Current Issue


Vol. 1 No. 2 2016

An effective data communication using IEEE 802.15.4 for wireless sensor network Original Research Article

Pages 35-39
S.Anthony Jesudurai, A.Senthilkumar , A.Puviarasu

Abstract

Wireless Sensor Network are commonly used in all sector for data processing. The design of low rate Wireless Personal Area Network (LR-WPAN) by IEEE 802.15.4 standard has been developed to support lower data rates and low power consuming application. Where in industry the wired communication is more expensive or impossible due to physical conditions. A shortcoming of the existing wireless industrial communication standards is the existence of overcomplicated routing protocols and design topology. Zigbee wireless sensor network works on the network application layer in IEEE 802.15.4. Zigbee networks are configured in star, tree or mesh topology whose performance varies from topology to topology. Performances parameters are network lifetime, energy consumption, throughput, data delivery delay and sensor field coverage area vary depend on the network topology. The applications of Industrial Wireless Sensor Networks for Process Automation are time-critical, subject to requirements in terms of end-to-end delay and reliability of data delivery. In this Paper, designing of hybrid topology by using three possible combinations such as star-tree, star-mesh and star-tree-mesh for Wireless Sensor Network. The designed hybrid star-tree-mesh topology uses Zigbee communication protocol with two different routing protocol AODV and DSR for safe and economic data communication in industrial fields. Proposed Star-Tree-Mesh hybrid zigbee sensor network performs better than other two topologies like Star-Tree and Star-Mesh.

Research Highlights

We developed a novel Wireless Personal Area Network (LR-WPAN) by IEEE 802.15.4 standard to support lower data rates and low power consuming application.

We demonstrated a hybrid topology using three possible combinations such as star-tree, star-mesh and star-tree-mesh for Wireless Sensor Network.

It has been found that proposed Star-Tree-Mesh hybrid zigbee sensor network performs better than other two topologies like Star-Tree and Star-Mesh topology.

An effective data communication using IEEE 802.15.4 for wireless sensor network

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Analysis of various peak to average power ratio reduction techniques of OFDM System Original Research Article

Pages 40-45
S.Anu, J.Jaya

Abstract

The OFDM technique is an attractive modulation technique for transmitting large amounts of data over radio waves. One major drawback of OFDM is that the time domain OFDM signal which is a sum of several sinusoids leads to high peak to average power ratio (PAPR). In the paper, the combination of Companding transform, Amplitude clipping and filtering, Partial transmit sequence (PTS) technique, Selected Mapping technique (SLM) and Hadamard transform techniques are proposed to reduce peak-to-average of OFDM signal for 64 subcarriers. Significant PAPR reduction and good performance in the BER is expected from the proposed system when compared to other PAPR reduction techniques. We use MATLAB software to analyze the system. The performance of the system is analyzed from BER vs. SNR graph. PAPR reduction is analyzed using Complementary Cumulative Distribution Function (CCDF) plots.

Research Highlights

We proposed a novel technique with the combination of Companding transform, Amplitude clipping and filtering, Partial transmit sequence (PTS) technique, Selected Mapping technique (SLM) and Hadamard transform to reduce peak-to-average of OFDM signal for 64 subcarriers.

We achieved Significant PAPR reduction and good performance in the BER when compared to other PAPR reduction techniques.

Analysis of various peak to average power ratio reduction techniques of OFDM System

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Disease Classification of Paddy Leaves using HSI feature extraction and SVM Technique Original Research Article

Pages 46-48
D. Swathi, A. Bharathi

Abstract

The value of paddy is strongly related to the quality, types and sizes of paddy without any damage or disease of that leaves. Hence detecting the disease or damage area of the leaf is very important to improve the utilization rate. Though the crop production is well grown there is still lagging in visual inspection of diseases. Although it is done manually, it is not accurate in all the times. So, there is a need for technique to detect the diseases. The system proposed is based on this method which can detect the diseases using artificial neural network and support vector machine classification. The main contribution of this approach is the support vector machine classification. This system involves image acquisition, converting the RGB images into HSI image where morphological process is used for removing noise. The block level feature extraction is used for extracting the features like mean and standard deviation. Finally, it is classified and compared both ANN and SVM approach for more accuracy and less execution time



Research Highlights

The system has been proposed to detect the diseases in leaves using artificial neural network and support vector machine classification.

The block level feature extraction method is used for extracting the features like mean and standard deviation.

Finally, it is classified and compared both ANN and SVM approach for more accuracy and less execution time.

Disease Classification of Paddy Leaves using HSI feature extraction and SVM Technique

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Efficient Error Approximation and Area Reduction in Multipliers and Squarers Using Array Based Approximate Arithmetic Computing Original Research Article

Pages 49-53
C. Ishwarya

Abstract

In this paper a general model for array-based approximate arithmetic computing (AAAC) is proposed to guide the minimization of processing error. In this model the key building block of AAAC circuits is the Error Compensation Unit (ECU). While designing the ECU, the two most critical problems are identified viz., determination of optimal error compensation values and identification of optimal error compensation scheme. This general AAAC model achieves optimal trade-offs between accuracy, energy and area overhead. Further reduction in area, energy dissipation and delay of AAAC can be achieved by simplifying ECU's design by introducing logic don't cares. Another unit that plays a key role next to the ECU is the Compression Unit (CU). By using a 5:2 compressor, area can be further minimized. Using the same approach, significant energy consumption and area and error reduction can be achieved in a squarer unit.





Research Highlights

In this research work, a general model for array-based approximate arithmetic computing (AAAC) is proposed to guide the minimization of processing error.

This general AAAC model achieves optimal trade-offs between accuracy, energy and area overhead.

By utilizing a 5:2 compressor, significant energy consumption and area and error reduction can be achieved in a squarer unit

Efficient Error Approximation and Area Reduction in Multipliers and Squarers Using Array Based Approximate Arithmetic Computing

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