Informatics Publishing Limited

C. Arunpriya ¹, Antony Selvadoss Thanamani ¹

Affiliations
1 Nallamuthu Gounder Mahalingam College, Pollachi, IN

Abstract

Background/Objectives: Biologists found that the morphological, physiological, bio-chemical and molecular methods of plant identification are found to be laborious and require great amount of technical knowledge. This research paper concentrates on the identification of varieties of tea using leaf images. It aims to identify the species in an easy and an accurate manner. Methods/Statistical analysis: The phases involved in this work are image pre processing, feature extraction and classification. Three classification algorithms such as Fuzzy Inference system, Radial basis function network and K-nearest neighbour were used and optimized to achieve a better accuracy and execution time. Results/Findings: The classification algorithm K-nearest neighbor, Radial basis function neural network and Fuzzy Inference System are trained with 40 samples and tested using 20 samples. Conclusions: Fuzzy Inference System has a better accuracy and a lesser execution time, when compared to the other classification algorithm.

Keywords

Classification Algorithm, Fuzzy Inference System (FIS), Leaf Recognition, Pre-Processing.

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N. Sumathi ¹, Antony Selvadoss Thanamani ²

Affiliations
1 SNR Sons College, Coimbatore, IN
2 NGM College (Autonomous), Pollachi, IN

Abstract

Many applications require guarantees on available bandwidth, small delays and few packet losses. To ensure the constraints, QoS is added to the network. When a node wants to transmit data, it has to consider the bandwidth consumed by the nodes in the transmission range as well as in the carrier sense range. In mobile adhoc networks, measuring the residual bandwidth is a challenging task. Residual bandwidth is estimated by subtracting the consumed bandwidth from channel bandwidth and this new available bandwidth is integrated into the routing process. This paper proposes a QoS based passive technique to measure the remaining bandwidth on the link by considering the bandwidth loss due to the control packets, backoff scheme and collision of packets. Also there is a black hole attack in MANets due to an incorrect reply from an intermediate node. This kind of attack consumes more bandwidth and uses more network resources. The attacker is identified and blocked. It is implemented using enhanced QoS AODV (Adhoc On Demand Distance Vector) routing protocol. This protocol improves performance metrics such as average end-end delay, throughput and packet delivery ratio.

Keywords

AODV, Backoff, QoS.

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N. Sumathi ¹, Antony Selvadoss Thanamani ²

Affiliations
1 SNR Sons College, Coimbatore, IN
2 NGM College, Pollachi, IN

Abstract

Now-a-days, Quality of Service (QoS) is the most important factor for Mobile Adhoc Networks (MANets). Various protocols were developed with metrics such as delay, bandwidth,jitter, energy, number of hops etc., to find the best route from source to destination. But few protocols are available to estimate the residual bandwidth along the path. Estimating the residual bandwidth at a given period of time is a difficult task in MANets. To solve this problem, intrusive and nonintrusive techniques are used. These techniques are better at sensing the channel when the carrier sensing mechanism blocks channel access. Intrusive technique uses probe packets whereas nonintrusive technique uses hello messages to know about channel utilization. These techniques perform QoS aware routing which discover the route satisfying the bandwidth requirements. In this paper, survey of these two techniques are presented.

Keywords

Quality of Service(QoS), Distributed Coordination Function(DCF), Point Coordination Function(PCF), Round Trip Time(RTT).

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R. Jeevarathinam ¹, Antony Selvadoss Thanamani ²

Affiliations
1 SNR Sons College, Coimbatore, IN
2 NGM College, Pollachi, IN

Abstract

Software testing is an important but expensive process because about fifty percent of the total development cost is spent for it. However, this part is the first one to miss by software developers if there is a limited time to complete the project. Tests are commonly generated from program source code, graphical models of software (such as control flow graphs), and specifications/requirements. Creating test cases manually is a huge work for software developers. It is time consuming and error prone. A solution which automatically generates test cases and test data can help the software developers to create test cases from software designs/models in early stage of the software development (before coding). High quality software can not be done without high quality testing. Heuristic techniques can be applied for creating quality test data. Exhaustive testing of a software is not possible so different techniques are invoked. Mutation testing is a powerful testing technique for generating software tests and evaluating the quality of software. Mutation testing measures how "good" our tests are by inserting faults into the program under test. This article presents a survey on various mutation testing tools available. Basic concepts and notations of mutation testing as well as how mutation testing works are described. Problems of automatic generation are identified and explained. Finally important and challenging future research topics are presented.

Keywords

Software Testing, Automatic Test Cases, Mutation Testing.

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R. Jeevarathinam ¹, Antony Selvadoss Thanamani ²

Affiliations
1 SNR Sons College, Coimbatore, IN
2 NGM College, Pollachi, IN

Abstract

Software testing is an important but expensive process because about fifty percent of the total development cost is spent for it. However, this part is the first one to miss by software developers if there is a limited time to complete the project. Tests are commonly generated from program source code, graphical models of software (such as control flow graphs), and specifications/requirements. Creating test cases manually is a huge work for software developers. It is time consuming and error prone. A solution which automatically generates test cases and test data can help the software developers to create test cases from software designs/models in early stage of the software development (before coding). High quality software can not be done without high quality testing. Heuristic techniques can be applied for creating quality test data. Exhaustive testing of a software is not possible so different techniques are invoked. Mutation testing is a powerful testing technique for generating software tests and evaluating the quality of software. Mutation testing measures how "good" our tests are by inserting faults into the program under test. This article presents a survey on various mutation testing tools available. Basic concepts and notations of mutation testing as well as how mutation testing works are described. Problems of automatic generation are identified and explained. Finally important and challenging future research topics are presented.

Keywords

Software Testing, Automatic Test Cases, Mutation Testing.

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R. Jeevarathinam ¹, Antony Selvadoss Thanamani ²

Affiliations
1 SNR Sons College, Coimbatore, IN
2 NGM College, Pollachi, IN

Abstract

Software testing is an important but expensive process because about fifty percent of the total development cost is spent for it. However, this part is the first one to miss by software developers if there is a limited time to complete the project. Tests are commonly generated from program source code, graphical models of software (such as control flow graphs), and specifications/requirements. Creating test cases manually is a huge work for software developers. It is time consuming and error prone. A solution which automatically generates test cases and test data can help the software developers to create test cases from software designs/models in early stage of the software development (before coding). High quality software can not be done without high quality testing. Heuristic techniques can be applied for creating quality test data. Exhaustive testing of a software is not possible so different techniques are invoked. Mutation testing is a powerful testing technique for generating software tests and evaluating the quality of software. Mutation testing measures how "good" our tests are by inserting faults into the program under test. This article presents a survey on various mutation testing tools available. Basic concepts and notations of mutation testing as well as how mutation testing works are described. Problems of automatic generation are identified and explained. Finally important and challenging future research topics are presented.

Keywords

Software Testing, Automatic Test Cases, Mutation Testing.

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S. Sasikala Devi ¹, Antony Selvadoss Thanamani ²

Affiliations
1 CMS College of Science and Commerce, Coimbatore, IN
2 Department of Computer Science, NGM College of Arts and Science, Pollachi, IN

Abstract

Efficient key distribution is an important problem for secure group communications in wireless networks. The Authentication is a vital requirement process in order to prevent intruders attack  prior to the key distribution and exchange process in  multicast key distribution. In this paper, we propose a new multicast key Authentication key transfer protocol based on MDS scheme that ensures secure distributed Standard authentication scheme. Instead of using conventional encryption algorithms, the scheme employs MDS codes, a class of error control codes, to distribute multicast key dynamically. This scheme drastically reduces the Authentication load of each group member compared to existing schemes employing traditional encryption algorithms. Such a scheme is desirable for many wireless applications where portable devices or sensors need to reduce their Authentication as much as possible due to battery power limitations. Easily combined with PFMH key-tree-based schemes, this scheme provides much lower Authentication complexity while maintaining low and balanced communication complexity and storage complexity for secure dynamic multicast key distribution.

Keywords

Key Authentication, MDS Codes, PFMH Tree, PACK.

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T. Lavanya ¹, Antony Selvadoss Thanamani ²

Affiliations
1 Department of Computer Science, Govt. Arts College for Women, Krishnagiri, Tamilnadu, IN
2 Department of Computer Science, NGM College, Pollachi, Coimbatore, Tamilnadu, IN

Abstract

An Invariant features play a key role in object and pattern recognition studies. Features that are invariant to geometrical transformations offer succinct representations of underlying objects so that they can be reliably identified. In this paper, an invariant features is introduced based on Cartan’s, theory of moving frames. These new features are called summation invariants. Compared to existing invariant features, summations invariants are inherently numerically stable, and do not require computationally complex numerical integrations or analytical representations of underlying data. The new invariant features are applied to 2D object recognition and compared to other methods. A robust method for extracting summation invariants from sampled 2D contours introduced.

Keywords

Object Recognition, Method of Moving Frames, Invariant, Integral Invariant, Summation Invariants.

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R. Jeevarathinam ¹, Antony Selvadoss Thanamani ²

Affiliations
1 SNR Sons College, Coimbatore, IN
2 NGM College, Pollachi, IN

Abstract

Specification mining is a machine learning approach for discovering formal specifications of the protocols that code must obey when interacting with an application program interface or abstract data type. Two major concerns in engineering software systems are high maintenance costs and reliability of systems. To reduce maintenance efforts, there is a need for automated tools to help software developers understand their existing code base. So, there is a need to extract specifications to aid program comprehension. In this paper a novel technique to efficiently mine software specifications, called FP_TraceMiner is proposed which mines software specifications from program execution traces. The FP-growth algorithm is currently one of the fastest approaches. To address the limitations of Apriori-like methods, a mining paradigm has been proposed, which uses FP-growth algorithm which transforms a database into FP-tree stored in main memory and then performs mining on that optimized FP-tree structure.

Keywords

Mining Specifications, Program Execution Traces, Apriori, FP_Growth, Frequent Itemsets, Frequent Pattern.

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B. M. Rajesh ¹, B. Chithra ², A. Finny Belwin ³, A. Linda Sherin ⁴, Antony Selvadoss Thanamani ⁵

Affiliations
1 Department of Information Technology, Dr.NGP Arts and Science College, IN
2 Department of Computer Technology, Shri Nehru Maha Vidyalaya College of Arts and Science, IN
3 Department of Computer Science, Angappa College of Arts and Science, IN
4 Department of Computer Science, AM Jain College, IN
5 Associate Professor and Head, Department of Computer Science, Nallamuthu Gounder Mahalingam College, IN

Abstract

Distribution of independent sensors can be termed as a Wireless Sensor Network (WSN) as it monitors the environmental or physical circumstances like pressure, vibration, sound, temperature and so on cooperatively. WSNs usually consumes less energy and has extremely long lifetime for network which are considered to be critical tasks, particularly in sensor networks involving of nodes which are observed to be lightweight and consumes constricted energy source. The Hybrid Energy-Efficient Multi-Path (HEEMP) routing is the preceding scheme modeled for wireless sensor networks. On the other hand, an appropriate selection methodology for CH possessing ideal skills is essential to stabilize the load of network lifetime and network’s energy-efficiency. Here the cost of energy needed to choose a path for forwarding of data is alone taken into account. Besides, it doesn’t learn about the quality of link to progress the ratio of packet delivery. So as to resolve this issue, the projected scheme modeled a Dynamic Binomial Distribution centered Glowworm Swarm Optimization algorithm along with Improved Link Quality Cost Function based data forwarding (DBD-GSO with ILQCF) methods. In the projected work of study, selection of Cluster Head (CH) is donebased on the transmission power, residual energy, node degree and minimum distance with the assistance of Dynamic Binomial Distribution based Glowworm Swarm Optimization algorithm (DBD-GSO). In order to exchange information with the cluster head inside the clusters, the nodes implement multi-hop routing technique. This technique after receiving of data packets from every member of cluster it transfers the data aggregated on the pre calculated track to the sink. The ideal path is selected in a way that the overall consumption of energy in the routing path is the least with high link quality and it is done by employing Improved Link Quality Cost Function (ILQCF). All the tests are carried by utilizing a simulator called NS-2. The projected and existing methods for detection are contrasted by means of features like throughput, end to end delay and consumption of total energy.

Keywords

Multi-Hop Routing, Dynamic Binomial Distribution and Link Quality, Wireless Sensor Network.

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