Dermatofibrosarcoma Protuberans of the Suprapubic Region: A Rare Clinical Entity

Introduction: Dermatofibrosarcoma Protuberans (DFSP), an incompletely understood disease entity, has been reported in literature at different sites. However, the suprapubic region as its location further adds to its unusual persona.Case: A 51 year old gentleman presented with a slow growing suprapubic lesion, which on clinical and laboratory evaluation was confirmed to be a Dermatofibrosarcoma Protuberans, subsequently managed adequately with wide excision and groin flap coverage.Conclusion: Dermatofibrosarcoma Protuberans, in itself, is a rare entity and the suprapubic region as its location further adds to the unknown persona of the condition. Thus, the importance of maintaining a vigil for DFSP even at the most unusual sites, for optimal and timely diagnosis and management. As is rightly said, “What the mind knows, is what the eyes see”

Two Central limit theorems in Diophantine approximation

We prove central limit theorems for Diophantine approximations with congruence conditions and for inhomogeneous Diophantine approximations following the approach of Bj\"{o}rklund and Gorodnik. The main tools are the cumulant method and dynamics on homogeneous spaces.Comment: 40 Pages, Comments Welcom

Movie Recommendations using Hybrid Recommendation Systems

A recommendation system for movies is important in our social life due to its strength in providing enhanced entertainment. Such a system can suggest a set of movies, to users based on their interest, and personal information. Although, there are many recommendation systems present, new recommender system technologies are needed that can quickly produce high quality recommendations, even for very large-scale information resources. The proposed system has the ability to recommend movies, to a new user as well as the others by using their Facebook data. It collects all the important information, such as, popularity, liking and disliking, required for recommendation. It also takes minimal information from new user without social network login. It generates recommendations for the user based on his/her behavior on social media. This system could also be used by movie producers to get an idea about the response of their upcoming movies since all the data is extracted from the user’s behaviors

Management of compound fractures of shaft femur: a study of 55 cases

Background: Compound femoral shaft fractures are a major cause of morbidity and mortality. Conservative treatment necessitates a long stay in hospital for traction and subsequent immobilization and chances of wound infection are much higher. The objective of this study was to find out the outcome of treatment of open femoral shaft fractures by various modalities like interlocked nailing, plating and external fixation.Methods: Fifty five patients with open femoral shaft fractures were treated under spinal or general anaesthesia. These fractures were in proximal one third (n=3), middle third (n=29), distal third (n=21). Fifty patients underwent surgery within 5 days of injury. Patients were followed for a minimum of 12 Months.Results: Patients achieved union in an average time of 20 weeks (range 17 to 24 weeks). Full weight bearing was started in a mean time of 16 weeks. Mean duration of hospital stay was 20 days. Complications were occurred in ten patients (4 non-unions and 3 patients with deep infection and 3 patients developed chronic osteomyelitis). Conclusions: The results were excellent in 31, good in 13, fair in 3 and poor in 7 patients while one patient lost follow up as he was from far off place. We concluded that open femoral shaft fracture can be well managed by surgical intervention

Recognizing Human Faces: Physical Modeling and Pattern Classification

Although significant work has been done in the field of face recognition, the performance of the state-of-the-art face recognition algorithms is not good enough to be effective in operational systems. Most algorithms work well for controlled images but are quite susceptible to changes in illumination, pose, etc. In this dissertation, we propose methods which address these issues, to recognize faces in more realistic scenarios. The developed approaches show the importance of physical modeling, contextual constraints and pattern classification for this task. For still image-based face recognition, we develop an algorithm to recognize faces illuminated by arbitrarily placed, multiple light sources, given just a single image. Though the problem is ill-posed in its generality, linear approximations to the subspace of Lambertian images in combination with rank constraints on unknown facial shape and albedo are used to make it tractable. In addition, we develop a purely geometric illumination-invariant matching algorithm that makes use of the bilateral symmetry of human faces. In particular, we prove that the set of images of bilaterally symmetric objects can be partitioned into equivalence classes such that it is always possible to distinguish between two objects belonging to different equivalence classes using just one image per object. For recognizing faces in videos, the challenge lies in suitable characterization of faces using the information available in the video. We propose a method that models a face as a linear dynamical system whose appearance changes with pose. Though the proposed method performs very well on the available datasets, it does not explicitly take the 3D structure or illumination conditions into account. To address these issues, we propose an algorithm to perform 3D facial pose tracking in videos. The approach combines the structural advantages of geometric modeling with the statistical advantages of a particle filter based inference to recover the 3D configuration of facial features in each frame of the video. The recovered 3D configuration parameters are further used to recognize faces in videos. From a pattern classification point of view, automatic face recognition presents a very unique challenge due to the presence of just one (or a few) sample(s) per identity. To address this, we develop a cohort-based framework that makes use of the large number of non-match samples present in the database to improve verification and identification performance

Mapping Causes and Implications of India’s Skewed Sex Ratio and Poverty problem using Fuzzy & Neutrosophic Relational Maps

This paper employs a new soft computing based methodology for identifying and analyzing the relationships among the causes and implications of the two challenging problems in India: unbalanced sex ratio and poverty

Analyzing the Efficacy of an LLM-Only Approach for Image-based Document Question Answering

Recent document question answering models consist of two key components: the vision encoder, which captures layout and visual elements in images, and a Large Language Model (LLM) that helps contextualize questions to the image and supplements them with external world knowledge to generate accurate answers. However, the relative contributions of the vision encoder and the language model in these tasks remain unclear. This is especially interesting given the effectiveness of instruction-tuned LLMs, which exhibit remarkable adaptability to new tasks. To this end, we explore the following aspects in this work: (1) The efficacy of an LLM-only approach on document question answering tasks (2) strategies for serializing textual information within document images and feeding it directly to an instruction-tuned LLM, thus bypassing the need for an explicit vision encoder (3) thorough quantitative analysis on the feasibility of such an approach. Our comprehensive analysis encompasses six diverse benchmark datasets, utilizing LLMs of varying scales. Our findings reveal that a strategy exclusively reliant on the LLM yields results that are on par with or closely approach state-of-the-art performance across a range of datasets. We posit that this evaluation framework will serve as a guiding resource for selecting appropriate datasets for future research endeavors that emphasize the fundamental importance of layout and image content information