Anindita Mondal

Enhancement of Storage Capacity and Conversion Efficiency of Photoelectrochemical Cells: Effect of Dyes Adsorbed on Carbon Nano Tubes

We report here our studies on photoelectrochemical (PEC) cells where two commonly used photosensitive dyes, thionine and Rose Bengal were used as photosensitizers for conversion of light energy to electrical energy. The performance of the cells increased radically in presence of oxidized multiwalled carbon nano tubes (OMWCNTs) as reflected by the values of conversion efficiency (∼3.69%) and open circuit voltage (∼548.9 mV). To understand the role of OMWCNTs in enhancing the performance of the cells, the spectral study of dye–OMWCNT mixed systems were performed. The absorption spectra indicated more absorption of incident photons in presence of OMWCNT, whereas the infrared spectra suggested that the basic structure of dyes remained unaltered. The spectral studies implied that the dye molecules got adsorbed on OMWCNTs side walls causing efficient absorption of the incident light quanta. Moreover, insertion of planar lipid membrane (PLM) separating the two chambers of PEC cell could effectively counteract the recombination of photodissociated charges and thereby caused better storage capacity of the PEC cells with further increase in efficiency.

Intelligent Building Control Solution Using Wireless Sensor—Actuator Networking Framework

Intelligent building refers to a residence that is automated through a network of electronic devices which cooperate transparently to provide protection and comfort to the residents and minimize the energy consumption drastically. In this paper, a novel approach is made to design an intelligent building control solution using wireless sensor actuator networks (WSAN) in hardware domain. The intelligent building control solution provides automation to most household operations such as intrusion alarm, environment monitoring and controlling, asset tracking, etc. Real-time sensing is established with the help of sensor modules whereas real-time tracking is achieved with the deployment of active radio frequency identification (RFID) module. The WSAN greatly consists of gateway, routers, and end devices. The main controlling unit of WSAN is AVR microcontroller which manages the transceiver section and processes the received data accordingly. This paper focuses on remote monitoring and management system for a partly automated building equipped with sensors and actuators. Here, we also explore the prospects of wireless mesh networks and design a framework for developing an intelligent and smart environment.

Comparative Analysis of Structured and Un-Structured Databases

The introduction of relational database systems helped in faster transactions compared to the existing system for handling structured data. However, in course of time the cost of storing huge volume of unstructured data became an issue in traditional relational database systems. This is where some unstructured database systems like NoSQL databases were introduced in the domain to store unstructured data. This paper focuses on four different structured(PostgreSQL) and un-structured database systems(MongoDB, OrientDB and Neo4j). In this paper, we will eventually see the different kind of data models they follow and analyze their comparative performances by experimental evidences.

Building a low cost solution using wireless sensor network for agriculture application

In many countries around the globe improper management of water resources for agriculture is one of the main issues for failure to crop yield. Hence there is a demand of water management system for agriculture which will maximize the crop yield. In this paper a novel approach is made to design and fabricate a closed-loop control system for soil-moisture monitoring and controlling. It is achieved through deployment of proposed Wireless Sensor Network (WSN) model in agriculture field. Since the end users are farmers, the cost of the product holds great importance. In market there are many WSN motes available but they are not application specific. The costs of these motes are much higher and beyond the reach of farmers. Due to this reason we have designed new sensor nodes with the help of Arduino Platform and Raspberry Pi module to minimize the cost of entire product. Selection of hardware component, firmware development, integration and field implementation, testing and optimization are the processes that have been followed to develop the product. The benefit of such design is to control all desired parameters for WSN according to own application requirement that sometimes is not achievable from the marketed product.

Object based schema oriented data storage system for supporting heterogeneous data

Object based data storage system provides application aware, hybrid cloud data storage system. Health data consists of multiple types of data sets like image, text, document, file etc. So, it is important to store multiple types of data in a seamless manner. A storage manager uses storage object or data container to store data. In this paper, we propose a schema oriented object storage space which describes the structure of the proposed object based data storage system. In the proposed system, data is stored as attribute values rather than data blocks or files. To describe the working procedure of the proposed object based data storage system which consults storage object to store the heterogeneous dataset, we have proposed an algorithm based on multilayer view of the data storage unit. Besides configuring data storage space, the proposed algorithm helps to support data operations. The utility of this storage system is described using certain use cases.

Knowledge discovery from HIV-1-human PPIs assimilating interaction keywords

Todays world is gradually getting agitated by Human Immunodeficiency Virus — Type 1 due to its pervasive and death-dealing nature. The virus replicates by exploiting a complex interaction network of HIV-1 and human proteins and destructs human immunity power, gradually leading to AIDS. Anti-HIV drugs are designed to utilize the information on viral-host protein-protein interactions (PPIs), so that the viral replication and infection can be prevented. In this article, we have presented an effective computational approach using pattern-mining based algorithm in order to predict novel interactions between HIV-1 and human proteins based on the experimentally validated interactions curated in public PPI database. Additionally, we have tried to provide the information on interaction types associated with each of the predicted interactions with an estimated confidence. Further, we have analyzed our predicted interactions by finding overlap with other studies. We believe that this article would enhance the discovery of HIV-1 medications in a way of designing the drug targets.

A suffix tree based parallel approach for association rule mining and biclustering

Data mining is the process of analyzing raw data from very large databases to turn them into useful and previously unknown information. This helps in finding out interesting patterns, trends and relationships within data. Association rule mining and bi-clustering are two very important data mining tasks for many application domains, especially in bio-informatics. FIST is one of the very few algorithms which extracts bases of association rules and bi-clustering conjointly in a single process. FIST algorithm is based on frequent closed itemsets framework and uses a suffix tree based data structure for efficiency. However, due to its sequential execution approach, the traditional FIST algorithm suffers from efficiency problems in terms of execution time for very large data sets with high dimensionality. Here, a parallelized version of FIST algorithm is proposed to improve the performance. In the new parallelize version of FIST algorithm (ParaFIST), a multi-threaded approach is taken to allow parallel processing of the suffix tree branches to achieve better execution time. We have used an example to demonstrate the correctness of the proposed algorithm.