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JournalISSN: 1549-3636

Journal of Computer Science 

Science Publications
About: Journal of Computer Science is an academic journal published by Science Publications. The journal publishes majorly in the area(s): Network packet & Routing protocol. It has an ISSN identifier of 1549-3636. Over the lifetime, 2713 publications have been published receiving 23536 citations. The journal is also known as: Journal of computer science.


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Journal ArticleDOI
TL;DR: This study emphasized on different types of normalization, each of which was tested against the ID3 methodology using the HSV data set, and recommendations were concluded on the best normalization method based on the factors and their priorities.
Abstract: This study is emphasized on different types of normalization. Each of which was tested against the ID3 methodology using the HSV data set. Number of leaf nodes, accuracy and tree growing time are three factors that were taken into account. Comparisons between different learning methods were accomplished as they were applied to each normalization method. A new matrix was designed to check for the best normalization method based on the factors and their priorities. Recommendations were concluded.

391 citations

Journal ArticleDOI
TL;DR: An imperceptible and a robust combined DWT-DCT digital image watermarking algorithm that watermarks a given digital image using a combination of the Discrete Wavelet Transform (DWT) and thediscrete Cosine transform (DCT).
Abstract: The proliferation of digitized media due to the rapid growth of networked multimedia systems, has created an urgent need for copyright enforcement technologies that can protect copyright ownership of multimedia objects. Digital image watermarking is one such technology that has been developed to protect digital images from illegal manipulations. In particular, digital image watermarking algorithms which are based on the discrete wavelet transform have been widely recognized to be more prevalent than others. This is due to the wavelets' excellent spatial localization, frequency spread, and multi-resolution characteristics, which are similar to the theoretical models of the human visual system. In this paper, we describe an imperceptible and a robust combined DWT-DCT digital image watermarking algorithm. The algorithm watermarks a given digital image using a combination of the Discrete Wavelet Transform (DWT) and the Discrete Cosine Transform (DCT). Performance evaluation results show that combining the two transforms improved the performance of the watermarking algorithms that are based solely on the DWT transform.

319 citations

Journal ArticleDOI
TL;DR: This system shows a high classification effectiveness for Arabic data set in term of F-measure (F=88.11) and uses CHI square method as a feature selection method in the pre-processing step of the Text Classification system design procedure.
Abstract: This paper aims to implement a Support Vector Machines (SVMs) based text classification system for Arabic language articles. This classifier uses CHI square method as a feature selection method in the pre-processing step of the Text Classification system design procedure. Comparing to other classification methods, our system shows a high classification effectiveness for Arabic data set in term of F-measure (F=88.11).

235 citations

Journal ArticleDOI
TL;DR: The potential use of classification based data mining techniques such as Rule based, decision tree and Artificial Neural Network to massive volume of healthcare data is examined.
Abstract: The healthcare environment is generally perceived as being ‘information rich’ yet ‘knowledge poor’. There is a wealth of data available within the healthcare systems. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. Knowledge discovery and data mining have found numerous applications in business and scientific domain. Valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, we briefly examine the potential use of classification based data mining techniques such as Rule based, decision tree and Artificial Neural Network to massive volume of healthcare data. In particular we consider a case study using classification techniques on a medical data set of diabetic patients.

230 citations

Journal ArticleDOI
TL;DR: The average time taken by K-Means algorithm is greater than the time takenby K-Medoids algorithm for both the case of normal and uniform distributions, and the r esults proved to be satisfactory.
Abstract: Problem statement: Clustering is one of the most important research ar eas in the field of data mining. Clustering means creating groups of ob jects based on their features in such a way that th e objects belonging to the same groups are similar an d those belonging to different groups are dissimila r. Clustering is an unsupervised learning technique. T he main advantage of clustering is that interesting patterns and structures can be found directly from very large data sets with little or none of the background knowledge. Clustering algorithms can be applied in many domains. Approach: In this research, the most representative algorithms K-Mean s and K-Medoids were examined and analyzed based on their basic approach. The best algorithm i n each category was found out based on their performance. The input data points are generated by two ways, one by using normal distribution and another by applying uniform distribution. Results: The randomly distributed data points were taken as input to these algorithms and clusters are found ou t for each algorithm. The algorithms were implemented using JAVA language and the performance was analyzed based on their clustering quality. The execution time for the algorithms in each category was compar ed for different runs. The accuracy of the algorith m was investigated during different execution of the program on the input data points. Conclusion: The average time taken by K-Means algorithm is greater than the time taken by K-Medoids algorithm for both the case of normal and uniform distributions. The r esults proved to be satisfactory.

211 citations

Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
202312
202213
202162
2020147
2019128
2018131