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Online Semantic Object Segmentation for Vision Robot Collected Video

IEEE ACCESS 2019年 7卷 107602-107615页

作者： Li, Kunqian Tao, Wenbing Liu, Liman Ocean Univ China Coll Engn Qingdao 266100 Shandong Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Natl Key Lab Sci & Technol Multispectral Informat Wuhan 430074 Hubei Peoples R China South Cent Univ Nationalities Sch Biomed Engn Wuhan 430074 Hubei Peoples R China

Video segmentation is the foundation of many senior computer vision applications. For robotic vision applications, video object segmentation is facing more difficulties. Since the videos are usually collected from those complicated scenes and the camera perspective may be static for some time, object saliency and motion clues which are widely used in traditional video segmentation approaches could be unreliable. Besides, its online processing ability is of crucial importance. In this paper, we propose an online video object segmentation method, which is organized as a segmentation-by-detection framework. It first effectively segments out meaningful objects in short video frame batches with the help of object detectors, and then the segmentation of different batches can be associated with each other via bi-directional notebook based connecting strategy. Experiments conducted on public available datasets verify the above-mentioned property and show good performance of the proposed method.

关键词： Online video segmentation object segmentation object detection object tracklets object proposal shortest path algorithm

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Finding the most reliable path with and without link travel time correlation: A Lagrangian substitution based approach

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2011年第10期45卷 1660-1679页

作者： Xing, Tao Zhou, Xuesong Univ Utah Dept Civil & Environm Engn Salt Lake City UT 84112 USA

path travel time reliability is an essential measure of the quality of service for transportation systems and an important attribute in travelers' route and departure time scheduling. This paper investigates a fundamental problem of finding the most reliable path under different spatial correlation assumptions, where the path travel time variability is represented by its standard deviation. To handle the non-linear and non-additive cost functions introduced by the quadratic forms of the standard deviation term, a Lagrangian substitution approach is adopted to estimate the lower bound of the most reliable path solution through solving a sequence of standard shortest path problems. A subgradient algorithm is used to iteratively improve the solution quality by reducing the optimality gap. To characterize the link travel time correlation structure associated with the end-to-end trip time reliability measure, this research develops a sampling-based method to dynamically construct a proxy objective function in terms of travel time observations from multiple days. The proposed algorithms are evaluated under a large-scale Bay Area, California network with real-world measurements. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： shortest path algorithm path travel time reliability Reliable route Lagrangian relaxation method

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The urban traffic noise monitoring system based on LoRaWAN technology

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WIRELESS NETWORKS 2022年第1期28卷 441-458页

作者： Dobrilovic, Dalibor Brtka, Vladimir Jotanovic, Gordana Stojanov, Zeljko Jausevac, Goran Malic, Milan Univ Novi Sad Tech Fac Mihajlo Pupin Zrenjanin Serbia Univ East Sarajevo Fac Transport & Traff Engn Doboj Bosnia & Herceg Schneider Elect DMS NS Novi Sad Serbia

Noise and air pollution are among the most important problems and challenges in urban environments. Noise can cause several problems in functioning within urban settlements and may result in a variety of health problems. Continuous monitoring, prevention, and active work on solving these problems are in the focus of research communities, local and national agencies and organizations, and many international organizations. Traffic noise on city roads has been identified as one of the major problems in urban settlements. Fortunately, it can be monitored and controlled in a way that can reduce its level and negative effects. One of the most effective and cheapest ways to monitor and control traffic noise is to use wireless sensor networks, IoT technology, and cloud-based architectures. This article presents an approach in designing urban traffic noise monitoring system based on LoRaWAN and microservices oriented architecture supported with open-source hardware and software solutions. Design of the system includes planning LoRaWAN network and development of the IoT system layered architecture. Methods for traffic routing and rerouting in urban areas, based on experiments that uses Dijkstra and Floyd-Warshall algorithms are presented. The system implementation and evaluation of the proposed routing modifications are presented in the case of the city of Zrenjanin in Serbia. Discussion of extensions and improvements of the presented system, as well as future research directions, are also presented.

关键词： Urban road traffic noise Planning LoRaWAN Traffic routing shortest path algorithm IoT layered architecture

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Distribution Network Expansion Planning Approach for Large Scale Electric Vehicles Accommodation

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IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 2023年第2期14卷 906-919页

作者： Wang, Xiaowen Shi, Xiaoying Xu, Yinliang Shen, Xinwei Tsinghua Univ Tsinghua Berkeley Shenzhen Inst Tsinghua Shenzhen Int Grad Sch Shenzhen 518055 Peoples R China

The increased power demand incurred by electric vehicles (EVs) has imposed new challenges on the distribution network. One significant responsibility of the distribution network operator (DNO) is to design and expand the distribution network periodically to accommodate the ever-increasing demand. The previous researches mainly use relaxation techniques to enhance the problem tractability, which would involve additional binary variables and incur computation burden to the optimization problem, or even worse, may lead to an intractable problem. This paper develops a mixed-integer non-linear programming (MINLP) model considering various network constraints for the distribution network expansion planning under a high penetration level of EVs. The stochastic characteristics of demands are addressed through set of scenarios. A distributed biased min-consensus algorithm based approach is proposed to solve the MINLP model. Finally, comparison tests are conducted on three different scales of distribution networks to validate the effectiveness of the proposed approach. Simulation results demonstrate that the computation time of the proposed approach is reduced by 42.46% on average for different systems compared with that of the traditional shortest path algorithm based approach.

关键词： Biased min-consensus algorithm network cons-traint shortest path algorithm distribution network expansion planning computation efficiency

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Designing Skid-Trail Networks to Reduce Skidding Cost and Soil Disturbance for Ground-Based Timber Harvesting Operations

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FOREST SCIENCE 2016年第1期62卷 48-58页

作者： Contreras, Marco A. Parrott, David L. Chung, Woodam Univ Kentucky Dept Forestry Lexington KY 40546 USA Univ Kentucky Lexington KY 40506 USA Oregon State Univ Corvallis OR 97331 USA

Skid-trail locations directly influence the economics and environmental impacts of harvesting operations. Typically, field managers design skid-trail networks manually based on field observations of vegetation and terrain conditions. We designed a model to automatically design skid-trail networks to reduce skidding costs and soil disturbances. The model simulates tree-bunch locations, creates a feasible skid-trail network across the harvest unit, estimates skidding cost and soil recovery cost for each feasible skid-trail segment, and finds the network design that connects each tree bunch to landings while reducing skidding and soil recovery costs. The model was applied to a 24-ha hypothetical harvest unit to test its ability to design optimal networks under different scenarios representing conditions commonly found in timber harvesting operations (e.g., skidding pattern, uneven volume distribution, skidding obstacles, and different weights given to skidding and soil recovery costs). It was also applied to an actual 124-ha harvest unit to evaluate its ability to design skid-trail networks considering more realistic conditions with multiple design factors. The model successfully created optimized skid-trail networks for all scenarios considered, and results suggest that it provides a useful tool to help forest engineers and field managers design economically efficient and environmentally sound ground-based timber harvesting operations.

关键词： forest operations planning shortest path algorithm forest optimization network programming

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APPROXIMATION BY SOLUTIONS OF THE PLANAR WAVE-EQUATION

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SIAM JOURNAL ON NUMERICAL ANALYSIS 1992年第3期29卷 816-830页

作者： VONGOLITSCHEK, M LIGHT, WA UNIV LANCASTER DEPT MATHLANCASTER LA1 4YWENGLAND

Let D subset-of R2 be a compact set, and let f be a continuous real-valued function on D. An algorithm is described that computes the distance (in the uniform norm parallel-to parallel-to on D) between f and the solutions w of the wave equation partial derivative 2w/partial derivative s partial derivative t = 0. If, for some M > 0, W(M) subset-of C(D) is the set of solutions of the wave equation which are in the Lipschitz class Lip(M)1, the algorithm finds in W(M) a function of minimal distance from f.

关键词： BOUNDARY VALUE PROBLEMS WAVE EQUATION GOURSAT PROBLEM shortest path algorithm

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Application of hyperpath strategy and driving experience to risk-averse navigation

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IET INTELLIGENT TRANSPORT SYSTEMS 2016年第5期10卷 338-346页

作者： Zeng, Weiliang Miwa, Tomio Morikawa, Takayuki Nagoya Univ Dept Civil Engn Furo Cho Nagoya Aichi Japan Nagoya Univ EcoTopia Sci Inst Furo Cho Nagoya Aichi Japan Nagoya Univ Inst Innovat Future Soc Furo Cho Nagoya Aichi Japan

This study aims to find an experientially reliable path considering travel time uncertainty and driving experience of local probe vehicle drivers. Accordingly, a two-stage route-finding procedure is proposed. First, a set of candidate paths is built by using the hyperpath algorithm, where the choice probability is assigned to each link with uncertain travel time. Second, the shortest path algorithm is applied to find the experientially reliable path on the graph of hyperpath where the modified link cost is penalised based on the link choice probability derived from hyperpath algorithm and the driving experience of local drivers. Four kinds of optimal path in a real-world network are compared with the observed one. It is found that the proposed path has the most similarity with the observed path and it has a higher degree of familiarity and reasonable time and distance.

关键词： vehicle routing navigation probability network theory (graphs) driving experience risk-averse navigation travel time uncertainty local probe vehicle drivers two-stage route-finding procedure shortest path algorithm penalised modified link cost link choice probability hyperpath algorithm real-world network

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Identifying novel protein phenotype annotations by hybridizing protein-protein interactions and protein sequence similarities

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MOLECULAR GENETICS AND GENOMICS 2016年第2期291卷 913-934页

作者： Chen, Lei Zhang, Yu-Hang Huang, Tao Cai, Yu-Dong Shanghai Univ Sch Life Sci Shanghai 200444 Peoples R China Shanghai Maritime Univ Coll Informat Engn Shanghai 201306 Peoples R China Chinese Acad Sci Shanghai Inst Biol Sci Inst Hlth Sci Shanghai 200031 Peoples R China

Studies of protein phenotypes represent a central challenge of modern genetics in the post-genome era because effective and accurate investigation of protein phenotypes is one of the most critical procedures to identify functional biological processes in microscale, which involves the analysis of multifactorial traits and has greatly contributed to the development of modern biology in the post genome era. Therefore, we have developed a novel computational method that identifies novel proteins associated with certain phenotypes in yeast based on the protein-protein interaction network. Unlike some existing network-based computational methods that identify the phenotype of a query protein based on its direct neighbors in the local network, the proposed method identifies novel candidate proteins for a certain phenotype by considering all annotated proteins with this phenotype on the global network using a shortest path (SP) algorithm. The identified proteins are further filtered using both a permutation test and their interactions and sequence similarities to annotated proteins. We compared our method with another widely used method called random walk with restart (RWR). The biological functions of proteins for each phenotype identified by our SP method and the RWR method were analyzed and compared. The results confirmed a large proportion of our novel protein phenotype annotation, and the RWR method showed a higher false positive rate than the SP method. Our method is equally effective for the prediction of proteins involving in all the eleven clustered yeast phenotypes with a quite low false positive rate. Considering the universality and generalizability of our supporting materials and computing strategies, our method can further be applied to study other organisms and the new functions we predicted can provide pertinent instructions for the further experimental verifications.

关键词： Phenotype Protein-protein interaction Protein sequence similarity shortest path algorithm

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Virtual pathway explorer (viPEr) and pathway enrichment analysis tool (PEANuT): creating and analyzing focus networks to identify cross-talk between molecules and pathways

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BMC GENOMICS 2015年第1期16卷 1-13页

作者： Garmhausen, Marius Hofmann, Falko Senderov, Viktor Thomas, Maria Kandel, Benjamin A. Habermann, Bianca Hermine CECAD Res Ctr D-50931 Cologne Germany Austrian Acacdemy Sci Gregor Mendel Inst Mol Plant Biol Vienna Bioctr VBC A-1030 Vienna Austria Dr Margarete Fischer Bosch Inst Clin Pharmacol D-70376 Stuttgart Germany Univ Tubingen D-70376 Stuttgart Germany Max Planck Inst Biochem Res Grp Computat Biol D-82152 Martinsried Germany

Background: Interpreting large-scale studies from microarrays or next-generation sequencing for further experimental testing remains one of the major challenges in quantitative biology. Combining expression with physical or genetic interaction data has already been successfully applied to enhance knowledge from all types of high-throughput studies. Yet, toolboxes for navigating and understanding even small gene or protein networks are poorly developed. Results: We introduce two Cytoscape plug-ins, which support the generation and interpretation of experiment-based interaction networks. The virtual pathway explorer viPEr creates so-called focus networks by joining a list of experimentally determined genes with the interactome of a specific organism. viPEr calculates all paths between two or more user-selected nodes, or explores the neighborhood of a single selected node. Numerical values from expression studies assigned to the nodes serve to score identified paths. The pathway enrichment analysis tool PEANuT annotates networks with pathway information from various sources and calculates enriched pathways between a focus and a background network. Using time series expression data of atorvastatin treated primary hepatocytes from six patients, we demonstrate the handling and applicability of viPEr and PEANuT. Based on our investigations using viPEr and PEANuT, we suggest a role of the FoxA1/A2/A3 transcriptional network in the cellular response to atorvastatin treatment. Moreover, we find an enrichment of metabolic and cancer pathways in the Fox transcriptional network and demonstrate a patient-specific reaction to the drug. Conclusions: The Cytoscape plug-in viPEr integrates -omics data with interactome data. It supports the interpretation and navigation of large-scale datasets by creating focus networks, facilitating mechanistic predictions from -omics studies. PEANuT provides an up-front method to identify underlying biological principles by calculating enriched path

关键词： Focus network Disease state shortest path algorithm Node neighborhood pathway enrichment

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Analysis of metabolic networks using a pathway distance metric through linear programming

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METABOLIC ENGINEERING 2003年第3期5卷 211-219页

作者： Simeonidis, E Rison, SCG Thornton, JM Bogle, IDL Papageorgiou, LG UCL Ctr Proc Syst Engn Dept Chem Engn London WC1E 7JE England UCL Dept Biochem & Mol Biol London WC1E 7HX England Univ London Birkbeck Coll Dept Crystallog London WC1E 7HX England

The solution of the shortest path problem in biochemical systems constitutes an important step for studies of their evolution. In this paper, a linear programming (LP) algorithm for calculating minimal pathway distances in metabolic networks is studied. Minimal pathway distances are identified as the smallest number of metabolic steps separating two enzymes in metabolic pathways. The algorithm deals effectively with circularity and reaction directionality. The applicability of the algorithm is illustrated by calculating the minimal pathway distances for Escherichia coli small molecule metabolism enzymes, and then considering their correlations with genome distance (distance separating two genes on a chromosome) and enzyme function (as characterised by enzyme commission number). The results illustrate the effectiveness of the LP model. In addition, the data confirm that propinquity of genes on the genome implies similarity in function (as determined by co-involvement in the same region of the metabolic network), but suggest that no correlation exists between pathway distance and enzyme function. These findings offer insight into the probable mechanism of pathway evolution. (C) 2003 Elsevier Inc. All rights reserved.

关键词： pathway distance shortest path algorithm linear programming metabolic pathways genome distance enzyme function

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