Heritage Institute of Technology

About: Heritage Institute of Technology is a based out in . It is known for research contribution in the topics: Support vector machine & Transconductance. The organization has 581 authors who have published 1045 publications receiving 8345 citations.

A solid transportation model with product blending and parameters as rough variables

Abstract: In this paper, we formulate a practical solid transportation problem with product blending which is a common issue in many operational and planning models in the chemical, petroleum, gasoline and process industries. In the problem formulation, we consider that raw materials from different sources with different quality (or purity) levels are to be transported to some destinations so that the materials received at each destination can be blended together into the final product to meet minimum quality requirement of that destination. The parameters such as transportation costs, availabilities, demands are considered as rough variables in designing the model. We construct a rough chance-constrained programming (RCCP) model for the problem with rough parameters based on trust measure. This RCCP model is then transformed into deterministic form to solve the problem. Numerical example is presented to illustrate the problem model and solution strategy. The results are obtained using the standard optimization solver LINGO.

Exploring an energy-efficient DTN framework supporting disaster management services in post disaster relief operation

Abstract: In recent years, several investigations have been made on "challenged network" [also known as, delay tolerant network (DTN)] architectures highlighting their advantages and disadvantages. In spite of its inherent shortcomings of unreliability and delay, smart-phone based opportunistic network is gaining immense popularity in the research community due to its applicability in different adverse and extreme communication scenarios where traditional communication infrastructure is either unavailable or incapacitated for a long time. Considerable research has been conducted till date to design efficient network architecture for emergency data dissemination in intermittently connected/challenged networks. Different architectures (ranging from flat to multi-tier) are proposed for implementing opportunistic DTN keeping in view of specific application requirements. However, very few of these proposed architectures have been examined from the perspective of a post disaster communication. Moreover, most DTN architectures are designed by aiming towards increasing delivery probability and reducing latency and as a whole, maximizing network throughput; with very little emphasis on its energy efficiency. The impact of different mobility patterns on existing DTN routing algorithms with respect to data dissemination and energy consumption has also not been studied so far. Our objective, in this paper, is to investigate the impact of different mobility patterns on existing DTN routing protocols and existing DTN architectures and subsequently, come up with a suitable energy efficient DTN framework combining suitable architecture and routing protocol that may be used to offer different disaster management services during post-disaster relief operation. We have done an extensive simulation on ONE simulator with different categories of well-known existing DTN architectures, mobility models, DTN routing protocols to study the network performance in terms of delivery probability, energy efficiency and overhead ratio. Based on the simulation results, we have tried to figure out a suitable combination of energy efficient architecture, mobility model and routing protocol that fits well in the post disaster communication scenario.

Zonal complexity based measure for lossy compression of photoplethysmogram using delta encoding

Abstract: Photoplethysmography (PPG) is one of the prime non-invasive vascular assessment methodology adopted in modern clinical practice. This paper proposes a modification of delta modulation for effective compression of PPG signal for real time measurements and monitoring applications. Based on the energy content and fluctuations, the PPG signal was windowed and categorized into ‘complex’ or ‘plain’ zones. The algorithm applies an adaptive hard thresholding, run length encoding and selective biasing of the first difference array based on zonal complexity. The final stage employs a selective nibble combination or offsetting rule for further compression. For performance assessment of the compression-decompression algorithms, PPG data was collected from fingers of healthy volunteers using Biopac Systems®. An average compression ratio of 3.84, percentage root mean square difference of 5.82 and percentage root mean square difference normalized of 7.57 were obtained with 20 sets of volunteers' data at 10 bit resolution and 125 Hz sampling. The decompressed data were clinically validated by Cardiologists.

GST profile expression study in some selected plants: in silico approach

Abstract: Glutathione acts as a protein disulphide reductant, which detoxifies herbicides by conjugation, either spontaneously or by the activity of one of a number of glutathione-S-transferases (GSTs), and regulates gene expression in response to environmental stress and pathogen attack. GSTs play roles in both normal cellular metabolisms as well as in the detoxification of a wide variety of xenobiotic compounds, and they have been intensively studied with regard to herbicide detoxification in plants. A newly discovered plant GST subclass has been implicated in numerous stress responses, including those arising from pathogen attack, oxidative stress and heavy-metal toxicity. In addition, plants GSTs play a role in the cellular response to auxins and during the normal metabolism of plant secondary products like anthocyanins and cinnamic acid. The present work involves two in silico analytical approaches-general secondary structure prediction studies of the proteins and detailed signature pattern studies of some selected GST classes in Arabdiopsis thaliana, mustard, maize and bread wheat by standard Bioinformatics tools; structure prediction tools; signature pattern tools; and the evolutionary trends were analyzed by ClustalW. For this purpose, sequences were obtained from standard databases. The work reveals that these proteins are mainly alpha helical in nature with specific signature pattern similar to phosphokinase C, tyrosine kinase and casein kinase II proteins, which are closely related to plant oxidative stress. This study aims to comprehend the relationship of GST gene family and plant oxidative stress with respect to certain specific conserved motifs, which may help in future studies for screening of biomodulators involved in plant stress metabolism.