52 Slices
Medium 9781601322517

The Interpretation of Maintainability Quality Attribute into Assessed Requirements

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, Joan Lu, George Jandieri, Ashu M. G. Solo, Fernando G. Tinetti CSREA Press PDF

264

Int'l Conf. Information and Knowledge Engineering | IKE'13 |

The Interpretation of Maintainability Quality

Attribute into Assessed Requirements

Mona Mohamed Abd Elghany

Assistant Professor in FAD department

Arab Academy for Science & Technology

Egypt

E-mail: mabdelghany2000@gmail.com

Nermine Mohamed Khalifa

Assistant Professor in BIS department

E-mail: nerminek@gmail.com

Marwa Mohamed Abd Elghany

Assistant Professor in BIS department

E-mail: marwam@aast.edu

Abstract— Maintainability denotes the ease of a defect correction or software changes that is extremely dependent on how simple the software can be understood and tested. The flexibility of a system is strongly linked to the maintainability of a system. High maintainability is essential for systems that are to go through periodical revisions and for products that are developed quickly. Most of the researchers do not have the adequate knowledge to define how maintainability quality factor should be assessed. This paper aims to claim the entities to be used in placing maintainability requirements and describe them into metrics. Then the main contribution of the proposed manuscript is the interpretation of the vague external maintainability quality attribute or in other words the imprecise non-functional requirements into specific structured functional requirements for implementation in the software system project.

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Medium 9781601322517

A Method for Search Result Accuracy and Indexing Efficiency on Author Name Search

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, Joan Lu, George Jandieri, Ashu M. G. Solo, Fernando G. Tinetti CSREA Press PDF
Medium 9781601322517

An Investigation of Data Privacy and Utility Preservation using KNN Classification as a Gauge

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, Joan Lu, George Jandieri, Ashu M. G. Solo, Fernando G. Tinetti CSREA Press PDF

Int'l Conf. Information and Knowledge Engineering | IKE'13 |

203

An Investigation of Data Privacy and Utility

Preservation using KNN Classification as a Gauge

Kato Mivule1 and Claude Turner PhD2 mivulek0220@students.bowiestate.edu,2cturner@bowiestate.edu

Computer Science Department, Bowie State University, Bowie, MD, USA

1

Abstract – It is obligatory that organizations by law safeguard the privacy of individuals when handling datasets containing personal identifiable information (PII).

Nevertheless, during the process of data privatization, the utility or usefulness of the privatized data diminishes. Yet achieving the optimal balance between data privacy and utility needs has been documented as an NP-hard challenge.

In this study, we investigate data privacy and utility preservation using KNN machine learning classification as a gauge.

K Nearest Neighbors (KNN): is a classification method that matches items in the test data to those in the training data by measuring the distance between the two items. Any k items that are closer to each other are then placed in the same class. The Euclidean distance is the normally used distance measure for KNN expressed as follows [5]:

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Medium 9781601322517

Intelligent Mobile App for Identifying Skin Pigments

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, Joan Lu, George Jandieri, Ashu M. G. Solo, Fernando G. Tinetti CSREA Press PDF

108

Int'l Conf. Information and Knowledge Engineering | IKE'13 |

Intelligent Mobile App for Identifying Skin Pigments

Mark Smith

Central Arkansas

Conway, Arkansas USA

Ray Hashemi

Armstrong Atlantic State

Savannah, Georgia USA

Azita Bahrami

IT Consultation

Savannah, Georgia USA

Abstract - The foundation is a cosmetic makeup applied to the face before other makeup is applied. In this research effort, a novel algorithm used to assist the selection of the optimal cosmetic foundation makeup color is presented. The algorithm is implemented as a mobile application on iPhone’s iOS platform. The selection process is done by: (1)

Intelligent segmenting of a pre-selected facial image into different skin regions, (2) Selecting (done by user) one of the facial region (or regions), (3) Merging regions based on their size and adjacency, if applicable, (4) Clustering the regions into 16 different colors using the k-means algorithm, (5) Selecting and averaging the top 4 clusters, (6) Mapping the average on a standard industry color table of cosmetic foundations, (7) Applying the identified color to the facial image. Results are shown for numerous samples from standard videos and images taken from the cameras used on the iPad.

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Medium 9781601322517

Mining the Boundaries of Social Networks: Crawling Facebook and Twitter for BlogIntelligence

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, Joan Lu, George Jandieri, Ashu M. G. Solo, Fernando G. Tinetti CSREA Press PDF

Int'l Conf. Information and Knowledge Engineering | IKE'13 |

223

Mining the Boundaries of Social Networks:

Crawling Facebook and Twitter for BlogIntelligence

Philipp Berger1 , Patrick Hennig1 , Thomas Klingbeil2 , Matthias Kohnen2 , Steffen Pade2 , and Christoph Meinel3

Hasso-Plattner-Institute, University of Potsdam, Germany

1 {philipp.berger, patrick.hennig}@hpi.uni-potsdam.de

2 {thomas.klingbeil, matthias.kohnen, steffen.pade}@student.hpi.uni-potsdam.de

3 office-meinel@hpi.uni-potsdam.de

Abstract— Today’s number of weblogs is higher than ever before and still growing. These blogs are interconnected by numerous links and other diverse connections, generating a series of notable patterns. Weblogs are not isolated and highly connected with other social networks like Facebook and Twitter. Thus, we analyze the references and investigate methods to gather data from the social platforms that are interconnected with weblogs. By analyzing the communication

flow between weblogs, Facebook and Twitter, we observe that Facebook is mostly used for referencing real people instead of posts. In contrast, tweets are primarily used for information propagation and citation.

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