also provide the experimental results. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Binary search Ternary search searching algorithm Average-case complexity

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Learning Node-Selection Strategies in Bounded-Suboptimal Conflict-Based Search for Multi-Agent Path Finding 21

Learning Node-Selection Strategies in Bounded-Suboptimal Con...

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International Conference on Autonomous Agents and Multiagent Systems

作者： Taoan Huang Bistra Dilkina Sven Koenig University of Southern California

ISBN: (纸本)9781713832621

Multi-Agent Path Finding (MAPF) is an NP-hard problem that has important applications for distribution centers, traffic management and computer games, and it is still difficult for current solvers to solve large instances optimally. Bounded suboptimal solvers, such as Enhanced Conflict-Based Search (ECBS) and its variants, are more efficient than optimal solvers in finding a solution with suboptimality guarantees. ECBS is a tree search algorithm that expands the search tree by repeatedly selecting search tree nodes from a focal list. In this work, we propose to use machine learning (ML) to learn a node-selection strategy to speed up ECBS. In the first phase of our framework, we use imitation learning and curriculum learning to learn node-selection strategies iteratively for different numbers of agents from training instances. In the second phase, we deploy the learned models in ECBS and test their solving performance on unseen instances drawn from the same distribution as the training instances. We demonstrate that our solver, ECBS+ML, shows substantial improvement in terms of the success rates and runtimes over ECBS on five different types of grid maps from the MAPF benchmark.

关键词： Multi-Agent path finding Heuristic search Machine learning heuristic search Tree searching European Central Bank Solvers Artificial Intelligence Machine Learning Runtime FINDINGS searching algorithm Nondeterministic polynomial-time hard Computer Games

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LC-MS/MS Software for Screening Unknown Erectile Dysfunction Drugs and Analogues: Artificial Neural Network Classification, Peak-Count Scoring, Simple Similarity Search, and Hybrid Similarity Search algorithms

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ANALYTICAL CHEMISTRY 2019年第14期91卷 9119-9128页

作者： Jang, Inae Lee, Jae-ung Lee, Jung-min Kim, Beom Hee Moon, Bongjin Hong, Jongki Oh, Han Bin Sogang Univ Dept Chem Seoul 04107 South Korea Kyung Hee Univ Coll Pharm Seoul 02447 South Korea

Screening and identifying unknown erectile dysfunction (ED) drugs and analogues, which are often illicitly added to health supplements, is a challenging analytical task. The analytical technique most commonly used for this purpose, liquid chromatography-tandem mass spectrometry (LC-MS/MS), is based on the strategy of searching the LC-MS/MS spectra of target compounds against database spectra. However, such a strategy cannot be applied to unknown ED drugs and analogues. To overcome this dilemma, we have constructed a standalone software named Al-SIDA (artificial intelligence screener of illicit drugs and analogues). AI-SIDA consists of three layers: LC-MS/MS viewer, Al classifier, and Identifier. In the second AI classifier layer, an artificial neural network (ANN) classification model, which was constructed by training 149 LC-MS/MS spectra (including 27 sildenafil-type, 6 vardenafil-type, 11 tadalafil-type ED drugs/analogues and other 105 compounds), is included to classify the LC-MS/MS spectra of the query compound into four categories: i.e., sildenafil, vardenafil, and tadalafil families and non-ED compounds. This ANN model was found to show 100% classification accuracy for the 187 LC-MS/MS modeling and test data sets. In the third Identifier layer, three search algorithms (pick-count scoring, simple similarity search, and hybrid similarity search) are implemented. In particular, the hybrid similarity search was found to be very powerful in identifying unknown ED drugs/analogues with a single modification from the library ED drugs/analogues. Altogether, the AI-SIDA software provides a very useful and powerful platform for screening unknown ED drugs and analogues.

关键词： computer software emergency room Pharmaceutical Preparations Unknown Erectile Dysfunction searching algorithm tandem mass spectrometry

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Inverse estimation of boundary conditions with forced convection heat transfer in two dimensional channels

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HEAT AND MASS TRANSFER 2019年第7期55卷 1927-1935页

作者： Shafipour, Marziyeh Safavinejad, Ali Zadeh, Mahdi Abbas Univ Birjand Dept Mech Engn Birjand Iran

In this paper, the inverse estimation of boundary conditions in a parallel plates channel with forced convection heat transfer is studied. The direct problem involves solving energy equation which is solved by use of finite difference method. A hydrodynamically fully developed and thermally developing laminar flow is considered. To minimize the objective function, heuristic optimization algorithms includes the particle swarm optimization and the gravitational search algorithms are used. The objective function is expressed by the sum of square residuals between measured and estimated temperatures. At the end, the results of solving the direct problem are validated by previous research. Then, the ability of optimization algorithms mentioned in inverse estimation of boundary conditions is discussed. The results indicate that the particle swarm optimization algorithm has a high accuracy in estimating boundary conditions, but in the gravitational search algorithm, the convergence rate becomes constant after the first few iterations. Furthermore, the effect of sensors number in the boundary conditions estimation indicates that the increase in the number of sensors improves the accuracy of estimations.

关键词： Particle swarm optimization Optimization algorithms Energy equation forced convection heat transfer Heat convection Inverse estimation searching algorithm boundary layer Objective function particle swarm algorithm Boundary conditions direct problem

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Latency-Aware Local Search for Distributed Constraint Optimization 21

Latency-Aware Local Search for Distributed Constraint Optimi...

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International Conference on Autonomous Agents and Multiagent Systems

作者： Ben Rachmut Roie Zivan William Yeoh Ben-Gurion University of the Negev Washington University in St. Louis

ISBN: (纸本)9781713832621

Most studies investigating models and algorithms for distributed constraint optimization problems (DCOPs) assume messages arrive instantaneously or within a (short) bounded delay. Specifically, distributed local search DCOP algorithms have been designed as synchronous algorithms, performing in an asynchronous environment, i.e., algorithms that perform in synchronous iterations in which each agent exchanges messages with all its neighbors. This is true also for an anytime mechanism that reports the best solution explored during the run of synchronous distributed local search algorithms. Thus, when the assumptions on instantaneous message arrival are relaxed, the state of the art local search algorithms and mechanism do not apply. In this work, we address this limitation by: (1) Investigating the performance of existing local search DCOP algorithms in the presence of message latency; (2) Proposing an asynchronous monotonic distributed local search DCOP algorithm; and (3) Proposing an asynchronous anytime framework for reporting the best solution explored by non-monotonic asynchronous local search DCOP algorithms. Our empirical results demonstrate that, up to some extent, message delays have a positive effect on distributed local search algorithms due to increased exploration. The asynchronous anytime framework proposed, allows a maximal benefit from such latency based explorative heuristics.

关键词： Distributed constraint optimization Distributed local search Message latency Constrained optimization searching algorithm algorithms Asynchronous Messages Distribute state of the art Latency

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A New Approach for Drug Target and Bioactivity Prediction: The Multifingerprint Similarity Search algorithm (MuSSeL)

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JOURNAL OF CHEMICAL INFORMATION AND MODELING 2019年第1期59卷 586-596页

作者： Alberga, Domenico Trisciuzzi, Daniela Montaruli, Michele Leonetti, Francesco Mangiatordi, Giuseppe Felice Nicolotti, Orazio Univ Bari Aldo Moro Dipartimento Farm Sci Farmaco Via E Orabona 4 I-70126 Bari Italy

We present MuSSeL, a multifingerprint similarity search algorithm, able to predict putative drug targets for a given query small molecule as well as to return a quantitative assessment of its bioactivity in terms of K-i or IC50 values. Predictions are automatically made exploiting a large collection of high quality experimental bioactivity data available from ChEMBL (version 22.1) combining, in a consensus-like approach, predictions resulting from a similarity search performed using 13 different fingerprint definitions. Importantly, the herein proposed algorithm is also effective in detecting and handling activity cliffs. A calibration set including small molecules present in the last updated version of ChEMBL (version 23) was employed to properly tune the algorithm parameters. Three randomly built external sets were instead challenged for model performances. The potential use of MuSSeL was also challenged by a prospective exercise for the prediction of five bioactive compounds taken from articles published in the Journal of Medicinal Chemistry just few months ago. The paper emphasizes the importance of implementing multifingerprint consensus strategies to increase the confidence in prediction of similarity search algorithms and provides a fast and easy-to-run tool for drug target and bioactivity prediction.

关键词： Mussel Medicinal chemistry searching algorithm Drug Liberation Biological activity small molecule

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