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A Review Study on the Critical Success Factors of Agile Software Development عبدالله محمد الدهمش

24th European Conference on Systems, Software and Services Process Improvement , EuroSPI 2017, Ostrava, Czech Republic, Sep 6, 2017.

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Evaluating phase level for critical success factors of BPM-system implementation: a case study in a Saudi government organization عبدالله محمد الدهمش

publication descriptionInternational Journal of Modern Engineering Research, Oct 2013.

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publication descriptionInternational Journal of Modern Engineering Research

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Using Factor Analysis to Study the Critical Success Factors of Agile Software Development عبدالله محمد الدهمش

Oct 25, 2017  publication description10th International Conference on Computer Science and Information Technology (ICCSIT) 2017, Florence, Italy.

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Measuring Success in Agile Software Development Projects: a GQM Approach عبدالله محمد الدهمش

Oct 9, 2018,  The Thirteenth International Conference on Software Engineering Advances ICSEA 2018, Nice, France.

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Comparison between File Carving from Disk Drive and Disk Image in Open Source Environment Yousuf Mohammed Uddin
The file carving is one of the methods in data recovery from corrupted or damaged hard disk drives (HDD). Numerous open source commercial tools with different features are available in the market. In the present work an attempt was made for file carving with two different methods: 1) File carving from hard disk drive directly and 2) File carving from disk image. In this investigation the file carving tool PhotoRec and disk imaging tools such as Gddrescue, safecopy were used. Quiet a significant improvement in data recovery was found in case of file carving from disk image method. All most 1GB more data was resulted in file carving through disk image when compared with that of targeted HDD directly. © 2014 IEEE. ...
Digital Forensics in Kingdom of Saudi Arabia Yousuf Mohammed Uddin

Digital forensics is growing field of technology which encompasses various fields such as computer forensics, network forensics, and cloud forensics. In the present investigation a brief survey of the global scenario and in particular status of digital forensics in Kingdom of Saudi Arabia (KSA) were outlined. No significant work is carried out in KSA in academics, research and development of digital forensics. King Fahad Security College is offering a diploma course and Naif Arab University of security science offering Master’s Program in network security. A brief account of Information Communication Technology report of 2014 has been discussed. It is observed that the population of the kingdom using smart phones and other digital devices at a very proportion. Therefore it is observed that a defined way of forensic framework is yet to be setup to curb the illegal activities and help law enforcement agencies.

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Clustering as Data Mining Technique in Risk factors Analysis of Diabetes, Hypertension and Obesity. Yousuf Mohammed Uddin

This investigation explores data mining using open source software WEKA in health care application. The cluster analysis technique is utilized to study the effects of diabetes, obesity and hypertension from the database obtained from Virginia school of Medicine. The simple k-means cluster techniques are adopted to form ten clusters which are clearly discernible to distinguish the differences among the risk factors such as diabetes, obesity and hypertension. Cluster formation was tried by trial and error method and also kept the SSE as low as possible. The SSE is low when numbers of clusters are more. Less than ten clusters formation unable to yield distinguishable information.

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Solid State Drive data recovery in open source environment. Yousuf Mohammed Uddin

In this paper we experiment and analyses the data recovery from solid state drive in an open source test environment, sample data of multiple file format is copied in to two partitions, data from first partition(sdc1)is deleted and second partition(sdc2) is formatted. Data recovery is performed in two different approaches one is directly from the disk drive and the other is imaging the SSD and recovering the data from image. Results shown that data recovery partition-wise from disk image is extracting more data.

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Errors Detection Mechanism in Big Data سلطان احمد علي شير

The rapid growth of information technologies has not been exempt from errors in the transmission and storage of data, which has affected the services, offered to customers on big data platforms. In these platforms, it has been particularly difficult to identify the causes given their complex nature, the large size and the growth of the data set. The detection and correction of errors in the processing of information in big data platforms are essential to guarantee the integrity of the stored data and thus give users confidence that the information is correctly stored without alterations. However, the options that exist to detect errors of this type lack efficiency in the methods used or use third party software that does not always allow determining the cause of the errors. In this research, big data analysis models are used to find bottlenecks of data processing management. Further, it is developed an alternative error detection mechanism that is based on analyzing error-log file with a variation of Fuzzy clustering mechanism. This approach, based on text mining, helps to look for error frequency and entity that had caused it. Moreover, it is shown how the errors that are presented are distributed according to the source.

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Deployment of Fog and Edge Computing in IoT for cyber-physical infrastructures in the 5G era سلطان احمد علي شير

To bridge the gap between existing cloud-based ICT architectures and large-scale Internet of Things (IoT) deployment, fog and edge computing (FEC) is becoming promising and anticipating paradigm to facilitate computing and communication for the next generation cyber-physical infrastructures. The key features of fog and edge computing include low latency, locality, scalability, security and privacy. Those features form a solid foundation to meet the service requirements of smart cyber-physical systems. However, although there are stand-alone, solutions exist already in this domain; many aspects are still unexplored yet in practical context also. In addition, we lack a coherent edge computing architecture that embeds these principles and can effectively enhance our cyber-physical infrastructures. In this research paper, we investigate how to enhance many expected features such as self-adaptiveness and resilience in cyber-physical systems in 5G era and IoT deployment. The focus is on fog and edge computing, which encompasses computing, communication, data analytics, security and privacy.

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