Global Journal of Computer Science and Technology (GJCST)
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Klikker: A Method and Infrastructure for Mining, Analysis, and Visualisation of User Behaviour and Usability Issues for Mobile Application Development.
No full textIn the early stages of mobile application development mockups can be used to receive feedback from potential end-users This richness of feedback is limited by the lack of interactivity and requires a lot of time for a more significant study population The Klikker methodology aims to unite the designer developers and end-users in the initial phases of development by utilising modern web technologies and readily available and interchangeable - design and analytic software Klikker combines the collection of quantitative user behaviour and qualitative feedback from end-users on their own devices without additional effort from researchers The method is intended to be deployed in the first few weeks of the development proces
Requirement Elicitation Model (REM) in the Context of Global Software Development
Get PDFContxext Requirement elicitation is difficult and critical phase of requirement engineering and the case is worst in global software development GSD The study is about requirement elicitation in the context of GSD Objective Development of requirement elicitation model REM which can address the factors that have positive impact and the factors that have negative impact during elicitation in GSD The propose model will give solutions and practices to the challenges during elicitation Method Systematic literature review SLR and empirical research study will be used for achieving the goals and objectives Expected Outcomes The expected results of this study will be REM that will help vendor organizations for better elicitation during GS
Implementation of Extracted Timing Methodology on Process Monitor for Silicon Characterization
Get PDFProcess variations are playing a key role in defining the behaviour of an IP. These process variations can accurately measure using process monitor. In order to verify process variations, the process monitor should meet all timing requirements. Static Timing Analysis (STA) uses best case/ and worst analysis overly pessimistic, and could be optimistic also in some cases. Static Timing Analysis (STA) is a method for estimating yield of a circuit in terms of timing activities. Model extraction is a technique that accurately captures the characteristics of interface logic of a design in the form of a timing library model and provides a capacity improvement in timing verification by more than two orders of magnitude. Extracted timing model is an efficient timing library model to get accurate timing arcs of the circuit. This paper describes Methodology for creating timing models and also the flow to develop IP (process monitor) ETMs (.lib) using Synopsys Primetime tool, which can be used in any SOC and ETMs (Extracted timing models)with necessary time-budgeting instead of IP Netlists. Generated ETM with and without annotation delays and compared the library file. And the process monitor2019;s ring oscillator is designed through Verilog code using cadence tool
Adoption of Cloud Computing Services for Sustainable Development of Commercial Banks in Uganda
Get PDFCommercial banks in Uganda have been realised to be continuously increasing in number of branches, sizes and operational activities in the last two decades. This increment has attracted high operational costs related to purchase and maintenance of IT infrastructure and even requiring larger spaces to accommodate them, which is always accompanied by poor data storage and management. Cloud computing is identified as the best and latest solution to curb the problems in commercial banks, if adopted. Cloud computing has the capacity to store and manage data on virtualized servers so that, applications, individuals and organizations around the world can have the ability to connect to data and computing resources anywhere and anytime which improves the reliability since the data and application are stored and backed up on a number of computers which reduces the chance of data and application loss. This paper aimed at studying the benefits of cloud computing to commercial institutions and how the services can be adopted by the institutions of Uganda so as to successfully overcome the continuous expanding challenges that are always reported. A proposed system for cloud computing deployment to serve commercial banks has been developed together with recommendations for cloud computing adoption and effective utilization and management. The relevant conclusions for the paper have also been drawn
Has Machine Learning arrived for Banking Risk Managers?
Get PDFMachine learning is one of the most exciting and powerful cognitive levers out there in the Industry and today Risk managers are grappling to make sense of whether it is just a hype or does it really have a value to add in Banking Risk Management. The article attempts to give a brief introduction into foundational concepts of machine learning and highlights some of the problems with the current predictive models and also some of the most popular pilot or candidate Use cases for Machine learning adoption. It also highlights the critical success factor which one needs to consider or be aware of in in adoption of Machine leaning to solve business problems. The paper intends to demystify the conundrum called as Machine learning and elucidate it to an extent which will enable the new age Ris
Improvement of Single Seeded Region Growing Algorithm on Image Segmentation
Get PDFTo form a hybrid approach for image segmentation, several researches have been done to combine some techniques for better improvements. This article is concerned with image segmentation using combined methods. To separate foreground from background in image the pixel intensities have been considered. For image segmentation region growing with seed pixel is one of the most important segmentation methods. In single seeded region growing, it is very difficult to find out the proper position of the pixel during the selection. By considering the limitation of single seeded region growing an improved algorithm for region growing has proposed. The position of the seed pixel can be chosen before growing the region for segmentation using the proposed technique. Then combine this method with existing single seeded region growing algorithm. After the comparison using segmentation evaluation parameters it can be seen that, this combined method works better than others existing methods
Performance Analysis of Adhoc On Demand Distance Vector (AODV) and Destination Sequence Routing (DSR) protocols in Mobile Adhoc Networks (MANET)
Get PDFThis research paper compares the performance of MANET routing protocol such as Ad-hoc On Demand Distance Vector (AODV) and Destination Sequence Routing (DSR) protocol at different Node mobility and node density under different Traffic loads. The experimental data that i got are different from the original data because of several factors like random seed value, number of packets to be sent, packet size, start and end time during simulation and interdeparture time of the Constant Bit Rate generator etc. AODV produced control packets with more than 34 times and DSR more than 4 times when the traffic load was increased. However, DSR is less vulnerable to node mobility and node density in terms routing overhead and is also best suited for scalability compared to AODV
Clustering on Spatial Data Sets Using Extended Linked Clustering Algorithms
Get PDFVarious clustering algorithms (CA) have been reported in literature, to group data into clusters in diverse domains. Literature further reported that, these CAs work satisfactorily either on pure numerical data or on pure categorical data and perform poorly on mixed numerical and categorical data. Clustering is the process of creating distribution patterns and obtaining intrinsic correlations in large datasets by arranging the data into similarity classes. The present work pertains to reviewing the available research papers on clustering spatial data. In a web perspective, a detailed inspection of grouped patterns and their belonging to well known characters will be very useful for evolution of clusters. The review work is split into spatial data mining, clustering on spatial data sets and extended linked clustering. This review work will enable the researchers to make an in depth study of the till date research work on above areas and will pave way for developing extended linked clustering algorithms with a view to find number of clusters on mixed datasets to produce results for several datasets. This work is likely to assist in deciding which clustering solution to use to obtain a coherent data solution for a particular character experiment. Further it could be used as an optimal tool to guide the clustering process towards better and character interpretable meaningful solutions. The major contribution of present work is to present an in depth literature review of research in the areas of Spatial data mining, clustering on spatial data sets and extended linked clustering with a view to assist researchers to develop optimum extended linked clustering and to develop optimum extended linked clustering algorithms for clustering process ,towards better and character interpretable meaningful solutions
Incremental Maintenance of a Materialized view in Data Warehousing : An Effective Approach
Get PDFA view is a derived relation defined in terms of base relations. A view can be materialized by storing its extent in the database. An index can be made of these views and access to materialized view is much faster that recomputing the view from scratch. A Data Warehouse stores large amount of information collected from a different data sources. In order to speed up query processing, warehouse usually contains a large number of materialized views. When the data sources are updated, the views need to be updated. The process of keeping view up to date called as materialize view maintenance. Accessing base relations for view maintenance can be difficult, because the relations may be being used by users. Therefore materialize view maintenance in data warehousing is an important issue. For these reasons, the issue of self-maintainability of the view is an important issue in data warehousing. In this paper we have shown that a materialized view can be maintained without accessing the view itself by materializing additional relations at the data warehouse site. We have developed a cost effective approach to reduce the burden of view maintenance and also proved that proposed approach is optimum as compared to other approaches. Here incremental evaluation algorithm to compute changes to materialized views in relational is presented
Quality of Service in Software Defined Networking
Get PDFSoftware Defined Networking SDN promises to provide a powerful way to introduce Quality of Service QoS concepts in today s communication networks SDN programmatically modifies the functionality and behavior of network devices using single high level program Software Defined Networking SDN instantiation OpenFlow has been designed according to these properties The realization of Quality of Service QoS concepts becomes possible in a flexible and dynamic manner with SDN This paper focuses on the existing architectures parameter such as response time switch capacity and bandwidth isolation that is calculated here Although concepts of QoS are well researched they were not realized in communication networks due to high implementation complexity and realization costs OpenFlow as the best-known SDN standard so far defines a standard protocol for network control These observations of switch variety may provide SDN application developer s insights when realizing QoS concepts in an SDN-based networ