Indian Sign Language Numbers Recognition using Intel RealSense Camera

The use of gesture based interaction with devices has been a significant area of research in the field of computer science since many years. The main idea of these kind of interactions is to ease the user experience by providing high degree of freedom and provide more interactive way of communication with the technology in a natural way. The significant areas of applications of gesture recognition are in video gaming, human computer interaction, virtual reality, smart home appliances, medical systems, robotics and several others. With the availability of the devices such as Kinect, Leap Motion and Intel RealSense cameras accessing the depth as well as color information has become available to the public with affordable costs. The Intel RealSense camera is a USB powered controller that can be supported with few hardware requirements such as Windows 8 and above. This is one such camera that can be used to track the human body information similar to the Kinect and Leap Motion. It was designed specifically to provide more minute information about the different parts of the human body such as face, hand etc. This camera was designed to give users more natural and intuitive interactions with the smart devices by providing some features such as creating 3D avatars, high quality 3D prints, high-quality graphic gaming visuals, virtual reality and others. The main aim of this study is to try to analyze hand tracking information and build a training model in order to decide if this camera is suitable for sign language. In this study, we have extracted the joint information of 22 joint labels per single hand .We trained the model to identify the Indian Sign Language(ISL) numbers from 0-9. Through this study we analyzed that multi-class SVM model showed higher accuracy of 93.5% when compared to the decision tree and KNN models

Quarter and Full Car Models Optimisation of Passive and Active Suspension System Using Genetic Algorithm

© The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/This study evaluates a suspension design of a passenger car to obtain maximum rider's comfort when the vehicle is subjected to different road profile or road surface condition. The challenge will be on finding a balance between the rider's comfort and vehicle handling to optimize design parameters. The study uses a simple passive suspension system and an active suspension model integrated with a pneumatic actuator controlled by proportional integral derivative (PID) controller in both quarter car and full car models having a different degree of freedoms (DOF) and increasing degrees of complexities. The quarter car considered as a 2-DOF model, while the full car model is a 7-DOF model. The design process set to optimise the spring stiffnesses, damping coefficients and actuator PID controller gains. For optimisation, the research featured genetic algorithm optimisation technique to obtain a balanced response of the vehicle as evaluated from the displacement, velocity and acceleration of sprung and unsprung masses along with different human comfort and vehicle performance criteria. The results revealed that the active suspension system with optimised spring stiffness, damping coefficients and PID gains demonstrated the superior riding comfort and road holding compared to a passive suspension system.Peer reviewe

Epigenetic silencing of miR-520c leads to induced S100A4 expression and its mediated colorectal cancer progression

The S100 calcium-binding protein A4 (S100A4) induces epithelial mesenchymal transition, migration, invasion, angiogenesis and metastasis. Its induced expression in several cancer types correlates with poor prognosis. Apart from the functional and transcriptional regulatory aspects of S100A4, its post-transcriptional regulation is not yet clearly elucidated. In this study, we show that microRNAs (miR) miR-505-5p and miR-520c-3p target the 3'-UTR of S100A4 and inhibits its expression and its mediated migration and invasion. 5-Aza treatment significantly increased miR-520c-3p expression and reduced the S100A4 protein amounts. The upstream promoter region of miR-520c is hypermethylated irrespective of the metastasis status of colorectal cancer (CRC) patient tissues and in all analyzed CRC cell lines. Moreover, in a cohort of CRC patient specimen (n = 59), miR-520c-3p was significantly downregulated. miR-520c-3p stably expressing HCT116 cells showed a reduced metastasis formation in livers after implanting in mice spleen. Taken together, our findings demonstrate that S100A4 is post-transcriptionally regulated by tumor suppressor miRs, miR-505c-5p and miR-520c-3p, and particularly miR-520c-3p expression is epigenetically silenced in CRC

MACC1 is post-transcriptionally regulated by miR-218 in colorectal cancer

Metastasis is a multistep molecular network process, which is lethal for more than 90% of the cancer patients. Understanding the regulatory functions of metastasis-inducing molecules is in high demand for improved therapeutic cancer approaches. Thus, we studied the post-transcriptional regulation of the crucial carcinogenic and metastasis-mediating molecule metastasis associated in colon cancer 1 (MACC1). In silico analysis revealed MACC1 as a potential target of miR-218, a tumor suppressor miRNA. Expression of these two molecules inversely correlated in colorectal cancer (CRC) cell lines. In a cohort of CRC patient tissues (n = 59), miR-218 is significantly downregulated and MACC1 is upregulated compared with normal mucosa. Luciferase reporter assays with a construct of the MACC1-3'-UTR harboring either the wild type or the mutated miR-218 seed sequence confirmed the specificity of the targeting. miR-218 inhibited significantly MACC1 protein expression, and consistently, MACC1-mediated migration, invasion and colony formation in CRC cells. Anti-miR-218 enhanced the MACC1-mediated migration, invasion and colony formation. Similar findings were observed in the gastric cancer cell line MKN-45. Further, we performed methylation-specific PCR of the SLIT2 and SLIT3 promoter, where miR-218 is encoded in intronic regions. The SLIT2 and SLIT3 promoters are hypermethylated in CRC cell lines. miR-218 and SLIT2 expressions correlated positively. Methyltransferase inhibitor 5-Azacytidine induced miR-218 expression and inhibited the expression of its target MACC1. We also determined that MACC1 has alternative polyadenylation (APA) sites, which results in different lengths of 3'-UTR variants in a CRC cell line. Taken together, miR-218 is post-transcriptionally inhibiting the MACC1 expression and its metastasis-inducing abilities

Developing and Applying Hybrid Deep Learning Models for Computer-Aided Diagnosis of Medical Image Data

The dissertation discusses three methods to address the challenges of applying deep learning models to medical imaging. The first method involves the development of a new joint deep learning model, J-Net, to achieve lesion segmentation and classification simultaneously. The J-Net model outperforms the individual models in accuracy with small datasets. The second method performs automatic image detection using a two-stage deep learning model to produce clean data. The third method involves developing multi-stage deep learning algorithms to generate synthetic medical image data, which can be used to overcome the lack of large, diverse datasets. These methods demonstrate that building enhanced training datasets can play a vital role in improving the performance of deep-learning models in medical imaging applications

Phytochemical Investigations and Screening of Antihyperlipidemic and Antioxidant Activities of some Medicinal Plants

Achyranthes aspera Linn and Achyranthes bidentata Blume are two perennial herbs with slender and rambling branches. The two plant materials were collected from different parts of Nilgiri district of Tamilnadu and authenticated. Physicochemical parameters like total ash, acid insoluble ash, water soluble ash, and sulphated ash values were determined. Fluorescence analysis was carried out for the plant powder and their extracts. The dried and powdered leaves and seeds of plants were extracted with water and 50% ethanol through cold maceration. Alcohol soluble extractive and water soluble extractive values were determined. Phytochemical studies from the plant extracts using column chromatography by gradient elution method was carried out for the TLC and HPTLC analysis and Rf values were recorded. The phytochemical studies of the plant extracts showed the presence of alkaloids, glycosides, triterpenoids, saponins, flavonoids and mucilage. These results gave clues regarding the presence of some particular phytoconstituents in the respective plant extracts. The in vitro antioxidant assays of the plant extract exhibited potent antioxidant activity with low IC50 values in DPPH reducing power ability and Nitric oxide scavenging activity. 50% ethanol of both plants at a dose level of 200 mg/kg showed better antioxidant activity. The in vivo screening for antihyperlipidemic activity with triton induced hyperlipidemia and high fat diet induced hyperlipidemia model showed that both aqueous and 50% ethanol extracts of plants at a dose of 200 mg/kg exhibited significant activity against hyperlipidemia. Antihyperlipidemic activity and in vitro antioxidant activity of the various extracts may be attributed to the presence of triterpenoids, saponins, and flavonoids. From these studies, it can be concluded that both the plants are endowed with significant antihyperlipidemic and antioxidant activity. However, the future studies need to be carried out to isolate and screen the phytoprinciples responsible for the anti-hyperlipidemic and antioxidant activity. More wide-cut understanding of mechanism needs further studies with more animal model viz. isoproterenol induced myocardial infarction for their anti-hyperlipidemic activity and SOD, GSH, and lipid peroxidation inhibition assays for antioxidant activity. Works in this direction are in progress in the institution

Uncovering Bugs in Distributed Storage Systems during Testing (not in Production!)

Testing distributed systems is challenging due to multiple sources of nondeterminism. Conventional testing techniques, such as unit, integration and stress testing, are ineffective in preventing serious but subtle bugs from reaching production. Formal techniques, such as TLA+, can only verify high-level specifications of systems at the level of logic-based models, and fall short of checking the actual executable code. In this paper, we present a new methodology for testing distributed systems. Our approach applies advanced systematic testing techniques to thoroughly check that the executable code adheres to its high-level specifications, which significantly improves coverage of important system behaviors. Our methodology has been applied to three distributed storage systems in the Microsoft Azure cloud computing platform. In the process, numerous bugs were identified, reproduced, confirmed and fixed. These bugs required a subtle combination of concurrency and failures, making them extremely difficult to find with conventional testing techniques. An important advantage of our approach is that a bug is uncovered in a small setting and witnessed by a full system trace, which dramatically increases the productivity of debugging

S100A4 in cancer metastasis: Wnt signaling-driven interventions for metastasis restriction

The aberrant activity of Wnt signaling is an early step in the transformation of normal intestinal cells to malignant tissue, leading to more aggressive tumors, and eventually metastases. In colorectal cancer (CRC), metastasis accounts for about 90% of patient deaths, representing the most lethal event during the course of the disease and is directly linked to patient survival, critically limiting successful therapy. This review focuses on our studies of the metastasis-inducing gene S100A4, which we identified as transcriptional target of {beta}-catenin. S100A4 increased migration and invasion in vitro and metastasis in mice. In patient CRC samples, high S100A4 levels predict metastasis and reduced patient survival. Our results link pathways important for tumor progression and metastasis: the Wnt signaling pathway and S100A4, which regulates motility and invasiveness. S100A4 suppression by interdicting Wnt signaling has potential for therapeutic intervention. As proof of principle, we applied S100A4 shRNA systemically and prevented metastasis in mice. Furthermore, we identified small molecule inhibitors from high-throughput screens of pharmacologically active compounds employing an S100A4 promoter-driven reporter. Best hits act, as least in part, via intervening in the Wnt pathway and restricted metastasis in mouse models. We currently translate our findings on restricting S100A4-driven metastasis into clinical practice. The repositioned FDA-approved drug niclosamide, targeting Wnt signaling, is being tested in a prospective phase II clinical trial for treatment of CRC patients. Our assay for circulating S100A4 transcripts in patient blood is used to monitor treatment success

Using standard typing algorithms incrementally

Modern languages are equipped with static type checking/inference that helps programmers to keep a clean programming style and to reduce errors. However, the ever-growing size of programs and their continuous evolution require building fast and efficient analysers. A promising solution is incrementality, aiming at only re-typing the diffs, i.e. those parts of the program that change or are inserted, rather than the entire codebase. We propose an algorithmic schema that drives an incremental usage of existing, standard typing algorithms with no changes. Ours is a grey-box approach: just the shape of the input, that of the results and some domain-specific knowledge are needed to instantiate our schema. Here, we present the foundations of our approach and the conditions for its correctmess. We show it at work to derive two different incremental typing algorithms. The first type checks an imperative language to detect information flow and non-interference, and the second infers types for a functional language. We assessed our proposal on a prototypical imple- mentation of an incremental type checker. Our experiments show that using the type checker incrementally is (almost) always rewardin