Using association rule mining to enrich semantic concepts for video retrieval

In order to achieve true content-based information retrieval on video we should analyse and index video with high-level semantic concepts in addition to using user-generated tags and structured metadata like title, date, etc. However the range of such high-level semantic concepts, detected either manually or automatically, usually limited compared to the richness of information content in video and the potential vocabulary of available concepts for indexing. Even though there is work to improve the performance of individual concept classifiers, we should strive to make the best use of whatever partial sets of semantic concept occurrences are available to us. We describe in this paper our method for using association rule mining to automatically enrich the representation of video content through a set of semantic concepts based on concept co-occurrence patterns. We describe our experiments on the TRECVid 2005 video corpus annotated with the 449 concepts of the LSCOM ontology. The evaluation of our results shows the usefulness of our approach

Cold atom confinement in an all-optical dark ring trap

We demonstrate confinement of $^{85}$Rb atoms in a dark, toroidal optical trap. We use a spatial light modulator to convert a single blue-detuned Gaussian laser beam to a superposition of Laguerre-Gaussian modes that forms a ring-shaped intensity null bounded harmonically in all directions. We measure a 1/e spin-relaxation lifetime of ~1.5 seconds for a trap detuning of 4.0 nm. For smaller detunings, a time-dependent relaxation rate is observed. We use these relaxation rate measurements and imaging diagnostics to optimize trap alignment in a programmable manner with the modulator. The results are compared with numerical simulations.Comment: 5 pages, 4 figure

Evaluation of therapeutic response of Keloid and Hypertrophic scars to bleomycin tatto and to cryotherapy followed by intralesional triamcinolone injection

کلوئید و اسکارهایپرتروفیک بیماری هایی هستند ناشی از پاسخ غیر طبیعی پوست بدن به صدمات وارده که به علت تولید بیش ازحد بافت های فیبروس متراکم در محل ضایعه ایجاد می شوند. از بین درمان های بسیار زیاد پیشنهاد شده برای این بیماری ها، کرایوتراپی و تزریق داخل ضایعه تریامسینولون جزء متداول ترین این درمان ها است، اما هنوز موفقیت درمانی در این بیماری کامل نیست. هدف از انجام این پژوهش بررسی پاسخ درمانی کلوئید و اسکارهایپرتروفیک به تاتوی بلئومایسین و مقایسه آن با درمان معمول کرایوتراپی و تزریق داخل ضایعه تریامسینولون می باشد. بدین منظور 45 نفر از بیماران مبتلا به کلوئید و اسکارهایپرتروفیک مراجعه کننده به درمانگاه های پوست دانشگاه علوم پزشکی اصفهان بر اساس ترتیب مراجعه به دوگروه A (23 نفر) و گروه B (22 نفر) تقسیم شدند. گروه A بوسیله تاتوی بلئومایسین و گروه B بوسیله کرایوتراپی و تزریق داخل ضایعه تریامسینولون درمان شدند. درمان ها در چهار مرحله و با فواصل یک ماهه در هر دو گروه انجام شد و بیماران تا 3 ماه پس از پایان درمان پیگیری شدند. قبل و پس از درمان اندازه (شامل ضخامت و وسعت ضایعات)، علائم کلینیکی، محل و تعداد ضایعات و دیگر اطلاعات مورد نیاز ثبت و در هر گروه مقایسه گردید. پاسخ درمانی که بر اساس کاهش اندازه ضایعات نسبت به ویزیت اول تعریف شده بود، در گروه A، 14±3/88 درصد و در گروه B، 5/22±3/67 درصد به دست آمد که تفاوت معنی داری بین دوگروه مشاهده می شود (001/0P=) ضمن آنکه 69 بیماران گروه A در مقایسه با قبل از درمان بدون علامت شده بودند در حالی که تعداد کسانی که در گروه B بدون علامت شده بودند 49 درصد بود. همچنین در گروه B هر چه اندازه ضایعه بزرگتر بود پاسخ درمانی ضعیف تری به دست می آمد ولی در گروه A اندازه ضایعات تقریباً اثری در پاسخ درمانی ایجاد نکرد. نتیجه آنکه تاتوی بلئومایسین پاسخ درمانی بالائی می تواند در این بیماری ها ایجاد کند خصوصاً آنکه در ضایعات با اندازه بزرگ نیز اثر درمانی آن حفظ می شود

Development of optimal accelerated test plan

This paper describes an optimal accelerated test plan considering an economic approach. We introduce a general framework to obtain plans of optimal accelerate tests with a specific objective, such as cost. The optimal test plans are defined by considering prior knowledge of reliability, including the reliability function and its scale and shape parameters, and the appropriate model to characterize the accelerated life. This information is used in Bayesian inference to optimize the test plan. The prior knowledge contains the uncertainty on real reliability of new product. So, the proposed methodology consists of defining an optimal accelerated testing plan while considering an objective function based on economic value, using Bayesian inference for optimizing the test plan, and using the uncertainty of the parameters to obtain a robust, optimal testing plan. The objective function consists of two terms: the cost linked to testing activities and the cost associated with operation of the product. Finally, we will develop our optimal plan by extending our approach to include theoretical formulation of the various degrees of freedom with respect to the parameters. To complete this development, we need to improve the algorithm of optimization. To obtain the best test plan, we propose an optimization procedure using the genetic algorithm. The proposed method will be illustrated by a numerical example based on a well-known problem

Optimal accelerated test plan: optimization procedure using Genetic Algorithm

This paper describes an optimization procedure using Genetic Algorithm to define an optimal accelerated test plan considering an economic approach. We introduce a general framework to obtain plans of optimal accelerate tests with a specific objective, such as cost. The objective is to minimize the costs involved in testing without reducing the quality of the data obtained. The optimal test plans are defined by considering prior knowledge of reliability, including the reliability function and its scale and shape parameters, and the appropriate model to characterize the accelerated life. This information is used in Bayesian inference to optimize the test plan. To perform optimization, a specific genetic algorithm is decribed and applied to obtain the best test plan. This procedure is then illustrated on a numerical example

Cylindrical vector beams for rapid polarization-dependent measurements in atomic systems

We demonstrate the use of cylindrical vector beams - beams with spatially varying polarization - for detecting and preparing the spin of a warm rubidium vapor in a spatially dependent manner. We show that a modified probe vector beam can serve as an atomic spin analyzer for an optically pumped medium, which spatially modulates absorption of the beam. We also demonstrate space-variant atomic spin by optical pumping with the vector beams. The beams are thus beneficial for making singleshot polarization-dependent measurements, as well as for providing a means of preparing samples with position-dependent spin.Comment: 8 pages, 5 figures. Accepted in Optics Expres

A low-loss photonic silica nanofiber for higher-order modes

Optical nanofibers confine light to subwavelength scales, and are of interest for the design, integration, and interconnection of nanophotonic devices. Here we demonstrate high transmission (> 97%) of the first family of excited modes through a 350 nm radius fiber, by appropriate choice of the fiber and precise control of the taper geometry. We can design the nanofibers so that these modes propagate with most of their energy outside the waist region. We also present an optical setup for selectively launching these modes with less than 1% fundamental mode contamination. Our experimental results are in good agreement with simulations of the propagation. Multimode optical nanofibers expand the photonic toolbox, and may aid in the realization of a fully integrated nanoscale device for communication science, laser science or other sensing applications.Comment: 12 pages, 5 figures, movies available onlin

A novel hybrid genetic algorithm to solve the make-to-order sequence-dependent flow-shop scheduling problem

Flow-shop scheduling problem (FSP) deals with the scheduling of a set of n jobs that visit a set of m machines in the same order. As the FSP is NP-hard, there is no efficient algorithm to reach the optimal solution of the problem. To minimize the holding, delay and setup costs of large permutation flow-shop scheduling problems with sequence-dependent setup times on each machine, this paper develops a novel hybrid genetic algorithm (HGA) with three genetic operators. Proposed HGA applies a modified approach to generate a pool of initial solutions, and also uses an improved heuristic called the iterated swap procedure to improve the initial solutions. We consider the make-to-order production approach that some sequences between jobs are assumed as tabu based on maximum allowable setup cost. In addition, the results are compared to some recently developed heuristics and computational experimental results show that the proposed HGA performs very competitively with respect to accuracy and efficiency of solution