Rekha Jain

Polarity Detection at Sentence Level

Opinions bear a very important place in the life of human beings. Human Beings are always surrounded by opinions, when a decision has to be taken; people always want to know the opinions of others. But as the impact of the web is increasing day by day, Web documents can be seen as a new source of opinions for the people. Large numbers of reviews are available on the Web related to every product. Whenever a customer buys any product, they express their feedbacks as opinions on the e-commerce website, thus it is very important to automatically analyze the huge amount of information on the web and develop methods to automatically classify the reviews. Opinion Mining or Sentiment Analysis is the mining of attitudes, opinions, and emotions automatically from text, speech, and database sources through Natural Language Processing (NLP). In this paper an opinion mining system is proposed using unsupervised technique to determine the polarity of sentences i.e. to classify the sentences as positive, negative or neutral. Negation is also handled in the proposed system. Experimental results using reviews of products show the effectiveness of the system.

Hybrid Spread Spectrum based Smart Meter Network using Fast Frequency Hopping

Smart metes used in electric grids need a dedicated network that should be highly reliable & cost effective. Various techniques like 3G cellular have been proposed to improve efficiency of this smart grid electric meter network. For distribution of proper information in smart grid system Hybrid Spread Spectrum using slow frequency technology is also better choice. To improve the performance of this network in the terms of throughput and number of smart meter per data aggregation point (DAP), we have proposed HSS-FFH (to implement AMI) method. These techniques give better result in terms of coverage high density population area & interference immunity.

Energy-Efficient Optimum Design for Massive MIMO

Massive MIMO technique is used to enhance spectral efficiency with the use of large number of antennas as well as to enhance energy efficiency. Energy Efficiency optimization can be done in massive MIMO by using linear interference mitigation techniques like maximum ratio transmission (MRT) and zero forcing (ZF) precoding, where base station is equipped with M antennas and these antennas are communicating with K user terminals (UT) equipped with single antenna. This paper proposes a new model to estimate channel matrix and ZF precoding which are complex in operation. Numerical results shows that in massive MIMO regime zero forcing is more energy efficient than maximum ratio transmission. Results also show that optimum number of M antennas with optimum number of K user terminals reveal better energy-efficient wireless communication system.

Fuzzy Logic Based Energy Efficient Network Lifetime Optimization in Wireless Sensor Network

Energy conservation is prime issue for wireless sensor network due to their limited battery life. Energy losses are occurring mostly on the edges of wireless sensor network, where most of the packet drops are occurred. In order to avoid this energy loss problem this paper has introduced concept of advance/ super node which can be deployed at edges of the network or inside to the network. For the cluster head selection both the methods e.g. clustering technique and direct communication are employed to minimize energy consumption loss. Proposed algorithm is improved form of E-zone model. The simulation is done with the help of MATLAB toolbox and result shows that our proposed model is better in terms of energy saving, reaming alive nodes and improved network lifetime for Wireless Sensor Network.

Marker-assisted selection and QTL mapping for yield, root morphology and agronomic traits using MASARB25 (aerobic) × Pusa Basmati 1460 F3 mapping populations

Increasing scarcity of water has threatened the sustainability of the irrigated rice production system and hence the food security and livelihood of rice producers. Experiments were conducted to study the correlation and QTL mapping for yield, root-related and agronomic traits under aerobic conditions using MASARB25 × Pusa Basmati 1460 F3 mapping population. Yield of aerobic rice variety MASARB25 was 9–12.3% higher than Basmati rice variety Pusa Basmati 1460. MASARB25 had 9.32% higher root length, 11.76% higher fresh root weight, 19.98% higher dry root weight as compared to Pusa Basmati 1460. A total of 15 QTLs associated with 10 traits were mapped on chromosomes 2, 4, 6, 8, 9, and 11. qGY8.1 with an R2 value of 36.3% and qGY2.1 with an R2 value of 29% and qRL8.1 with an R2 value of 27.2% were identified for root length indicating the role of root traits in improving grain yield under water limited conditions. A positive correlation was found between root traits and yield under aerobic conditions. Breeding lines with higher yield per plant, root length, dry root biomass, length-breadth ratio, and with Pusa Basmati 1460-specific alleles in a homozygous or heterozygous condition at the BAD2 locus were identified that will serve as novel material for the selection of stable aerobic Basmati rice breeding lines.

Fragrance analysis using molecular and biochemical methods in recombinant inbred lines of rice

The aroma or fragrance of Basmati rice is associated with the presence and content of the chemical compound, 2-acetyl-1-pyrroline and the trait is monogenic recessive. Several polymerase chain reaction (PCR)-based co-dominant markers based on RG28 locus were developed, which can differentiate between fragrant and non-fragrant rice cultivars. For molecular and biochemical analysis of aroma, a mapping population comprising 208 recombinant inbred lines (RILs) derived from a diverse cross between CSR10 and Taraori Basmati through Single seed descent (SSD) method was used. RILs are among the best mapping populations, which provide a novel material for linkage mapping of genes/QTLs marker for various traits. Biochemical analysis of aroma was performed with the 1.7% KOH solution and molecular analysis of aroma was carried out with microsatellite markers present on chromosome 8 (BAD2, BADEX7-5, SCUSSR1) to determine the extent of association between trait, marker and chromosome 8. Among these markers, BAD2 amplified aroma specific alleles having 256 bp in 72 lines, BADEX7-5 with 95 bp in 74 lines and SCUSSR1 with 129 bp in 79 lines. Mantel test of significance detected by biochemical analysis of RILs (with 1.7% KOH) and molecular marker study revealed high degree (>90%) of association of aroma with the above mentioned markers, respectively. Some of the F10 lines amplified the heterozygous alleles for two sets of specific markers (BAD2 and SCUSSR-1) but did not show the presence of aroma as analyzed by chemical test. Aromatic and nonaromatic lines were almost common in three markers, indicating association of markers with the trait and chromosome 8. The results reveal that these markers could be used for marker assisted selection and RIL population for mapping of aroma QTLs/genes.