DESIGNER COLLAGEN-FIBRIL BIOGRAFT MATERIALS FOR TUNABLE MOLECULAR DELIVERY

One of the biggest challenges in tissue engineering currently is the formation of a functional microvascular network as part of an engineered tissue graft. Despite many advances in tissue engineering methods, the field still awaits biograft designs that enable neovascularization at clinically relevant size scales. Critical to the design of such materials are tissue-specific physico-mechanical properties and controlled local therapeutic molecular release

Role of Machine Learning, Deep Learning and WSN in Disaster Management: A Review and Proposed Architecture

Disasters are occurrences that have the potential to adversely affect a community via casualties, ecological damage, or monetary losses. Due to its distinctive geoclimatic characteristics, India has always been susceptible to natural calamities. Disaster Management is the management of disaster prevention, readiness, response, and recovery tasks in a systematic manner. This paper reviews various types of disasters and their management approaches implemented by researchers using Wireless Sensor Networks (WSNs) and machine learning techniques. It also compares and contrasts various prediction algorithms and uses the optimal algorithm on multiple flood prediction datasets. After understanding the drawbacks of existing datasets, authors have developed a new dataset for Mumbai, Maharashtra consisting of various attributes for flood prediction. The performance of the optimal algorithm on the dataset is seen by the training, validation and testing accuracy of 100%, 98.57% and 77.59% respectively

Enhancing the Security of a Network System using Liquid State Machine- A Novel Approach

Today, most of the computer applications are network based and there is a steady grow in terms of its size and demand. To keep pace with its security aspects lot of techniques are used like IDS (Intrusion Detection System), anti-virus system etc. All are performing their jobs quite well but produced high volume alarms or messages. Further they are not able to unify the network. Hence to overcome these problems we recommend the use of network security situation assessment method. This paper starts with the discussion of network related security situation concept and proceeds with two concern techniques like SVM (Support Vector Machine) and ESN (Echo State Network) which are discussed in detail. Further we also compare both techniques in terms of their performances. Finally we proposed the application of LSM (Liquid State Machine) to enhance the overall performance of network system. DOI: 10.17762/ijritcc2321-8169.15052

Online Brand Communities and their Impact on Brand Equity of Indian Telecommunication Industry

Telecommunication space in India has become highly competitive and hence organizations are looking for newer value propositions and innovative ways to compete. With the advent of digital media, physical spaces are now being complimented with virtual spaces by organizations as a means of competitive advantage. Online brand communities (OBC’s) is one such source by which Telecom companies can achieve value creation and enhanced online customer engagement with customers.Hence this study is primarily an attempt to examine the impact of Online Brand Communities on selected brand equity dimensions of loyalty, awareness, association and perceived brand quality of telecom service providers. The purpose of this paper is to come up with a conceptual model which can explain the effects of the Online Brand Communities on value of the brand (brand equity) of telecommunication service providers.Primary data was collected from a sample of 120 respondents with the help of a questionnaire. For data analysis, statistical methods like factor analysis and regression analysis have been used to group inter related variables and predict the relationship between correlated variables respectively.Very few studies on OBC’s have been conducted in the telecommunication space hence the study will add to the academic literature and help telecom managers to determine how brand generated content and community participation can drive business to next level through engaged online customer experience. It will help the telecom companies in analysing brand equity building through online space, in turn enhancing the purchase decision, customer engagement and create competitive advantage

Molecular Imaging of Experimental Abdominal Aortic Aneurysms

Current laboratory research in the field of abdominal aortic aneurysm (AAA) disease often utilizes small animal experimental models induced by genetic manipulation or chemical application. This has led to the use and development of multiple high-resolution molecular imaging modalities capable of tracking disease progression, quantifying the role of inflammation, and evaluating the effects of potential therapeutics. In vivo imaging reduces the number of research animals used, provides molecular and cellular information, and allows for longitudinal studies, a necessity when tracking vessel expansion in a single animal. This review outlines developments of both established and emerging molecular imaging techniques used to study AAA disease. Beyond the typical modalities used for anatomical imaging, which include ultrasound (US) and computed tomography (CT), previous molecular imaging efforts have used magnetic resonance (MR), near-infrared fluorescence (NIRF), bioluminescence, single-photon emission computed tomography (SPECT), and positron emission tomography (PET). Mouse and rat AAA models will hopefully provide insight into potential disease mechanisms, and the development of advanced molecular imaging techniques, if clinically useful, may have translational potential. These efforts could help improve the management of aneurysms and better evaluate the therapeutic potential of new treatments for human AAA disease