Sign Language to Sentence Formation: A Real Time Solution for Deaf People

Communication is a basic need of every human being to exchange thoughts and interact with the society. Acute peoples usually confab through different spoken languages, whereas deaf people cannot do so. Therefore, the Sign Language (SL) is the communication medium of such people for their conversation and interaction with the society. The SL is expressed in terms of specific gesture for every word and a gesture is consisted in a sequence of performed signs. The acute people normally observe these signs to understand the difference between single and multiple gestures for singular and plural words respectively. The signs for singular words such as I, eat, drink, home are unalike the plural words as school, cars, players. A special training is required to gain the sufficient knowledge and practice so that people can differentiate and understand every gesture/sign appropriately. Innumerable researches have been performed to articulate the computer-based solution to understand the single gesture with the help of a single hand enumeration. The complete understanding of such communications are possible only with the help of this differentiation of gestures in computer-based solution of SL to cope with the real world environment. Hence, there is still a demand for specific environment to automate such a communication solution to interact with such type of special people. This research focuses on facilitating the deaf community by capturing the gestures in video format and then mapping and differentiating as single or multiple gestures used in words. Finally, these are converted into the respective words/sentences within a reasonable time. This provide a real time solution for the deaf people to communicate and interact with the society.     

Enhanced Catalytic,Antibacterial and Anti-cancer Activities of Erythromycin Capped Gold Nanoparticles

Journal of Inorganic and Organometallic Polymers and Materials - In this study, the nanosized spherical erythromycin capped gold nanoparticles (eryth-Au(0)NPs) were fabricated for the first time....     

N‐halamine‐modified polyglycolide (PGA) multifilament as a potential bactericidal surgical suture: In vitro study

In this study, new cationic homopolymer and anionic copolymer were synthesized, and deposited onto polyglycolide sutures using a layer‐by‐layer assembly technique. The coated sutures were rendered antibacterial by chlorinating with dilute solution of household bleach solution at pH 7. The chlorination treatment transformed the N? H groups of anionic copolymer into N‐halamine structures. The N‐halamine‐modified sutures were challenged with Staphylococcus aureus and Escherichia coli O157:H7 bacteria at different contact times. The suture with chlorine loading of 0.22% completely inactivated both bacterial strains in 30 min contact time. Fourier transform infrared spectroscopy, scanning electron microscopy, and analytical titration confirmed the successful deposition of the N‐halamine multilayers. The effect of layer‐by‐layer coatings of polyelectrolytes on the chlorine loading and antibacterial efficacy of sutures was evaluated. The straight‐pull and knot‐pull strength tests performed on the sutures reported slight decline in tensile properties after chlorination treatment. The in vitro hemolysis and cytocompatibility tests revealed that the N‐halamines‐based antibacterial sutures were biocompatible. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 42483.     

Binary phase solid-state photopolymerization of acrylates: design,characterization and biomineralization of 3D scaffolds for tissue engineering

Porous polymer scaffolds designed by the cryogel method are attractive materials for a range of tissue engineering applications. However, the use of toxic crosslinker for retaining the pore structure limits their clinical applications. In this research, acrylates (HEA/PEGDA, HEMA/PEGDA and PEGDA) were used in the low-temperature solid-state photopolymerization to produce porous scaffolds with good structural retention. The morphology, pore diameter, mineral deposition and water absorption of the scaffold were characterized by SEM and water absorption test respectively. Elemental analysis and cytotoxicity of the biomineralized scaffold were revealed by using XRD and MTT assay test. The PEGDA-derived scaffold showed good water absorption ability and a higher degree of porosity with larger pore size compared to others. XRD patterns and IR results confirmed the formation of hydroxyapatite crystals from an alternative socking process. The overall cell proliferation was excellent, where PEGDA-derived scaffold had the highest and the most uniform cell growth, while HEMA/PEGDA scaffold showed the least. These results suggest that the cell proliferation and adhesion are directly proportional to the pore size, the shape and the porosity of scaffolds.     

工艺参数设置和厚度对电子束熔融加工Ti-6Al-4V合金微观结构的影响

研究了试件尺寸和工艺参数(电子束强度,扫描速度,焦点偏移量和扫描长度)对电子束熔融(EBM)加工Ti-6Al-4V合金微观结构的影响。结果表明,可以观察到EBM加工的Ti-6Al-4V合金的微观结构由原始β相的柱状晶粒组成。在柱状晶粒内部观察到典型的(α+β)结构,即魏氏体α片和在细小的α晶粒的界面上形成的杆状β相。还发现沿原始β柱状晶粒的晶界形成的α层晶界。随着试件厚度、电子束能量密度和扫描长度的增加,先前的β柱状晶粒的直径增大,并且生长的方向与加工方向一致。同时,柱状晶粒直径随着试件高度的增加而减小。随着试件厚度和电子束能量密度的增加,α片会变得更粗大。     

Analysis of Radio Resource Allocation in LTE Uplink

Long term evolution (LTE) uses orthogonal frequency division multiple access (OFDMA) and single carrier frequency division multiple access (SC-FDMA) as the downlink and uplink transmission schemes respectively. The Quality of Service (QoS) provision to users is one of the key objectives of the wireless network operators. This paper analyses an uplink LTE radio scheduler, called bandwidth and QoS aware (BQA) scheduler and evaluates its QoS performance. The BQA uplink scheduler is designed to provide efficient and fair allocation of the radio resources to users according to: the QoS of various traffic classes and the instantaneous channel conditions. The scheduler functionality is divided into time domain packet scheduling (TDPS) and frequency domain packet scheduling (FDPS). In this paper, an innovative feature, that is user QoS provisioning with dynamic QoS weights, is employed for the BQA scheduler along with multi-bearer users support. The QoS performance of the BQA scheduler is analyzed in several simulation scenarios using heterogeneous traffic environment. The results show that the BQA scheduler guarantees provision of QoS to users.     

Review of Cross-cultural research methods in psychology.

Reviews the book, Cross-cultural research methods in psychology edited by David Matsumoto and Fons J. R. Van de Vijver (see record 2010-22491-000). The purpose of this book is to further the potential of cross-cultural psychology by helping researchers to understand the unique difficulties inherent in the field and the current methodologies used to advance quality research. Matsumoto and van de Vijver have compiled a comprehensive yet simply organized volume that speaks to the theoretical and analytic issues met by graduate students and advanced researchers alike. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Prediction of human breast and colon cancers from imbalanced data using nearest neighbor and support vector machines

This study proposes a novel prediction approach for human breast and colon cancers using different feature spaces. The proposed scheme consists of two stages: the preprocessor and the predictor. In the preprocessor stage, the mega-trend diffusion (MTD) technique is employed to increase the samples of the minority class, thereby balancing the dataset. In the predictor stage, machine-learning approaches of K-nearest neighbor (KNN) and support vector machines (SVM) are used to develop hybrid MTD-SVM and MTD-KNN prediction models. MTD-SVM model has provided the best values of accuracy, G-mean and Matthew's correlation coefficient of 96.71%, 96.70% and 71.98% for cancer/non-cancer dataset, breast/non-breast cancer dataset and colon/non-colon cancer dataset, respectively. We found that hybrid MTD-SVM is the best with respect to prediction performance and computational cost. MTD-KNN model has achieved moderately better prediction as compared to hybrid MTD-NB (Naïve Bayes) but at the expense of higher computing cost. MTD-KNN model is faster than MTD-RF (random forest) but its prediction is not better than MTD-RF. To the best of our knowledge, the reported results are the best results, so far, for these datasets. The proposed scheme indicates that the developed models can be used as a tool for the prediction of cancer. This scheme may be useful for study of any sequential information such as protein sequence or any nucleic acid sequence.