29 research outputs found
Solitary angiokeratoma of tongue: A rare entity clinically mistaken as a malignant tumor
No full textConventional renal cell carcinoma with renal capsular leiomyoma: A diagnostic dilemma
No full textPrimary renal leiomyomas are very rare benign tumors of the kidney, arising from smooth muscle cells of the renal capsule, pelvis or blood vessels. Simultaneous occurrence of a leiomyoma with conventional renal cell carcinoma (RCC) in the same kidney is an extremely rare incidence. Herein we describe a case, which to the best of our knowledge is the second reported case in the English literature. This 70-year-old female presented in surgical out-patient department with the complaints of hematuria and abdominal pain. Subsequently, on computed tomography a multifocal mass was noted in the right kidney, measuring 4.5 cm Χ 3 cm Χ 2 cm and 1 cm Χ 0.5 cm Χ 0.5 cm respectively. A radical nephrectomy was performed with the clinical diagnosis of a multifocal RCC. Histopathological examination revealed a conventional RCC in the larger nodule, whereas the smaller nodule showed a sub capsular leiomyoma, which was immune-positive for smooth muscle actin and HMB45. In the index case, radiology could not differentiate between the RCC and leiomyoma. Apart from being a radiological diagnostic dilemma, rare HMB45 immunostain positivity in capsular leiomyoma may create diagnostic dilemma for histopathologists too. Sole HMB45 positivity should not distract one to diagnose this lesion as an angiomyolipoma, unless the other components are seen
A finite element superconvergence approximations for singularly perturbed system of convection-diffusion problems
No full textWinning customer loyalty in an automotive company through Six Sigma: a case study
No full textSix Sigma is a disciplined approach to improving product, process and service quality. Since its inception at Motorola in the mid 1980s Six Sigma has evolved significantly and continues to expand to improve process performance, enhance business profitability and increase customer satisfaction. This paper presents an extensive literature review based on the experiences of both academics and practitioners on Six Sigma, followed by the application of the Define, Measure, Analyse, Improve, Control (DMAIC) problem-solving methodology to identify the parameters causing casting defects and to control these parameters. The results of the study are based on the application of tools and techniques in the DMAIC methodology, i.e. Pareto Analysis, Measurement System Analysis, Regression Analysis and Design of Experiment. The results of the study show that the application of the Six Sigma methodology reduced casting defects and increased the process capability of the process from 0.49 to 1.28. The application of DMAIC has resulted in a significant financial impact (over U.S. $110 000 per annum) on the bottom-line of the company
Field Screening of Pigeonpea Genotypes against the Infestation of Tur Pod Bug, Clavigralla gibbosa Spinola
No full textScreening of Pigeonpea Genotypes against Tur Pod Fly, Melanagromyza obtusa (Malloch) in Agro-Ecosystem
No full textMultimodal Representation Learning for Visual Reasoning and Text-to-Image Translation
Get PDFabstract: Multimodal Representation Learning is a multi-disciplinary research field which aims to integrate information from multiple communicative modalities in a meaningful manner to help solve some downstream task. These modalities can be visual, acoustic, linguistic, haptic etc. The interpretation of ’meaningful integration of information from different modalities’ remains modality and task dependent. The downstream task can range from understanding one modality in the presence of information from other modalities, to that of translating input from one modality to another. In this thesis the utility of multimodal representation learning for understanding one modality vis-à-vis Image Understanding for Visual Reasoning given corresponding information in other modalities, as well as translating from one modality to the other, specifically, Text to Image Translation was investigated.
Visual Reasoning has been an active area of research in computer vision. It encompasses advanced image processing and artificial intelligence techniques to locate, characterize and recognize objects, regions and their attributes in the image in order to comprehend the image itself. One way of building a visual reasoning system is to ask the system to answer questions about the image that requires attribute identification, counting, comparison, multi-step attention, and reasoning. An intelligent system is thought to have a proper grasp of the image if it can answer said questions correctly and provide a valid reasoning for the given answers. In this work how a system can be built by learning a multimodal representation between the stated image and the questions was investigated. Also, how background knowledge, specifically scene-graph information, if available, can be incorporated into existing image understanding models was demonstrated.
Multimodal learning provides an intuitive way of learning a joint representation between different modalities. Such a joint representation can be used to translate from one modality to the other. It also gives way to learning a shared representation between these varied modalities and allows to provide meaning to what this shared representation should capture. In this work, using the surrogate task of text to image translation, neural network based architectures to learn a shared representation between these two modalities was investigated. Also, the ability that such a shared representation is capable of capturing parts of different modalities that are equivalent in some sense is proposed. Specifically, given an image and a semantic description of certain objects present in the image, a shared representation between the text and the image modality capable of capturing parts of the image being mentioned in the text was demonstrated. Such a capability was showcased on a publicly available dataset.Dissertation/ThesisMasters Thesis Computer Engineering 201
Histiocytic Sarcoma of Submandibular Gland: A Rare Case Report
No full textHistiocytic Sarcoma (HS) is a rare malignant neoplasm characterised by the neoplastic proliferation of cells showing morphological
and immunophenotypic features of mature histiocytes. Majority of the reported cases present in extranodal sites, such as the head
and neck, thyroid, duodenum, small intestine, colon, urinary bladder, spleen, and leptomeninges. This report documents a case of
primary involvement of the salivary gland by HS. A 77-year-old male patient presented with a firm swelling in the left submandibular
region for the last three months. Multiple lymph nodes, along with the presence of lung and liver nodules, were seen. Thus the final
diagnosis of HS was made based on histopathology and IHC. Palliative chemotherapy was given to the patient, responded well,
and has been well for the last year. The present study is probably the first case of HS involving the submandibular gland
Optimising the performance of complex sociotechnical systems in high-stress, high-speed environments: the Formula 1 pit stop test case
Get PDFIn analysing the performance of complex sociotechnical systems, of particular interest is the inevitable and inherent variability that these systems exhibit, but can normally tolerate, in successfully operating in the real world. Knowing how that variability propagates and impacts the total function mix then allows an understanding of emergent behaviours. This interdependence, however, is not readily apparent from normal linear business process flow diagrams. An alternative approach to exploring the operability of complex systems, that addresses these limitations, is the functional resonance analysis method (FRAM). This is a way of visualising a system’s behaviour, by defining it as an array of functions, with all the interactions and interdependencies that are needed for it to work successfully. Until now this methodology has mainly been employed as a qualitative mind map. This paper describes a new development of the FRAM visualisation software that allows the quantification of the extent and effects of this functional variability. It then sets out to demonstrate its application in a practical, familiar test case. The example chosen is the complex sociotechnical system involved in a Formula 1 pit stop. This has shown the potential of the application and provided some interesting insights into the observed performances
