Research Cell: An International Journal of Engineering Sciences

Prabhjot Kaur ¹, Rupinder kaur ²

Affiliations
1 GZS, Punjab technical University, Bathinda, Punjab, IN
2 YCOE, Punjabi University campus Talwandi sabo, Punjab, IN

Abstract

Code duplication or copying a code fragment and then reuse by pasting with or without any modifications is a well known code smell in software maintenance. Several studies show that about 5% to 20% of a software systems can contain duplicated code, which is basically the results of copying existing code fragments and using then by pasting with or without minor modifications.. Since developers usually modify the copied-and-pasted code portions, there are some gaps between the original code portion and it. Here, we call such code portions include some gaps Gapped code clone. Up to the present, several code clone detection methods, which give consideration to such gap, have been proposed. However, it needs a lot of cost to detect all the gapped code clones. This paper proposes a new method to visualize the gapped code clones just as if they were actually detected, based on the detection results of conventional code clone using Solid SX and Solid SDD tool.

Keywords

Software Maintenance, Gapped Code Clone, Solid SX, solid SDD Tool.

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Prabhjot Kaur ¹, Preet Bala ¹, Shaveta Rani ²

Affiliations
1 GZS PTU CAMPUS, Bathinda, IN
2 CSE Dept., GZS PTU CAMPUS, Bathinda, IN

Abstract

Mobile Ad- hoc Networks (MANETS) consist of mobile nodes that connected through a wireless medium. The nodes communicate with each other without any centralized control. Each node in MANETS acts as host or router in the network. The nodes are free to move randomly. The main types of routing strategies are Proactive, Reactive and Hybrid. Each strategy has various routing protocols. These papers discuss characteristics and performance of AODV, DSR, OLSR and DSDV routing protocol. The basic aim of paper is to choose the best routing protocol to maximize the network performance.

Keywords

AODV, DSR, GRP, OLSR, DSDV, MANET.

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Prabhjot Kaur ¹, Neelofar Sohi ¹

Affiliations
1 Department of Computer Engineering, Punjabi University, Patiala, Punjab-147002, IN

Abstract

In the present scenario, storage, transmission and faster computation are the basic needs of image processing world. Image compression plays an important role in delivering these three features to image processing applications. Huge variety of algorithms and techniques are available for lossless and lossy image compression. This paper presents a systematic literature review of image compression techniques presenting the basic concepts and available methods with their research gaps. An approach is proposed by reinforcing ROI based compression method based on separation of ROI and Non-ROI parts of the image where Huffman Encoding is applied to compress ROI part and Quad Tree Decomposition is applied for Non-ROI part. Performance evaluation of studied image compression techniques is done using parameters like Compression Ratio (CR), Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Bits Per Pixel (BPP). Experimental results of performance evaluation demonstrate that proposed technique outperforms other techniques.

Keywords

Image Compression, Huffman Coding, Arithmetic Coding, Run Length Encoding.

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Dr. Rachhpal Singh ¹, Dr. Rupinder Singh ², Prabhjot Kaur ²

Affiliations
1 AP, Khalsa College, Amritsar, IN
2 Assistant Professor, Khalsa College, Amritsar, IN

Abstract

Tons of stubble is generated as residue after harvesting wheat and paddy agriculture crops. Farmers burn the stubble to dispose of it because there is not enough time for the next crop and take it as a quick and inexpensive solution. It harms our ecology and eco-system in numerous ways. For the survival of humanity, it is crucial right now in India to track and forecast the Air Quality Index (AQI). The most major and dangerous air contaminant in this area is particulate matter (PM). For making predictions, machine learning (ML) technology is more effective than earlier conventional methods. Numerous ML algorithms, such as Random Forest (RF), Support Vector Machine (SVM), classification methods, Regression analysis, etc., were widely used for maximum prediction. But here by using Random Forest with Genetic Algorithm (GA) a hybrid approach prediction takes place much better. In order to improve the output of the data-adaptive computation, GA was used. Presently, data on air pollution from the preceding five years have been analyzed and forecasted for a study on Punjab's key cities to estimate and forecast PM concentrations. It was examined how PM concentrations vary with the seasons and some air pollutants. Variable importance ranking (VIR) was used to assess the effectiveness of the presented model. Here, the main emphasis was on taking into account some of the data sets from important cities in Punjab for the prediction of ambient pollution and air quality by using machine learning with genetic algorithm. Various common metrics were used to compare the results of all the strategies.

Keywords

Particulate Matter (PM), Air Quality Index (AQI), Correlation Analysis, Machine Learning (ML), Variable Importance Ranking (VIR), Random Forests (RF), Support Vector Regression (SVR).

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