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Most polarization maintaining fibres available are single mode fibres. Does anyone know if any multimode polarization maintaining fibre products available? 
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Dear Dr. Chao Wang,
Though it is such a late answer, hope it may just help others while coming across the same issue.
Polarization-maintaining (PM) fibers are mostly single-mode fibers, only in rare cases few-mode fibers, and apparently never highly multimode (MM) fibers. This is because it is difficult to produce sufficiently strong and uniform birefringence in the fiberglass over a sufficiently large core area where many modes (MM) can be guided.
The link (polarization-maintaining fibers) on RP Photonics provided you a quite comprehensive descriptions about it.
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Edit: the paper was approved so if you want to see it just message me :)
I'm writing a paper on a multimodal active sham device for placebo interventions with electrostimulators. We believe it has a low manufacturing cost, but it's probably better to have some baseline for comparison. Have any of you ever requested a manufacturer to produce a sham replica of an electrostimulator to be used on blind trials? If so, how much did it cost? Was it an easy procedure?
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I would say, if you need it for a study purpose not for exhibition (just kidding), I would suggest to check if it is possible to use the original working device with just unplugged wires in a sham group. Just and idea, good luck with your paper!
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Basically, I have read about mulsemedia, more precisely, the MPEG-V standard. However, also we have multimodal applications and a standard, W3C Multimodal Interaction Framework.
I'd like to know if these concept are antagonistic or they have similarities.
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“multimedia” is the technological form or the medium of presentation, whereas the emphasis in “multimodal” is the means to persuasion.
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research work or ideas on road transport, multimodal transport, green transport, but applied to mopeds for example,
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A. Elattar, I am including some works, for your review.
Baloh, M., & Parent, M. (2003, December). Modeling and model verification of an intelligent self-balancing two-wheeled vehicle for an autonomous urban transportation system. In The conference on computational intelligence, robotics, and autonomous systems, 1-7). https://www.researchgate.net/profile/Michel-Parent-3/publication/228698167_Modeling_and_model_verification_of_an_intelligent_self-balancing_two-wheeled_vehicle_for_an_autonomous_urban_transportation_system/links/547344a70cf216f8cfaecda4/Modeling-and-model-verification-of-an-intelligent-self-balancing-two-wheeled-vehicle-for-an-autonomous-urban-transportation-system.pdf
Gerlici, J., Sakhno, V., Yefymenko, A., Verbitskii, V., Kravchenko, A., & Kravchenko, K. (2018). The stability analysis of two-wheeled vehicle model. In MATEC Web of Conferences, 157. EDP Sciences. https://www.matec-conferences.org/articles/matecconf/pdf/2018/16/matecconf_mms2018_01007.pdf
Li, A., & Ando, R. (2013). Measuring the acceptability of self-balancing two-wheeled personal mobility vehicles. Journal of the Eastern Asia Society for Transportation Studies, 10, 444-453. https://www.jstage.jst.go.jp/article/easts/10/0/10_444/_pdf
Szymlet, N., Lijewski, P., & Kurc, B. (2020). Road tests of a two-wheeled vehicle with the use of various urban road infrastructure solutions. Journal of Ecological Engineering, 21(7).
Tirmant, H., Baloh, M., Vermeiren, L., Guerra, T. M., & Parent, M. (2002, June). B2, an alternative two wheeled vehicle for an automated urban transportation system. In Intelligent Vehicle Symposium, 2002. IEEE, 2, 594-603. https://www.researchgate.net/profile/Thierry-Marie-Guerra/publication/4008030_B2_an_alternative_two_wheeled_vehicle_for_an_automated_urban_transportation_system/links/00b4951c1c48d8f219000000/B2-an-alternative-two-wheeled-vehicle-for-an-automated-urban-transportation-system.pdf
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We have proposed an algorithm for multiobjective multimodal optimization problems and tested it on CEC 2019 benchmark dataset. We need to show the results on some real problem also. Kindly help.
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Try implementing your methodology in structural optimization tasks. A quick literature search will get you up-to-date on all the details required.
Good Luck
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And how can I download images from the whole brain ATLAS dataset provided by Harvard.
the website is http://www.med.harvard.edu/AANLIB/home.html, I can not find where to download.
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Hi ! does anyone know if I can directly buy core only glass fibers ? Meaning no cladding or coating ?
I ideally am looking for a multimode glass core for biosensing purposes.
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Did you find those single glass composition rods, finally? I might be interested, too.
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Hello there!
I have searched everywhere for a MRI dataset for amyotrophic lateral sclerosis, ideally a multimodal one (DTI especially would be appreciated).
Thank you in advance.
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This would be a great question to post on our new free medical imaging question and answer site ( www.imagingQA.com ). We have a number of image analysis experts in the community. If useful, please feel free to open a new topic at the link below:
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I formulated chitosan nanoparticles from a 0.5% w / v chitosan solution and 0.5% w / v TPP. after adding the TPP solution drop by drop to the Chitosan solution, I obtained a turbid suspension. I centrifuged at 3500 rpm for 30min and a pellet formed which I was able to resuspend with an ultrasound probe. After the size measurement at the DLS I have a multimodal distribution with most of the particles having a radius greater than 400nm.
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try adding span 80 (0.5%) as a surfactant during the formation of nanoparticles it would probably stop your NPs from aggregating and also aid in resuspending, with a gentle shake.
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The actual registration process is far from optimal as you can see from the attached picture.
Any idea on how to improve the registration process result?
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Hey Erik,
I have come across the same problem. Can you remember how you solved it and help me fix my registration?
Warm regards
Renée
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What is the bandwidth specification of standard multimode OFC cables that are available for communications and networking? will they carry all UV-VIS-IR spectrum?
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  • In the recent CV field, the world's top journals and conferences, we can see that many papers use multimodal / multi view information for 3D object detection.
  • However, it is rare to use multimodal information for 2D object detection in autonomous driving scene. The most recent one is' seeing through fog without seeing fog. Bijelic et al., 2019 ', but this article is mainly about the contribution to adverse weather data set.
  • How to improve the performance of 2D target detector through multimodal fusion in the automatic driving scene?
  • Or, how to use depth information for 2D target detection?
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Dear Jiawei Ma
You may use one of my article for the same issues
Satya Prakash Yadav, Vision-Based Detection, Tracking and Classification of Vehicles, IEIE Transactions on Smart Processing and Computing, SCOPUS, ISSN: 2287-5255, 9(6), pp.427-434 https://doi.org/10.5573/IEIESPC.2020.9.6.427.
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Dear All, within our new European project SYN+AIR related with the air transport we are executing an online survey which aims at identifing the mobility choices related to and from the airport. We are glad to invite you fill in the survey https://ec.europa.eu/eusurvey/runner/SYN_AIR_Traveller_Survey_2021 The questionnaire is available in 5 languages (English, Greek, Spanish, Italian, Serbian) and lasts approximately 10 minutes. All adults that travel or used to travel by plane (before the Covid-19 pandemics) can answer this survey. You may find information related to the project at http://syn-air.eu/
Please, feel free to share/disseminate this request. Thanks a lot for your attention and contribution. #SESAR #H2020 #SYN+AIR
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Dear Prof. Ottomanelli!
I have filled in the survey, you posted. It was a nice experience. May I kindly recommend you a B2B - platform - the registration is for free, and there are many free of charge webinars, etc. resources you might benefit from:
3) A recent webinar: Patrick Keliher, Regional FAE Manager (RTI) and Maxx Becker, Field Application Engineer (RTI) (2021). On the High Speed Data Line: Accelerating the Evolution of Rail Transportation, March18 2021, Please see further details at: https://www.brighttalk.com/webcast/18279/473029?utm_source=brighttalk-portal&utm_medium=web&utm_content=transportation%20&utm_term=search-result-2&utm_campaign=webcasts-search-results-feed
Yours sincerely, Bulcsu Szekely
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We have datasets that have a Gaussian distribution.
,Data were obtained from different, irregular, and multimodal Gaussian distributions
How can we use the k-means clustering method for highly optimal clustering so that the most statistically similar data are in the same group?
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We have seen a stability in the supply chains of goods, food in particular, during the current pandemic of Covid19 continue, mostly undisturbed.
It is very reassuring at a time of uncertainty and macro-risks falling onto societies.
How much do we owe to the optimised management and supervision of Container transport, and multimodal support to it with deep sea vessels, harbour feeder vessels, trains and trucks/lorries?
What is the granularity involved? Hub to hub, regional distribution, local delivery?
Do we think that the connectivity models with matrices, modelling the transport connections, the flows per category (passengers, freight, within freight: categories of goods), could benefit from a synthetic model agreggation of a single matrix of set federating what has been so far spread over several separate matrices of numbers?
What do you think?
Below references on container transport, and on matrices of sets
REF
A) Matrices of set
[i] a simple rationale
[ii] use for containers
[iii] tutorial
B) Containers
[1] Generating scenarios for simulation and optimization of container terminal logistics by Sönke Hartmann, 2002
[2] Optimising Container Placement in a Sea Harbour, PhD thesis by by Yachba Khedidja
[3] Impact of integrating the intelligent product concept into the container supply chain platform, PhD thesis by Mohamed Yassine Samiri
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When I use multimode fiber to guide the quantum dot ensemble photoluminescence signal to my Horiba FHR100 spectrometer. I always get a spectrum with periodic peaks as pic.jpg .
It looks like the peaks has a exact period of 1.5 nm.
Only when I guide the PL signal with a single-mode fiber canI get the smooth signal I wanted to see.
Could someone please help explain what the source of this periodic peak is and How can I avoid them .
Thank you!
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Looks like you have cross-coupling between (strong) principal modes and (weak) neighboring modes. Take a look at the attached where similar observations are shown albeit with a different periodicy. I suspect your original signal is interacting with with up-shifted with your fluorescence signal.
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Hi everybody!
I am working on my diploma thesis regarding eye endoscope. I would like to know more about the speckles in the multimode fiber. I would like to reduce speckles in MM fiber using vibration. I do not know why the vibration reduce the speckles and what happens with modes that are in the optical fiber.
Thank you for your answer!
Regards
Barbora Spurná
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Jörn Bonse provides a very clear explanation of speckle motion in MM fiber resulting from fiber flexion. The next question is how to move the fiber to reduce the speckles adequately to meet you needs. Presumably, your aim is to create a smooth illumination field for your endoscope. So, how to vibrate the fiber, in terms of direction of motion, amplitude, frequency, etc? Some of these questions can be answered through experiment -- you will be time averaging (integrating) the moving speckle field over the frame time or exposure of your camera. Therefore, the vibration period must be less than 1/10 of the exposure and preferably much shorter to enable speckle patterns to average out. The amplitude of the vibration only needs to be enough to 'shake' the speckle pattern by a few characteristic speckle dimensions or so. Once you have a mechanism to vibrate the fiber, you can ensure that the amplitude of vibration is large enough. Finally, you need to create a diverse set of speckle patterns during an exposure time. Some schemes use two vibrators in orthogonal directions at different frequencies (that are not low integer multiples). It is probably best to build up your system with vibration frequency set first, then experiment to ensure that the speckle pattern averages out enough for your purposes. Add complexity if it is needed. Finally, there are other ways to smooth speckle patterns that use spinning diffusers in the light path. However, in your endoscope, your idea of vibration seems practical. Here is an interesting reference: https://www.osapublishing.org/oe/fulltext.cfm?uri=oe-28-9-13662&id=431120.
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Hi
I wanted to work on a comparison between the traditional class discourse interaction analysis and the new discourse version interaction system caused by the virus, and I also wanted to work on the part of the professors' opinions about the differences between these two discourse structures but I need some guidance to know poststructuralism or constructivism and in methodological frameworks, multimodal critical discourse analysis is the right one?. I have also doubted in the comparison that I should have one theory or draw results on two theories.
In advance thank you so much
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Hi dear friends,
Thank you very much for sharing the great information with me.
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Hi everybody!
I am working on my diploma thesis regarding eye endoscope. I would like to know more about the origin of speckles in the multimode fiber. I suppose that the speckles depend on fiber modes but I do not know why should high-order modes move with higher speed than low-order modes. And how does this fact influence the speckles.
Thank you for your answer!
Regards
Barbora Spurná
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speckle patters arise whenever lights from a variety of directions hit a scree, When the number of different directions is large (≈>50) the one sees the "normal" speckle pattern (BTW each fo the black spec is actually a phase singularly, or optical vortex). A multimode fibre typical supports >1000 fibre modes so their addition/interference is what creates the speckle.
within a ray optical picture, the rays associated with different fibre modes zig-zag down the fibre at different angles from each other 8every mode having ≈ its own zig zag). the higher order modes zig zag more tightly. remember that the wavevector has x, y, and z components (kx^2+ky^2 +kz^2 = k0^2). if the ray has non zero kx and ky then kz must be reduced below k0. the more tight the zig zag the more kz is reduced. phase velocity in z-direction is omega/kz, smaller kz gives larger Vphase.
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Accurate image captioning with the use of multimodal neural networks has been a hot topic in the field of Deep Learning. I have been working with several of these approaches and the algorithms seem to give very promising results.
But when it comes to using image captioning in real world applications, most of the time only a few are mentioned such as hearing aid for the blind and content generation.
I'm really interested to know if there are any other good applications (already existing or potential) where image captioning can be used either directly or as a support process. Would love to hear some ideas.
Thanks in advance.
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What kind of matrices and why ?
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From what i have used, some self-similarity metrics can really enhance the multi-modal image registration. Try to explore more about the structural information hidden in the images...
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I have to analyze construction project (it comprises images and text) from the viewpoint of multimodal analysis. Who has got some theoretical unformation about it or samples of multimodal analysis? Thanks a lot
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I am attaching some references in which the multimodal nature of human communication, the concepts of multimodality, about semiotic resources & modes, the type of relationships that are established between different semiotic resources, etc. are discussed in detail:
  1. Hodge, R. and Kress, G. (1998). Social Semiotics. Cambridge: Polity Press
  2. Kress, G., & Van Leeuwen, T. (1990). Reading Images. Geelong, Victoria: Deakin University Press.
  3. Kress, G., & Van Leeuwen, T. (2001). Multimodal Discourse: The Modes and Media of Contemporary Communication. London: Arnold. Kress, G., & Van Leeuwen, T. (2006 [1996]). Reading Images: The Grammar of Visual Design (2nd ed.). London: Routledge.
  4. Kress, G. (2010). Multimodality: A social semiotic approach to contemporary communication. London; New York, NY: Routledge.
  5. Norris, S. (2004). Analyzing Multimodal Interaction. A Methodological Framework. New York: Routledge.
  6. Norris, S. (2013). What is a mode? Smell, olfactory perception, and the notion of mode in multimodal mediated theory. Multimodal Communication, 2(2):155–169. https://doi.org/10.1515/mc-2013-0008.
  7. Scollon, R. (1998). Mediated Discourse as Social Interaction. London, New York: Longman.
van Leeuwen, T. (2005). Introducing Social Semiotics. London: Routledge
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I need to know if MM8 or MFP-3D origin gives more reliable data for the nanomechanical measurements like nanotube stiffness. Moreover, which one best performs in liquid and can give nanoparticle protein interaction forces. If anyone can tell me about vibration sensitivity of these that would be great also.
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I've used both systems for nanomechanics. Each of them has their unique characteristics. Some might be more suitable for you application than others.. I'm also wondering which one you chose.
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This dataset will be used in the context of a University Course.
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Is it ok to say political caricatures instead of political cartoons in visual and multimodal metaphor?
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Charles Forceville's remark seems to me as inspiring as can be. Political caricature, as a form of humor communication, borrows something from the visual structure of political banners, projecting certain features of the political character through the image, of course exacerbating them to be easily recognizable. On the other hand, in political cartoons, the reality effect of the animated film naturalizes and somehow insidiously gives way to the message, the verbal content.
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Recently, I have been using the multimodal machine learning method to study the computer-aided diagnosis of cataract, but the data is not enough. Where can I find a multimodal data set? it is better to include image and structured data modalities.
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I have a keystroke model which is one of the modes in my multimodal biometric system. The keystroke model gives me an EER of 0.09 using Manhattan Scaled Distance. But then I am normalizing this distance to fit in the range of [0, 1] using tanh normalization. And when I run a check on the normalized scores I am getting an EER of 0.997. Is there something I am doing wrong? The tanh normalization I am calculating based on the mean and std dev of matching scores for genuine users.
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w/a = (0.65+(1.619./V.^(3/2)+2.879./V.^6)
Is this formula is also valid for step index multimoded waveguide for calculating the spot size of fundamental mode?
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Your formula was derived for circular core step index fibres. D. Marcuse, Bell Syst. Tech. J. vol. 56 pp 703-718 (1977).
I don't know how accurate this will be outside the single mode regime.
It will be less accurate for waveguides lacking circular symmetry, but it may give some indication of the likely spot size if the core is almost circular and buried below the surface of the waveguide.
For a step profile planar waveguide, the field in the core follows a cosine distribution, with an exponential decay in the cladding. It is not too difficult to derive the transverse propagation parameters of the fundamental mode from the wave equation, given the core thickness and core and cladding refractive indices.
At high V-numbers for low order modes the field amplitude at the cladding boundary approaches zero. The transverse (x) field distribution of the fundamental tends towards cos(π x / (2a)) for a core of thickness 2a.
More generally, at high V-numbers the field in the core is given by
E ~ cos(U x / a) where
U ≈ (π/2) V / (V + 1) for TE modes
U ≈ (π/2) Vn2core / (Vn2core + n2clad) for TM modes
From Snyder and Love, "Optical Waveguide Theory", Tables 12.1, 12.2 (1983).
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I am conducting research on Multimodal Discourse Analysis (MMDA) field. Which are the seminal works (books, papers, ...) in Multimodal Discourse Analysis (MMDA)?
I really appreciate knowing other researchers' point of view.
Thank you.
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Hi Ilaria. I'm sorry to disagree with the two previous answers by Sergio and Weimin, but I assure that the suggested readings have nothing to do with your specific question and are not relevant at all with MDA.
To start off, my suggestion is that you read
Multimodal Discourse Analysis: Systemic Functional Perspectives (2004) edited by Kay O'Halloran. It's old, but it is foundational and basically sets out to introduce the field of multimodal discourse studies within SFL. Some people wrongly refer to another foundational book, that is the celebrated Reading Images (2006, second edition), bu Gunther Kress and Theo van Leeuwen. Impossible to udnerstand what multimodal studies are and where they come from without this reading, but please be informed that this is NOT about multimodal discourse analysis - that is a strand iniatiated more systematically by Kay O'Halloran in the early 2000s. Much stuff has been circulating from O'Halloran's edited collection, but I always suggest novice readers in multimodality to start from it all began.
You may also wish to selectively read chapters from The Routledge Handbook of Multimodal Analysis edited by Carey Jewitt (2nd edition, 2013, the first edition, 2009, includes less chapters) and/or as the best introduction with clear and concise explanations of the different strands within multimodal approaches to semiosis of communication (including MDA) I recomment the excellent Introducing Multimodality (2016), written by Carey Jewitt, Jeff Bezemer and Kay O'Halloran.
These are basic and most useful readings to my knowledge.
hope this helps!
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can we use score level fusion of Genuine and Imposter scores of a multi-Biomteric techniques to multimodal emotion recognition ?
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The performance of any unimodal biometric system is dependent on factors like environment, atmosphere, sensor precision. Also, there are several trait specific challenges such as pose, expression, aging etc for face recognition, occlusion and acquisition related issues for iris and poor quality and social acceptance related issues for fingerprint. Hence, fusion of more than one biometric samples, traits or algorithms to achieve superior performance is an alternative way to achieve the better performance and is termed in literature as multi-biometrics or multimodal biometrics.
Refere the following link. It may be useful for you.
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I currently doing a research in fiber sensor using MMI, but i don't know how to determine the lenght of the multimode sensor. All reference that i read used the 4th self-image for determining the lenght of the multimode sensor, why the 4th self-image used ?
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good question
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I'm doing some research on dimensionality reduction using swarm intelligent algorithms. As per the no free lunch rule, there is no algorithm that best suit all the problems. So, to be able to find the best subset I need to determine whether it's unimodal or multimodal? The data is of 300 features and 1000 instance. Is there any visualization methods that can help in this regard?
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Dear D\ Ahmed
No general methods for dimensionality reductions because of the various of data characteristics. To overcome this limitation, you can use ensemble learning (as, ensemble feature selection). It supports the diversity and stability terms. I recommend you this paper " Ensembles for feature selection: A review and future trends":
This book for more details "Recent Advances in Ensembles for Feature Selection",
Also check this paper " Swarm Intelligence Algorithms for Feature Selection: A Review
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I made an experiment where I measure certain parameter a number of times. The result is over a 100 samples which distribution is not really normal. Due to properties of my specimens, results tend to gather around 3 or 4 modes. The distribution is multimodal. I would like to find the type A uncertainty of the measurement. When the distribution is normal, unimodal, the standard deviation is easily calculated. How to proceed when the distribution is multimodal? I found the stdv, same way as for unimodal, but I am not sure that this is correct way. Are there any dedicated standard deviation formulas for multimodal distribution? Even if I split my results into 3 or 4 separate unimodal sets, each with its own stdv, how to find the overall deviation?
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It's as always: one size doen not fit it all. There is not one descriptive statistic (like the SD, for instance) that is useful to describe relevant featuresof any distribution. If I know that the distribution is (at least approximately) rectangular, provinding the limits is much much more useful that listing some moments (like mean, variance, skew, kurtosis etc.). If I know that the distribution is exponential, it is much much more useful to simply give the rate parameter. In your case, if you know that the distribution is multimodal, it might be useful to deconvolute it into individual unimodal parts for which you can give the means and the SDs (google for"expectation maximization", a technique that works quite well to achieve such a deconvolution for a given sample).
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I have known that the single-mode fiber (SMF) only allows the transmission of single-mode light, so we have to do mode-matching in SMF coupling. However, I am wondering what happens if we do not follow the strict mode coupling condition, we just couple all the energy into the SMF while do not follow the phase matching, how much loss will we get? Does the length of SMF have an influence on coupling efficiency in that situation?
Whether is it possible that we can still achieve less loss by a shorter SMF(with a range of few meters)?
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When you couple to a single mode fibre, only that part of the light which is matched to the waveguide's fundamental mode fields is guided. The remainder (ignoring Fresnel reflection losses) is coupled into the fibre, but will radiate away from the core and into the cladding.
What happens to the cladding light depends on the fibre structure and material composition.
If you have an unprotected bare glass cladding, the cladding acts as a multimode waveguide, which confines light by total internal reflection at the cladding glass/air boundary. In this case light can be transmitted long distances, limited by optical attenuation within the cladding glass and potentially by refraction or absorption where the cladding makes physical contact with its surroundings.
Most optical fibre is surrounded by a protective buffer coating, frequently an acrylic resin which has a higher refractive index than the cladding glass (typically silica). In this case much of the light incident at the cladding/buffer boundary is coupled by refraction into the buffer polymer and absorbed - probably within a few millimetres, depending on the wavelength and spectral attenuation of the buffer. Such coatings are sometimes referred to as "mode stripping".
Even with a higher index mode stripping medium surrounding the cladding, some rays striking the cladding boundary at glancing incidence can undergo repeated reflections, losing power by refraction at each encounter, but with significant transmission over tens of centimetres or longer. Transmission is maximised by keeping the fibre as straight as possible, or by maintaining a large constant radius of curvature to minimise mode coupling between low order cladding modes and higher order modes which are more strongly refracted into the buffer.
Some fibres are manufactured with a silicone buffer coating. This was more common in the late 1970's and 1980's. Silicone can offer excellent optical and mechanical properties from low temperatures up to much higher temperatures than are possibly with acrylic coatings, so may still be used in specialist cables.
Silicone has a lower refractive index than silica glass, so the glass cladding acts the core of a multimode waveguide, with a silicone cladding.
Attenuation of cladding light will depend on the composition of the cladding glass. For high purity synthetic silica, attenuation at 1300 nm can vary from around 1 dB/km for "dry" silica manufactured by plasma deposition, to around 1000 dB/km (1 dB/m) for flame hydrolysed (UV-grade) synthetic silica.
In a silicone-buffered fibre, there will be additional attenuation through evanescent coupling into the silicone resin, particularly near the strong absorption in the 1100-1200 nm region.
Some fibres manufactured by an "inside tube" process combine a high purity synthetic silica inner-cladding, deposited within a fused natural quartz substrate. The natural quartz can contain small (ppb) quantities of transition metals which cause additional attenuation, although losses over a few metres are likely to be modest.
So we can make guesses but precise predictions of transmission losses in the cladding are difficult, and require information about the fibre design, cladding and buffer compositions.
If your receiver has a sensitive area comparable to a single mode fibre core, much of any light remaining in the cladding will not be coupled. The fraction of cladding light intercepted is unlikely to be as high as 10%, and is more likely to be less than 1%, the actual proportion depending on the radial intensity distribution in the cladding modes, which in turn will depend on the magnitude and character of mode coupling induced by bending and other imperfections in the cable.
Alternatively, if you need to couple the output from a single mode fibre core to a somewhat larger detector, have you considered using a short length of multimode fibre, rather than a single mode fibre with poor mode matching to your source?
Is temporal dispersion a concern? If so, is the difference in propagation speed between core guided and cladding modes significant?
Hope this helps.
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In boundary condition ,it needs xmin xmax ymin ymax , should I put all of them pml or not?
And which size is enough for the FDE rectangular?
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@Mohamed-Mourad Lafifi
Thanks for your helpful answer.
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I am making a design where I have to splice PM single mode fiber to graded index multimode fiber, can it be possible with generic splicers or need some specialized one. what parameters should be considered to make an acceptable splice.
Thanks
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Hello Abbas
Try to change the time or/and current of the splicing arc. In order to understand the effect, try to use an additional arc several times after the main arc (in the main MM programm), observing the level of the loss. Using this method you can try to decrease the loss level. If not - try to decrease the time or the current of the main arc.
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In problems with many local optima (multimodal) and many variables to optimize (multidimensional) which PSO variants are those that provide:
  • better exploration capabilities at the beginning of the search,
  • possibility of escaping local optima,
  • capabilities to find the optimal solution when it is not at the center of the coordinate system,
  • better quality of the final solution (more exploitation in the final period of the search process), and
  • low computational load (less evaluations of the objective function, shorter computation times)
It is grateful that in your response the bibliographic source where the PSO version is published is informed.
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All the answers are great
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In (Wu, Y, et al 2017), the authors use 2 kind of objective functions (MI and DTV) with 4 optimization methods.
The attached table shows objective function result and RMSE. BTW, I can't understand how CLPSO with MI, DE with MI, ACO with MI and LMACO with MI have Mean and Best result for DTV? Since it runs with MI. If the authors says CLPSO, DE, ACO and LMACO without MI will be correct but they link the result with MI.
I hope my inquiry clear.
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Dear Mohammad Alnagdawi,
I think they are using MI and DTV (written in the first column) in order to rank the solution candidates while the algorithms are running, I mean these metrics are used to understand how good a solution candidate is. When the algorithm finds a solution, they can calculate MI, DTV and RMSE metrics using the found solution and the real answer. It would be strange if an algorithm running using MI would beat the same algorithm using DTV in terms of DTV, but that's not the case here.
Regards,
Ozan
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Dear Colleages,
I'm interested in visual and pictorial respresentations. Actaully, I have an idea that they have have a relationship with interextuality.
Please, there is any studies that focus on the intertextual analysis in the mutimodal (visual/pictorial) respresnetation, let me know.
Thanks
Hayder
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Dear Hayder,
When the meaning of a text depends or is its own visualization as argued by Farangis, this is called iconicity, where a text is an icon of itself, but not intertextuality as defined by De Beaugrande and Dressler (1981) as subsuming "the ways in which the production and reception of a given text depends upon the participants’ knowledge of other texts" (p. 183).
There is no direct and automatic relation between intertextuality and visual, pictorial, and multimodal communication. In ts simplest form, intertextuality may refer you to a written text. However, intertextuality in a text (written, oral, or even pictorial) could refer/send you to other (written, pictorial, or multimodal) scenes or texts. For instance, a written text could allude to something which you may readily visualize in your mind in the news, documentary, or film you have heard or watched. This is why I said there is no direct link between intertexuality and multimodality.
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I need some information on ATLAS.ti
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Many thanks .. They are naluable indeed. Pleased to have your response
Hussain
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Dear RG members,
Once I came across a software developed by Kay O Holloran to analyse moving pictures/videos. If you know such things, multimodal tools/models
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I am simulation one fiber optic liquid level sensor where I am taking 1cm long multimode fiber. The cladding of the multimode fiber is removed by chemical etching process. For, measuring the liquid level, some portion of the fiber is immersed in the liquid and the remaining portion in in the air. Thus, the guided mode beam profile in the air-cladding section and that in the fluid-cladding section should be different. So there should be mode conversion loss.
Is there any theoretical formula to calculate such mode conversion loss.
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In multimodal images, we use intensity variation (or difference) to describe different intensity levels of images represent same sense (captured by different sensors). Also, it has 3 types:
  • non-linear intensity variation
  • linear intensity variation
  • local intensity variation
I read many papers but I still unable to find a proper definition or exact borders between these kind of intensity variations.
Please don't hesitate to send any hint that may guide me. I don't ask to suggest a paper just I need to know the different between them
Thanks
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@Omar S. Al-Kadi: I think nonlinear radiometric differences is same as non-linear intensity variation. Are you agree with me?
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Considering that for ethics reasons participants need to know that they are being recorded in a spontaneous video-mediated conversation (ex. a Skype call), I need to find relevant studies that show how/when/to what extent such data can be considered as reliable, or really spontaneous.
Any relevant research literature you can direct me to?
Many thanks!!
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Yup, it would. But they didn't know they'd been recorded. We got in, probed for the material we were looking for and when we felt we had enough we stopped recording, informed them about the project and asked permission to use the recorded material. We only used material we were given permission for and deleted the rest. Most, even if surprised -or even annoyed- at first, were more than eager to allow use of the 'bootleg' recordings when we explained why we needed them, some asked for anonymization, only a few downright denied involvement.
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Why multimode fibers are used in medical applications ?
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Thank you Abdelhalim.
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I'm looking for examples of how street protests can be analysed from the perspective of multimodal discourse analysis. What coding techniques and methods of analysis are effective in studying how solidarity of protest movements and political dissent are constructed by multimodal texts of slogans, banners, ribbons etc. 
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"The linguistic landscape: mobile signs, code choice, symbolic meaning and territoriality in the discourse of protest," by Adrian Kasanga can be of help. Please, see the attached. A few of my own discourse analysis of discourse of protests might be of help too.
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Hi scholars, I am planning to employ neural networks for score-level multimodal biometric fusion. Any suggestions?
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Hi, 
I want to a link to any complete and available multimodal databases for socre-level fusion purpose.
 Thank you so much.
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Suppose barium concentration in coarse, accumulation and quasi-ultrafine stages is 0.039, 0.189 and 0.056 microgram cubic meter, the what distribution pattern it follows?
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Hi Himanshi
You may have to plot frequency (number of times on y axis) versus barium quantities (microgram per cubic metres on x axis). Have I got the question right?
Best regards
Ravi
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Hello All,
I would like to ask about the following  benchmark  functions:
Trid
Zakharov
Rosenbrock 
Colville
Sphere
Are these benchmark  functions  unimodal  or multimodal ?
Thanks to all who contribute to the answer.
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The classical Rosenbrock function is a two-dimensional unimodal function. Many researchers take the high-dimensional Rosenbrock function as a unimodal function by instinct. Some scholars found that the Rosenbrock function is not a unimodal function for higher dimensions although no theoretical analysis was provided.
check this paper: 
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Colleagues gave to our department the platereader, but the installation CD with the software (for winXP) was not in the box, and its presumably lost. We have looked for the original supply on the web, but there is no repository or tech support. 
If someone could share (via mega or google drive) the software, or (god bless you) send a CD copy, our department and I myself personally would be really thankful.
Thanks in advance. 
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hello
did you finally get the multimode analysis software ?
I have the same problem...
cheers
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The results of DLS measurment always give us Lognormal Size Distribution and Multimodal Size Distribution. I do not know exactly what is the different between them? and Which one is better?. For my experiment, I want to survey the change of diameter of nanoparticle after adsorption an extra molecular. 
Could everybody give me some advises?
Many thankful for !
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dont use log-normal. check our new paper
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I mean general information about multimodal learning in foreign languages teaching, some articles. I would be grateful if you sent some information about multimodal learning of some  images, sketches in ESP and ESL.
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Dear Ms Nata Kuzlo,
We are writing in connection
with  your questions. You are luky person,  becouse I read an interesting article on your topic during my preparation for doctorial disertation.
Please find attached article as a PDF file.
I hope i have been some of help.
Best regards,
Andrija
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I have a trimodal distribution and I would like to fit a model on it. I have already tried Gaussian Mixture Model (GMM) with different number of component to fit on distribution. The problem is whenever I ran GMM, I have got different weight and mean values for each modal in distribution. Is there any other reliable fitting model to fit on multimodal distributions.
Thanks 
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Thanks for your suggestion. In fact I am running both BIC and AIC on my samples and pick the stats. parm based on the best model with min BIC and/or AIC. But still the answers are not convenient and I am getting a range of answers by repeating the whole calculations. I appreciate if you have any suggestions or comments for me.
Thanks
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I am working with our team to develop ERAS protocols for spine surgery patients and have found nothing in the literature specific to this patient population. any help would be appreciated. I plan to post what we develop for others to adopt to their particular place of practice.
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Thank you so much for your input! Both of these have been very helpful.
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I am trying to get decent power out of a fiber I am coupling to my laser (dynamic range: 100mW) but am having a hard time.  The fiber is 400um multimode, 0.39 NA and is connected to an SMA adapter threaded to a mount whose angle you can adjust.  The fiber post is mounted on a translational stage.  I do not have any convex lenses between the fiber and lens at the moment because my spot size is already very, very small.  But the power that comes out of my fiber when the laser is set to ~60mW is around 1uW... Any tips?
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You may check if you can use a diverging lens in front of the laser output. That is a lens with convex-concave surfaces. The concave side should face the laser output. 
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Consider the identification of non linear system whose model is known beforehand.The identification problem is now that of the parameter estimation.
This problem is solved using meta heuristics.
But the issue is whether the MSE landscape for the non linear dynamical system is multi modal??
Can we have a mathematical proof of it?
I have attached a paper which says that the MSE will be multi modal but I don't understand how to prove it .Please help.
Thank you
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Yes.
All I need to verify is that it must have more than one local optima.
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i am using multimode 8, to study the piezohysteresis loop of the thin film. but i didn't get any good and flat curve. most of the time curve is collapsed and some time it's bit clear.  
can anybody give me good suggestions/steps regarding this.
maybe it's little bit hard to get good piezoresponse curve for thin film case, but i think it shouldn't be collapse nature... 
exactly don't know, some instrumental or scanning parameter issues.  
Regards.
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Multiliteracies is taking into account the various modes of meaning making/multimodality
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with continous simple practise
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Hello,
I want to find out how many modes are present in data distribution. As per my search I found many methods for testing whether a distribution is unimodal or multimodal but I am interested in finding out number of modes available in distribution. Can any one suggest me how to estimate this?
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By counting the pics in the histogram of your data.
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Is there anything, for instance, like the findings about preference organisation in conversation analysis, or hypercorrect patterns in sociolinguistics, or semantic prosody in corpus linguistics?
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Multimodality can be used to build inventories of the semiotic resources, organizing principles, and cultural references that modes make available to people in particular places and times: the actions, materials and artifacts people communicate with. This has included contributions to mapping the semiotic resources of visual communication and colour, gesture and movement, gaze, voice and music, to name a few.
Multimodal studies have also been conducted that set out to understand how semiotic resources are used to articulate discourses across a variety of contexts and media for instance school, workplaces, online environments, textbooks and advertisements. The relationships across and between modes in multimodal texts and interaction are a central area of multimodal research.
Multimodal research makes a significant contribution to research methods for the collection and analysis of digital data and environments within social research. It provides novel methods for the collection and analysis of types of visual data, video data and innovative methods of multimodal transcription and digital data management.
Four core concepts are common across multimodal research: mode, semiotic resource, modal affordance and inter-semiotic relations. Within social semiotics, a mode is understood as an outcome of the cultural shaping of a material through its use in the daily social interaction of people. The semiotic resources of a mode come to display regularities through the ways in which people use them and can be thought of as the connection between representational resources and what people do with them. The term modal affordance refers to the material and the cultural aspects of modes: what it is possible to express and represent easily with a mode. It is a concept connected to both the material as well as the cultural and social historical use of a mode. Modal affordance raises the question of what a mode is ‘best’ for what. This raises the concept of inter-semiotic relationships, and how modes are configured in particular contexts. These four concepts provide the starting point for multimodal analysis.
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It is well known, that co-expressive gesticulation gestures develop their structure of movement accompanying the verbal and melodic structure of the utterance and also that they are linked to it semantically and pragmatically.
When analysing gesticulation gestures linked to verbal language and intonation, it seems to me a little bit difficult to establish a close descriptive relation between the movement structure of gesticulation gestures and the verbal and melodic structure of the utterance in spontaneous speech.
I think, that one of these categories or aspects has to do with the close relation between the more prominent segment in pitch range of the utterance and the more prominent phase in gesticulation structure.
Could you suggest me other categories or aspects I should pay attention?
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Dear José,
As you know, Núria Esteve-Gibert recently discussed her PhD thesis exactly on the alignment between gesture, prosody and segmental material. Since the research question of "gesture-prosody-text alignament" is actually not new (dating back to even before McNeill's 1992 book), Nuria's thesis focussed on some more specific and new issues, that had to do mainly with language adquisition and infants. In case you are interested in the alignmanet/interplay among gesture, prosody and segmental material in adults, you might have a look at the Introduction of Nuria's thesis, where she summarizes in a few pages the most relevant studies about this subject.
See you in June :-)
Paolo
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im working with vehicle detection and tracking .. i just want to know whether this issue can  be handled here?
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Recently I have a paper in IEEE Xplore about vehicle detection/segmentation.
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We are trying to coupling light from a multimode fiber (core diameter of 100-200 um) to a normal single mode fiber (9/125 um). A lens system was used but coupling loss is still very significant. How can I achieve efficient light coupling from multimode to single mode fibers? Any off the shelf products available? 
Many thanks. 
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The second law of thermodynamics prevents efficient coupling from many modes to fewer modes. So do not be seduced by any "clever" coupling optics! (The only exception would be if you mode-locked the coherent source to the single mode fibre, probably not an option for you)
If all modes are equally excited in the Multimode fibre, then the coupling efficiency is defined by the ratio in the number of modes guided by the two fibre types: (2 orthogonally polarised ones in the Single mode fibre, and many hundreds in the Multimode fibre, dependant on core diameter, NA and wavelength). At the other extreme, if your launch conditions into the Multimode fibre preferentially excited low order modes, then this efficiency can be significantly increased.
Speckle will be a problem with coherent sources, (and is the cause of Modal Noise in multimode fibre transmission systems) wherever spatial filtering occurs. https://www.researchgate.net/publication/249650312_Phenomenon_of_modal_noise_in_fiber_systems
(NOTE I have now corrected the reference link)
You can suppress this noise if you are able to broaden the optical spectrum beyound the baseband bandwidth of your receiver.
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i want to design a multimod bandpass filter as a quarter CPW waveguide microstrip line to reduce noice application.please if you know about it please share to me thanks a lot,or send any citation to me.
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thanks
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Changing  the power ratio or so called modes power in the VCSEL does not necessary change the numerical values of the power coupling coefficient.
What is that?
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thank you very much for your prompt response.  Definitely,  the aforementioned parameters are going to have an effect on the coupling.  My main concern is this particular parameter "modes power ratio".  Changing this parameter in any design while all other parameters are constant "default values",  will not have an effect on the coupling at the multimede fiber, even if you excite more than 2 or even 10 modes.  The Power coupling coefficient will always be the same.  I'm wondering,  why? 
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Currently, I am working on a research topic related to multimodal transportation in continuous hub location routing problem. I was wondering if there are any research papers, studying the impacts of using different modes of transportation on hub discount factor (alpha). 
To be precise, how the value of alpha can be changed for different modes of transportation in a multimodal hub network
Addressing research papers would be highly appreciated.
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How to numerically find the values of propagation constant of different modes inside a step index multimode fiber using eigen value equation??
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please refer to the attached manuscript, which is soon to be submitted somewhere. it takes some time for exercise and familiarity with such numerica methods.
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In optical fiber, coupling co-efficient of each mode in a multimode fiber core has a finite value . Sometimes its value comes as (0.1+0.3*i), where i is the imaginary term. What is the physical interpretation of real and imaginary coupling co efficient at the multimode fiber core?
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Complex coupling coefficient indicates polarisation mode dispersion and polarisation dependent loss. It shows that eigenmodes and eigenvalues are affected (gain/loss of coupled mode).
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Can we explain the light guiding principle inside a single mode fiber by ray theory approach like a multimode fiber and how?
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Unfortunately a ray description of propagating light offers little of constructive value in understanding Single Mode fibres, as the small core diameter, and the low differential refractive index between the core and cladding, create a diffraction limited scenario. For example the energy spreads out significantly beyond the core into the cladding. (The optical spot size is larger than the core size). In no sense is the light reflected at the discrete interface between core and cladding. So the propagation velocity is intermediate between what one might expect from the core and cladding refractive indeces respectively.
However the general idea of lossless total internal reflection does provide a "handwaving" explanation of why the loss in optical fibres is so low.
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I have constructed a multimode fiber laser with the normalized frequency V of ~6, and the output mode is in the  multimode regime. We can distinguish clearly the LP01 mode and the LP11 mode, but we are not sure the further high-order mode is the LP21 mode or the LP02 mode. We now don't have a beam profiler at this wavelength. Will the LP21 mode definitely oscillate first than the LP02 mode when the pump power is increased?
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I a little agree with what Mikael said. We can choose certain modes to oscillate through carefully coiling the fiber. So, what important is what's the overlap between the mode volume and the gain volume, i.e., how much gain a certain mode can get, which can be disigned. 
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please tell me how to find the propagation constant of different LP(Linearly polarized) modes inside a multimode step index fiber. Is there any formula to calculate the value of propagation constant?? please suggest me some help
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In the scalar wave approximation, LP modes of a cylindrical core step index waveguide are described by Bessel functions in the core, and modified Bessel functions in the infinite, uniform refractive index cladding.  The propagation constants are found by solving a simple transcendental equation involving these Bessel functions.
For LPm,n modes, the core field at radius r is proportional to Jm(U r/a) where U is the transverse wavevector normalised to the core radius, a.  Jm(x) is a Bessel function of the first kind of order m.
The cladding field varies as Km(W r/a), where W is the cladding transverse evanescent propagation constant, normalised to the core radius.  Km(x) is a modified Bessel function of the second kind of order m.
The Eigenvalue equation is derived by matching the core and cladding fields and gradients at the core-cladding boundary:  U Jm+1(U) / Jm(U) = W Km+1(W) / Km(W); U2 + W2 = V2
The normalised frequency:  V = 2 pi / wavelength sqrt(n2core - n2clad)
Allan W. Snyder & John D. Love's "Optical Waveguide Theory" has more details in chapter 14.  Chapter 12 presents exact solutions which are valid for larger values of refractive index difference where the scalar wave equation and the LP mode description are less accurate.
The Eigenvalue equation must be solved numerically, but this will generally be faster and more accurate than a generic solver using methods such as finite element or finite difference, which are typically required for arbitrary refractive index profiles.
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In the field of multiobjective evolutionary optimization and solving multimodal problems there  many algorithms are  introduced up until now but some like NSGA-I, NSGA-II,SPEA-I and SPEA-II are much more famous than others. In NSGA-II  as I read in some papers the concept of crowding distance is used instead of fitness sharing that is used in its predecessor, NSGA-I.
I want to know the cons and pros of fitness sharing and crowding distance when you compare them and despite the lower order of calculation of  NSGA-II, what is the drawback of using the crowding distance method in it?
Thanks in advance. 
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This formulation of the crowding distance presents an instability in the produced results when the front F includes some individuals sharing the same fitness. 
Assuming an unstable sort, the crowding distance assigned to individuals sharing the same fitness can vary between calculations Most implementations, including Deb's reference implemen ation, use an unstable quicksort to sort the individuals
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What is the physical limit of the edge steepness of a flat top beam Profile?
We image the output (IR ns pulses) of a multimode fiber to our target in order to drill holes. But the low steepness of the flat top causes flaking on the edges of the hole. The material is a mulilayer structure.
I like to know the physical relation between the steepness of the beam profile edges with respect to the fiber core diameter, NA and wavelength.
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Thanks for your prompt answers - it helped!
We added a phase plate into the TEM00 beam and got a soft flat top. That was coupled into a multimode fiber whitch is some 10m long and coiled in order to mix to modes. At the output we use a 4f transformation with a spatial filter (pin hole) and a high performance optic to focus to the target. All this together gives us a nice and sharp flat top – and as you mentioned – it correlates with the number of modes one can create in the fiber. Hence, as bigger the fiber core as better the result. Off cores all is limited by the aperture of the following optics.
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Please send me the links so that i can download the multimodal biometrics database.
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You can request the MCYT signature+fingerprint database, for example:
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