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A simple and accurate theoretical investigation is presented, based on a novel, effective, and straightforward ABCD matrix technique, in relation to estimation of optimum coupling efficiency between the laser diode and the photonic crystal fiber (PCF) with a hyperbolic microlens (HML) on its tip. By tailoring different parameters, such as the air-filling factor and lattice constant of the PCF, the criteria for achieving maximum coupling are predicted and reported for two different light wavelengths of practical interest. It is observed that such fiber parameters play a crucial role in predicting the optimum focal length of HML for a particular wavelength. The formulation should find application in the design of HML, for achieving a long working distance between the laser source facet and the fiber tip. Downloaded From: http://opticalengineering.spiedigitallibrary.org/ on 08/19/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx Somenath Sarkar is currently a professor of the Department of Electronic Science, CU, where he has rendered services since September 1989. He received his MSc degree (physics) from Delhi University and his PhD (physics) from IIT, Delhi, in fiber optics. He carried out investigations successfully through two R&D projects of CSIR and AICTE and one DST-FIST and AICTE MODROB project with colleagues to upgrade teaching and laboratories. He is an associate editor of Advances in Optoelectronics. Optical Engineering 086102-7 August 2015 • Vol. 54(8) Karak et al.: Investigation of coupling of a laser diode to photonic crystal fiber via hyperbolic microlens. . . Downloaded From: http://opticalengineering.spiedigitallibrary.org/ on 08/19/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx

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Community question answering services provide an open platform for users to acquire and share their knowledge. In the last decade, popularity of such services has increased noticeably. Large number of unanswered questions is a major problem for the growth of such services. A common way to address this issue is to route a new question to some selected users who have the potentiality in answering the question. Expert finding is the process of selecting such potential answerers. In this article, we have introduced an efficient method for expert finding using the theme in query likelihood language (QLL) model. Theme of a query is nothing but its subject matter and we have decided it based on the parts of speech (POS) of the words in the query. Depending on the theme of the given question, its similarity to a question in the archive is determined using the QLL model. Aggregating the similarity values of the questions a user answered previously (i.e., in the archive), his/her expertise for the given question is obtained. The performance of the proposed method is verified on a real world dataset (obtained from Yahoo! Answers) and it is found to be quite encouraging.