Image Spam Classification using Deep Learning

Image classification is a fundamental problem of computer vision and pattern recognition. Spam is unwanted bulk content and image spam is unwanted content embedded inside the images. Image spam creates threat to the email based communication systems. Nowadays, a lot of unsolicited content is circulated over the internet. While a lot of machine learning techniques are successful in detecting textual based spam, this is not the case for image spams, which can easily evade these textual-spam detection systems. In this project, we explore and evaluate four deep learning techniques that detect image spams. First, we study neural networks and the deep neural networks, which we train on various image features. We explore their robustness on an improved dataset, which was especially build in order to outsmart current image spam detection techniques. Finally, we design two convolution neural network architectures and provide experimental results for these alongside the existing VGG19 transfer learning model for detecting image spams. Our work offers a new tool for detecting image spams and is compared against recent related tools

Traumatic bilateral hip dislocation with bilateral sciatic nerve palsy

AbstractBilateral hip dislocation rarely occurs. In this paper, a case of bilateral hip dislocation associated with bilateral sciatic nerve palsy resulted from a road traffic accident is reported. Both hips were emergently reduced under general anaesthesia. Acetabular reconstruction was done bilaterally due to the unstable hips. The patient subsequently developed heterotopic ossification and avascular necrosis on the left hip and underwent total hip arthroplasty. The sciatic nerve on the right side achieved complete recovery but that on the left side only partly recovered and was augmented by tendon transfer. Such injuries are serious and one should be aware of the complications because they can resurface and so patients should be followed up for a long time. To the best of our knowledge, this kind of injury has not been reported in the English language literature

Virtual Grader for Apple Qualityassessment using Fruit Size and Illumiation Features

The present paper reports on the development of an intelligent virtual grader for assessing apple quality using machine vision. The heart of the proposed virtual grader was executed in the form of K-Nearest Neighbor (K-NN) classifier designed on the architecture of Euclidean distance metric. KNN classifier is executed for this particular application due to its robustness to the noisy environment. The present study revealed that fruit surface illumination is one of the major deterministic parameters affecting accuracy substantially while assessing apple quality based on fruit size. The performance of the proposed virtual grader was examined experimentally under different conditions of fruit surface illumination. An industrial grade camera connected to an image grabber was used to implement the proposed industrial-grade virtual grader using machine vision. Results of this study are quite promising with an achievement of 99% efficiency at 100% repeatability when fruit surface is exposed to an optimal value of 310 lux. However, such an attempt has not been made earlier

Understanding the Impact of Early Citers on Long-Term Scientific Impact

This paper explores an interesting new dimension to the challenging problem of predicting long-term scientific impact (LTSI) usually measured by the number of citations accumulated by a paper in the long-term. It is well known that early citations (within 1-2 years after publication) acquired by a paper positively affects its LTSI. However, there is no work that investigates if the set of authors who bring in these early citations to a paper also affect its LTSI. In this paper, we demonstrate for the first time, the impact of these authors whom we call early citers (EC) on the LTSI of a paper. Note that this study of the complex dynamics of EC introduces a brand new paradigm in citation behavior analysis. Using a massive computer science bibliographic dataset we identify two distinct categories of EC - we call those authors who have high overall publication/citation count in the dataset as influential and the rest of the authors as non-influential. We investigate three characteristic properties of EC and present an extensive analysis of how each category correlates with LTSI in terms of these properties. In contrast to popular perception, we find that influential EC negatively affects LTSI possibly owing to attention stealing. To motivate this, we present several representative examples from the dataset. A closer inspection of the collaboration network reveals that this stealing effect is more profound if an EC is nearer to the authors of the paper being investigated. As an intuitive use case, we show that incorporating EC properties in the state-of-the-art supervised citation prediction models leads to high performance margins. At the closing, we present an online portal to visualize EC statistics along with the prediction results for a given query paper

In-Vitro Studies on the Antioxidant Assay Profiling of Root of Withania somnifera L. (Ashwagandha) Dunal: Part 2

The anti-oxidative activities of six different extracts of Withania somnifera (Ashwagandha) root, prepared in a sequential manner starting from non-polar (hexane) to polar (water) solvent, were investigated employing various established in-vitro systems that include total antioxidant activity (TAA), total reducing power (TRP), nitric oxide scavenging activity (NOSA) and lipid peroxidation inhibition activity (LPIA). Among all the extracts, methanol extract was found the most potent and additionally, its DNA damage protective efficacy was tested using pRSET-A vector system. Positive correlations were established between total polyphenolic contents (TPC) and various activities strongly suggesting that the observed activities of the extracts may be ascribed to their phenolic compounds that could be responsible, at least partly, for the observed antioxidant activities. Six main compounds viz. alkaloids, hydroxybenzene, terpene ansteroid, saponin, organic acids and flavone were identified in methanol extract using thin layer chromatography (TLC) while by employing reverse-phase high pressure liquid chromatography (RP-HPLC) four polyphenols namely epicatechin (3.21 μg/g), quercetin-3-rhamnoside (1.12 μg/g), gallic acid (0.05 μg/g) and rutin hydrate (0.01 μg/g) were identified and quantified in aforementioned extract. Overall, the results of study clearly demonstrated that methanolic extract of Ashwagandha root possesses a marked antioxidant activity

A comparative study of the relationship between the recovery of movement and the anatomical alignment in fractures around the elbow

Background: The injury around the elbow joint is a common condition in any age group, especially in children as a result of fall, during the course of a child's normal play. The aim of the present study was to study the relationship between the recovery of movements and the anatomical alignment in fractures around the elbow.Methods: In the present study, 110 cases of fractures around elbow were included. The treatment with conservative or operative procedure depends on the surgeon concerned and his priorities. Sixty-six cases were treated conservatively, and 56 cases required operative intervention. At the time of follow up examination, cases were assessed as to the anatomical and functional point of view according to Flynn's criteria. We evaluated the reduction as per alignment in anteroposterior axis, lateral axis, and angulation. The patients were followed up for over 24 months.Results: Patients who had good anatomical alignment (grade A) showed 96.87% satisfactory result as compared to the patient who had fair anatomical alignment (91.66%) and poor anatomical alignment (54.54%). Thus in grade A where alignment was up to 76 points, we had satisfactory result in 96.87% patients, where as in grade C where alignment was less than 50 points, the result in 45.5% of patients was poor.Conclusions: Patients who had good anatomical alignment achieved, showed higher recovery of movement compared to the patient who had fair anatomical alignment and poor anatomical alignment

An Overview on Fast Disintegrating Sublingual Tablets

The demand of fast disintegrating tablets has been growing during the last decade, due to the characteristics of fast disintegrating sublingual tablets for the potential emergency treatment. In terms of permeability, the sublingual area of the oral cavity (i.e, the floor of the mouth) is more permeable than the buccal (cheek) area, which in turn is more permeable than the palatal (roof) of the mouth. Drug delivery through the oral mucous membrane is considered to be a promising alternative to the oral route. Fast disintegrating sublingual tablets may lead to significant improvements over current treatment options for specific patient group, for instance pediatric and geriatric patients. This review highlights the mechanism of sublingual absorption, factors affecting sublingual absorption, formulation techniques, types of sublingual tablets, advantages, evaluation parameters and commercially available sublingual dosage forms

Determination of Maximum Recommended Weight Limit for Manual Lifting Task in Industry through Taguchi Parametric Optimization Technique

In this paper Authors have tried to calculate the maximum Recommended Weight Limit (RWL) for manual lifting task in industry on the basis of revised Load constant (LC), Horizontal Multiplier (HM), Vertical Multiplier (VM), which are calculated according to the collected data from industry. The purpose of this paper is to efficiently determine the optimum combination of those three factors to achieve the maximum recommended weight limit. In the order to meet the purpose in term of Recommended Weight Limit (RWL), author has applied the taguchi parametric optimization technique. The base of this study is NIOSH lifting equation, in this equation the recommended weight is calculated by the multiplication of seven factors, authors have worked only three factors i.e. LC, HM, VM respectively