Rajasthan Technical University

About: Rajasthan Technical University is a education organization based out in Kota, Rajasthan, India. It is known for research contribution in the topics: Photovoltaic system & PID controller. The organization has 716 authors who have published 1084 publications receiving 4530 citations. The organization is also known as: RTU.

Big Data Challenges and Issues: A Review

Abstract: Data is expanding immensely as well as colossally, multiplying each year. There is no denying the fact that data is and will keep on moulding our lives. Big Data can be thought of as the “development of perpetual information”. Big data is pulling in technologists, researchers, and analysts in the last couple of years in different areas of large databases. Big data gathers data from multiple distributed sources in large volumes which makes it a vital issue to process data accurately for better utilization and information quality. Big data poses great challenges in many areas. The paper relates to recent findings in big data science and technology.

A miniature quad-band band pass filter using modified stepped impedance resonator and parallel resonating stubs for satellite communication

Abstract: A miniature planer quad-band bandpass filter (BPF) using stepped impedance resonator with loadings stubs, parallel resonating stubs and defected ground structure is proposed. Loading stub used to give extra parameters to tune resonant frequency. Three parallel resonating stubs are used to generate three extra pass bands by shifting higher order resonant mode to desired frequency bands and make quad-band BPF. Stop band performance improved by cross coupling of parallel feed structure and SIR, which generates transmission zeros at edge of lower and upper stop band of each band. Defected ground structure provides superior band and out-of-band performance of filter. Filter can be utilized for four bands listed as 4.4-4.5GHz (fixed and mobile communication), 5.15-5.25Ghz (fixed satellite/WLAN/Wi-Fi/aeronautical navigation), 5.925-6.425GHz (commercial c-band satellite communication) and 7.55-7.75Ghz (fixed satellite communication). Designed filter have some commendable features like closely spaced, highly isolated bands (deep zeros between bands), miniature sized (180 mm2), low loss performance, adequate stopband and cost efficient structure. Alumina (Epsilon=9.9) used as substrate and Simulation of design done using commercial software CST microwave studio 2015.

Genetic Algorithm Based Method for Analyzing Reliability State of Wireless Sensor Network

Abstract: Wireless sensor networks are application specific and consist of large number of sensor nodes deployed in a harsh environment/area. Sensor nodes are deployed randomly to monitor or sense the area of interest. Wireless sensor networks have a wide range of application such as military surveillance, environment monitoring, agriculture, health monitoring and many more. Reliability of a wireless sensor network is defined in terms of area covered by sensor nodes and redundancy in sensed data. Redundancy in data is caused by overlapping in sensed area of nodes. Redundancy is required to gather high quality of information. Sensor nodes have limited battery power and harsh deployed environment makes it quite impossible to recharge or replace the battery of nodes. Energy of nodes is consumed in sensing, computing and communicating data. Due to the non-uniform energy consumption of nodes in field, nodes start dying over the time. As nodes start dying, area is not completely sensed and redundancy of data also decreases. That makes the network unreliable. Hence the gathered data from the network is also unreliable. So it is necessary to find when network is in unreliable state so that proper action can be taken. In this paper, we have proposed a genetic algorithm based method to find whether wireless sensor network is reliable or unreliable. Our proposed method finds the optimal minimal number of nodes that can sense the whole area with minimum desired redundancy in data to have good quality of information gathered. Minimum number of nodes and minimum required redundancy for a network are application dependent. We have experimented with different number of topologies and different parameters. Our result show that for a network to be in reliable state at least 48% to 52% of the initial nodes (random) should be active to sense the complete area with 20% to 30% overlapping the sensed area respectively.

A Fast Block-level Error Identification and Rectification of Error Burst in Big data on Cloud

Abstract: It is an undeniable fact that we need deal with huge datasets of petabytes order. So, there is a real need of processing this extent of big datasets. In current years, so many approaches have been brought to practice big data sets on cloud. But, existing systems are not very successful for rapid identification and rectification of error burst in big data. For fast and efficacious data error identification and rectification of error burst in big data sets, we bring a new and unique approach by assembling the data nodes of big data sets into clusters or blocks thereby eliminating the computation overhead involved in processing at each node. Uniquely, in our recommended proposal, operations to identify and rectify the errors can be done temporally as well as spatially on a group or cluster of nodes instead of a single node in a given big data set. Thus, the task of error identification and rectification can be accomplished faster. Arranging the data nodes into blocks is basis of our work. The recommended work can substantially lessen the time for error identification and rectification in big data sets generated by Big network systems.

Modified Textural Soil Classification

Abstract: In this world, different types of soils are present. These soils are consisting of different types of soil particles. The engineering properties of soil are defined on the basis of particles size and consistency limits. Soil was classified into different divisions and subdivisions by different organizations. International classification, highway research board, MIT, AASHTO and many other classifications are available, but these classifications are having limitations in describing or defining the soil and soil mass. Due to this reason, a new classification of soil is proposed with the name modified textural soil classification. The modified textural classification is developed using the concept of two existing soil classifications, namely the international classification system of soil and textural classification system of soil. The original textural classification systems of soil used triangle for soil classification based on particle size distribution considering sand, silt and clay as the type of particles. Modified textural soil classification has introduced two overlapping triangles, coarse and fine triangle based on particle size considering gravel, sand, majla, silt, clay and ultra-clay as the type of particles. In this way, another triangle is formed, namely middle triangle which is more helpful in classifying soil. In modified textural classification, the two triangles are overlapped at the 50%.