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International Journal of Advances in Applied Sciences

IJAAS
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Published by Institute of Advanced Engineering and Science

ISSN : 22528814 EISSN : 27222594 DOI : http://doi.org/10.11591/ijaas

Core Subject : Science, Education, Social,

Earth & Planetary Sciences Environmental Science Materials Science & Nanotechnology Mathematics Physics

International Journal of Advances in Applied Sciences (IJAAS) is a peer-reviewed and open access journal dedicated to publish significant research findings in the field of applied and theoretical sciences. The journal is designed to serve researchers, developers, professionals, graduate students and others interested in state-of-the art research activities in applied science areas, which cover topics including: chemistry, physics, materials, nanoscience and nanotechnology, mathematics, statistics, geology and earth sciences.

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Articles 12 Documents

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Search results for , issue "Vol 7, No 1: March 2018" : 12 Documents clear

A Fusion Based Visibility Enhancement of Single Underwater Hazy Image Samarth Borkar; Sanjiv V. Bonde
International Journal of Advances in Applied Sciences Vol 7, No 1: March 2018
Publisher : Institute of Advanced Engineering and Science

Underwater images are prone to contrast loss, limited visibility, and undesirable color cast. For underwater computer vision and pattern recognition algorithms, these images need to be pre-processed. We have addressed a novel solution to this problem by proposing fully automated underwater image dehazing using multimodal DWT fusion. Inputs for the combinational image fusion scheme are derived from Singular Value Decomposition (SVD) and Discrete Wavelet Transform (DWT) for contrast enhancement in HSV color space and color constancy using Shades of Gray algorithm respectively. To appraise the work conducted, the visual and quantitative analysis is performed. The restored images demonstrate improved contrast and effective enhancement in overall image quality and visibility. The proposed algorithm performs on par with the recent underwater dehazing techniques.

Experimental and Modeling Dynamic Study of the Indirect Solar Water Heater: Application to Rabat Morocco Ouhammou Badr; Azeddine Frimane; Aggour Mohammed; Brahim Daouchi; Abdellah Bah; Halima Kazdaba
International Journal of Advances in Applied Sciences Vol 7, No 1: March 2018
Publisher : Institute of Advanced Engineering and Science

The Indirect Solar Water Heater System (SWHS) with Forced Circulation is modeled by proposing a theoretical dynamic multi-node model. The SWHS, which works with a 1,91 m2 PFC and 300 L storage tank, and it is equipped with available forced circulation scale system fitted with an automated sub-system that controlled hot water, is what the experimental setup consisted of. The system, which 100% heated water by only using solar energy. The experimental weather conditions are measured every one minute. The experiments validation steps were performed for two periods, the first one concern the cloudy days in December, the second for the sunny days in May; the average deviations between the predicted and the experimental values is 2 %, 5 % for the water temperature output and for the useful energy are 4 %, 9 % respectively for the both typical days, which is very satisfied. The thermal efficiency was determined experimentally and theoretically and shown to agree well with the EN12975 standard for the flow rate between 0,02 kg/s and 0,2kg/s.

SLIC Superpixel Based Self Organizing Maps Algorithm for Segmentation of Microarray Images Durga Prasad Kondisetty; Mohammed Ali Hussain
International Journal of Advances in Applied Sciences Vol 7, No 1: March 2018
Publisher : Institute of Advanced Engineering and Science

We can find the simultaneous monitoring of thousands of genes in parallel Microarray technology. As per these measurements, microarray technology have proven powerful in gene expression profiling for discovering new types of diseases and for predicting the type of a disease. Gridding, Intensity extraction, Enhancement and Segmentation are important steps in microarray image analysis. This paper gives simple linear iterative clustering (SLIC) based self organizing maps (SOM) algorithm for segmentation of microarray image. The clusters of pixels which share similar features are called Superpixels, thus they can be used as mid-level units to decrease the computational cost in many vision applications. The proposed algorithm utilizes superpixels as clustering objects instead of pixels. The qualitative and quantitative analysis shows that the proposed method produces better segmentation quality than k-means, fuzzy c-means and self organizing maps clustering methods.

Optimal Bidding and Generation Scheduling of Utilities Participating in Single Side Auction Markets Including Ancillary Services B. Rampriya
International Journal of Advances in Applied Sciences Vol 7, No 1: March 2018
Publisher : Institute of Advanced Engineering and Science

This paper presents the solution for the supplier’s profit maximization problem with unit commitment decisions participating in single side auction markets of a deregulated power system. The bids from market participants are received by a central pool mechanism and the Market Clearing Price (MCP) for energy and spinning reserve is fixed. The bid quantities are optimized using Differential Evolution (DE) algorithm. The supplier aims to achieve (more) profit than that of the rival’s participating in the competition. A GENCO with 6-unit participating in 24-hour day ahead energy and spinning reserve market is used to illustrate the methodology. The bidding parameters of rival’s participating in the competition are calculated by multi-variant Probability Density Functions (PDF). The results of the proposed methodology are compared with Refined Genetic Algorithm (RGA). Numerical results illustrate the effectiveness of the method in solving the supplier profit maximization problem.

Data Mining Techniques for Providing Network Security through Intrusion Detection Systems: a Survey Prabhu Kavin B; Ganapathy S
International Journal of Advances in Applied Sciences Vol 7, No 1: March 2018
Publisher : Institute of Advanced Engineering and Science

Intrusion Detection Systems are playing major role in network security in this internet world. Many researchers have been introduced number of intrusion detection systems in the past. Even though, no system was detected all kind of attacks and achieved better detection accuracy. Most of the intrusion detection systems are used data mining techniques such as clustering, outlier detection, classification, classification through learning techniques. Most of the researchers have been applied soft computing techniques for making effective decision over the network dataset for enhancing the detection accuracy in Intrusion Detection System. Few researchers also applied artificial intelligence techniques along with data mining algorithms for making dynamic decision. This paper discusses about the number of intrusion detection systems that are proposed for providing network security. Finally, comparative analysis made between the existing systems and suggested some new ideas for enhancing the performance of the existing systems.

An Improved Greedy Parameter Stateless Routing In Vehicular Ad Hoc Network Kavita Kavita; Neera Batra; Rishi Pal Singh
International Journal of Advances in Applied Sciences Vol 7, No 1: March 2018
Publisher : Institute of Advanced Engineering and Science

Congestion problem and packet delivery related issues in the vehicular ad hoc network environment is a widely researched problem in recent years. Many network designers utilize various algorithms for the design of ad hoc networks and compare their results with the existing approaches. The design of efficient network protocol is a major challenge in vehicular ad hoc network which utilizes the value of GPS and other parameters associated with the vehicles. In this paper GPSR protocol is improved and compared with the existing GPSR protocol and AODV protocol on the basis of various performance parameters like throughput of the network, delay and packet delivery ratio. The results also validate the performance of the proposed approach.

Workload Aware Incremental Repartitioning of NoSQL for Online Transactional Processing Applications Anagha Bhunje; Swati Ahirrao
International Journal of Advances in Applied Sciences Vol 7, No 1: March 2018
Publisher : Institute of Advanced Engineering and Science

Numerous applications are deployed on the web with the increasing popularity of internet. The applications include, 1) Banking applications, 2) Gaming applications, 3) E-commerce web applications. Different applications reply on OLTP (Online Transaction Processing) systems. OLTP systems need to be scalable and require fast response. Today modern web applications generate huge amount of the data which one particular machine and Relational databases cannot handle. The E-Commerce applications are facing the challenge of improving the scalability of the system. Data partitioning technique is used to improve the scalability of the system. The data is distributed among the different machines which results in increasing number of transactions. The work-load aware incremental repartitioning approach is used to balance the load among the partitions and to reduce the number of transactions that are distributed in nature. Hyper Graph Representation technique is used to represent the entire transactional workload in graph form. In this technique, frequently used items are collected and Grouped by using Fuzzy C-means Clustering Algorithm. Tuple Classification and Migration Algorithm is used for mapping clusters to partitions and after that tuples are migrated efficiently.

Data Partitioning in Mongo DB with Cloud Aakanksha Jumle; Swati Ahirrao
International Journal of Advances in Applied Sciences Vol 7, No 1: March 2018
Publisher : Institute of Advanced Engineering and Science

Cloud computing offers various and useful services like IAAS, PAAS SAAS for deploying the applications at low cost. Making it available anytime anywhere with the expectation to be it scalable and consistent. One of the technique to improve the scalability is Data partitioning. The alive techniques which are used are not that capable to track the data access pattern. This paper implements the scalable workload-driven technique for polishing the scalability of web applications. The experiments are carried out over cloud using NoSQL data store MongoDB to scale out. This approach offers low response time, high throughput and less number of distributed transaction. The results of partitioning technique is conducted and evaluated using TPC-C benchmark.

Study of Absorption Loss Effects on Acoustic Wave Propagation in Shallow Water Using Different Empirical Models Yasin Yousif Al-Alaboosi; Jenan Abdulkhalq Al-Aboosi
International Journal of Advances in Applied Sciences Vol 7, No 1: March 2018
Publisher : Institute of Advanced Engineering and Science

Efficient underwater acoustic communication and target locating systems require detailed study of acoustic wave propagation in the sea. Many investigators have studied the absorption of acoustic waves in ocean water and formulated empirical equations such as Thorp’s formula, Schulkin and Marsh model and Fisher and Simmons formula. The Fisher and Simmons formula found the effect associated with the relaxation of boric acid on absorption and provided a more detailed form of absorption coefficient which varies with frequency. However, no simulation model has made for the underwater acoustic propagation using these models. This paper reports the comparative study of acoustic wave absorption carried out by means of modeling in MATLAB. The results of simulation have been evaluated using measured data collected at Desaru beach on the eastern shore of Johor in Malaysia. The model has been used to determine sound absorption for given values of depth (D), salinity (S), temperature (T), pH, and acoustic wave transmitter frequency (f). From the results a suitable range, depth and frequency can be found to obtain best propagation link with low absorption loss.

Graph Based Workload Driven Partitioning System by using MongoDB Arvind Sahu; Swati Ahirrao
International Journal of Advances in Applied Sciences Vol 7, No 1: March 2018
Publisher : Institute of Advanced Engineering and Science

The web applications and websites of the enterprises are accessed by a huge number of users with the expectation of reliability and high availability. Social networking sites are generating the data exponentially large amount of data. It is a challenging task to store data efficiently. SQL and NoSQL are mostly used to store data. As RDBMS cannot handle the unstructured data and huge volume of data, so NoSQL is better choice for web applications. Graph database is one of the efficient ways to store data in NoSQL. Graph database allows us to store data in the form of relation. In Graph representation each tuple is represented by node and the relationship is represented by edge. But, to handle the exponentially growth of data into a single server might decrease the performance and increases the response time. Data partitioning is a good choice to maintain a moderate performance even the workload increases. There are many data partitioning techniques like Range, Hash and Round robin but they are not efficient for the small transactions that access a less number of tuples. NoSQL data stores provide scalability and availability by using various partitioning methods. To access the Scalability, Graph partitioning is an efficient way that can be easily represent and process that data. To balance the load data are partitioned horizontally and allocate data across the geographical available data stores. If the partitions are not formed properly result becomes expensive distributed transactions in terms of response time. So the partitioning of the tuple should be based on relation. In proposed system, Schism technique is used for partitioning the Graph. Schism is a workload aware graph partitioning technique. After partitioning the related tuples should come into a single partition. The individual node from the graph is mapped to the unique partition. The overall aim of Graph partitioning is to maintain nodes onto different distributed partition so that related data come onto the same cluster.

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