1,721,000 research outputs found
Description of a new subspecies, Macrobrachium aemulum madhusoodani (Decapoda: Palaemonidae) from Neyyar River, Kerala, S. India
No full textUnnikrishnan, V. (2013): Description of a new subspecies, Macrobrachium aemulum madhusoodani (Decapoda: Palaemonidae) from Neyyar River, Kerala, S. India. Zootaxa 3722 (1), DOI: 10.11646/zootaxa.3722.1.
FIGURE 4 in Description of a new subspecies, Macrobrachium aemulum madhusoodani (Decapoda: Palaemonidae) from Neyyar River, Kerala, S. India
No full textFIGURE 4. Macrobrachium aemulum madhusoodani subsp. nov., specimen no. 2, paratype. Carapace left lateral view.Published as part of Unnikrishnan, V., 2013, Zootaxa 3722 (1), DOI: 10.11646/zootaxa.3722.1.4, http://zenodo.org/record/22421
A replacement name for Macrobrachium aemulum madhusoodani Pillai & Unnikrishnan, 2013, a junior homonym of Macrobrachium madhusoodani Unnikrishnan, Pillai & Jayachandran, 2011 (Decapoda: Palaemonidae)
No full textPillai, P.M., Unnikrishnan, V. (2013): A replacement name for Macrobrachium aemulum madhusoodani Pillai & Unnikrishnan, 2013, a junior homonym of Macrobrachium madhusoodani Unnikrishnan, Pillai & Jayachandran, 2011 (Decapoda: Palaemonidae). Zootaxa 3741 (3): 400-400, DOI: http://dx.doi.org/10.11646/zootaxa.3741.3.
FIGURE 2 in Morphology and molecular phylogeny of Macrobrachium snpurii, a new species of the genus Macrobrachium Bate, 1868 from Kerala, India
No full textFIGURE 2. Agarose gel electrophoresis of PCR product of M. snpurii sp. nov.Published as part of Pil Lai, P. M. & Unnikrishnan, V., 2013, Morphology and molecular phylogeny of Macrobrachium snpurii, a new species of the genus Macrobrachium Bate, 1868 from Kerala, India, pp. 434-444 in Zootaxa 3664 (4) on page 435, DOI: 10.11646/zootaxa.3664.4.2, http://zenodo.org/record/22102
Description, DNA barcode and phylogeny of a new species, Macrobrachium abrahami (Decapoda: Palaemonidae) from Kerala, India
No full textPillai, P. M., Unnikrishnan, V., Kumar, U. Suresh (2014): Description, DNA barcode and phylogeny of a new species, Macrobrachium abrahami (Decapoda: Palaemonidae) from Kerala, India. Zootaxa 3768 (5): 546-556, DOI: 10.11646/zootaxa.3768.5.
Visual mapping of internal pipe walls using sparse features for application on board autonomous underwater vehicles
No full textIn this project an algorithm to generate a single image of an entire water pipe's inside wall was developed. An Autonomous Underwater Vehicle (AUV) equipped with a fish-eye camera will be deployed to dive through the pipe and take pictures of its inside wall. The algorithm was implemented that maps such pictures to the three dimensional model of the water pipe and based on that, generates the image that one would see if the photographed section of pipe was cut along the side and rolled out. The algorithm then uses the rolled out versions of a series of consecutively taken photos to generate a mosaic showing the entire pipe in a single picture based on the recognition of sparse, structural features. The performance of the algorithm was verified in land based experiments and the robustness of the system to measurement inaccuracy was assessed. Finally two mosaicked images were created for different paths taken through the pipe, to demonstrate that the system is capable of generating the same image, regardless of the path taken by the AUV
Mapping the inside of a water pipe with an underwater robot
No full textIn this project a program that is capable of generating one image of an entire water pipe's inside wall was developed. An Autonomous Underwater Vehicle (AUV) equipped with a fish-eye camera will be deployed to dive through the pipe and take pictures of its inside wall. A computer program was implemented that maps such pictures to the 3 dimensional model of the water pipe and based on that, generates the image that one would see if the photographed section of pipe was cut along the side and rolled out. A second algorithm uses the rolled out versions of a series of consecutively taken photos to generate a mosaic showing the entire pipe in a single picture.<br/
Positioning and control of an AUV inside a water pipeline for non-contact in-service inspection
No full textWater pipelines are an important part of our social infrastructure. Early failure detection of the pipelines will help to prevent breakdown and avoid the large cost involved if a accident occurs. As pipelines are enclosed environments and difficult to access, pipeline inspection robots are increasingly used for routine inspection and early failure detection. In our research we propose the use of a small untethered AUV for the visual inspection of the pipeline interior. The vehicle carries optical sensors to aid non-contact motion inside the pipeline and also to capture images of the pipeline interior. The vehicle has identical front and rear sections and has a pair of cone laser and fish eye camera on either ends. The cone lasers and cameras act as range sensors as well as payload to capture pipe line interior images. A realtime vision based control system was developed for the autonomous operation of the proposed vehicle inside pipelines. A new offline position estimation algorithm estimates lateral position and pose of the vehicle inside pipeline. Laboratory experiments were performed in a test pipeline without and with water flow. The results of the experiment show that the proposed technique is efficient for non-contact inspection of a pipeline and helps to make vehicle compact to navigate through the enclosed environment inside pipelines.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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