Learning multiple experiences useful visual features for active maps localization in crowded environments

Crowded urban environments are composed of different types of dynamic and static elements. Learning and classification of features is a major task in solving the localization problem in such environments. This work presents a gradual learning methodology to learn the useful features using multiple experiences. The usefulness of an observed element is evaluated by a scoring mechanism which uses two scores – reliability and distinctiveness. The visual features thus learned are used to partition the visual map into smaller regions. The robot is efficiently localized in such a partitioned environment using two-level localization. The concept of active map (AM) is proposed here, which is a map that represents one partition of the environment in which there is a high probability of the robot existing. High-level localization is used to track the mode of the AMs using discrete Bayes filter. Low-level localization uses a bag-of-words model to retrieve images and accurately localize the robot. The pose of the robot is the one retrieved from the AM that has maximum a posteriori. Experiments have been conducted on a unique highly crowded data-set collected from Indian roads. The results support the proposed method due to speed and localization accuracy.     

Pluronic lecithin organogel of 5-aminosalicylic acid for wound healing

5-Aminosalicylic acid (5-ASA) is an aminosalicylate anti-inflammatory drug, which is also known as mesalazine or mesalamine. Currently employed in treating inflammatory bowel disease, ulcerative colitis, inflamed anus or rectum, and maintain remission in Crohn's disease. Evidence from the researchers highlighted its significant re-epithelization in allergic asthma, aphthous, and gastric ulcerative conditions. The objective of the study was to formulate the pluronic lecithin organogel (PLO) containing 5-ASA and evaluate its wound-healing ability in a full thickness excision wound rat model. The data obtained from in silico docking studies revealed 5-ASA is having an affinity towards the transforming growth factor-beta (TGF-β) specifically towards beta1. Among various formulations prepared (F1 to F8), F1, and F6 have shown a maximum in vitro drug release with optimum pH and viscosity. From MTT assay it was found that selected PLO formulations showed no toxicity and enhanced cell proliferation in HaCaT cell lines. In vivo wound-healing studies in albino Wistar rats has revealed that PLO accelerates wound closure and reepithelization to the statistically significant level on day 3 (p?相似文献   

Threshold accepting and Ant-colony optimization algorithms for scheduling m-machine flow shops with lot streaming

This paper addresses the problem of making sequencing and scheduling decisions for n jobs m machines flow shops under lot sizing environment. Lot streaming (lot sizing) is the process of creating sublots to move the completed portion of a production sublots to down stream machines. There is a scope for efficient algorithms for scheduling problems in m-machine flow shop with lot streaming. In recent years, much attention is given to heuristics and search techniques. On this concern this paper proposes Ant-colony optimization algorithm (ACO) and threshold accepting algorithm (TA) to evolve best sequence for makespan/total flow time criterion for m-machine flow shop involved with lot streaming and setup time. The following two algorithms are used to evaluate the performance of the proposed ACO and TA: (i) Baker's algorithm (BA), an optimal solution procedure for two-machine flow shop problem with lot streaming and makespan objective criterion and (ii) genetic and hybrid genetic algorithm for m-machine flow shop problem with lot streaming and makespan and total flow time criteria.     

Iterated fast local search algorithm for solving quadratic assignment problems

This paper concentrates on multi-row machine layout problems that can be accurately formulated as quadratic assignment problems (QAPs). A genetic algorithm-based local search approach is proposed for solving QAPs. In the proposed algorithm, three different mutation operators namely adjacent, pair-wise and insertion or sliding operators are separately combined with a local search method to form a mutation cycle. Effectiveness of introducing the mutation cycle in place of mutation is studied. Performance of the proposed iterated approach is analyzed and the solution qualities obtained are reported.     

Asking questions on handwritten document collections

International Journal on Document Analysis and Recognition (IJDAR) - This work addresses the problem of Question Answering (QA) on handwritten document collections. Unlike typical QA and Visual...     

Knowledge-based workcell attribute oriented dynamic schedulers for flexible manufacturing systems

The economy of production in flexible manufacturing systems (FMS) depends mainly on how effectively the production is planned and how the resources are used. This requires efficient and dynamic factory scheduling and control procedures. This paper addresses two knowledge-based scheduling schemes (work cell attribute oriented dynamic schedulers WCAODSs) to control the flow of parts efficiently in real-time for FMS in which the part-mix varies continually with the planning horizon. The present work employs a hybrid optimisation approach in the generalised A1 framework. A genetic algorithm that provides an optimal combination of a set of priority dispatching rules, one for each work cell WC (WCwisepdr set), for each of the problem instances characterised by their WC attributes, is used for generating examples. The WC attributes reflect the information about the operating environment of each individual WC. Two inductive learning algorithms are employed to learn the examples, and scheduling rules are formulated as a knowledge base. The learning algorithms employed are: the Genetic CID3 (Continuous Interactive Dichotomister3 algorithm extended with genetic program for weight optimisation) and the Classification Decision Tree algorithm. The knowledge base obtained through the above learning schemes generates robust and effective schedules intelligently with respect to the part-mix changes in real-time, for makespan criteria. The comparison made with a GA-based scheduling methodology shows that WCAODSs provide solutions closer to the optimum.     

Semi-supervised annotation of faces in image collection

The objective of this work is to correctly detect and recognize faces in an image collection using a database of known faces. This has applications in photo-tagging, video indexing, surveillance and recognition in wearable computers. We propose a two-stage approach for both detection and recognition tasks. In the first stage, we generate a seed set from the given image collection using off-the-shelf face detection and recognition algorithms. In the second stage, the obtained seed set is used to improve the performance of these algorithms by adapting them to the domain at hand. We propose an exemplar-based semi-supervised framework for improving the detections. For recognition of images, we use sparse representation classifier and generate seed images based on a confidence measure. The labels of the seed set are then propagated to other faces using label propagation framework by imposing appropriate constraints. Unlike traditional approaches, our approach exploits the similarities among the faces in collection to obtain improved performance. We conduct extensive experiments on two real-world photo-album and video collections. Our approach consistently provides an improvement of \({\sim } 4\)% for detection and \(5{-}9\)% for recognition on all these datasets.     

A genetic algorithm for scheduling flexible manufacturing systems

General job shop scheduling and rescheduling with alternative route choices for an FMS environment is addressed in this paper. A genetic algorithm is proposed to derive an optimal combination of priority dispatching rules pdrs (independentpdrs one each for one Work Cell WC), to resolve the conflict among the contending jobs in the Giffler and Thompson GT procedure. The performance is compared with regard to makes-pan criteria and computational time. The optimal WCwise-pdr is proved to be efficient in providing optimal solutions in a reasonable computational time. Also, the proposed GA based heuristic method is extended to revise schedules on the arrival of new jobs, and on the failure of equipment to address the dynamic operation mode of flexible manufacturing systems. An iterative search technique is proposed to find the best route choice for all operations to provide a feasible and optimal solution. The applicability and usefulness of the proposed methodology for the operation and control of FMS in real-time are illustrated with examples. The scope of the genetic search process and future research directions are discussed.     

Experimental studies on the thermal performance of a parabolic dish solar receiver with the heat transfer fluids SiC + water nano fluid and water

An experimental investigation has been carried out with aa point focusing dish reflector of 12 square meters aperture area,exposed to the average direct normal irradiations of 810 W/m2.This work focuses on enhancinge the energy and exergy efficiencies of the cavity receiver by minimizing the temperature difference between the wall and heat transfer fluids.Two heat transfer fluids Water and SiC + water nano fluid have been prepared from 50 nm particle size and 1％ of volume fraction,and experimented separately for the flow rates of 0.2 lpm to 0.6 lpm with an interval of 0.1 lpm.The enhanced thermal conductivity of nano fluid is 0.800115 W/mK with the keff/kb ratio of 1.1759 determined by using the Koo and Kleinstreuer correlation.The maximum attained energy and exergy efficiencies are 29.14％ and 24.82％ for water,and 32.91％ and 39.83％ for SiC+water nano fluid.The nano fluid exhibits enhanced energy and exergy efficiency of 12.94％ and 60.48％ than that of water at the flow rate of 0.5 lpm.The result shows that the system with SiC+Water produces higher exergy efficiency as compared to energy efficiency;in the case ofwater alone,the energy efficiency is higher than exergy efficiency.